974 results on '"LI Zhi"'
Search Results
2. Genetic Polymorphism rs6505162 in MicroRNA-423 May Not Be Associated with Susceptibility of Breast Cancer: A Systematic Review and Meta-Analysis
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Xiao-Mei Guo, Meng Wang, Li Zhi, Hui-bing Chen, Min-Min Zhang, Xiao-Ping Chen, Jin Wang, and Li-Juan Dong
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Oncology ,medicine.medical_specialty ,business.industry ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Review Article ,Knowledge infrastructure ,medicine.disease ,Breast cancer ,Polymorphism (computer science) ,Internal medicine ,Meta-analysis ,Genetic model ,microRNA ,medicine ,Dominant model ,Allele ,business ,RC254-282 - Abstract
Background. MicroRNA-423 (miR-423) rs6505162 polymorphism is found to be associated with breast cancer (BC) risk. However, the results were inconsistent. This study meta-analyzed the literature on possible association between rs6505162 polymorphism and BC risk. Methods. PubMed, Embase, Google Scholar, and the Chinese National Knowledge Infrastructure (CNKI) databases were systematically searched to identify relevant studies. Meta-analyses were performed to examine the association between rs6505162 polymorphism and BC. Results. None of the five genetic models suggested a significant association between rs6505162 polymorphism and BC risk: allelic model, OR 1.02, 95% CI 0.18–1.28, P = 0.85 ; recessive model, OR 0.99, 95% CI 0.72–1.38, P = 0.97 ; dominant model, OR 0.93, 95% CI 0.72–1.21, P = 0.60 ; homozygous model, OR 1.04, 95% CI 0.66–1.65, P = 0.87 ; and heterozygous model, OR 1.07, 95% CI 0.90–1.28, P = 0.45 . Similar results were obtained in subgroup analyses of Asian, Chinese, and Caucasian patients. Conclusion. The available evidence suggests no significant association between rs6505162 polymorphism and BC risk. These conclusions should be verified in large, well-designed studies.
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- 2021
3. Modelling of Deformation Resistance with Big Data and Its Application in the Prediction of Rolling Force of Thick Plate
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Li Zhi Che, Xin Ying Liu, and Shun Hu Zhang
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Normalization (statistics) ,Article Subject ,Artificial neural network ,Computer science ,business.industry ,Generalization ,General Mathematics ,Big data ,General Engineering ,Structural engineering ,Deformation (meteorology) ,Engineering (General). Civil engineering (General) ,Backpropagation ,Data set ,Test set ,QA1-939 ,TA1-2040 ,business ,Mathematics - Abstract
The precision of traditional deformation resistance model is limited, which leads to the inaccuracy of the existing rolling force model. In this paper, the back propagation (BP) neural network model was established according to the industrial big data to accurately predict the deformation resistance. Then, a new rolling force model was established by using the BP neural network model. During the establishment of the neural network model, the data set of deformation resistance was established, which was calculated back from the actual rolling force data. Based on the data set after normalization, the BP neural network model of deformation resistance was established through the optimization of algorithm and network structure. It is shown that both the prediction accuracy of the neural network model on the training set and the test set are high, indicating that the generalization ability of the model is strong. The neural network model of the deformation resistance is compared with the theoretical one, and the maximum error is only 3.96%. Furthermore, by comparison with the traditional rolling force model, it is found that the prediction accuracy of the rolling force model imbedding with the present neural network model is improved obviously. The maximum error of the present rolling force model is just 3.86%. The research in this paper provides a new way to improve the prediction accuracy of rolling force model.
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- 2021
4. Automatic Rocks Segmentation Based on Deep Learning for Planetary Rover Images
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Haichao Li, Zhang Zhimin, Linwei Qiu, Li Zhi, Huang Jianbin, and Meng Bo
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Computer science ,business.industry ,Deep learning ,Aerospace Engineering ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Mars Exploration Program ,Image segmentation ,Convolutional neural network ,GeneralLiterature_MISCELLANEOUS ,Computer Science Applications ,Mars rover ,Deep space exploration ,Segmentation ,Computer vision ,Motion planning ,Artificial intelligence ,Electrical and Electronic Engineering ,business - Abstract
Accurate detection and segmentation of obstacles is the key to the smooth operation of the planetary rovers and the basic guarantee of scientific exploration mission. The traditional method of rock...
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- 2021
5. Targeting hexokinase 2 increases the sensitivity of oxaliplatin by Twist1 in colorectal cancer
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Zhao-Xia Dong, Li-Zhi Deng, Shu-Na Chen, Zhi-Ying Mai, Xue-Qi Liu, Di-Sheng Zhou, Xingding Zhang, Yuan-Yuan Shi, Xin-Rong Shao, Sze-Hoi Chan, Bo Zhang, Li-Yuan Zheng, Tian-Liang Fang, and Miao Li
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Colorectal cancer ,Regulator ,Vimentin ,colorectal cancer ,Metastasis ,Mice ,In vivo ,Cell Line, Tumor ,Hexokinase ,medicine ,Animals ,Humans ,neoplasms ,Gene knockdown ,Mice, Inbred BALB C ,biology ,business.industry ,Twist-Related Protein 1 ,chemoresistance ,Nuclear Proteins ,Cell Biology ,Original Articles ,medicine.disease ,hexokinase 2 ,digestive system diseases ,Oxaliplatin ,Gene Expression Regulation, Neoplastic ,Apoptosis ,Drug Resistance, Neoplasm ,Cancer research ,biology.protein ,Molecular Medicine ,Original Article ,business ,Colorectal Neoplasms ,medicine.drug ,Twist1 - Abstract
Colorectal cancer (CRC) is the third most malignant tumour worldwide, with high mortality and recurrence. Chemoresistance is one of the main factors leading to metastasis and poor prognosis in advanced CRC patients. By analysing the Gene Expression Omnibus data set, we found higher hexokinase 2 (HK2) expression levels in patients with metastatic CRC than in those with primary CRC. Moreover, we observed higher enrichment in oxaliplatin resistance‐related gene sets in metastatic CRC than in primary CRC. However, the underlying relationship has not yet been elucidated. In our study, HK2 expression was significantly elevated in CRC patients. Gene set enrichment analysis (GSEA) revealed multi‐drug resistance and epithelial‐mesenchymal transition (EMT) pathways related to high HK2 expression. Our results showed that knockdown of HK2 significantly inhibited vimentin and Twist1 expression and promoted TJP1 and E‐cadherin expression in CRC cells. Additionally, transcriptional and enzymatic inhibition of HK2 by 3‐bromopyruvate (3‐bp) impaired oxaliplatin resistance in vitro and in vivo. Mechanistically, HK2 interacts with and stabilized Twist1 by preventing its ubiquitin‐mediated degradation, which is related to oxaliplatin resistance, in CRC cells. Overexpression of Twist1 reduced the apoptosis rate by HK2 knockdown in CRC cells. Collectively, we discovered that HK2 is a crucial regulator that mediates oxaliplatin resistance through Twist1. These findings identify HK2 and Twist1 as promising drug targets for CRC chemoresistance.
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- 2021
6. Angle calibration and error analysis of wide-angle X-ray scattering (WAXS) with a one-dimensional linear detector
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Yuexiang Wang, Rongchao Chen, Li-Zhi Liu, Baoliang Lv, Ying Shi, and Zhihong Li
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Diffraction ,Standard sample ,Materials science ,Scattering ,business.industry ,General Chemical Engineering ,Detector ,Optics ,Error analysis ,Calibration ,business ,Wide-angle X-ray scattering ,Instrumentation ,General Environmental Science - Abstract
Wide-angle X-ray scattering (WAXS) is routinely used to characterize the ordered structure in materials. The measured angles are generally calibrated by using standard samples with several diffract...
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- 2021
7. Long-term tumor-free survival after cyst excision plus pancreaticoduodenectomy for the treatment of congenital choledochal cyst with malignant change
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Xinghua Huang, Li-Zhi Lv, Huan-Zhang Hu, and Yi Jiang
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medicine.medical_specialty ,RD1-811 ,business.industry ,Choledochal cyst ,Carcinogenesis ,medicine.medical_treatment ,Anastomosis, Surgical ,Surgical procedures ,medicine.disease ,Pancreaticoduodenectomy ,Surgery ,P rognosis ,Pancreatectomy ,Bile Duct Neoplasms ,Congenital Choledochal Cyst ,Medicine ,Humans ,Cyst ,Choledochal cysts ,business ,Tumor free survival - Published
- 2021
8. The impacts of environmental performance and development of financing decisions on economic sustainable performance: from the view of renewable and clean energy industry
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Hsing Hung Chen, Kai Quan Zhang, and Li Zhi Tang
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Finance ,Sustainable development ,Economics and Econometrics ,Environmental Engineering ,business.industry ,020209 energy ,media_common.quotation_subject ,Environmental pollution ,02 engineering and technology ,010501 environmental sciences ,Management, Monitoring, Policy and Law ,01 natural sciences ,General Business, Management and Accounting ,Green economy ,Renewable energy ,Environmental governance ,Debt ,Value (economics) ,0202 electrical engineering, electronic engineering, information engineering ,Environmental Chemistry ,External financing ,business ,0105 earth and related environmental sciences ,media_common - Abstract
Developing green economy and mitigating environmental pollution have strategically important role in China's commitments against global climate warming. An ongoing issue energy industry has been how to craft a financing structure which maximizes economic value under increasing environmental pressures. This study theorized that environmental management impacts on financing decisions by external effects and that the interaction between corporate environmental performance and external financing choices is associated with economic performance. It used the generalized method of moments estimation technique to analyze a sample of Chinese-listed clean and renewable energy companies during the period 2008–2018. The findings demonstrate that debt and equity financing composition have significant impacts on short- and long-term economic. The environmental performance has contributed to economic performance, which has increased to a great degree in the long run, but engendered negative effects in the short term. The empirical analyses provide that environmental governance moderates the relationship between external financing and economic performance.
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- 2021
9. Detection method of sports scene conversion for MPEG compressed video based on fuzzy logic
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Zhiran Lin, Li Ma, Chao Li, Li Zhi, Zhu Zhengyu, and Fu Qiang
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Statistics and Probability ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,General Engineering ,020207 software engineering ,02 engineering and technology ,Fuzzy logic ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business ,Video based - Abstract
At present, the majority of sports games video adopts MPEG image technology, and MPEG video compression is the current more mainstream approach. After compression, the quality of the video will decline, and other practical problems. However, the existing detection methods of sports video scene conversion, when dealing with MPEG compressed video, are not ideal, often appear the phenomenon of missing detection and wrong detection. In order to solve this problem, this paper proposes a detection method of sports scene conversion on MPEG compressed video based on fuzzy logic. Introducing fuzzy logic into the detection method of video scene conversion is the highlight of this method. Firstly, this paper preprocessed the video image according to the Convention. In this paper, the recognition of image features and specific extraction methods are introduced in detail, and the extraction algorithm of image color features is further optimized. For the design of the detection method, the main innovation is to fully combine the fuzzy logic and macroblock information. In the existing detection methods, different detection schemes are given for the abrupt change of video scene and the gradual change of scene. Finally, in order to verify the actual effect of the detection method in this paper, an experimental analysis based on the keyframe complexity detection method is established. After a number of experiments including the experimental results of scene transition, analysis, and processing time, through the analysis of data, a step-by-step proof of this method has good accuracy and recall.
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- 2021
10. Development of structurally modified OER catalysts with enhanced performance and longevity for PEM-based electrolytic air dehumidification
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Ronghui Qi, Dujuan Li, Li-Zhi Zhang, and Wei Yan
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Anode catalyst ,Materials science ,Renewable Energy, Sustainability and the Environment ,business.industry ,Energy Engineering and Power Technology ,02 engineering and technology ,Electrolyte ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,01 natural sciences ,Accelerated aging ,Durability ,0104 chemical sciences ,Catalysis ,Fuel Technology ,0210 nano-technology ,Process engineering ,business - Abstract
PEM-based electrolytic air dehumidification is innovative in dehumidification that requires high precision and small space due to its high efficiency, compactness, and cleanness. However, the system dehumidification performance and durability are limited by using commercial Anatase-IrO2 catalysts. In this study, two types of structurally modified OER catalyst materials, ATO-IrO2 and ND-MnO2-IrO2, are developed to improve the performance of the system. System experiments showed that, compared to the commercial catalysts, the use of ATO-IrO2 and ND-MnO2-IrO2 as the anode catalyst can improve the dehumidification performance by 45% and 20%, respectively. Furthermore, in 50-h accelerated aging tests, the attenuation rates of the ATO-IrO2 and ND-MnO2-IrO2 systems are 3% and 8% respectively, which are far lower than the 35% attenuation of commercial catalyst. The results indicate that, as catalysts with a classic core-shell structure, ATO-IrO2 and ND-MnO2-IrO2 still have a significant impact on improving the performance of the electrolytic dehumidification systems.
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- 2021
11. Fused Group Lasso: A New EEG Classification Model With Spatial Smooth Constraint for Motor Imagery-Based Brain–Computer Interface
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Zhibin Zhu, Benxin Zhang, Li Zhi, Tianyou Yu, Shaorong Zhang, and Bao Feng
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business.industry ,Computer science ,Interface (computing) ,010401 analytical chemistry ,Pattern recognition ,01 natural sciences ,0104 chemical sciences ,Data set ,Motor imagery ,Lasso (statistics) ,Norm (mathematics) ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Instrumentation ,Shrinkage ,Brain–computer interface - Abstract
The traditional group sparse optimization method can simultaneously achieve the channel selection and classification for the motor imagery electroencephalogram (EEG) signals, but it doesn’t consider the spatial structure information between the electrode channels. Combining the group sparsity and spatial smoothness of EEG signals, a new EEG classification model is proposed, which is an improvement of group least absolute shrinkage and selection operator (LASSO). We call it fused group LASSO. First, group LASSO is used to model the group sparsity of EEG signals, the features of the same channel are assigned the same weights. Then, based on group LASSO, channel weights are regularized by total variation norm (TV-norm), which constrains the weights of adjacent channels to the same or similar, thereby the spatial smoothness modeling of EEG signals can be achieved. Using the primal-dual theory, an optimization algorithm for the new model is given. In order to verify the effectiveness of the new model, experiments were performed on two public brain-computer interface (BCI) competition data sets and one self-collected data set. Compared with the existing sparse optimization methods, the proposed method has achieved the highest average classification accuracy of 79.24%, 86.64% and 81.09%, respectively, and with better physiological interpretability. Compared with spatial filtering methods with smooth constraints, the proposed method realized global spatial smooth in a data-driver manner, and achieved the highest average classification accuracy of 84.96% in two competition data sets. All the experimental results showed that the proposed method can significantly improve the performance of BCI systems.
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- 2021
12. Reduced-order modeling of DFIG-based wind turbine connected into weak AC grid based on electromechanical time scale
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Han Wu, Rende Zhao, Hailiang Xu, Li Zhi, and Jiabing Hu
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Computer science ,020209 energy ,02 engineering and technology ,Turbine ,law.invention ,Electromechanical time scale ,020401 chemical engineering ,Control theory ,law ,0202 electrical engineering, electronic engineering, information engineering ,Phase-locked loop (PLL) ,0204 chemical engineering ,Electrical impedance ,Wind power ,State-space representation ,Rotor (electric) ,business.industry ,AC power ,Grid ,Doubly fed induction generator (DFIG) ,General Energy ,Weak AC grid ,lcsh:Electrical engineering. Electronics. Nuclear engineering ,business ,Wind turbine ,lcsh:TK1-9971 - Abstract
Nowadays, the stability issue of the doubly fed induction generator (DFIG)-based wind turbines tied into weak AC power grid has attracted more and more attention. To analyze the stability of such cascade system, it is a common way to establish the small-signal model of the whole system. Although there have been various modeling methods, few of them can be easily utilized in practice due to the high order of the presented models. To address this issue, this paper simplifies the fast time scale subsystems and proposes a reduced-order state space model of the DFIG system based on electromechanical time scale, considering the rotor current controller (RCC), the phase-locked loop (PLL), the remained value of the grid voltage, and the impedance of the weak AC grid as well. Based on the simplified model, the stability of the wind turbine during weak AC grid voltage dips can be easily analyzed. The correctness of the integrated model and its convenience for stability analysis have been proved by eigenvalue matching method and computer simulations.
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- 2020
13. Gemcitabine plus concurrent irreversible electroporation vs gemcitabine alone for locally advanced pancreatic cancer
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Hong-Mei Li, Li-Zhi Niu, Jibing Chen, Yan-Li Xing, Yin Leng, and Yang-Yang Ma
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endocrine system diseases ,business.industry ,Locally advanced pancreatic cancer ,fungi ,Clinical Trials Study ,General Medicine ,Irreversible electroporation ,urologic and male genital diseases ,Prognostic factors ,Gemcitabine ,03 medical and health sciences ,0302 clinical medicine ,030220 oncology & carcinogenesis ,medicine ,Cancer research ,Overall survival ,Progression free survival ,030211 gastroenterology & hepatology ,Progression-free survival ,business ,medicine.drug - Abstract
BACKGROUND Locally advanced pancreatic cancer (LAPC) is a common malignant digestive system tumor that ranks as the fourth leading cause of cancer-related death in the world. The prognosis of LAPC is poor even after standard treatment. Irreversible electroporation (IRE) is a novel ablative strategy for LAPC. Several studies have confirmed the safety of IRE. To date, no prospective studies have been performed to investigate the therapeutic efficacy of conventional gemcitabine (GEM) plus concurrent IRE. AIM To compare the therapeutic efficacy between conventional GEM plus concurrent IRE and GEM alone for LAPC. METHODS From February 2016 to September 2017, a total of 68 LAPC patients were treated with GEM plus concurrent IRE n = 33) or GEM alone n = 35). Overall survival (OS), progression free survival (PFS), and procedure-related complications were compared between the two groups. Multivariate analyses were performed to identify any prognostic factors. RESULTS There were no treatment-related deaths. The technical success rate of IRE ablation was 100%. The GEM + IRE group had a significantly longer OS from the time of diagnosis of LAPC (19.8 mo vs 9.3 mo, P < 0.0001) than the GEM alone group. The GEM + IRE group had a significantly longer PFS (8.3 mo vs 4.7 mo, P < 0.0001) than the GEM alone group. Tumor volume less than 37 cm3 and GEM plus concurrent IRE were identified as significant favorable factors for both the OS and PFS. CONCLUSION Gemcitabine plus concurrent IRE is an effective treatment for patients with LAPC.
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- 2020
14. In situ SAXS study of fractal structure of non-caking coal during carbonisation
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Zhihong Li, Wenyan Guo, Baoliang Lv, Guang Mo, Qi Lv, Dongfeng Li, Yixin Zhao, and Li-Zhi Liu
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010302 applied physics ,In situ ,Materials science ,business.industry ,Small-angle X-ray scattering ,Scattering ,Synchrotron radiation ,02 engineering and technology ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,01 natural sciences ,Fractal dimension ,Caking ,Fractal ,Chemical engineering ,0103 physical sciences ,Coal ,0210 nano-technology ,business - Abstract
The changes in fractal structure during high-temperature (1200°C) carbonisation of a Chinese non-caking coal were studied in situ by synchrotron radiation small-angle X-ray scattering (SAXS). The r...
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- 2020
15. Association Between Plasma Homocysteine Levels and Subclinical Hypothyroidism in Adult Subjects: A Meta-Analysis
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Fang-Fang Liu, Ya-Qing Zhang, Li-Zhi Li, Jin-Rong Guo, Kai Ma, Shao-Hua Chen, Shou-Fa Zhang, and Wei Zhang
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Adult ,Hyperhomocysteinemia ,medicine.medical_specialty ,Endocrinology, Diabetes and Metabolism ,Clinical Biochemistry ,030204 cardiovascular system & hematology ,Cochrane Library ,Biochemistry ,03 medical and health sciences ,0302 clinical medicine ,Endocrinology ,Hypothyroidism ,Risk Factors ,Internal medicine ,Humans ,Medicine ,Euthyroid ,030212 general & internal medicine ,Homocysteine ,Subclinical infection ,business.industry ,Biochemistry (medical) ,General Medicine ,Publication bias ,medicine.disease ,Meta-analysis ,Plasma homocysteine ,Observational study ,business - Abstract
Increased plasma homocysteine (Hcy) levels have been widely documented in patients with overt hypothyroidism; however, the significance of Hcy level changes in patients with subclinical hypothyroidism (SCH) remains controversial. The aim of this meta-analysis was to determine the Hcy status in patients with SCH compared with euthyroid subjects. We searched PubMed, Embase, and Cochrane Library databases prior to December 2019 to identify eligible studies and assessed the quality of selected studies using the Newcastle-Ottawa Quality Assessment Scale. Publication bias was evaluated by Begg’s test and Egger’s test. Meta-regression analysis was conducted to investigate the source of heterogeneity. A likely source of heterogeneity was the year of the study. All statistical analyses were performed with RevMan 5.3 and Stata 12.0 software. Our meta-analysis of twelve observational studies with 684 patients showed that those with SCH aged between 18 and 65 years old were associated with a slightly increased plasma Hcy level compared with euthyroid controls. The pooled result of the weighted mean difference (WMD) of increased tHcy levels was 1.16 μmol/l (95% CI: 0.51, 1.82; p=0.0005). The Hcy level in patients with SCH aged between 18 and 65 years old is significantly increased compared to euthyroid controls.
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- 2020
16. The independent risks and specific biomarker of breast cancer-related ischemic stroke
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Xue-Min Cheng, Zhijian Liang, Yunfei Wei, Chunyong Chen, Daobin Cheng, Dacheng Wang, Hong-Bin Liang, Shengyu Li, Li-Zhi Lu, Qixiong Qin, Guohui Li, and Haihua Li
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0301 basic medicine ,Oncology ,medicine.medical_specialty ,Breast Neoplasms ,Sensitivity and Specificity ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,Risk Factors ,Internal medicine ,Biomarkers, Tumor ,medicine ,Humans ,Aged ,Ischemic Stroke ,Retrospective Studies ,business.industry ,General Neuroscience ,Retrospective cohort study ,General Medicine ,Middle Aged ,medicine.disease ,humanities ,030104 developmental biology ,Ischemic stroke ,Biomarker (medicine) ,Female ,business ,030217 neurology & neurosurgery - Abstract
This retrospective study was designed to investigate the independent risks and specific biomarker for breast cancer-related ischemic stroke (BCRS).Clinical features and laboratory findings were compared between BCRS group and breast cancer group without stroke, and further multivariate analyses were performed to predict independent risks factors for BCRS patients. A receiver operator characteristic (ROC) curve analysis was configured to estimate the diagnostic efficacy of each independent risk and the product of these risks and to obtain the optimal cut-off value of diagnosis, which was termed the BCRS Index.BCRS patients had elevated plasma D-dimer and CA153 levels and platelet-to-lymphocyte ratio (PLR), as well as more patients received endocrine therapy (allEndocrine therapy, as well as elevated plasma D-dimer and CA153 levels and PLR values may be independent risks for BCRS. Furthermore, BCRS Index should be served as a novel specific biomarker for BCRS, which is useful to distinguish BCRS for clinicians.
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- 2020
17. Knockdown of Arginyl-tRNA Synthetase Attenuates Ischemia-Induced Cerebral Cortex Injury in Rats After Middle Cerebral Artery Occlusion
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Zi Wang, Li-Zhi Zhang, Xue-Bin Hu, Rong Fu, and Yang Liu
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Male ,medicine.medical_specialty ,Ischemia ,medicine.disease_cause ,Neuroprotection ,Brain Ischemia ,Small hairpin RNA ,Rats, Sprague-Dawley ,RNA interference ,Internal medicine ,Cortex (anatomy) ,medicine ,Animals ,Middle cerebral artery occlusion ,Injections, Intraventricular ,Cerebral Cortex ,Gene knockdown ,Glucose metabolism ,business.industry ,General Neuroscience ,Arginyl-tRNA synthetase ,Infarction, Middle Cerebral Artery ,Arginine-tRNA Ligase ,medicine.disease ,Rats ,medicine.anatomical_structure ,Endocrinology ,Cerebral cortex ,Oxidative stress ,Gene Knockdown Techniques ,Original Article ,Neurology (clinical) ,Mitochondrial function ,Cardiology and Cardiovascular Medicine ,business - Abstract
Some researchers have previously shown that RNAi knockdown of arginyl-tRNA synthetase (ArgRS) before or after a hypoxic injury can rescue animals from death, based on the model organism, C. elegans. However, there has been no study on the application of arginyl-tRNA synthetase knockdown in treating mammalian ischemic stroke, and its potential mechanism and effect on ischemic brain damage are still unknown. Here, we focused on the Rars gene, which encodes an arginyl-tRNA synthetase, and examined the effects of Rars knockdown in a permanent middle cerebral artery occlusion model in rats. To achieve this aim, adult male Sprague-Dawley (SD) rats were given right cerebral cortex injections of short hairpin RNA (shRNA) adenovirus (AV) particles to knock down arginyl-tRNA synthetase, and a non-targeting control (NTC) vector or phosphate-buffered solution served as the controls. After 4 days, the rats were exposed to permanent middle cerebral artery occlusion (pMCAO). Then, the right cerebral cortex level of arginyl-tRNA synthetase was examined, and the effects of the Rars knockdown were evaluated by differences in infarction volume, oxidative stress, blood-brain barrier, mitochondrial function, and glucose metabolism at 1 day and 3 days after MCAO. The injection of shRNA adenovirus particles successfully suppressed the expression of arginyl-tRNA synthetase in the cerebral cortex. We observed an improvement in oxidative stress, mitochondrial function, and glucose utilization and a reduction in brain edema compared with the non-targeting control rats with suppressed expression of arginyl-tRNA synthetase mRNA in the ipsilateral ischemic cortex of the brain. Our findings indicate that knockdown of arginyl-tRNA synthetase in the cerebral cortex exerted neuroprotective effects, which were achieved not only by the improvement of oxidative stress and glucose utilization but also by the maintenance of mitochondrial morphological integrity and the preservation of mitochondrial function. Knockdown of ArgRS administration could be a promising approach to protect ischemic stroke.
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- 2020
18. A mitotically active SMARCB1-deficient myoepithelioma-like tumour of the vulvar region with probable benign behaviour
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Zhang Fen, Li Zhi, Liu Jian, Chen Yu, and Wu Hongmei
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Pathology ,medicine.medical_specialty ,Myoepithelioma ,business.industry ,Medicine ,SMARCB1 ,business ,Pathology and Forensic Medicine - Published
- 2020
19. Different Numbers of Long-Pulse 1064-nm Nd-YAG Laser Treatments for Onychomycosis: A Pilot Study
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Linfeng Li, Dong-kun Wang, Rui-na Zhang, Jun-ying Zhao, Li-zhi Ma, and Feng-lin Zhuo
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Adult ,Male ,China ,Long pulse ,Article Subject ,Adolescent ,Dentistry ,Pilot Projects ,Lasers, Solid-State ,General Biochemistry, Genetics and Molecular Biology ,Group B ,Young Adult ,030207 dermatology & venereal diseases ,03 medical and health sciences ,Laser treatments ,0302 clinical medicine ,Onychomycosis ,Humans ,Medicine ,In patient ,030212 general & internal medicine ,Pulse ,Aged ,General Immunology and Microbiology ,business.industry ,Laser treatment ,Significant difference ,General Medicine ,Middle Aged ,Treatment Outcome ,Nails ,Nd:YAG laser ,Female ,business ,Research Article - Abstract
Purpose. To examine the benefits of different numbers of 1064-nm Nd-YAG laser treatments in patients with onychomycosis. Methods. This was a pilot study of patients with onychomycosis who were divided into three groups: four treatment sessions (group A), eight sessions (group B), and 12 sessions (group C). Only infected nails of degrees II–III (Scoring Clinical Index for Onychomycosis) were included. Treatment was given once a week using a long-pulse Nd-YAG 1064-nm laser. Patients were followed at 8, 16, and 24 weeks after the first treatment. Side effects were recorded. Results. Treatments were completed for 442 nails in 102 patients. The efficacy rates at 8, 16, and 24 weeks were 35.5%, 38.7%, and 37.4% for group A; 31.4%, 41.7%, and 44.0% for group B; and 27.7%, 50.0%, and 55.4% for group C, respectively. There was a significant difference in the efficacy rate at 24 weeks (P=0.016) between groups A and C, but not for groups A vs. B, or for groups B vs. C. No difference in the efficacy rate at 8 or 16 weeks was observed among the three groups. In all three groups, the efficacy was better for degree II nails than for degree III nails (all P<0.05). No side effects occurred. Conclusions. The 1064-nm Nd-YAG laser had clinical benefits against onychomycosis. Higher numbers of treatments provided better long-term (24-week) benefits, but had no impact on the short-term outcomes. The efficacy of laser treatment on degree II onychomycosis was better than for degree III.
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- 2020
20. Reactive Current Constraints and Coordinated Control of DFIG’s RSC and GSC During Asymmetric Grid Condition
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Rende Zhao, Hailiang Xu, Yufeng Zhang, Jiabing Hu, and Li Zhi
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Wind power ,General Computer Science ,biology ,Computer science ,business.industry ,Rotor (electric) ,Oscillation ,020209 energy ,020208 electrical & electronic engineering ,Control (management) ,General Engineering ,02 engineering and technology ,Grid ,law.invention ,Control theory ,law ,0202 electrical engineering, electronic engineering, information engineering ,biology.protein ,General Materials Science ,Chromatin structure remodeling (RSC) complex ,Current (fluid) ,business ,Doubly fed electric machine - Abstract
Doubly fed induction generator (DFIG) based wind turbines have been found to be very sensitive to asymmetrical grid fault, wherein the harmful oscillations in the electromagnetic torque has being made a big concern. What makes things harder is that latest grid codes require grid-connected wind turbines to possess the ability of positive- and negative-sequence reactive current supporting. Hence, it becomes a guide mechanism to meet the grid codes and to ensure the operation safety of the wind turbines. Even though a tradeoff could be made between them, it is still quite difficult to coordinate the current dispatch of the DFIG’s rotor- and grid-side converters (RSC and GSC), since there are totally eight currents needing to be carefully designed, i.e., the positive- and negative-sequence active and reactive currents in each converter. To address this issue, this article analyzes the reactive current constraints in detail, based on which a coordinated reactive current control strategy is put forward for the DFIG-based wind turbines during asymmetrical grid condition. Simulation studies demonstrate the effectiveness of the proposed strategy.
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- 2020
21. Irreversible electroporation for liver metastasis from pancreatic cancer: A case report
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Jibing Chen, Ke-Chen Xu, Juan-Juan Shi, Li-Zhi Niu, and Yang-Yang Ma
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medicine.medical_specialty ,medicine.medical_treatment ,Perforation (oil well) ,Tegafur ,Gastroenterology ,Metastasis ,03 medical and health sciences ,0302 clinical medicine ,Maintenance therapy ,Internal medicine ,Pancreatic cancer ,Irreversible electroporation ,Case report ,medicine ,Chemotherapy ,business.industry ,General Medicine ,Complete response ,medicine.disease ,030220 oncology & carcinogenesis ,Adenocarcinoma ,030211 gastroenterology & hepatology ,business ,Liver metastasis from pancreatic cancer ,medicine.drug - Abstract
Background Pancreatic cancer has a poor prognosis; 40%-50% of patients have liver metastases at the time of initial diagnosis and only 15%-20% undergo surgical resection. Irreversible electroporation (IRE) is a new, non-thermal local ablation method for solid tumors, which can induce cell membrane permeabilization, resulting in unrecoverable nanoscale perforation and apoptotic cell death without damaging the structural components of tissues. Case summary We report the case of a 66-year-old female patient with liver metastasis from pancreatic cancer with a pathological diagnosis of poorly differentiated adenocarcinoma. Carbohydrate antigen 19-9 was elevated to 420.3 U/mL. Computed tomography showed a pancreas mass of 2.7 cm × 2.5 cm and single liver metastasis of 1.4 cm × 1.1 cm in the S6 area. The patient underwent IRE and arterial infusion chemotherapy and received tegafur. The therapeutic effect of the combination treatment has been evaluated as complete response. To date, the patient has survived for > 12 mo and is receiving tegafur as maintenance therapy (at the time this case report was written). Conclusion IRE plus arterial infusion chemotherapy and tegafur may be synergistic, providing a reference for treating liver metastasis from pancreatic cancer.
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- 2020
22. Cryoablation for liver metastasis from solid pseudopapillary tumor of the pancreas: A case report
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Li-Zhi Niu, Juan-Juan Shi, Yang-Yang Ma, Ke-Chen Xu, and Jibing Chen
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Cryoablation ,medicine.medical_specialty ,business.industry ,medicine.medical_treatment ,General Medicine ,medicine.disease ,Metastasis ,Solid pseudopapillary tumor ,medicine.anatomical_structure ,Case report ,medicine ,Interventional embolization ,Radiology ,Pancreas ,business ,Liver metastasis - Abstract
BACKGROUND Solid pseudopapillary tumor (SPT) of the pancreas is a rare pancreatic tumor and 10% to 15% of cases are associated with metastasis. Cryoablation is a new method that can induce tumor necrosis, and treatment of tumors by cryoablation can cause anti-tumor immune responses. CASE SUMMARY A 16-year-old woman with SPT of the pancreas developed liver metastases 5.3 years after complete resection of the primary pancreatic tumor. She was admitted with chief complaints of abdominal pain in the upper abdomen and a weight loss of approximately 5 kg over 4 mo. Carbohydrate antigen (CA) 125, carcinoembryonic antigen, and CA 199 were normal. An abdominal computed tomography scan found multiple nodules in the right lobe of the liver that measured approximately 13.5 cm × 10.8 cm × 21.4 cm. Immunohistochemical staining results showed that CD10 and CD56 were positive, and the patient was diagnosed with SPT of the pancreas with liver metastasis. The patient underwent percutaneous cryoablation and interventional embolization. During the 5-year follow-up, the patient remained disease-free after cryoablation, with relatively normal immune function. CONCLUSION Herein, we for the first time report the treatment of liver metastasis from SPT of the pancreas using cryoablation plus interventional embolization, which could be a promising alternative therapy for pancreatic SPT liver metastasis.
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- 2020
23. Relative Phase Determination and Locking of High-order Transverse Mode of Laser
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马其旺 Ma Qi-wang, 郜江瑞 Gao Jiang-rui, 刘奎 Liu Kui, 李治 Li Zhi, and 孙恒信 Sun Heng-xin
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Materials science ,Optics ,business.industry ,law ,General Medicine ,Relative phase ,High order ,business ,Laser ,law.invention ,Transverse mode - Published
- 2020
24. Optimization of Interface Layers in Small Molecule Organic Tandem Solar Cells
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刘昱玮 Liu Yu-wei, 张 宇 Zhang Yu, 林志坚 Lin Zhi-jian, 李志祥 Li Zhi-xiang, 骆 昕 Luo Xin, 金 玉 Jin Yu, and 吴志军 Wu Zhi-jun
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Radiation ,Materials science ,Tandem ,business.industry ,Interface (Java) ,Optoelectronics ,Condensed Matter Physics ,business ,Small molecule ,Electronic, Optical and Magnetic Materials - Published
- 2020
25. Synchrotron Radiation-Based Three-Dimensional Visualization of Angioarchitectural Remodeling in Hippocampus of Epileptic Rats
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Qian-Fang Deng, Zhuohui Chen, Xianzhen Yin, Tiqiao Xiao, Shi-Xin Liu, Hui Wang, Mengqi Zhang, Xinhang Hu, Pan Gu, Bo Xiao, Hui Ding, Li-Zhi Li, Hong-Lei Li, Zhuolu Wang, Sheng-Hui Liao, Yu-Ze Cao, Zi-Hao Xu, and Shupeng Shi
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Male ,0301 basic medicine ,Pathology ,medicine.medical_specialty ,Neurology ,Physiology ,Hippocampus ,Synchrotron radiation ,Tortuosity ,Rats, Sprague-Dawley ,Pathogenesis ,03 medical and health sciences ,Epilepsy ,Imaging, Three-Dimensional ,0302 clinical medicine ,Animals ,Medicine ,medicine.diagnostic_test ,business.industry ,General Neuroscience ,General Medicine ,medicine.disease ,Rats ,030104 developmental biology ,medicine.anatomical_structure ,Angiography ,Original Article ,business ,Synchrotrons ,030217 neurology & neurosurgery ,Blood vessel - Abstract
Characterizing the three-dimensional (3D) morphological alterations of microvessels under both normal and seizure conditions is crucial for a better understanding of epilepsy. However, conventional imaging techniques cannot detect microvessels on micron/sub-micron scales without angiography. In this study, synchrotron radiation (SR)-based X-ray in-line phase-contrast imaging (ILPCI) and quantitative 3D characterization were used to acquire high-resolution, high-contrast images of rat brain tissue under both normal and seizure conditions. The number of blood microvessels was markedly increased on days 1 and 14, but decreased on day 60 after seizures. The surface area, diameter distribution, mean tortuosity, and number of bifurcations and network segments also showed similar trends. These pathological changes were confirmed by histological tests. Thus, SR-based ILPCI provides systematic and detailed views of cerebrovascular anatomy at the micron level without using contrast-enhancing agents. This holds considerable promise for better diagnosis and understanding of the pathogenesis and development of epilepsy.
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- 2019
26. Falling film liquid desiccant air dehumidification
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Lin Lu, Li-Zhi Zhang, Chuanshuai Dong, and Takashi Hibiki
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Desiccant ,business.industry ,Liquid desiccant ,Environmental science ,Falling (sensation) ,Process engineering ,business ,Lower energy - Abstract
Falling film liquid desiccant dehumidification technology is attracting more and more attention due to lower energy consumption, less pollution, and more flexible humidity control in recent years. This paper conducts a comprehensive review on falling film liquid desiccant dehumidification systems. Firstly, the working principles and features of the liquid desiccant dehumidification are introduced to describe the dehumidification process. The existing liquid desiccants including organic and inorganic desiccants are reviewed. Then, the structures of falling film dehumidifiers including both adiabatic dehumidifiers and internally-cooled dehumidifiers are described. Besides, the simulation models of falling film dehumidifiers, such as finite difference models, effectiveness NTU (e-NTU) models and simplified simulation models are summarized. Finally, the exiting performance enhancing methods of falling film dehumidifiers are collected, which provide valuable guidance to researchers and engineers to improve the dehumidification performance.
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- 2019
27. Effect of moxibustion on expressions of HSP70 mRNA and protein in gastric cancer-bearing rats
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Yan Peng, Shou-Xiang Yi, Ya-ping Lin, Huan Zhao, Jing Tan, Zhuo-jun Peng, and Li-zhi Ouyang
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medicine.medical_specialty ,medicine.medical_treatment ,0211 other engineering and technologies ,02 engineering and technology ,Moxibustion ,Zusanli ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Internal medicine ,021105 building & construction ,Extracellular ,Medicine ,business.industry ,Stomach ,Cancer ,medicine.disease ,030205 complementary & alternative medicine ,Hsp70 ,Endocrinology ,medicine.anatomical_structure ,Complementary and alternative medicine ,chemistry ,Cancer cell ,Growth inhibition ,business - Abstract
Objective: To observe the effect of moxibustion on the mRNA and protein expressions of heat-shock protein 70 (HSP70) in gastric cancer-bearing rats. Methods: A total of 40 healthy Sprague-Dawley (SD) rats were adaptively fed for one week. The gastric cancer model was prepared by Walker-256 cancer tissue transplantation. After 7 d, 10 rats were randomly selected to verify the successful modeling, and the remaining 30 rats were divided into a model group, a moxibustion group and an infrared group by the random number table method, with 10 rats in each group. After enrollment, the moxibustion group received suspended moxibustion at Zhongwan (CV 12), Guanyuan (CV 4) and bilateral Zusanli (ST 36), (the first group of acupoints) on the 1st day, and suspended moxibustion at bilateral Pishu (BL 20) and Weishu (BL 21), (the second group of acupoints) on the 2nd day, 20 min each time, once a day. Moxibustion was alternately performed every other day at the two groups of acupoints for 21 d. From the day of enrollment, rats in the infrared group were irradiated with the infrared radiation at the stomach area on the 1st day, and at the T12-T13 interspinous region on the 2nd day, 20 min each time, once a day, and the two locations were alternately irradiated every other day for 21 d. During the treatment, rats in the model group were intervened by grasping and fixation without treatment. At the end of the treatment, blood was collected from the inner eye orbit, and the HSP70 expression in peripheral blood was determined by enzyme linked immunosorbent assay (ELISA). Rats were sacrificed, the tumor volume and growth inhibition rate were measured. The position and changes of HSP70 in gastric cancer were observed by streptavidin-perosidase (SP); HSP70 protein expression was determined by ELISA; HSP70 mRNA expression in cancer tissues was determined by reverse transcription-polymerase chain reaction (RT-PCR) assay. Results: In comparison of the model group, the volume growth of the gastric cancer in the moxibustion group was significantly restricted (P
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- 2019
28. A novel mutation of COL7A1 in a Chinese DEB‐Pt family and review of the literature
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Li Zhi, Xuejun Zhang, Sen Yang, Bo Zhang, Cong Xin, Lili Tang, and Ling Jin
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Male ,medicine.medical_specialty ,Pathology ,Collagen Type VII ,Adolescent ,DNA Mutational Analysis ,Mutation, Missense ,Scars ,Dermatology ,Genetic analysis ,Young Adult ,030207 dermatology & venereal diseases ,03 medical and health sciences ,Exon ,0302 clinical medicine ,Asian People ,Dermis ,Exome Sequencing ,medicine ,COL7A1 Gene ,Humans ,Missense mutation ,Sequence Deletion ,Skin ,business.industry ,Exons ,Middle Aged ,Epidermolysis Bullosa Dystrophica ,Pedigree ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Mutation (genetic algorithm) ,Female ,Histopathology ,RNA Splice Sites ,medicine.symptom ,business - Abstract
Background Pretibial dystrophic epidermolysis bullosa (DEB-Pt) is an extremely rare subtype of dystrophic epidermolysis bullosa (DEB) characterized by blistering and scar formation. The pathogenesis of the disease is mainly due to the mutation of COL7A1 gene encoding type VII collagen fibers, resulting in the destruction of the anchoring structure of the epidermis and dermis. Aims The purpose of this study was to discover the major mutations in DEB-Pt by studying this family and reviewing the literature on DEB-Pt. Patients/methods We examined the patients by clinical manifestations and histopathology, extracted DNA from blood samples from 7 individuals in the family via FlexiGene DNA Kit, and then sequenced the samples using whole-exon sequencing (WES). Result Characteristic clinical manifestations such as blisters and scars were found in the patients. Genetic analysis revealed a missense mutation in exon 87(c.6860G>A) of COL7A1 gene, which has never been reported before. Conclusion The discovery of the new mutation extends the COL7A1 mutation database. We also reviewed all the mutation in DEB-Pt from relevant literature at home and abroad. This will facilitate the molecular diagnosis, treatment, and prognosis of DEB-Pt.
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- 2019
29. Characterization of the quasiparticle lifetime of microwave kinetic inductance detector
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Li Zhi, Zheng Wang, Qing Shi, Sheng-Cai Shi, Jing Li, and Wei-tao Lv
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Superconductivity ,Resonator ,Materials science ,business.industry ,Condensed Matter::Superconductivity ,Phase response ,Quasiparticle ,Optoelectronics ,Dilution refrigerator ,business ,LED circuit ,Microwave ,Pulse (physics) - Abstract
We design and fabricate a 350GHz 8×8 Al Microwave Kinetic Inductance Detector (MKIDs) array for the demonstration of its characteristics, mainly focus on the quasiparticle lifetime of the resonators. The quasiparticle lifetime data is collected by measuring a resonator’s phase response to a LED pulse at resonant frequency in a dilution refrigerator cooled to mK stage. We also measure and discuss the influence of various parameters on the change of quasiparticle lifetime, including different LED voltage supply, bath temperature of the MKIDs, and superconducting film thickness.
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- 2021
30. Optical design of a light-controlled pulsed x-ray source with photocathode
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Bao-Sheng Zhao, Li-Zhi Sheng, Xuehan Zhang, Qiang Pengfei, Hao Xuan, and Yong’an Liu
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Materials science ,business.industry ,Electromagnetic spectrum ,Electron ,Photon energy ,Cathode ,Photocathode ,law.invention ,Optics ,law ,Modulation ,Focal Spot Size ,business ,Voltage - Abstract
X-rays have the characteristics of high single photon energy, high frequency, and strong penetrating ability, are widely used in space communication, radiation imaging, medical diagnosis, non-destructive testing, and other fields. The development of X-rays has had a positive impact on broadening the use of the electromagnetic spectrum. As the core component of the X-ray application, high modulation rate, low power consumption, and excellent performance X-ray generators have been a hot research topic for decades. In this paper, a light-controlled pulsed X-ray source is modeled by simulation software. We perform simulation calculations and summary analysis on the effects of cathode structure, focus structure height, and metal anode voltage on the focal spot size, electron transit-time, and transit-time spread. At an operating voltage of 30KV, if the photocathode is 42mm in diameter, the focal spot diameter is about 1.5mm, the electron transit-time is 3.75ns, and the transit-time spread is 895ps when the focusing structure height is 6mm. And if the diameter of the photocathode is 12mm, the focal spot diameter is the smallest when the focusing pole height is 9mm, which is about 0.7mm, as for the time characteristics, the electron transit-time is 4.1ns, and the transit-time spread is 242ps. The results suggest that the light-controlled pulsed X-ray source is expected to be the next-generation source with easy modulation and short X-ray pulse properties.
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- 2021
31. Spatial X-ray detection system based on simultaneous communication and radar
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Sheng Li-Zhi, Chen Rui, Liu Jiani, Ma Weihong, Zhang Furui, Zhang Yingjun, Xia Fangyuan, Li Yao, Tan Zhenkun, and Su Tong
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Materials science ,business.industry ,media_common.quotation_subject ,X-ray ,Statistical and Nonlinear Physics ,engineering.material ,Condensed Matter Physics ,law.invention ,Optics ,Coating ,law ,engineering ,Contrast (vision) ,Radar ,business ,media_common - Abstract
An integrated scheme of X-ray communication and detection is proposed in this paper, which is used for the detection of the unknown target inside the coating while communication. In contrast to the X-ray communication methods reported previously, simultaneous communication and radar detection have two distinct features. One is that both communication and detection signals share the same X-ray source and channel, so the spatial resources can be effectively utilized. The other is that X-ray can penetrate the metal shielding structure and detect the internal materials effectively. In order to achieve the above goals, the propagation feasibility of an X-ray signal in space and space sparse plasma environment are first analyzed. Simulation and experiment results indicate that the X-ray carrier can realize transmission without attenuation in space environment. Then, an X-ray radar and communication demonstration system is built to verify the detection ability of coated materials. Experimental results show that when the characteristic spectrum value of the unknown target is much higher than that of the rest shell, the spatial X-ray radar system can achieve more accurate discrimination. Finally, a conclusion is reached, and some feasible detection suggestions are provided for this simultaneous detection and communication system.
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- 2021
32. Strategy of injectable hydrogel and its application in tissue engineering
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Wei Zhu, Yan-Wen Liu, Li-Zhi Zhou, Xi-Sheng Weng, and Pei-Fang Wei
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Tissue Engineering ,Tissue Scaffolds ,Chemistry ,business.industry ,lcsh:R ,MEDLINE ,lcsh:Medicine ,Biocompatible Materials ,Hydrogels ,General Medicine ,Hydrogel, Polyethylene Glycol Dimethacrylate ,Text mining ,Tissue engineering ,Perspective ,business ,Biomedical engineering - Published
- 2021
33. Identifying the Long-Term Thermal Storage Stability of SBS-Polymer-Modified Asphalt, including Physical Indexes, Rheological Properties, and Micro-Structures Characteristics
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Peng Wang, Xi-Yin Liu, Hong-Rui Wei, Li-zhi Wang, and Ren Ruibo
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relationship between macro performance and micro structures ,Materials science ,Environmental effects of industries and plants ,Correlation coefficient ,Softening point ,Renewable Energy, Sustainability and the Environment ,business.industry ,Attenuation ,Geography, Planning and Development ,partial least squares regression ,TJ807-830 ,Management, Monitoring, Policy and Law ,TD194-195 ,Thermal energy storage ,Renewable energy sources ,Environmental sciences ,Pavement engineering ,thermal storage stability ,polymer-modified asphalt ,Rheology ,Asphalt ,GE1-350 ,Composite material ,Ductility ,business - Abstract
The thermal storage stability of styrene–butadiene–styrene tri-block copolymer modified bitumen (SBSPMB) is the key to avoid performance attenuation during storage and transportation in pavement engineering. However, existing evaluation index softening point difference within 48 h (ΔSP48) cannot effectively distinguish this attenuation of SBSPMB. Thus, conventional physical indexes, rheological properties, and micro-structure characteristics of SBSPMB during a 10-day storage were investigated in this research. Results showed that during long-term thermal storage under 163 °C for 10 days, penetration, ductility, softening point, recovery rate (R%), and anti-rutting factor (G*/sinδ) were decayed with storage time increasing. This outcome was ascribed to the phase separation of SBS, which mainly occurred after a 4-day storage. However, ΔSP48 after a 6-day storage met the specification requirements (i.e., below 2.5 °C). Thus, the attenuation degree of asphalt performance in field storage was not effectively characterized by ΔSP48 alone. Results from network strength (I) and SBS swelling degree tests revealed that the primary cause was SBS degradation and base asphalt aging. Moreover, conventional indexes, including penetration, ductility, and softening point, were used to build a prediction model for rheological properties after long-term storage using partial least squares regression model, which can effectively predict I, R, Jnr, G*/sinδ, and SBS amount. Correlation coefficient is above 0.8. G*/sinδ and I at the top and bottom storage locations had high coefficient with SBS amount. Thus, phase separation of SBSPMB should be evaluated during thermal storage.
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- 2021
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34. Progress of NUV and FUV MCP-based photon-counting imaging detectors
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Li-zhi Sheng, Yong-an Liu, and Shizhao Li
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Physics ,business.industry ,Detector ,medicine.disease_cause ,Photocathode ,Photon counting ,Wavelength ,Optics ,Stack (abstract data type) ,medicine ,Quantum efficiency ,business ,Image resolution ,Ultraviolet - Abstract
Photon counting imaging technology has been widely used in nuclear radiation detection, space environment detection, astronomy observation, nuclear physics and ultra-weak bioluminescence. In this paper, the progress and parameters of NUV (160-320nm) and FUV (102-170nm) photon-counting imaging detectors were described. The NUV detector was developed based on a sealed MCP-image intensifier which comprises input window, photocathode, MCP stack, Ge-layer and its ceramic substrate. To maximize the quantum efficiency, a Cesium Telluride (Cs2Te) photocathode was adopted, which was deposited on input window and mounted close to the MCP. For the FUV detector, because of the lower cut-off wavelength, there are no suitable window materials in this band and the open-faced design should be used to meet the requirements of the detection. Therefore, a Cesium Iodide (CsI) photocathode deposited on the input surface of the MCP was used to optimize detector efficiency. By using an existing wedge and strip anode (WSA), the imaging performance of the NUV and FUV detectors was tested respectively. Experimental results show that the quantum efficiency of Cs2Te is 12.1% (at 230nm), the spatial resolution of NUV and FUV detectors is better than 70μm, the dark count rate of NUV and FUV detectors is about 10.5- and 2.3-counts/s*cm2 respectively.
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- 2021
35. Multiparameter MRI Radiomics Model Predicts Preoperative Peritoneal Carcinomatosis in Ovarian Cancer
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Aishi Liu, Guangming Niu, Yushan Jia, Hui Wu, Jialiang Ren, Yang Gao, Li-Zhi Xie, Xiao Yu Yu, and Fen'e Hao
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Cancer Research ,medicine.diagnostic_test ,Receiver operating characteristic ,business.industry ,Area under the curve ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,peritoneal carcinomatosis ,Magnetic resonance imaging ,Nomogram ,Logistic regression ,medicine.disease ,Peritoneal carcinomatosis ,ovarian cancer ,Radiomics ,Oncology ,radiomics ,medicine ,magnetic resonance imaging ,predictions ,business ,Ovarian cancer ,Nuclear medicine ,RC254-282 ,Original Research - Abstract
ObjectivesTo evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for peritoneal carcinomatosis (PC) in patients with ovarian cancer (OC).MethodsA total of 86 patients with epithelial OC were included in this retrospective study. All patients underwent FS-T2WI, DWI, and DCE-MRI scans, followed by total hysterectomy plus omentectomy. Quantitative imaging features were extracted from preoperative FS-T2WI, DWI, and DCE-MRI images, and feature screening was performed using a minimum redundancy maximum correlation (mRMR) and least absolute shrinkage selection operator (LASSO) methods. Four radiomics models were constructed based on three MRI sequences. Then, combined with radiomics characteristics and clinicopathological risk factors, a multi-factor Logistic regression method was used to construct a radiomics nomogram, and the performance of the radiomics nomogram was evaluated by receiver operating characteristic curve (ROC) curve, calibration curve, and decision curve analysis.ResultsThe radiomics model from the MP-MRI combined sequence showed a higher area under the curve (AUC) than the model from FS-T2WI, DWI, and DCE-MRI alone (0.846 vs. 0.762, 0.830, 0.807, respectively). The radiomics nomogram (AUC=0.902) constructed by combining radiomics characteristics and clinicopathological risk factors showed a better diagnostic effect than the clinical model (AUC=0.858) and the radiomics model (AUC=0.846). The decision curve analysis shows that the radiomics nomogram has good clinical application value, and the calibration curve also proves that it has good stability.ConclusionRadiomics nomogram based on MP-MRI combined sequence showed good predictive accuracy for PC in patients with OC. This tool can be used to identify peritoneal carcinomatosis in OC patients before surgery.
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- 2021
36. Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths
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Bastard, Paul, Gervais, Adrian, Le Voyer, Tom, Rosain, Jérémie, Philippot, Quentin, Manry, Jérémy, Michailidis, Eleftherios, Hoffmann, Hans-Heinrich, Eto, Shohei, Garcia-Prat, Marina, Bizien, Lucy, Parra-Martínez, Alba, Yang, Rui, Haljasmägi, Liis, Migaud, Mélanie, Särekannu, Karita, Maslovskaja, Julia, de Prost, Nicolas, Tandjaoui-Lambiotte, Yacine, Luyt, Charles-Edouard, Amador-Borrero, Blanca, Gaudet, Alexandre, Poissy, Julien, Morel, Pascal, Richard, Pascale, Cognasse, Fabrice, Troya, Jesus, Trouillet-Assant, Sophie, Belot, Alexandre, Saker, Kahina, Garçon, Pierre, Rivière, Jacques G., Lagier, Jean-Christophe, Gentile, Stéphanie, Rosen, Lindsey B., Shaw, Elana, Morio, Tomohiro, Tanaka, Junko, Dalmau, David, Tharaux, Pierre-Louis, Sene, Damien, Stepanian, Alain, Megarbane, Bruno, Triantafyllia, Vasiliki, Fekkar, Arnaud, Heath, James R., Franco, José Luis, Anaya, Juan-Manuel, Solé-Violán, Jordi, Imberti, Luisa, Biondi, Andrea, Bonfanti, Paolo, Castagnoli, Riccardo, Delmonte, Ottavia M., Zhang, Yu, Snow, Andrew L., Holland, Steven M., Biggs, Catherine M., Moncada-Vélez, Marcela, Arias, Andrés Augusto, Lorenzo, Lazaro, Boucherit, Soraya, Coulibaly, Boubacar, Anglicheau, Dany, Planas, Anna M., Haerynck, Filomeen, Duvlis, Sotirija, Nussbaum, Robert L., Ozcelik, Tayfun, Keles, Sevgi, Bousfiha, Ahmed A., El Bakkouri, Jalila, Ramirez-Santana, Carolina, Paul, Stéphane, Pan-Hammarström, Qiang, Hammarström, Lennart, Dupont, Annabelle, Kurolap, Alina, Metz, Christine N., Aiuti, Alessandro, Casari, Giorgio, Lampasona, Vito, Ciceri, Fabio, Barreiros, Lucila A., Dominguez-Garrido, Elena, Vidigal, Mateus, Zatz, Mayana, van de Beek, Diederik, Sahanic, Sabina, Tancevski, Ivan, Stepanovskyy, Yurii, Boyarchuk, Oksana, Nukui, Yoko, Tsumura, Miyuki, Vidaur, Loreto, Tangye, Stuart G., Burrel, Sonia, Duffy, Darragh, Quintana-Murci, Lluis, Klocperk, Adam, Kann, Nelli Y., Shcherbina, Anna, Lau, Yu-Lung, Leung, Daniel, Coulongeat, Matthieu, Marlet, Julien, Koning, Rutger, Reyes, Luis Felipe, Chauvineau-Grenier, Angélique, Venet, Fabienne, Monneret, Guillaume, Nussenzweig, Michel C., Arrestier, Romain, Boudhabhay, Idris, Baris-Feldman, Hagit, Hagin, David, Wauters, Joost, Meyts, Isabelle, Dyer, Adam H., Kennelly, Sean P., Bourke, Nollaig M., Halwani, Rabih, Sharif-Askari, Narjes Saheb, Dorgham, Karim, Sallette, Jérome, Mehlal Sedkaoui, Souad, AlKhater, Suzan, Rigo-Bonnin, Raúl, Morandeira, Francisco, Roussel, Lucie, Vinh, Donald C., Ostrowski, Sisse Rye, Condino-Neto, Antonio, Prando, Carolina, Bondarenko, Anastasiia, Spaan, András N., Gilardin, Laurent, Fellay, Jacques, Lyonnet, Stanislas, Bilguvar, Kaya, Lifton, Richard P., Mane, Shrikant, Anderson, Mark S., Boisson, Bertrand, Béziat, Vivien, Zhang, Shen-Ying, Andreakos, Evangelos, Hermine, Olivier, Pujol, Aurora, Peterson, Pärt, Mogensen, Trine H., Rowen, Lee, Mond, James, Debette, Stéphanie, de Lamballerie, Xavier, Duval, Xavier, Mentré, France, Zins, Marie, Soler-Palacin, Pere, Colobran, Roger, Gorochov, Guy, Solanich, Xavier, Susen, Sophie, Martinez-Picado, Javier, Raoult, Didier, Vasse, Marc, Gregersen, Peter K., Piemonti, Lorenzo, Rodríguez-Gallego, Carlos, Notarangelo, Luigi D., Su, Helen C., Kisand, Kai, Okada, Satoshi, Puel, Anne, Jouanguy, Emmanuelle, Rice, Charles M., Tiberghien, Pierre, Zhang, Qian, Cobat, Aurélie, Abel, Laurent, Casanova, Jean-Laurent, Bigio, Benedetta, de la Chapelle, Aliénor, Chen, Jie, Chrabieh, Maya, Liu, Dana, Nemirowskaya, Yelena, Cruz, Inés Marín, Materna, Marie, Pelet, Sophie, Seeleuthner, Yoann, Thibault, Chloé, Liu, Zhiyong, Abad, Jorge, Accordino, Giulia, Achille, Cristian, Aguilera-Albesa, Sergio, Aguiló-Cucurull, Aina, Özkan, Esra Akyüz, Darazam, Ilad Alavi, Roblero Albisures, Jonathan Antonio, Aldave, Juan C, Ramos, Miquel Alfonso, Khan, Taj Ali, Aliberti, Anna, Nadji, Seyed Alireza, Alkan, Gulsum, Alkhater, Suzan A., Allardet-Servent, Jerome, Allende, Luis M, Alonso-Arias, Rebeca, Alshahrani, Mohammed S, Alsina, Laia, Alyanakian, Marie-Alexandra, Borrero, Blanca Amador, Amoura, Zahir, Antolí, Arnau, Aubart, Mélodie, Auguet, Teresa, Avramenko, Iryna, Aytekin, Gökhan, Azot, Axelle, Bahram, Seiamak, Bajolle, Fanny, Baldanti, Fausto, Baldolli, Aurélie, Ballester, Maite, Feldman, Hagit Baris, Barrou, Benoit, Barzagh, Federica, Basso, Sabrina, Bayhan, Gulsum Iclal, Bezrodnik, Liliana, Bilbao, Agurtzane, Blanchard-Rohner, Geraldine, Blanco, Ignacio, Blandinières, Adeline, Blázquez-Gamero, Daniel, Bleibtreu, Alexandre, Bloomfield, Marketa, Bolivar-Prados, Mireia, Borghesi, Alessandro, Borie, Raphael, Botdhlo-Nevers, Elisabeth, Bousfiha, Ahmed A, Bousquet, Aurore, Boutolleau, David, Bouvattier, Claire, Bravais, Juliette, Briones, M. Luisa, Brunner, Marie-Eve, Bruno, Raffaele, Bueno, Maria Rita P, Bukhari, Huda, Bustamante, Jacinta, Cáceres Agra, Juan José, Capra, Ruggero, Carapito, Raphael, Carrabba, Maria, Casasnovas, Carlos, Caseris, Marion, Cassaniti, Irene, Castelle, Martin, Castelli, Francesco, de Vera, Martín Castillo, Castro, Mateus V, Catherinot, Emilie, Celik, Jale Bengi, Ceschi, Alessandro, Chalumeau, Martin, Charbit, Bruno, Cheng, Matthew P., Clavé, Père, Clotet, Bonaventura, Codina, Anna, Cohen, Yves, Comarmond, Cloé, Combes, Alain, Comoli, Patrizia, Corsico, Angelo G, Coşkuner, Taner, Cvetkovski, Aleksandar, Cyrus, Cyril, Danion, François, Darley, David Ross, Das, Vincent, Dauby, Nicolas, Dauger, Stéphane, De Munter, Paul, de Pontual, Loic, Dehban, Amin, Delplancq, Geoffroy, Demoule, Alexandre, Desguerre, Isabelle, Di Sabatino, Antonio, Diehl, Jean-Luc, Dobbelaere, Stephanie, Domínguez-Garrido, Elena, Dubost, Clément, Ekwall, Olov, Bozdemir, Şefika Elmas, Elnagdy, Marwa H, Emiroglu, Melike, Endo, Akifumi, Erdeniz, Emine Hafize, Aytekin, Selma Erol, Lasa, Maria Pilar Etxart, Euvrard, Romain, Fabio, Giovanna, Faivre, Laurence, Falck, Antonin, Fartoukh, Muriel, Faure, Morgane, Arquero, Miguel Fernandez, Ferrer, Ricard, Ferreres, Jose, Flores, Carlos, Francois, Bruno, Fumadó, Victoria, Fung, Kitty S C, Fusco, Francesca, Gagro, Alenka, Solis, Blanca Garcia, Gaussem, Pascale, Gayretli, Zeynep, Gil-Herrera, Juana, Gatineau, Audrey Giraud, Girona-Alarcón, Mònica, Cifuentes Godínez, Karen Alejandra, Goffard, Jean-Christophe, Gonzales, Nacho, Gonzalez-Granado, Luis I, González-Montelongo, Rafaela, Guerder, Antoine, Gülhan, Belgin, Gumucio, Victor Daniel, Hanitsch, Leif Gunnar, Gunst, Jan, Gut, Marta, Hadjadj, Jérôme, Hancerli, Selda, Hariyan, Tetyana, Hatipoglu, Nevin, Heppekcan, Deniz, Hernandez-Brito, Elisa, Ho, Po-ki, Holanda-Peña, María Soledad, Horcajada, Juan P, Hraiech, Sami, Humbert, Linda, Hung, Ivan F N, Iglesias, Alejandro D., Íñigo-Campos, Antonio, Jamme, Matthieu, Arranz, María Jesús, Jimeno, Marie-Thérèse, Jordan, Iolanda, Yüksek, Saliha Kanık, Kara, Yalcin Burak, Karahan, Aydın, Karbuz, Adem, Yasar, Kadriye Kart, Kasapcopur, Ozgur, Kashimada, Kenichi, Demirkol, Yasemin Kendir, Kido, Yasutoshi, Kizil, Can, Kılıç, Ahmet Osman, Koutsoukou, Antonia, Król, Zbigniew J., Ksouri, Hatem, Kuentz, Paul, Kwan, Arthur M C, Kwan, Yat Wah M, Kwok, Janette S Y, Lam, David S Y, Lampropoulou, Vicky, Lanternier, Fanny, Le Bourgeois, Fleur, Leo, Yee-Sin, Lopez, Rafael Leon, Levin, Michael, Levy, Michael, Lévy, Romain, Li, Zhi, Lilleri, Daniele, Lima, Edson Jose Adrian Bolanos, Linglart, Agnes, López-Collazo, Eduardo, Lorenzo-Salazar, José M., Louapre, Céline, Lubetzki, Catherine, Lung, Kwok-Cheung, Lye, David C, Magnone, Cinthia, Mansouri, Davood, Marchioni, Enrico, Marioli, Carola, Marjani, Majid, Marques, Laura, Pereira, Jesus Marquez, Martín-Nalda, Andrea, Pueyo, David Martínez, Marzana, Iciar, Mata-Martínez, Carmen, Mathian, Alexis, Matos, Larissa RB, Matthews, Gail V, Mayaux, Julien, McLaughlin-Garcia, Raquel, Meersseman, Philippe, Mège, Jean-Louis, Mekontso-Dessap, Armand, Melki, Isabelle, Meloni, Federica, Meritet, Jean-François, Merlani, Paolo, Akcan, Özge Metin, Mezidi, Mehdi, Migeotte, Isabelle, Millereux, Maude, Million, Matthieu, Mirault, Tristan, Mircher, Clotilde, Mirsaeidi, Mehdi, Mizoguchi, Yoko, Modi, Bhavi P, Mojoli, Francesco, Moncomble, Elsa, Melián, Abián Montesdeoca, Martinez, Antonio Morales, Morange, Pierre-Emmanuel, Mordacq, Clémence, Morelle, Guillaume, Mouly, Stéphane J, Muñoz-Barrera, Adrián, Nafati, Cyril, Nagashima, Shintaro, Nakagama, Yu, Neven, Bénédicte, Neves, João Farela, Ng, Lisa FP, Ng, Yuk-Yung, Nielly, Hubert, Medina, Yeray Novoa, Cuadros, Esmeralda Nuñez, Ocejo-Vinyals, J. 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Montse, Ruiz del Prado, Maria Yolanda, Ruiz-Rodriguez, Juan Carlos, Sabater-Riera, Joan, Saks, Kai, Salagianni, Maria, Sanchez, Oliver, Sánchez-Montalvá, Adrián, Sánchez-Ramón, Silvia, Schidlowski, Laire, Schluter, Agatha, Schmidt, Julien, Schmidt, Matthieu, Schuetz, Catharina, Schweitzer, Cyril E, Scolari, Francesco, Sediva, Anna, Seijo, Luis, Seminario, Analia Gisela, Seng, Piseth, Senoglu, Sevtap, Seppänen, Mikko, Llovich, Alex Serra, Shahrooei, Mohammad, Siguret, Virginie, Siouti, Eleni, Smadja, David M, Smith, Nikaia, Sobh, Ali, Soler, Catherine, Soler-Palacín, Pere, Sözeri, Betül, Stella, Giulia Maria, Stepanovskiy, Yuriy, Stoclin, Annabelle, Taccone, Fabio, Taupin, Jean-Luc, Tavernier, Simon J, Tello, Loreto Vidaur, Terrier, Benjamin, Thiery, Guillaume, Thorball, Christian, THORN, Karolina, Thumerelle, Caroline, Tipu, Imran, Tolstrup, Martin, Tomasoni, Gabriele, Toubiana, Julie, Alvarez, Josep Trenado, Troya, Jesús, Tsang, Owen T Y, Tserel, Liina, Tso, Eugene Y K, Tucci, Alessandra, Tüter Öz, Şadiye Kübra, Ursini, Matilde Valeria, Utsumi, Takanori, Uzunhan, Yurdagul, Vabres, Pierre, Valencia-Ramos, Juan, Van Den Rym, Ana Maria, Vandernoot, Isabelle, Velez-Santamaria, Valentina, Zuniga Veliz, Silvia Patricia, Vidigal, Mateus C, Viel, Sébastien, Vilain, Cédric, Vilaire-Meunier, Marie E, Villar-García, Judit, Vincent, Audrey, Vogt, Guillaume, Voiriot, Guillaume, Volokha, Alla, Vuotto, Fanny, Wauters, Els, Wu, Alan K L, Wu, Tak-Chiu, Yahşi, Aysun, Yesilbas, Osman, Yildiz, Mehmet, Young, Barnaby E, Yükselmiş, Ufuk, Zecca, Marco, Zuccaro, Valentina, Jens, Van Praet, Lambrecht, Bart N., Eva, Van Braeckel, Cédric, Bosteels, Levi, Hoste, Eric, Hoste, Bauters, Fré, De Clercq, Jozefien, Cathérine, Heijmans, Hans, Slabbynck, Leslie, Naesens, Florkin, Benoit, Boulanger, Cécile, Vanderlinden, Dimitri, Foti, Giuseppe, Bellani, Giacomo, Citerio, Giuseppe, Contro, Ernesto, Pesci, Alberto, Valsecchi, Maria Grazia, Cazzaniga, Marina, Danielson, Jeffrey J., Dobbs, Kerry, Kashyap, Anuj, Ding, Li, Dalgard, Clifton L., Sottini, Alessandra, Quaresima, Virginia, Quiros-Roldan, Eugenia, Rossi, Camillo, Bettini, Laura Rachele, D’Angio’, Mariella, Beretta, Ilaria, Montagna, Daniela, Licari, Amelia, Marseglia, Gian Luigi, Batten, Isabella, Reddy, Conor, McElheron, Matt, Noonan, Claire, Connolly, Emma, Fallon, Aoife, Storgaard, Merete, Jørgensen, Sofie, Erikstrup, Christian, Pedersen, Ole Birger, Sørensen, Erik, Mikkelsen, Susan, Dinh, Khoa Manh, Larsen, Margit Anita Hørup, Paulsen, Isabella Worlewenut, Von Stemann, Jakob Hjorth, Hansen, Morten Bagge, Townsend, Liam, Cheallaigh, Cliona Ni, Bergin, Colm, Martin-Loeches, Ignacio, Dunne, Jean, Conlon, Niall, Bourke, Nollaig, O'Farrelly, Cliona, Allavena, Clotilde, Andrejak, Claire, Angoulvant, François, Azoulay, Cecile, Bachelet, Delphine, Bartoli, Marie, Basmaci, Romain, Behilill, Sylvie, Beluze, Marine, Benech, Nicolas, Benkerrou, Dehbia, Bhavsar, Krishna, Bitker, Laurent, Bouadma, Lila, Bouscambert-Duchamp, 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Nawal, Migaud, Maria-Claire, Djossou, Félix, Mergeay-Fabre, Mayka, Lucarelli, Aude, Demar, Magalie, Bruneau, Léa, Gérardin, Patrick, Maillot, Adrien, Payet, Christine, Laviolle, Bruno, Paris, Christophe, Desille-Dugast, Mireille, Fouchard, Julie, Pistone, Thierry, Perreau, Pauline, Gissot, Valérie, Le Goas, Carole, Montagne, Samatha, Richard, Lucie, Bouiller, Kévin, Desmarets, Maxime, Meunier, Alexandre, Lefévre, Benjamin, Jeulin, Hélène, Legrand, Karine, Lomazzi, Sandra, Tardy, Bernard, Gagneux-Brunon, Amandine, Bertholon, Frédérique, Botelho-Nevers, Elisabeth, Kouakam, Christelle, Leturque, Nicolas, Roufai, Layidé, Amat, Karine, Espérou, Hélène, Hendou, Samia, van Agtmael, Michiel, Algera, Anne Geke, Appelman, Brent, van Baarle, Frank, Bax, Diane, Beudel, Martijn, Bogaard, Harm Jan, Bomers, Marije, Bonta, Peter, Bos, Lieuwe, Botta, Michela, de Brabander, Justin, de Bree, Godelieve, de Bruin, Sanne, Buis, David T.P., Bugiani, Marianna, Bulle, Esther, Chouchane, Osoul, Cloherty, Alex, 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Michèle, Wouters, Dorien, Zwinderman, A. H (Koos, Brouwer, Matthijs C., Wiersinga, W. Joost, Vlaar, Alexander P.J., Al-Muhsen, Saleh, Al-Mulla, Fahd, Arias, Andrés A., Bogunovic, Dusan, Bolze, Alexandre, Bryceson, Yenan, Bustamante, Carlos D., Butte, Manish J., Chakravorty, Samya, Christodoulou, John, Constantinescu, Stefan N., Cooper, Megan A., Desai, Murkesh, Drolet, Beth A., El Baghdadi, Jamila, Espinosa-Padilla, Sara, Froidure, Antoine, Henrickson, Sarah E., Hsieh, Elena W.Y., Husebye, Eystein S., Imai, Kohsuke, Itan, Yuval, Jarvis, Erich D., Karamitros, Timokratis, Ku, Cheng-Lung, Ling, Yun, Lucas, Carrie L., Maniatis, Tom, Maródi, László, Milner, Joshua D., Mironska, Kristina, Ng, Lisa F.P., Novelli, Antonio, Novelli, Giuseppe, de Diego, Rebeca Perez, Renia, Laurent, Resnick, Igor, Sancho-Shimizu, Vanessa, Seppänen, Mikko R.J., Shahrooei, Mohammed, Slaby, Ondrej, Abou Tayoun, Ahmad, Ramaswamy, Sathishkumar, Turvey, Stuart E, Uddin, K M Furkan, Uddin, Mohammed J., von Bernuth, Horst, Zawadzki, Pawel, Nadif, Rachel, Goldberg, Marcel, Ozguler, Anna, Henny, Joseph, Lemonnier, Sylvie, Coeuret-Pellicer, Mireille, Le Got, Stéphane, Tzourio, Christophe, Dufouil, Carole, Soumaré, Aïcha, Lachaize, Morgane, Fievet, Nathalie, Flaig, Amandine, Martin, Fernando, Bonneaudeau, Brigitte, Cannet, Dorothée, Gallian, Pierre, Jeanne, Michel, Perroquin, Magali, Hamzeh-Cognasse, Hind, Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Groupe de recherche clinique CARMAS (Cardiovascular and Respiratory Manifestations of Acute lung injury and Sepsis) (CARMAS), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-CHU Henri Mondor [Créteil], Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Hôpital Lariboisière-Fernand-Widal [APHP], Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Hôpital Roger Salengro [Lille], Etablissement Français du Sang [La Plaine Saint-Denis] (EFS), Interactions hôte-greffon-tumeur, ingénierie cellulaire et génique - UFC (UMR INSERM 1098) (RIGHT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS BFC)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Santé Ingénierie Biologie Saint-Etienne (SAINBIOSE), Centre Ingénierie et Santé (CIS-ENSMSE), École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Etablissement français du sang - Auvergne-Rhône-Alpes (EFS), Hospices Civils de Lyon (HCL), Centre International de Recherche en Infectiologie (CIRI), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Grand Hôpital de l'Est Francilien (GHEF), Microbes évolution phylogénie et infections (MEPHI), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institut Hospitalier Universitaire Méditerranée Infection (IHU Marseille), Assistance Publique - Hôpitaux de Marseille (APHM), Centre d'études et de recherche sur les services de santé et la qualité de vie (CEReSS), Aix Marseille Université (AMU), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Recherche clinique appliquée à l'hématologie ((EA_3518)), Université Paris Diderot - Paris 7 (UPD7), Service de Réanimation Médicale et Toxicologique [Hôpital Lariboisière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Lariboisière-Fernand-Widal [APHP], Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut Necker Enfants-Malades (INEM - UM 111 (UMR 8253 / U1151)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Centre d'Investigation Clinique - Epidémiologie Clinique Saint-Etienne (CIC-EC), Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Récepteurs Nucléaires, Maladies Métaboliques et Cardiovasculaires - U1011 (RNMCD), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Immunologie Translationnelle - Translational Immunology lab, Institut Pasteur [Paris] (IP), Génétique Evolutive Humaine - Human Evolutionary Genetics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Collège de France - Chaire Génomique humaine et évolution, Collège de France (CdF (institution)), CHU Trousseau [Tours], Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Morphogénèse et antigénicité du VIH et du virus des Hépatites (MAVIVH - U1259 Inserm - CHRU Tours ), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Robert Ballanger [Aulnay-sous-Bois], Hôpital Edouard Herriot [CHU - HCL], Physiopathologie de l'immunodépression associée aux réponses inflammatoires systémiques / Pathophysiology of Injury-induced Immunosuppression (PI3), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Centre d'Immunologie et des Maladies Infectieuses (CIMI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Hôpital Jean Verdier [AP-HP], Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité des Virus Emergents (UVE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'investigation Clinique [CHU Bichat] - Épidémiologie clinique (CIC 1425), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Cohortes épidémiologiques en population (CONSTANCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Université Paris Cité (UPCité), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Modeling & analysis for medical imaging and Diagnosis (MYRIAD), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques (LCBPT - UMR 8601), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Agents infectieux, résistance et chimiothérapie - UR UPJV 4294 (AGIR ), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie, CHU Amiens-Picardie, French COVID cohort study group, Howard Hughes Medical Institute, Rockefeller University, European Commission, Jeffrey Modell Foundation, Université de Bordeaux, Meath Foundation, National Human Genome Research Institute, Agence Nationale de la Recherche, Fondation pour la Recherche Médicale, Fondation du Souffle, Instituto de Salud Carlos III, Institut National de la Santé et de la Recherche Médicale, St. Giles Foundation, Ministère des Solidarités et de la Santé, Sorbonne Université, Mutuelle Générale de l'Education Nationale, Conseil Régional Aquitaine, Conseil régional de Bourgogne-Franche-Comté, Meyer Foundation, Fondation de France, National Cancer Institute, European Regional Development Fund, Fundación DISA, Ministero della Salute, ANR-20-COVI-0003,GENCOVID,Identification des défauts monogéniques de l'immunité responsables des formes sévères de COVID-19 chez les patients précédemment en bonne santé(2020), ANR-20-CE93-0003,GENVIR,Analyse multi-omique de l'immunité anti-virale: de l'identification des circuits biologiques pertinents à la découverte de défauts monogéniques héréditaires de l'immunité chez les patients avec infections virales sévères(2020), ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), European Project: IdEx Bordeaux (ANR-10-IDEX- 003-02), Bastard, Paul, Gervais, Adrian, Le Voyer, Tom, Rosain, Jérémie, Philippot, Quentin, Manry, Jérémy, Michailidis, Eleftherio, Hoffmann, Hans-Heinrich, Eto, Shohei, Garcia-Prat, Marina, Bizien, Lucy, Parra-Martínez, Alba, Yang, Rui, Haljasmägi, Lii, Migaud, Mélanie, Särekannu, Karita, Maslovskaja, Julia, de Prost, Nicola, Tandjaoui-Lambiotte, Yacine, Luyt, Charles-Edouard, Amador-Borrero, Blanca, Gaudet, Alexandre, Poissy, Julien, Morel, Pascal, Richard, Pascale, Cognasse, Fabrice, Troya, Jesu, Trouillet-Assant, Sophie, Belot, Alexandre, Saker, Kahina, Garçon, Pierre, Rivière, Jacques G, Lagier, Jean-Christophe, Gentile, Stéphanie, Rosen, Lindsey B, Shaw, Elana, Morio, Tomohiro, Tanaka, Junko, Dalmau, David, Tharaux, Pierre-Loui, Sene, Damien, Stepanian, Alain, Megarbane, Bruno, Triantafyllia, Vasiliki, Fekkar, Arnaud, Heath, James R, Franco, José Lui, Anaya, Juan-Manuel, Solé-Violán, Jordi, Imberti, Luisa, Biondi, Andrea, Bonfanti, Paolo, Castagnoli, Riccardo, Delmonte, Ottavia M, Zhang, Yu, Snow, Andrew L, Holland, Steven M, Biggs, Catherine, Moncada-Vélez, Marcela, Arias, Andrés Augusto, Lorenzo, Lazaro, Boucherit, Soraya, Coulibaly, Boubacar, Anglicheau, Dany, Planas, Anna M, Haerynck, Filomeen, Duvlis, Sotirija, Nussbaum, Robert L, Ozcelik, Tayfun, Keles, Sevgi, Bousfiha, Ahmed A, El Bakkouri, Jalila, Ramirez-Santana, Carolina, Paul, Stéphane, Pan-Hammarström, Qiang, Hammarström, Lennart, Dupont, Annabelle, Kurolap, Alina, Metz, Christine N, Aiuti, Alessandro, Casari, Giorgio, Lampasona, Vito, Ciceri, Fabio, Barreiros, Lucila A, Dominguez-Garrido, Elena, Vidigal, Mateu, Zatz, Mayana, van de Beek, Diederik, Sahanic, Sabina, Tancevski, Ivan, Stepanovskyy, Yurii, Boyarchuk, Oksana, Nukui, Yoko, Tsumura, Miyuki, Vidaur, Loreto, Tangye, Stuart G, Burrel, Sonia, Duffy, Darragh, Quintana-Murci, Llui, Klocperk, Adam, Kann, Nelli Y, Shcherbina, Anna, Lau, Yu-Lung, Leung, Daniel, Coulongeat, Matthieu, Marlet, Julien, Koning, Rutger, Reyes, Luis Felipe, Chauvineau-Grenier, Angélique, Venet, Fabienne, Monneret, Guillaume, Nussenzweig, Michel C, Arrestier, Romain, Boudhabhay, Idri, Baris-Feldman, Hagit, Hagin, David, Wauters, Joost, Meyts, Isabelle, Dyer, Adam H, Kennelly, Sean P, Bourke, Nollaig M, Halwani, Rabih, Sharif-Askari, Narjes Saheb, Dorgham, Karim, Sallette, Jérome, Sedkaoui, Souad Mehlal, Alkhater, Suzan, Rigo-Bonnin, Raúl, Morandeira, Francisco, Roussel, Lucie, Vinh, Donald C, Ostrowski, Sisse Rye, Condino-Neto, Antonio, Prando, Carolina, Bonradenko, Anastasiia, Spaan, András N, Gilardin, Laurent, Fellay, Jacque, Lyonnet, Stanisla, Bilguvar, Kaya, Lifton, Richard P, Mane, Shrikant, Anderson, Mark S, Boisson, Bertrand, Béziat, Vivien, Zhang, Shen-Ying, Vandreakos, Evangelo, Hermine, Olivier, Pujol, Aurora, Peterson, Pärt, Mogensen, Trine H, Rowen, Lee, Mond, Jame, Debette, Stéphanie, de Lamballerie, Xavier, Duval, Xavier, Mentré, France, Zins, Marie, Soler-Palacin, Pere, Colobran, Roger, Gorochov, Guy, Solanich, Xavier, Susen, Sophie, Martinez-Picado, Javier, Raoult, Didier, Vasse, Marc, Gregersen, Peter K, Piemonti, Lorenzo, Rodríguez-Gallego, Carlo, Notarangelo, Luigi D, Su, Helen C, Kisand, Kai, Okada, Satoshi, Puel, Anne, Jouanguy, Emmanuelle, Rice, Charles M, Tiberghien, Pierre, Zhang, Qian, Cobat, Aurélie, Abel, Laurent, Casanova, Jean-Laurent, St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller University [New York], CHU Necker - Enfants Malades [AP-HP], Human genetics of infectious diseases : Mendelian predisposition (Equipe Inserm U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Hiroshima University, Vall d’Hebron Research Institute (VHIR), University of Tartu, Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), CHU Henri Mondor [Créteil], Service de Réanimation Médicale [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Mycologie moléculaire - Molecular Mycology, Members of the The Milieu Intérieur Consortium: Laurent Abel1 , Andres Alcover2 , Hugues Aschard2 , Philippe Bousso2 , Nollaig Bourke3 , Petter Brodin4 , Pierre Bruhns2 , Nadine Cerf-Bensussan5 , Ana Cumano2 , Christophe D’Enfert2 , Ludovic Deriano2 , Marie-Agnès Dillies2 , James Di Santo2 , Françoise Dromer2 , Gérard Eberl2 , Jost Enninga2 , Jacques Fellay6 , Ivo Gomperts-Boneca2 , Milena Hasan2 , Gunilla Karlsson Hedestam4 , Serge Hercberg7 , Molly A. Ingersoll2 , Olivier Lantz8 , Rose Anne Kenny3 , Mickaël Ménager5 , Frédérique Michel2 , Hugo Mouquet2 , Cliona O’Farrelly3 , Etienne Patin2 , Sandra Pellegrini2 , Antonio Rausell5 , Frédéric Rieux-Laucat5 , Lars Rogge2 , Magnus Fontes9 , Anavaj Sakuntabhai2 , Olivier Schwartz2 , Benno Schwikowski2 , Spencer Shorte2 , Frédéric Tangy2 , Antoine Toubert10 , Mathilde Touvier12 , Marie-Noëlle Ungeheuer2 , Christophe Zimmer2 , Matthew L. Albert11 , Darragh Duffy2 , Lluis Quintana-Murc, ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), European Project: 824110,H2020-INFRAIA-2018-1,EASI-Genomics(2019), European Project: 948959,ERC-2020-STG,MORE2ADA2(2021), National Institutes of Health (US), National Center for Advancing Translational Sciences (US), George Mason University, National Human Genome Research Institute (US), Agence Nationale de la Recherche (France), Institut National de la Santé et de la Recherche Médicale (France), Université de Paris, Ministère des Solidarités et de la Santé (France), National Health and Medical Research Council (Australia), Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Cabildo de Tenerife, Fondation Bettencourt Schueller, Estonian Research Council, Michailidis, Eleftherios, García-Prat, Marina, Paul, Stephanie, Metz, Christine N., Barreiros, Lucila, Domínguez-Garrido, Elena, Vidigal, Mateus, Beek, Diederik van der, Stepanovskyy, Yuriy, Tangye, Stuart G., Quintana-Murci, Lluis, Kan, Nelli, Nussenzweig, Michel C., Baris, Hagit N., Dyer, Adam, Bourke, Nollaig, Vinh, Donald C., Spaan, András N., Fellay, Jacques, Mane, Shrikant M., Anderson, MarK S., Andreakos, Evangelos, Haljasmägi, Liis, Mogensen, Trine, Lamballerie, Xavier de, Soler-Palacín, Pere, Martínez-Picado, Javier, Gregersen, Peter K., Rodríguez-Gallego, Carlos, Notarangelo, Luigi D., Su, Helen C., Prost, Nicolas de, Amador-Borrero, Blanco, Troya, Jesús, Rivière, Jacques G., Gentile, Stephanie, Rosen, Lindsey B., Tharaux, Pierre-Louis, Stépanian, Alain, Mégarbane, Bruno, Heath, James R., Franco, José Luis, Anaya, Juan Manuel, Snow, Andrew L., Holland, Steven M., Biggs, Catherine M., Moncada-Velez, Marcela, Planas, Anna M., Nussbaum, Robert, Bousfiha, Ahmed Aziz, Ramírez-Santana, Carolina, Intensive care medicine, Internal medicine, AII - Infectious diseases, Pulmonary medicine, ACS - Pulmonary hypertension & thrombosis, Pathology, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, ACS - Diabetes & metabolism, Amsterdam Cardiovascular Sciences, Radiology and nuclear medicine, AMS - Rehabilitation & Development, VU University medical center, Laboratory Medicine, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Neuroscience - Neuroinfection & -inflammation, Anesthesiology, APH - Quality of Care, ACS - Heart failure & arrhythmias, Özçelik, Tayfun, Children's Hospital, HUS Children and Adolescents, Clinicum, Department of Medicine, Infektiosairauksien yksikkö, HUS Inflammation Center, Admin, Oskar, Identification des défauts monogéniques de l'immunité responsables des formes sévères de COVID-19 chez les patients précédemment en bonne santé - - GENCOVID2020 - ANR-20-COVI-0003 - COVID-19 - VALID, Analyse multi-omique de l'immunité anti-virale: de l'identification des circuits biologiques pertinents à la découverte de défauts monogéniques héréditaires de l'immunité chez les patients avec infections virales sévères - - GENVIR2020 - ANR-20-CE93-0003 - AAPG2020 - VALID, Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19. - - AABIFNCOV2020 - ANR-20-CO11-0001 - COVID-19 - VALID, Program Initiative d’Excellence - IdEx Bordeaux (ANR-10-IDEX- 003-02) - INCOMING, CHU Tenon [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Henri Mondor, Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS [Bourgogne-Franche-Comté])-Université de Franche-Comté (UFC), INSERM U1059, SAINBIOSE - Santé, Ingénierie, Biologie, Saint-Etienne (SAINBIOSE-ENSMSE), Centre International de Recherche en Infectiologie - UMR (CIRI), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service de Parasitologie - Mycologie [CHU Pitié-Salpétrière], CIC Saint Etienne, Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Nord (Saint Etienne), Récepteurs Nucléaires, Maladies Métaboliques et Cardiovasculaires (RNMCD - U1011), Physiopathologie de l'immunodépression associée aux réponses inflammatoires systémiques - EA 7426 (PI3), École pratique des hautes études (EPHE), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Neurology, ANS - Neuroinfection & -inflammation, Graduate School, Infectious diseases, Center of Experimental and Molecular Medicine, APH - Aging & Later Life, APH - Global Health, AII - Amsterdam institute for Infection and Immunity, APH - Health Behaviors & Chronic Diseases, Global Health, APH - Methodology, APH - Digital Health, APH - Personalized Medicine, ACS - Microcirculation, Bastard, P, Gervais, A, Le Voyer, T, Rosain, J, Philippot, Q, Manry, J, Michailidis, E, Hoffmann, H, Eto, S, Garcia-Prat, M, Bizien, L, Parra-Martínez, A, Yang, R, Haljasmägi, L, Migaud, M, Särekannu, K, Maslovskaja, J, de Prost, N, Tandjaoui-Lambiotte, Y, Luyt, C, Amador-Borrero, B, Gaudet, A, Poissy, J, Morel, P, Richard, P, Cognasse, F, Troya, J, Trouillet-Assant, S, Belot, A, Saker, K, Garçon, P, Rivière, J, Lagier, J, Gentile, S, Rosen, L, Shaw, E, Morio, T, Tanaka, J, Dalmau, D, Tharaux, P, Sene, D, Stepanian, A, Megarbane, B, Triantafyllia, V, Fekkar, A, Heath, J, Franco, J, Anaya, J, Solé-Violán, J, Imberti, L, Biondi, A, Bonfanti, P, Castagnoli, R, Delmonte, O, Zhang, Y, Snow, A, Holland, S, Biggs, C, Moncada-Vélez, M, Arias, A, Lorenzo, L, Boucherit, S, Coulibaly, B, Anglicheau, D, Planas, A, Haerynck, F, Duvlis, S, Nussbaum, R, Ozcelik, T, Keles, S, Bousfiha, A, El Bakkouri, J, Ramirez-Santana, C, Paul, S, Pan-Hammarström, Q, Hammarström, L, Dupont, A, Kurolap, A, Metz, C, Aiuti, A, Casari, G, Lampasona, V, Ciceri, F, Barreiros, L, Dominguez-Garrido, E, Vidigal, M, Zatz, M, van de Beek, D, Sahanic, S, Tancevski, I, Stepanovskyy, Y, Boyarchuk, O, Nukui, Y, Tsumura, M, Vidaur, L, Tangye, S, Burrel, S, Duffy, D, Quintana-Murci, L, Klocperk, A, Kann, N, Shcherbina, A, Lau, Y, Leung, D, Coulongeat, M, Marlet, J, Koning, R, Reyes, L, Chauvineau-Grenier, A, Venet, F, Monneret, G, Nussenzweig, M, Arrestier, R, Boudhabhay, I, Baris-Feldman, H, Hagin, D, Wauters, J, Meyts, I, Dyer, A, Kennelly, S, Bourke, N, Halwani, R, Sharif-Askari, N, Dorgham, K, Sallette, J, Sedkaoui, S, Alkhater, S, Rigo-Bonnin, R, Morandeira, F, Roussel, L, Vinh, D, Ostrowski, S, Condino-Neto, A, Prando, C, Bonradenko, A, Spaan, A, Gilardin, L, Fellay, J, Lyonnet, S, Bilguvar, K, Lifton, R, Mane, S, Anderson, M, Boisson, B, Béziat, V, Zhang, S, Vandreakos, E, Hermine, O, Pujol, A, Peterson, P, Mogensen, T, Rowen, L, Mond, J, Debette, S, de Lamballerie, X, Duval, X, Mentré, F, Zins, M, Soler-Palacin, P, Colobran, R, Gorochov, G, Solanich, X, Susen, S, Martinez-Picado, J, Raoult, D, Vasse, M, Gregersen, P, Piemonti, L, Rodríguez-Gallego, C, Notarangelo, L, Su, H, Kisand, K, Okada, S, Puel, A, Jouanguy, E, Rice, C, Tiberghien, P, Zhang, Q, Cobat, A, Abel, L, Casanova, J, Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Laboratory of Human Genetics of Infectious Diseases (Necker Branch - INSERM U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), HGID Lab, COVID Clinicians, COVID-STORM Clinicians, NIAID Immune Response to COVID Group, NH-COVAIR Study Group, Danish CHGE, Danish Blood Donor Study, St. James's Hospital, SARS CoV2 Interest group, French COVID Cohort Study Group, Imagine COVID-Group, Milieu Intérieur Consortium, CoV-Contact Cohort, Amsterdam UMC Covid-19, Biobank Investigators, COVID Human Genetic Effort, CONSTANCES cohort, 3C-Dijon Study, Cerba Health-Care, Etablissement du Sang study group, Bigio, B., Boucherit, S., de la Chapelle, A., Chen, J., Chrabieh, M., Coulibaly, B., Liu, D., Nemirowskaya, Y., Cruz, I.M., Materna, M., Pelet, S., Seeleuthner, Y., Thibault, C., Liu, Z., Abad, J., Accordino, G., Achille, C., Aguilera-Albesa, S., Aguiló-Cucurull, A., Aiuti, A., Özkan, E.A., Darazam, I.A., Roblero Albisures, J.A., Aldave, J.C., Ramos, M.A., Khan, T.A., Aliberti, A., Nadji, S.A., Alkan, G., Alkhater, S.A., Allardet-Servent, J., Allende, L.M., Alonso-Arias, R., Alshahrani, M.S., Alsina, L., Alyanakian, M.A., Borrero, B.A., Amoura, Z., Antolí, A., Arrestier, R., Aubart, M., Auguet, T., Avramenko, I., Aytekin, G., Azot, A., Bahram, S., Bajolle, F., Baldanti, F., Baldolli, A., Ballester, M., Feldman, H.B., Barrou, B., Barzagh, F., Basso, S., Bayhan, G.I., Belot, A., Bezrodnik, L., Bilbao, A., Blanchard-Rohner, G., Blanco, I., Blandinières, A., Blázquez-Gamero, D., Bleibtreu, A., Bloomfield, M., Bolivar-Prados, M., Bondarenko, A., Borghesi, A., Borie, R., Botdhlo-Nevers, E., Bousfiha, A.A., Bousquet, A., Boutolleau, D., Bouvattier, C., Boyarchuk, O., Bravais, J., Briones, M.L., Brunner, M.E., Bruno, R., Bueno, MRP, Bukhari, H., Bustamante, J., Cáceres Agra, J.J., Capra, R., Carapito, R., Carrabba, M., Casari, G., Casasnovas, C., Caseris, M., Cassaniti, I., Castelle, M., Castelli, F., de Vera, M.C., Castro, M.V., Catherinot, E., Celik, J.B., Ceschi, A., Chalumeau, M., Charbit, B., Cheng, M.P., Clavé, P., Clotet, B., Codina, A., Cohen, Y., Colobran, R., Comarmond, C., Combes, A., Comoli, P., Corsico, A.G., Coşkuner, T., Cvetkovski, A., Cyrus, C., Dalmau, D., Danion, F., Darley, D.R., Das, V., Dauby, N., Dauger, S., De Munter, P., de Pontual, L., Dehban, A., Delplancq, G., Demoule, A., Desguerre, I., Di Sabatino, A., Diehl, J.L., Dobbelaere, S., Domínguez-Garrido, E., Dubost, C., Ekwall, O., Bozdemir, Ş.E., Elnagdy, M.H., Emiroglu, M., Endo, A., Erdeniz, E.H., Aytekin, S.E., Lasa, MPE, Euvrard, R., Fabio, G., Faivre, L., Falck, A., Fartoukh, M., Faure, M., Arquero, M.F., Ferrer, R., Ferreres, J., Flores, C., Francois, B., Fumadó, V., Fung, KSC, Fusco, F., Gagro, A., Solis, B.G., Gaussem, P., Gayretli, Z., Gil-Herrera, J., Gilardin, L., Gatineau, A.G., Girona-Alarcón, M., Cifuentes Godínez, K.A., Goffard, J.C., Gonzales, N., Gonzalez-Granado, L.I., González-Montelongo, R., Guerder, A., Gülhan, B., Gumucio, V.D., Hanitsch, L.G., Gunst, J., Gut, M., Hadjadj, J., Haerynck, F., Halwani, R., Hammarström, L., Hancerli, S., Hariyan, T., Hatipoglu, N., Heppekcan, D., Hernandez-Brito, E., Ho, P.K., Holanda-Peña, M.S., Horcajada, J.P., Hraiech, S., Humbert, L., Hung, IFN, Iglesias, A.D., Íñigo-Campos, A., Jamme, M., Arranz, M.J., Jimeno, M.T., Jordan, I., Yüksek, S.K., Kara, Y.B., Karahan, A., Karbuz, A., Yasar, K.K., Kasapcopur, O., Kashimada, K., Keles, S., Demirkol, Y.K., Kido, Y., Kizil, C., Kılıç, A.O., Klocperk, A., Koutsoukou, A., Król, Z.J., Ksouri, H., Kuentz, P., Kwan, AMC, Kwan, YWM, Kwok, JSY, Lagier, J.C., Lam, DSY, Lampropoulou, V., Lanternier, F., Lau, Y.L., Le Bourgeois, F., Leo, Y.S., Lopez, R.L., Leung, D., Levin, M., Levy, M., Lévy, R., Li, Z., Lilleri, D., Lima, EJAB, Linglart, A., López-Collazo, E., Lorenzo-Salazar, J.M., Louapre, C., Lubetzki, C., Lung, K.C., Luyt, C.E., Lye, D.C., Magnone, C., Mansouri, D., Marchioni, E., Marioli, C., Marjani, M., Marques, L., Pereira, J.M., Martín-Nalda, A., Pueyo, D.M., Martinez-Picado, J., Marzana, I., Mata-Martínez, C., Mathian, A., Matos, L.R., Matthews, G.V., Mayaux, J., McLaughlin-Garcia, R., Meersseman, P., Mège, J.L., Mekontso-Dessap, A., Melki, I., Meloni, F., Meritet, J.F., Merlani, P., Akcan, Ö.M., Meyts, I., Mezidi, M., Migeotte, I., Millereux, M., Million, M., Mirault, T., Mircher, C., Mirsaeidi, M., Mizoguchi, Y., Modi, B.P., Mojoli, F., Moncomble, E., Melián, A.M., Martinez, A.M., Morandeira, F., Morange, P.E., Mordacq, C., Morelle, G., Mouly, S.J., Muñoz-Barrera, A., Nafati, C., Nagashima, S., Nakagama, Y., Neven, B., Neves, J.F., Ng, L.F., Ng, Y.Y., Nielly, H., Medina, Y.N., Cuadros, E.N., Ocejo-Vinyals, J.G., Okamoto, K., Oualha, M., Ouedrani, A., Özçelik, T., Ozkaya-Parlakay, A., Pagani, M., Pan-Hammarström, Q., Papadaki, M., Parizot, C., Parola, P., Pascreau, T., Paul, S., Paz-Artal, E., Pedraza, S., González Pellecer, N.C., Pellegrini, S., de Diego, R.P., Pérez-Fernández, X.L., Philippe, A., Philippot, Q., Picod, A., de Chambrun, M.P., Piralla, A., Planas-Serra, L., Ploin, D., Poissy, J., Poncelet, G., Poulakou, G., Pouletty, M.S., Pourshahnazari, P., Qiu-Chen, J.L., Quentric, P., Rambaud, T., Raoult, D., Raoult, V., Rebillat, A.S., Redin, C., Resmini, L., Ricart, P., Richard, J.C., Rigo-Bonnin, R., Rivet, N., Rivière, J.G., Rocamora-Blanch, G., Rodero, M.P., Rodrigo, C., Rodriguez, L.A., Rodriguez-Gallego, C., Rodriguez-Palmero, A., Romero, C.S., Rothenbuhler, A., Roux, D., Rovina, N., Rozenberg, F., Ruch, Y., Ruiz, M., Ruiz Del Prado, M.Y., Ruiz-Rodriguez, J.C., Sabater-Riera, J., Saks, K., Salagianni, M., Sanchez, O., Sánchez-Montalvá, A., Sánchez-Ramón, S., Schidlowski, L., Schluter, A., Schmidt, J., Schmidt, M., Schuetz, C., Schweitzer, C.E., Scolari, F., Sediva, A., Seijo, L., Seminario, A.G., Sene, D., Seng, P., Senoglu, S., Seppänen, M., Llovich, A.S., Shahrooei, M., Shcherbina, A., Siguret, V., Siouti, E., Smadja, D.M., Smith, N., Sobh, A., Solanich, X., Solé-Violán, J., Soler, C., Soler-Palacín, P., Sözeri, B., Stella, G.M., Stepanovskiy, Y., Stoclin, A., Taccone, F., Tandjaoui-Lambiotte, Y., Taupin, J.L., Tavernier, S.J., Tello, L.V., Terrier, B., Thiery, G., Thorball, C., Thorn, K., Thumerelle, C., Tipu, I., Tolstrup, M., Tomasoni, G., Toubiana, J., Alvarez, J.T., Triantafyllia, V., Trouillet-Assant, S., Troya, J., Tsang, OTY, Tserel, L., Tso, EYK, Tucci, A., Tüter Öz, Ş.K., Ursini, M.V., Utsumi, T., Uzunhan, Y., Vabres, P., Valencia-Ramos, J., Van Den Rym, A.M., Vandernoot, I., Velez-Santamaria, V., Zuniga Veliz, S.P., Vidigal, M.C., Viel, S., Vilain, C., Vilaire-Meunier, M.E., Villar-García, J., Vincent, A., Vogt, G., Voiriot, G., Volokha, A., Vuotto, F., Wauters, E., Wauters, J., Wu, AKL, Wu, T.C., Yahşi, A., Yesilbas, O., Yildiz, M., Young, B.E., Yükselmiş, U., Zatz, M., Zecca, M., Zuccaro, V., Jens, V.P., Lambrecht, B.N., Eva, V.B., Cédric, B., Levi, H., Eric, H., Bauters, F., De Clercq, J., Cathérine, H., Hans, S., Leslie, N., Florkin, B., Boulanger, C., Vanderlinden, D., Foti, G., Bellani, G., Citerio, G., Contro, E., Pesci, A., Valsecchi, M.G., Cazzaniga, M., Danielson, J.J., Dobbs, K., Kashyap, A., Ding, L., Dalgard, C.L., Sottini, A., Quaresima, V., Quiros-Roldan, E., Rossi, C., Bettini, L.R., D'Angio', M., Beretta, I., Montagna, D., Licari, A., Marseglia, G.L., Batten, I., Reddy, C., McElheron, M., Noonan, C., Connolly, E., Fallon, A., Storgaard, M., Jørgensen, S., Erikstrup, C., Pedersen, O.B., Sørensen, E., Mikkelsen, S., Dinh, K.M., Larsen, MAH, Paulsen, I.W., Von Stemann, J.H., Hansen, M.B., Ostrowski, S.R., Townsend, L., Cheallaigh, C.N., Bergin, C., Martin-Loeches, I., Dunne, J., Conlon, N., Bourke, N., O'Farrelly, C., Abel, L., Allavena, C., Andrejak, C., Angoulvant, F., Azoulay, C., Bachelet, D., Bartoli, M., Basmaci, R., Behilill, S., Beluze, M., Benech, N., Benkerrou, D., Bhavsar, K., Bitker, L., Bouadma, L., Bouscambert-Duchamp, M., Paz, P.C., Cervantes-Gonzalez, M., Chair, A., Chirouze, C., Coelho, A., Cordel, H., Couffignal, C., Couffin-Cadiergues, S., d'Ortenzio, E., De Montmollin, E., Debard, A., Debray, M.P., Deplanque, D., Descamps, D., Desvallée, M., Diallo, A., Diouf, A., Dorival, C., Dubos, F., Duval, X., Eloy, P., Enouf, V., Epaulard, O., Esperou, H., Esposito-Farese, M., Etienne, M., Garot, D., Gault, N., Gaymard, A., Ghosn, J., Gigante, T., Gilg, M., Goehringer, F., Guedj, J., Hoctin, A., Hoffmann, I., Houas, I., Hulot, J.S., Jaafoura, S., Kafif, O., Kaguelidou, F., Kali, S., Kerroumi, Y., Khalil, A., Khan, C., Kimmoun, A., Laine, F., Laouénan, C., Laribi, S., Le, M., Le Bris, C., Le Gac, S., Le Hingrat, Q., Le Mestre, S., Le Nagard, H., Lemaignen, A., Lemee, V., Lescure, F.X., Letrou, S., Levy, Y., Lina, B., Lingas, G., Lucet, J.C., Machado, M., Malvy, D., Mambert, M., Manuel, A., Mentré, F., Meziane, A., Mouquet, H., Mullaert, J., Neant, N., Nguyen, D., Noret, M., Papadopoulos, A., Paul, C., Peiffer-Smadja, N., Peigne, V., Petrov-Sanchez, V., Peytavin, G., Pham, H., Picone, O., Piquard, V., Puéchal, O., Rosa-Calatrava, M., Rossignol, B., Rossignol, P., Roy, C., Schneider, M., Su, R., Tardivon, C., Tellier, M.C., Téoulé, F., Terrier, O., Timsit, J.F., Tual, C., Tubiana, S., Van Der Werf, S., Vanel, N., Veislinger, A., Visseaux, B., Wiedemann, A., Yazdanpanah, Y., Annereau, J.P., Briseño-Roa, L., Gribouval, O., Pelet, A., Alcover, A., Aschard, H., Bousso, P., Brodin, P., Bruhns, P., Cerf-Bensussan, N., Cumano, A., D'Enfert, C., Deriano, L., Dillies, M.A., Di Santo, J., Dromer, F., Eberl, G., Enninga, J., Fellay, J., Gomperts-Boneca, I., Hasan, M., Hedestam, G.K., Hercberg, S., Ingersoll, M.A., Lantz, O., Kenny, R.A., Ménager, M., Michel, F., Patin, E., Rausell, A., Rieux-Laucat, F., Rogge, L., Fontes, M., Sakuntabhai, A., Schwartz, O., Schwikowski, B., Shorte, S., Tangy, F., Toubert, A., Touvier, M., Ungeheuer, M.N., Zimmer, C., Albert, M.L., Duffy, D., Quintana-Murci, L., Alavoine, L., Behillil, S., Burdet, C., Charpentier, C., Dechanet, A., Ecobichon, J.L., Frezouls, W., Houhou, N., Lehacaut, J., Manchon, P., Nouroudine, M., Quintin, C., Thy, M., van der Werf, S., Vignali, V., Chahine, A., Waucquier, N., Migaud, M.C., Djossou, F., Mergeay-Fabre, M., Lucarelli, A., Demar, M., Bruneau, L., Gérardin, P., Maillot, A., Payet, C., Laviolle, B., Paris, C., Desille-Dugast, M., Fouchard, J., Pistone, T., Perreau, P., Gissot, V., Le Goas, C., Montagne, S., Richard, L., Bouiller, K., Desmarets, M., Meunier, A., Lefévre, B., Jeulin, H., Legrand, K., Lomazzi, S., Tardy, B., Gagneux-Brunon, A., Bertholon, F., Botelho-Nevers, E., Kouakam, C., Leturque, N., Roufai, L., Amat, K., Espérou, H., Hendou, S., van Agtmael, M., Algera, A.G., Appelman, B., van Baarle, F., Bax, D., Beudel, M., Bogaard, H.J., Bomers, M., Bonta, P., Bos, L., Botta, M., de Brabander, J., de Bree, G., de Bruin, S., Buis, DTP, Bugiani, M., Bulle, E., Chouchane, O., Cloherty, A., Dijkstra, M., Dongelmans, D.A., Dujardin, RWG, Elbers, P., Fleuren, L., Geijtenbeek, SGT, Girbes, A., Goorhuis, B., Grobusch, M.P., Hafkamp, F., Hagens, L., Hamann, J., Harris, V., Hemke, R., Hermans, S.M., Heunks, L., Hollmann, M., Horn, J., Hovius, J.W., de Jong, M.D., Koning, R., Lim, EHT, van Mourik, N., Nellen, J., Nossent, E.J., Paulus, F., Peters, E., Pina-Fuentes, DAI, van der Poll, T., Preckel, 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[0000-0003-1347-7767], Ostrowski, Sisse Rye [0000-0001-5288-3851], Condino-Neto, Antonio [0000-0002-1069-3117], Prando, Carolina [0000-0002-9570-9770], Spaan, András N. [0000-0001-5981-7259], Gilardin, Laurent [0000-0001-9212-0859], Yang, Rui [0000-0003-4427-2158], Fellay, Jacques [0000-0002-8240-939X], Bilguvar, Kaya [0000-0002-7313-7652], Mane, Shrikant M. [0000-0002-3267-5139], Anderson, MarK S. [0000-0002-3093-4758], Boisson, Bertrand [0000-0001-5240-3555], Béziat, Vivien [0000-0002-4020-824X], Andreakos, Evangelos [0000-0001-5536-1661], Hermine, Olivier [0000-0003-2574-3874], Pujol, Aurora [0000-0002-9606-0600], Peterson, Pärt [0000-0001-6755-791X], Haljasmägi, Liis [0000-0001-7162-9808], Mogensen, Trine [0000-0002-1853-9704], Lamballerie, Xavier de [0000-0001-7895-2720], Zins, Marie [0000-0002-4540-4282], Soler-Palacín, Pere [0000-0002-0346-5570], Colobran, Roger [0000-0002-5964-536X], Gorochov, Guy [0000-0003-2097-9677], Solanich, Xavier [0000-0002-2572-2187], Susen, Sophie [0000-0001-5953-163X], Martínez-Picado, Javier [0000-0002-4916-2129], Gregersen, Peter K. [0000-0003-1613-1518], Migaud, Mélanie [0000-0003-3062-1214], Piemonti, Lorenzo [0000-0002-2172-2198], Rodríguez-Gallego, Carlos [0000-0002-4344-8644], Notarangelo, Luigi D. [0000-0002-8335-0262], Su, Helen C. [0000-0002-5582-9110], Kisand, Kai [0000-0002-5426-4648], Okada, Satoshi [0000-0002-4622-5657], Puel, Anne [0000-0003-2603-0323], Jouanguy, Emmanuelle [0000-0002-7358-9157], Tiberghien, Pierre [0000-0002-9310-8322], Zhang, Qian [0000-0002-9040-3289], Särekannu, Karita [0000-0002-5984-668X], Cobat, Aurélie [0000-0001-7209-6257], Abel, Laurent [0000-0001-7016-6493], Casanova, Jean-Laurent [0000-0002-7782-4169], Prost, Nicolas de [0000-0002-4833-4320], Tandjaoui-Lambiotte, Yacine [0000-0003-1123-4788], Luyt, Charles-Edouard [0000-0001-7424-2705], Amador-Borrero, Blanco [0000-0001-6170-8721], Poissy, Julien [0000-0001-6017-5353], Richard, Pascale [0000-0003-1864-3824], Cognasse, Fabrice [0000-0001-8041-928X], Troya, Jesús [0000-0001-7323-114X], Trouillet-Assant, Sophie [0000-0001-6439-4705], Belot, Alexandre [0000-0003-4902-5332], Saker, Kahina [0000-0001-8825-5400], Rivière, Jacques G. [0000-0003-1055-2063], Gentile, Stephanie [0000-0003-3858-9503], Rosen, Lindsey B. [0000-0001-5894-3878], Shaw, Elana [0000-0001-9265-8026], Dalmau, David [0000-0003-1936-478X], Tharaux, Pierre-Louis [0000-0002-6062-5905], Stépanian, Alain [0000-0002-2942-0901], Mégarbane, Bruno [0000-0002-2522-2764], Triantafyllia, Vasiliki [0000-0001-5832-4014], Fekkar, Arnaud [0000-0001-9954-075X], Heath, James R. [0000-0001-5356-4385], Franco, José Luis [0000-0001-5664-6415], Anaya, Juan Manuel [0000-0002-6444-1249], Imberti, Luisa[0000-0002-2075-8391], Bonfanti, Paolo [0000-0001-7289-8823], Castagnoli, Riccardo [0000-0003-0029-9383], Snow, Andrew L. [0000-0002-8728-6691], Holland, Steven M. [0000-0003-3207-5464], Biggs, Catherine M. [0000-0002-4363-2660], Moncada-Velez, Marcela [0000-0002-3073-5345], Arias, Andrés Augusto [0000-0002-9478-8403], Lorenzo, Lazaro [0000-0001-6648-8684], Boucherit, Soraya [0000-0002-8819-7594], Anglicheau, Dany [0000-0001-5793-6174], Planas, Anna M. [0000-0002-6147-1880], Haerynck, Filomeen [0000-0001-9161-7361], Duvlis, Sotirija [0000-0001-8587-7386], Nussbaum, Robert [0000-0003-3445-8880], Bousfiha, Ahmed Aziz [0000-0002-5011-9873], El Bakkouri, Jalila [0000-0003-2303-3369], Ramírez-Santana, Carolina [0000-0003-2137-4899], Paul, Stephanie [0000-0002-8830-4273], Pan-Hammarström, Qiang [0000-0003-1990-8804], Hammarström, Lennart [0000-0002-8635-9609], Dupont, Annabelle [0000-0002-1554-9931], Kurolap, Alina [0000-0002-7005-3621], Metz, Christine N. [0000-0002-1013-1691], Aiuti, Alessandro [0000-0002-5398-1717], Casari, Giorgio [0000-0002-0115-8980], Lampasona, Vito [0000-0001-5162-8445], Ciceri, Fabio [0000-0003-0873-0123], Barreiros, Lucila [0000-0002-9818-2345], Domínguez-Garrido, Elena [0000-0002-2066-0511], Vidigal, Mateus [0000-0002-8895-652X], Zatz, Mayana [0000-0003-3970-8025], Beek, Diederik van der [0000-0002-4571-044X], Stepanovskyy, Yuriy [0000-0001-6339-5490], Boyarchuk, Oksana [0000-0002-1234-0040], Nukui, Yoko [0000-0002-6123-5212], Vidaur, Loreto [0000-0002-6720-4900], Tangye, Stuart G. [0000-0002-5360-5180], Burrel, Sonia [0000-0002-7783-2601], Duffy, Darragh [0000-0002-8875-2308], Quintana-Murci, Lluis [0000-0003-2429-6320], Klocperk, Adam [0000-0002-1526-4557], Kan, Nelli [0000-0003-3564-6496], Shcherbina, Anna [0000-0002-3113-4939], Lau, Yu-Lung [0000-0002-4780-0289], Leung, Daniel [0000-0002-9360-6233], Coulongeat, Matthieu [0000-0003-1986-3546], Marlet, Julien [0000-0002-8645-8703], Koning, Rutger [0000-0003-3128-5072], Reyes, Luis Felipe [0000-0003-1172-6539], Venet, Fabienne [0000-0003-0462-4235], Monneret, Guillaume [0000-0002-9961-5739], Nussenzweig, Michel C. [0000-0003-0592-8564], Baris, Hagit N. [0000-0003-4065-7560], Hagin, David [0000-0003-2702-1031], Wauters, Joost [0000-0002-5983-3897], Meyts, Isabelle [0000-0003-1214-0302], Dyer, Adam [0000-0003-1356-510X], Bourke, Nollaig [0000-0003-4313-6859], Halwani, Rabih [0000-0002-6516-7771], and Sharif-Askari, Narjes Saheb [0000-0003-0482-6777]
- Subjects
Interferon Type I/immunology ,AUTOIMMUNITY ,[SDV]Life Sciences [q-bio] ,Interferó ,Gastroenterology ,COVID-19 (Malaltia) ,Immunoglobulin G ,Basic medicine ,0302 clinical medicine ,Medicine and Health Sciences ,80 and over ,Immunologia ,Young adult ,Child ,Neutralizing ,MYASTHENIA-GRAVIS PATIENTS ,ComputingMilieux_MISCELLANEOUS ,Aged, 80 and over ,0303 health sciences ,education.field_of_study ,biology ,General Medicine ,Middle Aged ,3. Good health ,COVID-19/immunology ,Settore MED/03 ,030220 oncology & carcinogenesis ,Child, Preschool ,Interferon Type I ,Antibody ,medicine.symptom ,INTERFERON ,Adult ,medicine.medical_specialty ,Adolescent ,Critical Illness ,Immunology ,Population ,Aged ,Antibodies, Neutralizing ,Autoantibodies ,COVID-19 ,Case-Control Studies ,Humans ,Infant ,Infant, Newborn ,Interferon-alpha ,Young Adult ,Alpha interferon ,Immunoglobulins ,IMMUNITY ,Asymptomatic ,PATIENT ,03 medical and health sciences ,Internal medicine ,medicine ,Preschool ,education ,Antibodies, Neutralizing/blood ,HOMENS ,030304 developmental biology ,ANTINUCLEAR ,business.industry ,Autoantibody ,Case-control study ,Antibodies, Neutralizing/immunology ,Autoantibodies/blood ,Autoantibodies/immunology ,COVID-19/mortality ,Immunoglobulin G/blood ,Immunoglobulin G/immunology ,Interferon-alpha/immunology ,Newborn ,DISTINCT FUNCTIONS ,ALPHA ,[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie ,3121 General medicine, internal medicine and other clinical medicine ,ANTIBODIES ,biology.protein ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,business ,Immunoglobulines - Abstract
Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-α and/or IFN-ω are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or IFN-ω (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or IFN-ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases., The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Awards (CTSA) program (UL1 TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at George Mason University, the Yale Center for Mendelian Genomics and the GSP Coordinating Center funded by the National Human Genome Research Institute (NHGRI) (UM1HG006504 and U24HG008956), the Yale High Performance Computing Center (S10OD018521), the Fisher Center for Alzheimer’s Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the “Investments for the Future” program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the FRM and ANR GENCOVID project (ANR-20-COVI-0003), ANRS Nord-Sud (ANRS-COV05), ANR GENVIR (ANR-20-CE93-003) and ANR AABIFNCOV (ANR-20-CO11-0001) projects, the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 824110 (EASI-Genomics), the Square Foundation, Grandir–Fonds de solidarité pour l’Enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM; and the University of Paris. P.B. was supported by the FRM (EA20170638020). P.B., J.R., and T.L.V. were supported by the MD-PhD program of the Imagine Institute (with the support of the Fondation Bettencourt Schueller). Work in the Laboratory of Virology and Infectious Disease was supported by the NIH (P01AI138398-S1, 2U19AI111825, and R01AI091707-10S1), a George Mason University Fast Grant, and the G. Harold and Leila Y. Mathers Charitable Foundation. The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (RECOVER WP 6). This work was also partly supported by the Intramural Research Program of the NIAID and NIDCR, NIH (grants ZIA AI001270 to L.D.N. and 1ZIAAI001265 to H.C.S.). This program is supported by the Agence Nationale de la Recherche (reference ANR-10-LABX-69-01). K.K.’s group was supported by the Estonian Research Council grants PRG117 and PRG377. R.H. was supported by an Al Jalila Foundation Seed Grant (AJF202019), Dubai, UAE, and a COVID-19 research grant (CoV19-0307) from the University of Sharjah, UAE. S.G.T. is supported by Investigator and Program Grants awarded by the National Health and Medical Research Council of Australia and a UNSW Sydney COVID Rapid Response Initiative Grant. L.I. reported funding from Regione Lombardia, Italy (project “Risposta immune in pazienti con COVID-19 e co-morbidità”). L.I. and G. L. Marseglia reported funding from Regione Lombardia, Italy (project Risposta immune in pazienti con COVID-19 e co-morbidità). This research was partially supported by the Instituto de Salud Carlos III (COV20/0968). J.R.H. reported funding from Biomedical Advanced Research and Development Authority HHSO10201600031C. S.O. reports funding Research Program on Emerging and Re-emerging Infectious Diseases from Japan Agency for Medical Research and Development, AMED (grant number JP20fk0108531). G.G. was supported by ANR Flash COVID-19 program and SARS-CoV-2 Program of the Faculty of Medicine from Sorbonne University iCOVID programs. The Three-City (3C) Study was conducted under a partnership agreement among the INSERM, the Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also supported by the Caisse Nationale d’Assurance Maladie des Travailleurs Salariés, Direction générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Programme “Cohortes et collections de données biologiques”. S. Debette was supported by the University of Bordeaux Initiative of Excellence. P.K.G. reports funding from the National Cancer Institute, NIH, under contract no. 75N91019D00024, task order no. 75N91021F00001. J.W. is supported by an FWO Fundamental Clinical Mandate (1833317N). Sample processing at IrsiCaixa was possible thanks to the crowdfunding initiative YoMeCorono. Work at Vall d’Hebron was also partly supported by research funding from Instituto de Salud Carlos III grant PI17/00660 cofinanced by the European Regional Development Fund (ERDF). C.R.-G. and colleagues of the Canarian Health System Sequencing Hub were supported by the Instituto de Salud Carlos III (COV20_01333 and COV20_01334, Spanish Ministry for Science and Innovation RTC-2017-6471-1; AEI/FEDER, UE), Fundación DISA (OA18/017 and OA20/024), and Cabildo Insular de Tenerife (CGIEU0000219140 and “Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19”). C.M.B. is supported by a MSFHR Health Professional-Investigator Award. P.Q.H. and L.H. were funded by the European Union’s Horizon 2020 research and innovation program (ATAC, 101003650). Work at Y.-L.L.’s laboratory in the University of Hong Kong (HKU) was supported by the Society for the Relief of Disabled Children. MBBS/PhD study of D.L. in HKU was supported by the Croucher Foundation. J.L.F. was supported in part by the Coopération Scientifique France-Colciencias (ECOS-Nord/COLCIENCIAS/MEN/ICETEX (806-2018) and Colciencias contract 713-2016 (code 111574455633)]. A.K. was in part supported by grants NU20-05-00282 and NV18-05-00162 issued by the Czech Health Research Council and Ministry of Health, Czech Republic. L.P. was funded by Program Project COVID-19 OSR-UniSR and Ministero della Salute (COVID-2020-12371617). I.M. is a Senior Clinical Investigator at the Research Foundation–Flanders and is supported by the CSL Behring Chair of Primary Immunodeficiencies; by the KU Leuven C1 grant C16/18/007; by a VIB-GC PID grant; by the FWO frants G0C8517N, G0B5120N, and G0E8420N; and by the Jeffrey Modell Foundation. I.M. has received funding under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 948959). E.A. received funding from the Hellenic Foundation for Research and Innovation (INTERFLU, no. 1574). M.Vi received funding from the São Paulo Research Foundation (FAPESP) (grant number 2020/09702-1) and JBS SA (grant number 69004). The NH-COVAIR study group consortium was supported by a grant from the Meath Foundation
- Published
- 2021
37. X-linked recessive TLR7 deficiency in ~1% of men under 60 years old with life-threatening COVID-19
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Asano, Takaki, Boisson, Bertrand, Onodi, Fanny, Matuozzo, Daniela, Moncada-Velez, Marcela, Maglorius Renkilaraj, Majistor Raj Luxman, Zhang, Peng, Meertens, Laurent, Bolze, Alexandre, Materna, Marie, Korniotis, Sarantis, Gervais, Adrian, Talouarn, Estelle, Bigio, Benedetta, Seeleuthner, Yoann, Bilguvar, Kaya, Zhang, Yu, Neehus, Anna-Lena, Ogishi, Masato, Pelham, Simon J., Le Voyer, Tom, Rosain, Jérémie, Philippot, Quentin, Soler-Palacín, Pere, Colobran, Roger, Martin-Nalda, Andrea, Rivière, Jacques G., Tandjaoui-Lambiotte, Yacine, Chaïbi, Khalil, Shahrooei, Mohammad, Darazam, Ilad Alavi, Olyaei, Nasrin Alipour, Mansouri, Davood, Hatipoğlu, Nevin, Palabiyik, Figen, Ozcelik, Tayfun, Novelli, Giuseppe, Novelli, Antonio, Casari, Giorgio, Aiuti, Alessandro, Carrera, Paola, Bondesan, Simone, Barzaghi, Federica, Rovere-Querini, Patrizia, Tresoldi, Cristina, Franco, Jose Luis, Rojas, Julian, Reyes, Luis Felipe, Bustos, Ingrid G., Arias, Andres Augusto, Morelle, Guillaume, Kyheng, Christèle, Troya, Jesús, Planas-Serra, Laura, Schlüter, Agatha, Gut, Marta, Pujol, Aurora, Allende, Luis M., Rodriguez-Gallego, Carlos, Flores, Carlos, Cabrera-Marante, Oscar, Pleguezuelo, Daniel E., Pérez de Diego, Rebeca, Keles, Sevgi, Aytekin, Gokhan, Metin Akcan, Ozge, Bryceson, Yenan T., Bergman, Peter, Brodin, Petter, Smole, Daniel, Smith, C. I. Edvard, Norlin, Anna-Carin, Campbell, Tessa M., Covill, Laura E., Hammarström, Lennart, Pan-Hammarström, Qiang, Abolhassani, Hassan, Mane, Shrikant, Marr, Nico, Ata, Manar, Al Ali, Fatima, Khan, Taushif, Spaan, András N., Dalgard, Clifton L., Bonfanti, Paolo, Biondi, Andrea, Tubiana, Sarah, Burdet, Charles, Nussbaum, Robert, Kahn-Kirby, Amanda, Snow, Andrew L., Bustamante, Jacinta, Puel, Anne, Boisson-Dupuis, Stéphanie, Zhang, Shen-Ying, Béziat, Vivien, Lifton, Richard P., Bastard, Paul, Notarangelo, Luigi D., Abel, Laurent, Su, Helen C., Jouanguy, Emmanuelle, Amara, Ali, Soumelis, Vassili, Cobat, Aurélie, Zhang, Qian, Casanova, Jean-Laurent, Al-Muhsen, Saleh, Al-Mulla, Fahd, Anderson, Mark S., Andreakos, Evangelos, Arias, Andrés A., Feldman, Hagit Baris, Belot, Alexandre, Biggs, Catherine M., Bogunovic, Dusan, Bondarenko, Anastasiia, Bousfiha, Ahmed A., Bryceson, Yenan, Bustamante, Carlos D., Butte, Manish J., Chakravorty, Samya, Christodoulou, John, Condino-Neto, Antonio, Constantinescu, Stefan N., Cooper, Megan A., Desai, Murkesh, Drolet, Beth A., El Baghdadi, Jamila, Espinosa-Padilla, Sara, Fellay, Jacques, Franco, José Luis, Froidure, Antoine, Gregersen, Peter K., Haerynck, Filomeen, Hagin, David, Halwani, Rabih, Heath, James R., Henrickson, Sarah E., Hsieh, Elena W.Y., Husebye, Eystein, Imai, Kohsuke, Itan, Yuval, Jarvis, Erich D., Karamitros, Timokratis, Kisand, Kai, Ku, Cheng-Lung, Lau, Yu-Lung, Ling, Yun, Lucas, Carrie L., Maniatis, Tom, Maródi, László, Meyts, Isabelle, Milner, Joshua D., Mironska, Kristina, Mogensen, Trine H., Morio, Tomohiro, Ng, Lisa F.P., O'Farrelly, Cliona, Okada, Satoshi, de Diego, Rebeca Perez, Planas, Anna M., Prando, Carolina, Quintana-Murci, Lluis, Renia, Laurent, Resnick, Igor, Rodríguez-Gallego, Carlos, Sancho-Shimizu, Vanessa, Sediva, Anna, Seppänen, Mikko R.J., Shahrooei, Mohammed, Shcherbina, Anna, Slaby, Ondrej, Tancevski, Ivan, Tangye, Stuart G., Abou Tayoun, Ahmad, Ramaswamy, Sathishkumar, Turvey, Stuart E, Uddin, K M Furkan, Uddin, Mohammed J., van de Beek, Diederik, Vinh, Donald C., von Bernuth, Horst, Zatz, Mayana, Zawadzki, Pawel, Foti, Giuseppe, Bellani, Giacomo, Citerio, Giuseppe, Contro, Ernesto, Pesci, Alberto, Valsecchi, Maria Grazia, Cazzaniga, Marina, Abad, Jorge, Accordino, Giulia, Achille, Cristian, Aguilera-Albesa, Sergio, Aguiló-Cucurull, Aina, Özkan, Esra Akyüz, Roblero Albisures, Jonathan Antonio, Aldave, Juan C, Ramos, Miquel Alfonso, Khan, Taj Ali, Aliberti, Anna, Nadji, Seyed Alireza, Alkan, Gulsum, AlKhater, Suzan A., Allardet-Servent, Jerome, Allende, Luis M, Alonso-Arias, Rebeca, Alshahrani, Mohammed S, Alsina, Laia, Alyanakian, Marie-Alexandra, Borrero, Blanca Amador, Amoura, Zahir, Antolí, Arnau, Arrestier, Romain, Aubart, Mélodie, Auguet, Teresa, Avramenko, Iryna, Aytekin, Gökhan, Azot, Axelle, Bahram, Seiamak, Bajolle, Fanny, Baldanti, Fausto, Baldolli, Aurélie, Ballester, Maite, Barrou, Benoit, Barzagh, Federica, Basso, Sabrina, Bayhan, Gulsum Iclal, Bezrodnik, Liliana, Bilbao, Agurtzane, Blanchard-Rohner, Geraldine, Blanco, Ignacio, Blandinières, Adeline, Blázquez-Gamero, Daniel, Bleibtreu, Alexandre, Bloomfield, Marketa, Bolivar-Prados, Mireia, Borghesi, Alessandro, Borie, Raphael, Botdhlo-Nevers, Elisabeth, Bousfiha, Ahmed A, Bousquet, Aurore, Boutolleau, David, Bouvattier, Claire, Boyarchuk, Oksana, Bravais, Juliette, Briones, M. Luisa, Brunner, Marie-Eve, Bruno, Raffaele, Bueno, Maria Rita P, Bukhari, Huda, Cáceres Agra, Juan José, Capra, Ruggero, Carapito, Raphael, Carrabba, Maria, Casasnovas, Carlos, Caseris, Marion, Cassaniti, Irene, Castelle, Martin, Castelli, Francesco, de Vera, Martín Castillo, Castro, Mateus V, Catherinot, Emilie, Celik, Jale Bengi, Ceschi, Alessandro, Chalumeau, Martin, Charbit, Bruno, Cheng, Matthew P., Clavé, Père, Clotet, Bonaventura, Codina, Anna, Cohen, Yves, Comarmond, Cloé, Combes, Alain, Comoli, Patrizia, Corsico, Angelo G, Coşkuner, Taner, Cvetkovski, Aleksandar, Cyrus, Cyril, Dalmau, David, Danion, François, Darley, David Ross, Das, Vincent, Dauby, Nicolas, Dauger, Stéphane, De Munter, Paul, de Pontual, Loic, Dehban, Amin, Delplancq, Geoffroy, Demoule, Alexandre, Desguerre, Isabelle, Di Sabatino, Antonio, Diehl, Jean-Luc, Dobbelaere, Stephanie, Domínguez-Garrido, Elena, Dubost, Clément, Ekwall, Olov, Bozdemir, Şefika Elmas, Elnagdy, Marwa H, Emiroglu, Melike, Endo, Akifumi, Erdeniz, Emine Hafize, Aytekin, Selma Erol, Lasa, Maria Pilar Etxart, Euvrard, Romain, Fabio, Giovanna, Faivre, Laurence, Falck, Antonin, Fartoukh, Muriel, Faure, Morgane, Arquero, Miguel Fernandez, Ferrer, Ricard, Ferreres, Jose, Francois, Bruno, Fumadó, Victoria, Fung, Kitty S C, Fusco, Francesca, Gagro, Alenka, Solis, Blanca Garcia, Gaussem, Pascale, Gayretli, Zeynep, Gil-Herrera, Juana, Gilardin, Laurent, Gatineau, Audrey Giraud, Girona-Alarcón, Mònica, Cifuentes Godínez, Karen Alejandra, Goffard, Jean-Christophe, Gonzales, Nacho, Gonzalez-Granado, Luis I, González-Montelongo, Rafaela, Guerder, Antoine, Gülhan, Belgin, Gumucio, Victor Daniel, Hanitsch, Leif Gunnar, Gunst, Jan, Hadjadj, Jérôme, Hancerli, Selda, Hariyan, Tetyana, Hatipoglu, Nevin, Heppekcan, Deniz, Hernandez-Brito, Elisa, Ho, Po-ki, Holanda-Peña, María Soledad, Horcajada, Juan P, Hraiech, Sami, Humbert, Linda, Hung, Ivan F N, Iglesias, Alejandro D., Íñigo-Campos, Antonio, Jamme, Matthieu, Arranz, María Jesús, Jimeno, Marie-Thérèse, Jordan, Iolanda, Yüksek, Saliha Kanık, Kara, Yalcin Burak, Karahan, Aydın, Karbuz, Adem, Yasar, Kadriye Kart, Kasapcopur, Ozgur, Kashimada, Kenichi, Demirkol, Yasemin Kendir, Kido, Yasutoshi, Kizil, Can, Kılıç, Ahmet Osman, Klocperk, Adam, Koutsoukou, Antonia, Król, Zbigniew J., Ksouri, Hatem, Kuentz, Paul, Kwan, Arthur M C, Kwan, Yat Wah M, Kwok, Janette S Y, Lagier, Jean-Christophe, Lam, David S Y, Lampropoulou, Vicky, Lanternier, Fanny, LAU, Yu-Lung, Le Bourgeois, Fleur, Leo, Yee-Sin, Lopez, Rafael Leon, Leung, Daniel, Levin, Michael, Levy, Michael, Lévy, Romain, Li, Zhi, Lilleri, Daniele, Bolanos Lima, Edson Jose Adrian, Linglart, Agnes, López-Collazo, Eduardo, Lorenzo-Salazar, José M., Louapre, Céline, Lubetzki, Catherine, Lung, Kwok-Cheung, Luyt, Charles-Edouard, Lye, David C, Magnone, Cinthia, Marchioni, Enrico, Marioli, Carola, Marjani, Majid, Marques, Laura, Pereira, Jesus Marquez, Martín-Nalda, Andrea, Pueyo, David Martínez, Martinez-Picado, Javier, Marzana, Iciar, Mata-Martínez, Carmen, Mathian, Alexis, Matos, Larissa RB, Matthews, Gail V, Mayaux, Julien, McLaughlin-Garcia, Raquel, Meersseman, Philippe, Mège, Jean-Louis, Mekontso-Dessap, Armand, Melki, Isabelle, Meloni, Federica, Meritet, Jean-François, Merlani, Paolo, Akcan, Özge Metin, Mezidi, Mehdi, Migeotte, Isabelle, Millereux, Maude, Million, Matthieu, Mirault, Tristan, Mircher, Clotilde, Mirsaeidi, Mehdi, Mizoguchi, Yoko, Modi, Bhavi P, Mojoli, Francesco, Moncomble, Elsa, Melián, Abián Montesdeoca, Martinez, Antonio Morales, Morandeira, Francisco, Morange, Pierre-Emmanuel, Mordacq, Cléemence, Mouly, Stéphane J, Muñoz-Barrera, Adrián, Nafati, Cyril, Nagashima, Shintaro, Nakagama, Yu, Neven, Bénédicte, Neves, João Farela, Ng, Lisa FP, Ng, Yuk-Yung, Nielly, Hubert, Medina, Yeray Novoa, Cuadros, Esmeralda Nuñez, Ocejo-Vinyals, J. Gonzalo, Okamoto, Keisuke, Oualha, Mehdi, Ouedrani, Amani, Özçelik, Tayfun, Ozkaya-Parlakay, Aslinur, Pagani, Michele, Papadaki, Maria, Parizot, Christophe, Parola, Philippe, Pascreau, Tiffany, Paul, Stéphane, Paz-Artal, Estela, Pedraza, Sigifredo, González Pellecer, Nancy Carolina, Pellegrini, Silvia, de Diego, Rebeca Pérez, Pérez-Fernández, Xosé Luis, Philippe, Aurélien, Picod, Adrien, de Chambrun, Marc Pineton, Piralla, Antonio, Ploin, Dominique, Poissy, Julien, Poncelet, Géraldine, Poulakou, Garyphallia, Pouletty, Marie S, Pourshahnazari, Persia, Qiu-Chen, Jia Li, Quentric, Paul, Rambaud, Thomas, Raoult, Didier, Raoult, Violette, Rebillat, Anne-Sophie, Redin, Claire, Resmini, Léa, Ricart, Pilar, Richard, Jean-Christophe, Rigo-Bonnin, Raúl, Rivet, Nadia, Rivière, Jacques G, Rocamora-Blanch, Gemma, Rodero, Mathieu P, Rodrigo, Carlos, Rodriguez, Luis Antonio, Rodriguez-Palmero, Agustí, Romero, Carolina Soledad, Rothenbuhler, Anya, Roux, Damien, Rovina, Nikoletta, Rozenberg, Flore, Ruch, Yvon, Ruiz, Montse, Ruiz del Prado, Maria Yolanda, Ruiz-Rodriguez, Juan Carlos, Sabater-Riera, Joan, Saks, Kai, Salagianni, Maria, Sanchez, Oliver, Sánchez-Montalvá, Adrián, Sánchez-Ramón, Silvia, Schidlowski, Laire, Schluter, Agatha, Schmidt, Julien, Schmidt, Matthieu, Schuetz, Catharina, Schweitzer, Cyril E, Scolari, Francesco, Seijo, Luis, Seminario, Analia Gisela, Sene, Damien, Seng, Piseth, Senoglu, Sevtap, Seppänen, Mikko, Llovich, Alex Serra, Siguret, Virginie, Siouti, Eleni, Smadja, David M, Smith, Nikaia, Sobh, Ali, Solanich, Xavier, Solé-Violán, Jordi, Soler, Catherine, Sözeri, Betül, Stella, Giulia Maria, Stepanovskiy, Yuriy, Stoclin, Annabelle, Taccone, Fabio, Taupin, Jean-Luc, Tavernier, Simon J, Tello, Loreto Vidaur, Terrier, Benjamin, Thiery, Guillaume, Thorball, Christian, Thorn, Karolina, Thumerelle, Caroline, Tipu, Imran, Tolstrup, Martin, Tomasoni, Gabriele, Toubiana, Julie, Alvarez, Josep Trenado, Triantafyllia, Vasiliki, Trouillet-Assant, Sophie, Tsang, Owen T Y, Tserel, Liina, Tso, Eugene Y K, Tucci, Alessandra, Tüter Öz, Şadiye Kübra, Ursini, Matilde Valeria, Utsumi, Takanori, Uzunhan, Yurdagul, Vabres, Pierre, Valencia-Ramos, Juan, Van Den Rym, Ana Maria, Vandernoot, Isabelle, Velez-Santamaria, Valentina, Zuniga Veliz, Silvia Patricia, Vidigal, Mateus C, Viel, Sébastien, Vilain, Cédric, Vilaire-Meunier, Marie E, Villar-García, Judit, Vincent, Audrey, Vogt, Guillaume, Voiriot, Guillaume, Volokha, Alla, Vuotto, Fanny, Wauters, Els, Wauters, Joost, Wu, Alan K L, Wu, Tak-Chiu, Yahşi, Aysun, Yesilbas, Osman, Yildiz, Mehmet, Young, Barnaby E, Yükselmiş, Ufuk, Zecca, Marco, Zuccaro, Valentina, Jens, Van Praet, Lambrecht, Bart N., Eva, Van Braeckel, Cédric, Bosteels, Levi, Hoste, Eric, Hoste, Bauters, Fré, De Clercq, Jozefien, Cathérine, Heijmans, Hans, Slabbynck, Leslie, Naesens, Florkin, Benoit, Boulanger, Cécile, Vanderlinden, Dimitri, Annereau, Jean-Philippe, Briseño-Roa, Luis, Gribouval, Olivier, Pelet, Anna, Andrejak, Claire, Angoulvant, 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Quentin, Le Mestre, Soizic, Le Nagard, Hervé, Lescure, François-Xavier, Letrou, Sophie, Levy, Yves, Lina, Bruno, Lingas, Guillaume, Lucet, Jean Christophe, Malvy, Denis, Mambert, Marina, Mentré, France, Meziane, Amina, Mouquet, Hugo, Mullaert, Jimmy, Neant, Nadège, Nguyen, Duc, Noret, Marion, Nseir, Saad, Papadopoulos, Aurélie, Paul, Christelle, Peiffer-Smadja, Nathan, Perpoint, Thomas, Petrov-Sanchez, Ventzislava, Peytavin, Gilles, Pham, Huong, Picone, Olivier, Piquard, Valentine, Puéchal, Oriane, Rabaud, Christian, Rosa-Calatrava, Manuel, Rossignol, Bénédicte, Rossignol, Patrick, Roy, Carine, Schneider, Marion, Su, Richa, Tardivon, Coralie, Tellier, Marie-Capucine, Téoulé, François, Terrier, Olivier, Timsit, Jean-François, Tual, Christelle, Van Der Werf, Sylvie, Vanel, Noémie, Veislinger, Aurélie, Visseaux, Benoit, Wiedemann, Aurélie, Yazdanpanah, Yazdan, Alavoine, Loubna, Behillil, Sylvie, Charpentier, Charlotte, Dechanet, Aline, Ecobichon, Jean-Luc, Frezouls, Wahiba, Houhou, Nadhira, Lehacaut, Jonathan, Lucet, Jean-Christophe, Manchon, Pauline, Nouroudine, Mariama, Quintin, Caroline, Thy, Michael, van der Werf, Sylvie, Vignali, Valérie, Chahine, Abir, Waucquier, Nawal, Migaud, Maria-Claire, Djossou, Félix, Mergeay-Fabre, Mayka, Lucarelli, Aude, Demar, Magalie, Bruneau, Léa, Gérardin, Patrick, Maillot, Adrien, Payet, Christine, Laviolle, Bruno, Laine, Fabrice, Paris, Christophe, Desille-Dugast, Mireille, Fouchard, Julie, Pistone, Thierry, Perreau, Pauline, Gissot, Valérie, Le Goas, Carole, Montagne, Samatha, Richard, Lucie, Bouiller, Kévin, Desmarets, Maxime, Meunier, Alexandre, Lefévre, Benjamin, Jeulin, Hélène, Legrand, Karine, Lomazzi, Sandra, Tardy, Bernard, Gagneux-Brunon, Amandine, Bertholon, Frédérique, Botelho-Nevers, Elisabeth, Kouakam, Christelle, Leturque, Nicolas, Roufai, Layidé, Amat, Karine, Espérou, Hélène, Hendou, Samia, van Agtmael, Michiel, Algera, Anne Geke, Appelman, Brent, van Baarle, Frank, Bax, Diane, Beudel, Martijn, Bogaard, Harm 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Marry, Stijnis, Cornelis S., Stilma, Willemke, Teunissen, Charlotte, Thoral, Patrick, Tsonas, Anissa M, Tuinman, Pieter R., van der Valk, Marc, Veelo, Denise, Volleman, Carolien, de Vries, Heder, Vught, Lonneke A., van Vugt, Michèle, Wouters, Dorien, Zwinderman, A. H (Koos), Brouwer, Matthijs C., Wiersinga, W. Joost, Vlaar, Alexander P.J., Tompkins, Miranda F., Alba, Camille, Hupalo, Daniel N., Rosenberger, John, Sukumar, Gauthaman, Wilkerson, Matthew D., Zhang, Xijun, Lack, Justin, Oler, Andrew J., Dobbs, Kerry, Delmonte, Ottavia M., Danielson, Jeffrey J., Bettini, Laura Rachele, D’Angio, Mariella, Beretta, Ilaria, Imberti, Luisa, Sottini, Alessandra, Quaresima, Virginia, Quiros-Roldan, Eugenia, Rossi, Camillo, Children's Hospital, HUS Children and Adolescents, Clinicum, Department of Medicine, UCL - SSS/IREC/PNEU - Pôle de Pneumologie, ORL et Dermatologie, AII - Infectious diseases, ANS - Neuroinfection & -inflammation, Neurology, Infectious diseases, Center of Experimental and Molecular Medicine, APH - Aging & Later Life, APH - Global Health, APH - Quality of Care, AII - Amsterdam institute for Infection and Immunity, APH - Health Behaviors & Chronic Diseases, Global Health, APH - Methodology, Graduate School, ACS - Heart failure & arrhythmias, Anesthesiology, ACS - Diabetes & metabolism, APH - Digital Health, APH - Personalized Medicine, ACS - Microcirculation, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques (LCBPT - UMR 8601), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Laboratory of Human Genetics of Infectious Diseases (Necker Branch - INSERM U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Rockefeller University [New York], Génomes, biologie cellulaire et thérapeutiques (GenCellDi (UMR_S_944)), Collège de France (CdF (institution))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Helix [San Mateo, CA], Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Özçelik, Tayfun, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Pathology, Asano, T., Boisson, B., Onodi, F., Matuozzo, D., Moncada-Velez, M., Renkilaraj, M. R. L. M., Zhang, P., Meertens, L., Bolze, A., Materna, M., Korniotis, S., Gervais, A., Talouarn, E., Bigio, B., Seeleuthner, Y., Bilguvar, K., Zhang, Y., Neehus, A. -L., Ogishi, M., Pelham, S. J., Le Voyer, T., Rosain, J., Philippot, Q., Soler-Palacin, P., Colobran, R., Martin-Nalda, A., Riviere, J. G., Tandjaoui-Lambiotte, Y., Chaibi, K., Shahrooei, M., Darazam, I. A., Olyaei, N. A., Mansouri, D., Hatipoglu, N., Palabiyik, F., Ozcelik, T., Novelli, G., Novelli, A., Casari, G., Aiuti, A., Carrera, P., Bondesan, S., Barzaghi, F., Rovere-Querini, P., Tresoldi, C., Franco, J. L., Rojas, J., Reyes, L. F., Bustos, I. G., Arias, A. A., Morelle, G., Kyheng, C., Troya, J., Planas-Serra, L., Schluter, A., Gut, M., Pujol, A., Allende, L. M., Rodriguez-Gallego, C., Flores, C., Cabrera-Marante, O., Pleguezuelo, D. E., Diego, R. P. D., Keles, S., Aytekin, G., Akcan, O. M., Bryceson, Y. T., Bergman, P., Brodin, P., Smole, D., Smith, C. I. E., Norlin, A. -C., Campbell, T. M., Covill, L. E., Hammarstrom, L., Pan-Hammarstrom, Q., Abolhassani, H., Mane, S., Marr, N., Ata, M., Ali, F. A., Khan, T., Spaan, A. N., Dalgard, C. L., Bonfanti, P., Biondi, A., Tubiana, S., Burdet, C., Nussbaum, R., Kahn-Kirby, A., Snow, A. L., Bustamante, J., Puel, A., Boisson-Dupuis, S., Zhang, S. -Y., Beziat, V., Lifton, R. P., Bastard, P., Notarangelo, L. D., Abel, L., Su, H. C., Jouanguy, E., Amara, A., Soumelis, V., Cobat, A., Zhang, Q., Casanova, J. -L., Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Génomes, biologie cellulaire et thérapeutiques (GenCellDi (U944 / UMR7212)), Collège de France (CdF (institution))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut Pasteur [Paris] (IP), Génétique Moléculaire des Virus à ARN - Molecular Genetics of RNA Viruses (GMV-ARN (UMR_3569 / U-Pasteur_2)), Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Agents infectieux, résistance et chimiothérapie - UR UPJV 4294 (AGIR ), Université de Picardie Jules Verne (UPJV)-CHU Amiens-Picardie, CHU Amiens-Picardie, French COVID cohort study group, The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, Rockefeller University, the St. Giles Foundation, the NIH (R01AI088364), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Award (CTSA) program (UL1TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at the George Mason University, the Yale Center for Mendelian Genomics and the GSP Coordinating Center funded by the National Human Genome Research Institute (NHGRI) (UM1HG006504 and U24HG008956), the Fisher Center for Alzheimer’s Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the 'Investments for the Future' program (ANR-10-IAHU-01) and the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the FRM and ANR GENCOVID project, the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), and ANR AABIFNCOV (ANR-20-CO11-0001) projects, the European Union’s Horizon 2020 Research and Innovation Program under grant agreement no. 824110 (EASI-genomics), the Square Foundation, Grandir–Fonds de solidarité pour l’enfance, the SCOR Corporate Foundation for Science, Fondation du Souffle, Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM, and the University of Paris. The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (RECOVER WP 6). The Neurometabolic Diseases Laboratory received funding from the European Union’s Horizon 2020 Research and Innovation Program (EasiGenomics grant no. 824110 COVID-19/PID12342). A.P., R.P.d.D., C.R.-G., and C.F. were funded by Instituto de Salud Carlos III (COV20_01333 and COV20_01334), the Spanish Ministry of Science and Innovation (RTC-2017-6471-1, AEI/FEDER, UE), Fundación DISA (OA18/017), and Cabildo Insular de Tenerife (CGIEU0000219140 and 'Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19'). The laboratories of G.N. and A.N. were supported by a grant awarded to Regione Lazio (PROGETTI DI GRUPPI DI RICERCA 2020) no. A0375-2020-36663, GecoBiomark. A. Amara’s laboratory was supported by ANR under the 'Investments for the Future' program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the FRM (EQU202003010193), ANR (ANR-20-COVI-000 project IDISCOVR and ANR-20-CO11-0004 project FISHBP), and the University of Paris (Plan de Soutien Covid-19: RACPL20FIR01-COVID-SOUL). This work was supported, in part, by the Division of Intramural Research, NIAID, NIH (grants 1ZIAAI001265 to H.C.S. and ZIA AI001270 to L.D.N.). The G.C. laboratory was supported by the Italian Ministry of Health (grant COVID-2020-12371617) and the intramural COVID Host Genetics program. The J.L.F. laboratory was supported, in part, by the Coopération Scientifique France-Colciencias (ECOS-Nord/COLCIENCIAS/MEN/ICETEX, 806-2018) and Colciencias contract 713-2016 (no. 111574455633). The V.S. laboratory was supported by ANR DENDRISEPSIS (ANR-17-CE15-0003) and ANR APCOD (ANR-17-CE15-0003-01), a Fast Grant from the Mercatus Center, FRM, University of Paris PLAN D’URGENCE COVID19. The N.M. laboratory was supported by Sidra Medicine (SDR400048) and the Qatar National Research Fund (grant No. NPRP9-251-3-045). A.-L.N. was supported by the Bettencourt Schueller Foundation and the International PhD program of the Imagine Institute. P. Bergman and C.I.E.S received support from the Center for Medical Innovation (CIMED), the Swedish Medical Research Council and the Stockholm County Council (ALF-project). Part of this work was generated within the European Reference Network for rare primary immunodeficiency, autoinflammatory and autoimmune diseases (RITA)., Members of French COVID Cohort Study Group: Laurent Abel1, Claire Andrejak2, François Angoulvant3, Delphine Bachelet4, Marie Bartoli5, Romain Basmaci6, Sylvie Behilill7, Marine Beluze8, Dehbia Benkerrou9, Krishna Bhavsar4, Lila Bouadma4, Sabelline Bouchez10, Maude Bouscambert11, Minerva Cervantes-Gonzalez4, Anissa Chair4, Catherine Chirouze12, Alexandra Coelho13, Camille Couffignal4, Sandrine Couffin-Cadiergues14, Eric d’Ortenzio5, Marie-Pierre Debray4, Lauren Deconinck4, Dominique Deplanque15, Diane Descamps4, Mathilde Desvallée16, Alpha Diallo5, Alphonsine Diouf13, Céline Dorival9, François Dubos17, Xavier Duval4, Brigitte Elharrar18, Philippine Eloy4, Vincent Enouf7, Hélène Esperou14, Marina Esposito-Farese4, Manuel Etienne19, Eglantine Ferrand Devouge19, Nathalie Gault4, Alexandre Gaymard11, Jade Ghosn4, Tristan Gigante20, Morgane Gilg20, Jérémie Guedj21, Alexandre Hoctin13, Isabelle Hoffmann4, Ikram Houas14, Jean-Sébastien Hulot22, Salma Jaafoura14, Ouifiya Kafif4, Florentia Kaguelidou23, Sabrina Kali4, Antoine Khalil4, Coralie Khan16, Cédric Laouénan4, Samira Laribi4, Minh Le4, Quentin Le Hingrat4, Soizic Le Mestre5, Hervé Le Nagard24, François-Xavier Lescure4, Sophie Letrou4, Yves Levy25, Bruno Lina11, Guillaume Lingas24, Jean Christophe Lucet4, Denis Malvy26, Marina Mambert13, France Mentré4, Amina Meziane9, Hugo Mouquet7, Jimmy Mullaert4, Nadège Neant24, Duc Nguyen26, Marion Noret27, Saad Nseir17, Aurélie Papadopoulos14, Christelle Paul5, Nathan Peiffer-Smadja4, Thomas Perpoint28, Ventzislava Petrov-Sanchez5, Gilles Peytavin4, Huong Pham4, Olivier Picone6, Valentine Piquard4, Oriane Puéchal29, Christian Rabaud30, Manuel Rosa-Calatrava11, Bénédicte Rossignol20, Patrick Rossignol30, Carine Roy4, Marion Schneider4, Richa Su4, Coralie Tardivon4, Marie-Capucine Tellier4, François Téoulé9, Olivier Terrier11, Jean-François Timsit4, Christelle Tual31, Sarah Tubiana4, Sylvie Van Der Werf7, Noémie Vanel32, Aurélie Veislinger31, Benoit Visseaux4, Aurélie Wiedemann25, Yazdan Yazdanpanah4, ANR-17-CE15-0003,DENDRISEPSIS,Analyse systémique des cellules présentatrices d'antigène dans le sepsis humain(2017), ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), Asano, T, Boisson, B, Onodi, F, Matuozzo, D, Moncada-Velez, M, Maglorius Renkilaraj, M, Zhang, P, Meertens, L, Bolze, A, Materna, M, Korniotis, S, Gervais, A, Talouarn, E, Bigio, B, Seeleuthner, Y, Bilguvar, K, Zhang, Y, Neehus, A, Ogishi, M, Pelham, S, Le Voyer, T, Rosain, J, Philippot, Q, Soler-Palacín, P, Colobran, R, Martin-Nalda, A, Rivière, J, Tandjaoui-Lambiotte, Y, Chaïbi, K, Shahrooei, M, Darazam, I, Olyaei, N, Mansouri, D, Hatipoğlu, N, Palabiyik, F, Ozcelik, T, Novelli, G, Novelli, A, Casari, G, Aiuti, A, Carrera, P, Bondesan, S, Barzaghi, F, Rovere-Querini, P, Tresoldi, C, Franco, J, Rojas, J, Reyes, L, Bustos, I, Arias, A, Morelle, G, Christèle, K, Troya, J, Planas-Serra, L, Schlüter, A, Gut, M, Pujol, A, Allende, L, Rodriguez-Gallego, C, Flores, C, Cabrera-Marante, O, Pleguezuelo, D, de Diego, R, Keles, S, Aytekin, G, Akcan, O, Bryceson, Y, Bergman, P, Brodin, P, Smole, D, Smith, C, Norlin, A, Campbell, T, Covill, L, Hammarström, L, Pan-Hammarström, Q, Abolhassani, H, Mane, S, Marr, N, Ata, M, Al Ali, F, Khan, T, Spaan, A, Dalgard, C, Bonfanti, P, Biondi, A, Tubiana, S, Burdet, C, Nussbaum, R, Kahn-Kirby, A, Snow, A, Bustamante, J, Puel, A, Boisson-Dupuis, S, Zhang, S, Béziat, V, Lifton, R, Bastard, P, Notarangelo, L, Abel, L, Su, H, Jouanguy, E, Amara, A, Soumelis, V, Cobat, A, Zhang, Q, and Casanova, J
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Male ,SUBSETS ,[SDV]Life Sciences [q-bio] ,Penetrance ,REDUNDANT ,COVID-19 (Malaltia) ,0302 clinical medicine ,Resposta immunitària ,80 and over ,Medicine and Health Sciences ,Medicine ,Young adult ,Child ,X-linked recessive inheritance ,ComputingMilieux_MISCELLANEOUS ,Aged, 80 and over ,0303 health sciences ,education.field_of_study ,PYOGENIC BACTERIAL-INFECTIONS ,virus diseases ,Genetic Diseases, X-Linked ,HUMANS ,General Medicine ,Middle Aged ,PROTECTIVE IMMUNITY ,3. Good health ,Pedigree ,Settore MED/03 ,Immune System Diseases ,Genetic Diseases ,Child, Preschool ,Cohort ,medicine.symptom ,SINGLE-STRANDED RNA ,Adult ,Adolescent ,Aged ,Alleles ,COVID-19 ,Humans ,Infant ,Toll-Like Receptor 7 ,Young Adult ,Immunology ,Population ,Asymptomatic ,Article ,03 medical and health sciences ,HOST-DEFENSE ,Immune response ,Allele ,Preschool ,education ,030304 developmental biology ,TOLL-LIKE RECEPTORS ,business.industry ,RECOGNITION ,Proteins ,X-Linked ,medicine.disease ,Pneumonia ,3121 General medicine, internal medicine and other clinical medicine ,PLASMACYTOID DENDRITIC CELLS ,business ,Proteïnes ,030215 immunology - Abstract
Autosomal inborn errors of type I IFN immunity and autoantibodies against these cytokines underlie at least 10% of critical COVID-19 pneumonia cases. We report very rare, biochemically deleterious X-linked TLR7 variants in 16 unrelated male individuals aged 7 to 71 years (mean: 36.7 years) from a cohort of 1,202 male patients aged 0.5 to 99 years (mean: 52.9 years) with unexplained critical COVID-19 pneumonia. None of the 331 asymptomatically or mildly infected male individuals aged 1.3 to 102 years (mean: 38.7 years) tested carry such TLR7 variants (p = 3.5 × 10-5). The phenotypes of five hemizygous relatives of index cases infected with SARS-CoV-2 include asymptomatic or mild infection (n=2, 5 and 38 years), or moderate (n=1, 5 years), severe (n=1, 27 years), or critical (n=1, 29 years) pneumonia. Two boys (aged 7 and 12 years) from a cohort of 262 male patients with severe COVID-19 pneumonia (mean: 51.0 years) are hemizygous for a deleterious TLR7 variant. The cumulative allele frequency for deleterious TLR7 variants in the male general population is < 6.5x10-4 We also show that blood B cell lines and myeloid cell subsets from the patients do not respond to TLR7 stimulation, a phenotype rescued by wild-type TLR7 The patients' blood plasmacytoid dendritic cells (pDCs) produce low levels of type I IFNs in response to SARS-CoV-2. Overall, X-linked recessive TLR7 deficiency is a highly penetrant genetic etiology of critical COVID-19 pneumonia, in about 1.8% of male patients below the age of 60 years. Human TLR7 and pDCs are essential for protective type I IFN immunity against SARS-CoV-2 in the respiratory tract. Funding: The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, Rockefeller University; the St. Giles Foundation; the NIH (R01AI088364), the National Center for Advancing Translational Sciences (NCATS); NIH Clinical and Translational Science Award (CTSA) program (UL1TR001866); a Fast Grant from Emergent Ventures; Mercatus Center at the George Mason University; the Yale Center for Mendelian Genomics and the GSP Coordinating Center funded by the National Human Genome Research Institute (NHGRI) (UM1HG006504 and U24HG008956); the Meyer Foundation; the JPB Foundation; the French National Research Agency (ANR) under the “Investments for the Future” program (ANR-10-IAHU-01) and the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID); the French Foundation for Medical Research (FRM) (EQU201903007798); the FRM and ANR GENCOVID project, the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), and ANR AABIFNCOV (ANR-20-CO11-0001) projects; the European Union’s Horizon 2020 Research and Innovation Program under grant agreement no. 824110 (EASI-genomics). The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (RECOVER WP 6). The Neurometabolic Diseases Laboratory received funding from the European Union’s Horizon 2020 Research and Innovation Program (EasiGenomics grant no. 824110 COVID-19/PID12342). A.P., R.P.d.D., C.R.-G., and C.F. were funded by Instituto de Salud Carlos III (COV20_01333 and COV20_01334), the Spanish Ministry of Science and Innovation (RTC-2017-6471-1; AEI/FEDER, UE), Fundación DISA (OA18/017), and Cabildo Insular de Tenerife (CGIEU0000219140 and “Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19”). The laboratories of G.N. and A.N. were supported by a grant awarded to Regione Lazio (PROGETTI DI GRUPPI DI RICERCA 2020) no. A0375-2020-36663, GecoBiomark. A. Amara’s laboratory was supported by ANR under the “Investments for the Future” program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the FRM (EQU202003010193), ANR (ANR-20-COVI-000 project IDISCOVR and ANR-20-CO11-0004 project FISHBP), and the University of Paris (Plan de Soutien Covid-19: RACPL20FIR01-COVID-SOUL). This work was supported, in part, by the Division of Intramural Research, NIAID, NIH (grants 1ZIAAI001265 to H.C.S. and ZIA AI001270 to L.D.N.). The G.C. laboratory was supported by the Italian Ministry of Health (grant COVID-2020-12371617) and the intramural COVID Host Genetics program. The J.L.F. laboratory was supported, in part, by the Coopération Scientifique France-Colciencias (ECOS-Nord/COLCIENCIAS/MEN/ICETEX; 806-2018) and Colciencias contract 713-2016 (no. 111574455633). The V.S. laboratory was supported by ANR DENDRISEPSIS (ANR-17-CE15-0003) and ANR APCOD (ANR-17-CE15-0003-01), a Fast Grant from the Mercatus Center, FRM, University of Paris PLAN D’URGENCE COVID19. The N.M. laboratory was supported by Sidra Medicine (SDR400048) and the Qatar National Research Fund (grant No. NPRP9-251-3-045)
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- 2021
38. Pure modulation and accurate measurement of optical beam's tilt and displacement
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Li Zhi, Hengxin Sun, Jiangrui Gao, Kui Liu, and Hui Guo
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010302 applied physics ,Physics ,business.industry ,Local oscillator ,Physics::Optics ,01 natural sciences ,Signal ,Displacement (vector) ,010305 fluids & plasmas ,law.invention ,Lens (optics) ,Optics ,Tilt (optics) ,Homodyne detection ,law ,Modulation ,0103 physical sciences ,business ,Instrumentation ,Beam (structure) - Abstract
We developed a tilt modulation technique of a laser beam with a wedged crystal. Combined with a phase-compensating crystal, a pure tilt modulation with a wide bandwidth (actually determined by the bandwidth of electro-optic crystals) is realized. By Fourier transformation with a lens, the tilt signal is transformed into displacement. With homodyne detection using a local oscillator of the first-order Hermite-Gauss mode (HG10) and a 4F phase-monitoring system, we measure the displacement and tilt of a laser probe beam. This technique can be used in metrology, such as Newtonian gravitational constant determination and gravitational wave detection, or the calibration of a spatial sensor, such as tilt/displacement sensors.
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- 2021
39. Rotation correction method of thread image based on machine vision
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Jie Wang, Man Long Chen, Kui Li, and Li Zhi Yan
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business.industry ,Computer science ,Machine vision ,Coordinate system ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Skew ,Thread (computing) ,Gauge (firearms) ,Image (mathematics) ,Computer Science::Performance ,Screw thread ,Computer Science::Programming Languages ,Computer vision ,Artificial intelligence ,business ,Computer Science::Operating Systems ,Rotation (mathematics) - Abstract
In order to obtain accurate diameter parameters when measuring cylindrical thread by machine vision, it is necessary to calibrate the measuring coordinate system of acquired thread image. Firstly, the principle, model of thread image rotation correction is established. Secondly, the relationship between the deflection Angle of the thread image and the measurement result of the middle diameter of the thread is obtained by theoretical pushover. An algorithm flow of image rotation correction is proposed. At last, the thread plug gauge is taken as the experimental object to carry out the comparative test. The experimental data show that the proposed algorithm can realize the correction of thread image, the measurement data fluctuated in a small range, and the measured diameter variance of thread is reduced by 77.1% compared with the traditional correction algorithm. It is shown that the proposed correction algorithm can accurately and efficiently measure the parameters of skew thread images.
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- 2021
40. Repair of symptomatic bilateral L5 spondylolysis with autogenous iliac crest graft and temporary intersegmental pedicle screw fixation in youth
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Tian-Sheng Sun, Kai Guan, Li-Zhi Zhang, Zhang Zhicheng, Dajiang Ren, Yang Zhang, Guang-Min Zhao, and Fang Li
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Adult ,Male ,medicine.medical_specialty ,Adolescent ,medicine.medical_treatment ,Spondylolysis ,Diseases of the musculoskeletal system ,Iliac crest ,Ilium ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Pedicle Screws ,Back pain ,medicine ,Internal fixation ,Humans ,Orthopedics and Sports Medicine ,Autografts ,Device Removal ,Fixation (histology) ,Motion segment ,Retrospective Studies ,Orthopedic surgery ,Bone Transplantation ,Lumbar Vertebrae ,business.industry ,030229 sport sciences ,medicine.disease ,Low back pain ,Sagittal plane ,Surgery ,medicine.anatomical_structure ,Spinal Fusion ,Treatment Outcome ,RC925-935 ,Female ,medicine.symptom ,business ,Lumbar spondylolysis ,030217 neurology & neurosurgery ,RD701-811 ,Repair ,Research Article - Abstract
Background When symptomatic spondylolysis fail to respond to nonoperative treatment, surgical management may be required. A number of techniques have been described for repair by intrasegmental fixation with good results; however, there are still some problems. We reported a repair technique with temporary intersegmental pedicle screw fixation and autogenous iliac crest graft. The aim of present study is to assess the clinical outcomes of L5 symptomatic spondylolysis with this technique. Methods A retrospective analysis of 128 patients with L5 spondylolysis treated with this method was performed. According to CT scan, the spondylolysis were classified into 3 categories: line, intermediate, and sclerosis type. The diagnostic block test of L5 bilateral pars defect was done in all patients preoperatively. The sagittal and axial CT images were used to determine the bone union. The healing time, complications, number of spina bifida occulta, Japanese Orthopedic Association (JOA) score, and VAS for back pain were recorded. After fixation removal, the rate of ROM preservation at L5S1 was calculated. Results There were 97 patients (194 pars) followed with mean follow-up of 23 months (range, 12–36 months). The union rate of pars was 82.0% at 12 months and 94.3% at 24 months postoperatively. Low back pain VAS significantly (P < 0.05) improved from preoperative mean value of 7.2 to 1.3 at the final follow-up postoperatively (P < 0.05). JOA score increased significantly postoperatively (P < 0.05) with average improvement rate of 79.3%. The rates of L5S1 ROM preservation were 79.8% and 64.0% after fixation removal at 1 and 2 years postoperatively. There were 3 patients of delayed incision healing without other complications. Conclusions Although sacrificing L5S1 segment motion temporarily, more stability was obtained with intersegmental fixation. This technique is reliable for spondylolysis repair which has satisfactory symptom relief, high healing rate, low incidence of complications, and preserve a large part of ROM for fixed segment.
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- 2021
41. Rational Route of Delivery Mesenchymal Stem Cell Therapy for Acute Myocardial Infarction (AMI) and Chronic Ischemic Cardiomyopathy (ICM): a Systematic Review and Meta-analysis
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Huang Yan ting, Lin Zhishan, Su Yiwan, Gao Kai, Chen Shuqing, Lin Weizhao, Li Zhi, Yang Xiangbin, and Xu Meiling
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medicine.medical_specialty ,Ischemic cardiomyopathy ,Text mining ,business.industry ,Internal medicine ,Meta-analysis ,Mesenchymal stem cell ,Cardiology ,Medicine ,cardiovascular diseases ,Myocardial infarction ,business ,medicine.disease - Abstract
Background: Recent studies suggest that mesenchymal stem cells (MSCs) may have therapeutic potential for both acute myocardial infarction (AMI) and chronic ischemic cardiomyopathy (ICM). However, the rational route of delivery MSC therapy has not reached consensus. We performed a systematic review of clinical trials evaluating the rational route of delivery MSCs for AMI or ICM.Methods: Databases including Embase, PubMed, and Cochrane Central Register of Controlled Trials were searched from inception to February 2021. Studies that examined the use of MSCs in adults with AMI or ICM were eligible. Bias of included studies were assessed by the Cochrane risk of bias tool. The primary outcome was cardiac function assessed by left ventricular ejection fraction (LVEF) and the secondary outcome was cardiac remodeling which was assessed by left ventricular end-systolic volume (LVESV) and left ventricular end-diastolic volume (LVEDV), we also explored the safety between different routes. Results: 18 studies fulfilled eligibility criteria, which consist of 11 studies evaluated AMI and 7 studies evaluated ICM. In AMI group, only when patients received intracoronary infusion(IC) can improve LVEF (SMD 0.88, 95% CI 0.64-1.12), and there was a decrease in LVEDV&LVESV when administered IC or intravenous infusion (IV). While in ICM group, no significant difference in LVEF was noted no matter administered which route, and transendocardial stem cell injection(TESI) seems to be effective in decreasing LVEDV&LVESV. Safety appeared no difference between different routes. Conclusions: Results from our systematic review suggest that intracoronary infusion seems more effective for MSC’s delivery in AMI group, while in ICM group, TESI better.
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- 2021
42. The Clinical Significance of miR-21 in Guiding Chemotherapy for Patients with Osteosarcoma
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Zhuangzhuang Wu, Li-Zhi Li, and Zhi Lv
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Pharmacology ,Oncology ,medicine.medical_specialty ,Chemotherapy ,business.industry ,medicine.medical_treatment ,medicine.disease ,Control subjects ,chemotherapy ,Tumor tissue ,Pharmacogenomics and Personalized Medicine ,Potential biomarkers ,Internal medicine ,osteosarcoma ,medicine ,Molecular Medicine ,Osteosarcoma ,Clinical significance ,tumor tissue ,miR-21 ,Stage (cooking) ,business ,Pathological ,serum ,Original Research - Abstract
Li-Zhi Li, Zhuang-Zhuang Wu, Zhi Lv Department of Orthopaedics, The Second Hospital of Shanxi Medical University, Taiyuan, 030001, Peopleâs Republic of ChinaCorrespondence: Li-Zhi LiDepartment of Orthopaedics, The Second Hospital of Shanxi Medical University, NO. 382 Wuyi Road, Taiyuan, 030001, Peopleâs Republic of ChinaTel +86 351-3365105Email lzlsun_09dr@aliyun.comObjective: The present study aims to explore the correlation between osteosarcoma (OS) chemosensitivity and the expression levels of serum and tumor tissue micro-ribonucleic acid-21 (miR-21).Methods: The relevant miR-21 expression levels in 30 patients with OS were detected, and the gender, age, tumor location, pathological type, Enneking stage, and miR-21 expression changes before and after chemotherapy were retrospectively analyzed.Results: Serum and tumor tissue miR21 expression levels were significantly higher in patients with OS than in control subjects; the serum miR-21 expressions before and after chemotherapy were not related to patient age and gender. The effective chemotherapy group showed significant differences in miR-21 expression levels before and after chemotherapy.Conclusion: Serum and tumor tissue miR-21 expression levels in patients with OS are closely related to the effects of chemotherapy, making miR-21 a potential biomarker and therapeutic target for the diagnosis and evaluation of chemotherapy effects on patients with OS.Keywords: osteosarcoma, tumor tissue, serum, miR-21, chemotherapy
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- 2021
43. A review: Enhanced recovery of natural gas hydrate reservoirs
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Chang-Yu Sun, Li Zhi, Guang-Jin Chen, Tianduo Li, Qing Yuan, and Fengguang Li
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Environmental Engineering ,Petroleum engineering ,business.industry ,General Chemical Engineering ,02 engineering and technology ,General Chemistry ,Unconventional oil ,021001 nanoscience & nanotechnology ,Biochemistry ,Hydraulic fracturing ,Thermal stimulation ,020401 chemical engineering ,Enhanced recovery ,Natural gas ,Environmental science ,Fluid injection ,0204 chemical engineering ,0210 nano-technology ,Hydrate ,business ,Geothermal gradient - Abstract
Natural gas hydrate (NGH) is a highly efficient and clean energy, with huge reserves and widespread distribution in permafrost and marine areas. Researches all over the world are committed to developing an effective exploring technology for NGH reservoirs. In this paper, four conventional in-situ hydrate production methods, such as depressurization, thermal stimulation, inhibitor injection and CO2 replacement, are briefly introduced. Due to the limitations of each method, there has been no significantly breakthrough in hydrate exploring technology. Inspired by the development of unconventional oil and gas fields, researchers have put forward some new hydrate production methods. We summarize the enhanced hydrate exploiting methods, such as CO2/N2–CH4 replacement, CO2/H2–CH4 replacement, hydraulic fracturing treatment, and solid exploration; and potential hydrate mining techniques, such as self-generating heat fluid injection, geothermal stimulation, the well pattern optimization of hydrate exploring. The importance of reservoir stimulation technology for hydrate exploitation is emphasized, and it is believed that hydrate reservoir modification technology is a key to open hydrate resources exploitation, and the major challenges in the process of hydrate exploitation are pointed out. The combination of multiple hydrate exploring technologies and their complementary advantages will be the development trend in the future so as to promote the process of hydrate industrialization.
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- 2019
44. Mechanism of Cxc Chemokine Ligand 5 (CXCL5)/Cxc Chemokine Receptor 2 (CXCR2) Bio-Axis in Mice with Acute Respiratory Distress Syndrome
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Qing-Shan Zhou, Li-Zhi Feng, Chen-Liang Zhou, Min Shang, Ke Hu, and Chang-Yong Wang
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Male ,Pathology ,medicine.medical_specialty ,Chemokine ,ARDS ,Chemokine CXCL5 ,Lipopolysaccharide ,030204 cardiovascular system & hematology ,Receptors, Interleukin-8B ,03 medical and health sciences ,chemistry.chemical_compound ,Mice ,0302 clinical medicine ,Lab/In Vitro Research ,Medicine ,Animals ,CXC chemokine receptors ,Diffuse alveolar damage ,Lung ,Inflammation ,Respiratory Distress Syndrome ,biology ,business.industry ,Tumor Necrosis Factor-alpha ,Respiratory Distress Syndrome, Adult ,General Medicine ,respiratory system ,medicine.disease ,Pulmonary edema ,Mice, Inbred C57BL ,Disease Models, Animal ,medicine.anatomical_structure ,chemistry ,Matrix Metalloproteinase 9 ,CXCL5 ,030220 oncology & carcinogenesis ,biology.protein ,Matrix Metalloproteinase 2 ,business ,Chemokines, CXC - Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS) is a common acute and severe disease in clinic. Recent studies indicated that Cxc chemokine ligand 5 (CXCL5), an inflammatory chemokine, was associated with tumorigenesis. The present study investigated the role of the CXCL5/Cxc chemokine receptor 2 (CXCR2) bio-axis in ARDS, and explored the underlying molecular mechanism. MATERIAL AND METHODS The pathological morphology of lung tissue and degree of pulmonary edema were assessed by hematoxylin-eosin staining and pulmonary edema score, respectively. Real-time PCR and Western blot analysis were performed to detect the expression levels of CXCL5, CXCR2, Matrix metalloproteinases 2 (MMP2), and Matrix metalloproteinases 9 (MMP9) in lung tissues. Enzyme-linked immunosorbent assay (ELISA) was performed to determine the expression levels of CXCL5 and inflammatory factors (IL-1s, IL-6, TNF-alpha, and IL-10) in serum. RESULTS The results demonstrated that diffuse alveolar damage and pulmonary edema appeared in lipopolysaccharide (LPS)-induced ARDS and were positively correlated with the severity of ARDS. In addition, CXCL5 and its receptor CXCR2 were overexpressed by upregulation of MMP2 and MMP9 in lung tissues of ARDS. In addition, CXCL5 neutralizing antibody effectively alleviated inflammatory response, diffuse alveolar damage, and pulmonary edema, and decreased the expression levels of MMP2 and MMP9 compared to LPS-induced ARDS. CONCLUSIONS We found that CXCL5/CXCR2 accelerated the progression of ARDS, partly by upregulation of MMP2 and MMP9 in lung tissues with the release of inflammatory factors.
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- 2019
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45. Prognostic Value of Deep Learning PET/CT-Based Radiomics: Potential Role for Future Individual Induction Chemotherapy in Advanced Nasopharyngeal Carcinoma
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Wen Fei Li, Lei Chen, Wei Fan, Li Tian, Di Dong, Lu Li, Yan Ping Mao, Ling Long Tang, Jun Ma, Hao Peng, Li Zhi Liu, Ying Sun, Ai Hua Lin, Mengjie Fang, and Jie Tian
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Adult ,Male ,Cancer Research ,medicine.medical_specialty ,Adolescent ,Concordance ,030218 nuclear medicine & medical imaging ,Young Adult ,03 medical and health sciences ,Deep Learning ,0302 clinical medicine ,Risk Factors ,Positron Emission Tomography Computed Tomography ,medicine ,Humans ,Child ,Survival rate ,Aged ,Retrospective Studies ,PET-CT ,Nasopharyngeal Carcinoma ,medicine.diagnostic_test ,Receiver operating characteristic ,business.industry ,Induction chemotherapy ,Nasopharyngeal Neoplasms ,Induction Chemotherapy ,Middle Aged ,Nomogram ,Prognosis ,medicine.disease ,Survival Rate ,Nomograms ,ROC Curve ,Oncology ,Nasopharyngeal carcinoma ,Positron emission tomography ,030220 oncology & carcinogenesis ,Female ,Radiology ,business - Abstract
Purpose: We aimed to evaluate the value of deep learning on positron emission tomography with computed tomography (PET/CT)–based radiomics for individual induction chemotherapy (IC) in advanced nasopharyngeal carcinoma (NPC). Experimental Design: We constructed radiomics signatures and nomogram for predicting disease-free survival (DFS) based on the extracted features from PET and CT images in a training set (n = 470), and then validated it on a test set (n = 237). Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis were applied to evaluate the discriminatory ability of radiomics nomogram, and compare radiomics signatures with plasma Epstein–Barr virus (EBV) DNA. Results: A total of 18 features were selected to construct CT-based and PET-based signatures, which were significantly associated with DFS (P < 0.001). Using these signatures, we proposed a radiomics nomogram with a C-index of 0.754 [95% confidence interval (95% CI), 0.709–0.800] in the training set and 0.722 (95% CI, 0.652–0.792) in the test set. Consequently, 206 (29.1%) patients were stratified as high-risk group and the other 501 (70.9%) as low-risk group by the radiomics nomogram, and the corresponding 5-year DFS rates were 50.1% and 87.6%, respectively (P < 0.0001). High-risk patients could benefit from IC while the low-risk could not. Moreover, radiomics nomogram performed significantly better than the EBV DNA-based model (C-index: 0.754 vs. 0.675 in the training set and 0.722 vs. 0.671 in the test set) in risk stratification and guiding IC. Conclusions: Deep learning PET/CT-based radiomics could serve as a reliable and powerful tool for prognosis prediction and may act as a potential indicator for individual IC in advanced NPC.
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- 2019
46. Correlation between APACHE III score and sleep quality in ICU patients
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Li-Zhi Feng, Qing-Shan Zhou, Chang-Yong Wang, Chen-Liang Zhou, Min Shang, and Ke Hu
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Male ,Medicine (General) ,APACHE III score ,Icu patients ,medicine.medical_specialty ,Clinical Research Reports ,Critical Illness ,Severity of Illness Index ,intensive care unit ,Biochemistry ,law.invention ,Correlation ,03 medical and health sciences ,R5-920 ,0302 clinical medicine ,law ,Severity of illness ,Humans ,Medicine ,Hospital Mortality ,Prospective Studies ,severity of illness ,sleep ,APACHE ,Aged ,Sleep quality ,business.industry ,Biochemistry (medical) ,030208 emergency & critical care medicine ,Cell Biology ,General Medicine ,APACHE III ,Middle Aged ,Prognosis ,Intensive care unit ,Sleep in non-human animals ,Intensive Care Units ,030228 respiratory system ,Emergency medicine ,Female ,Observational study ,business ,Follow-Up Studies - Abstract
Objective To reveal the correlation between APACHE III score and sleep quality in patients in the intensive care unit (ICU). Methods This prospective, observational study included patients aged ≥18 years, who had been admitted to an integrated ICU for ≥48 h. Age, sex, Pittsburgh Sleep Quality Index (PSQI) prior to ICU, Numeric Rating Scales (NRS), noise, illumination, number of nursing interventions, Richards Campbell Sleep Questionnaire (RCSQ), and APACHE III score during sleep were evaluated. Results A total of 124 ICU patients were included, all with APACHE III scores Conclusion In ICU patients with APACHE III scores below 60 points, APACHE III score was not associated with sleep quality. PSQI score prior to ICU and noise were significantly inversely associated with sleep quality in this ICU patient population.
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- 2019
47. Relationship of circulating tumor cells and Epstein–Barr virus DNA to progression‐free survival and overall survival in metastatic nasopharyngeal carcinoma patients
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Ming Huang Hong, Hai Qiang Mai, Ming Yuan Chen, Ting Kang, Rui You, Wan Li Liu, Xiong Zou, Yi Nuan Zhang, Pei Yu Huang, Wei Bang Guo, Ai Hua Lin, Ke Ming Zhao, Li Zhi Liu, Mei Lin, Mu Sheng Zeng, You Ping Liu, Lin Quan Tang, and Yi Pan
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Adult ,Male ,Oncology ,Herpesvirus 4, Human ,Cancer Research ,medicine.medical_specialty ,Adolescent ,medicine.medical_treatment ,Kaplan-Meier Estimate ,Virus ,Young Adult ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Circulating tumor cell ,Predictive Value of Tests ,hemic and lymphatic diseases ,Internal medicine ,Antineoplastic Combined Chemotherapy Protocols ,Biomarkers, Tumor ,medicine ,Overall survival ,Humans ,Prospective Studies ,Progression-free survival ,Aged ,Chemotherapy ,Nasopharyngeal Carcinoma ,business.industry ,Epstein-Barr virus DNA ,Nasopharyngeal Neoplasms ,Middle Aged ,Neoplastic Cells, Circulating ,Prognosis ,medicine.disease ,Progression-Free Survival ,Nasopharyngeal carcinoma ,chemistry ,030220 oncology & carcinogenesis ,DNA, Viral ,Female ,business ,DNA - Abstract
We analyzed the number of circulating tumor cells (CTCs) and Epstein-Barr virus DNA (EBV DNA) for diagnosis, monitoring and prognosis of patients with metastatic nasopharyngeal carcinoma (mNPC). The levels of CTCs and EBV DNA were measured at baseline and after first-line chemotherapy in 148 mNPC patients prospectively enrolled between December 2014 and August 2016. We also collected 122 non-mNPC cases within the same time frame for examining CTCs and EBV DNA at baseline. In 270 NPC patients, we observed improved specificity (86.0% vs. 41.0%) and inferior sensitivity (42.3% vs. 81.3%) of CTCs as compared to EBV DNA for diagnosis of distant metastasis. mNPC patients were stratified into unfavorable and favorable prognostic groups, respectively, based on CTC of 12 at baseline and 1 after first-line chemotherapy and EBV DNA of 10,000 at baseline and 4,000 after first-line chemotherapy. Conversion of baseline unfavorable CTCs and EBV DNA to favorable after first-line chemotherapy was associated with significantly longer progression-free survival (PFS) and overall survival (OS) compared to patients with unfavorable CTCs and EBV DNA at both time points. Among patients with a complete/partial response as per imaging evaluation, favorable CTCs and EBV DNA levels after first-line chemotherapy were associated with significantly longer PFS and OS. In conclusion, our data demonstrated the number of CTCs and EBV DNA before, after and during first-line chemotherapy were strong predictive markers for mNPC patients. When utilized in conjunction with imaging studies, CTCs and EBV DNA could provide additional prognostic information.
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- 2019
48. The orbit deployment strategy of OOS system for refueling near-earth orbit satellites
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Pang Yujia, Zhang Zhimin, Li Zhi, Huang Jianbin, Meng Bo, Han Xu, and Huang Longfei
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020301 aerospace & aeronautics ,Earth's orbit ,business.industry ,Computer science ,Process (computing) ,Geosynchronous orbit ,Aerospace Engineering ,Response time ,02 engineering and technology ,01 natural sciences ,Multi-objective optimization ,0203 mechanical engineering ,Software deployment ,Physics::Space Physics ,0103 physical sciences ,Astrophysics::Earth and Planetary Astrophysics ,Orbit (control theory) ,Aerospace engineering ,business ,010303 astronomy & astrophysics ,Medium Earth orbit - Abstract
Extend lifetime of near-earth orbit satellites by on-orbit refueling has significant economic benefits, while the orbit deployment strategy of the on-orbit servicing (OOS) system which implements the refueling task directly affects the efficiency of on-orbit refueling mission. Three orbit deployment modes were proposed, including ground deployment, low earth orbit (LEO) deployment and the same orbit deployment. For the client satellites to be refueled on near-earth orbit including LEO, medium earth orbit (MEO) and geosynchronous orbit (GEO), the three deployment modes were compared quantitatively based on two evaluation indicators: the refueling response time and the economic benefits. The comparing results showed that for MEO and GEO client satellites, it is appropriate to adopt the same orbit deployment mode, while for LEO client satellites, ground deployment mode is more suitable. As the maximum economic benefits can be earned to refuel GEO client satellites, the orbit deployment scheme of OOS system for refueling GEO client satellites was further studied. A new architecture of OOS system called “1+N” consist of 1 fuel storage station and N refueling vehicles was proposed. The fuel storage station carries a great deal of fuel, running on orbit steadily. The refueling vehicles maneuver on GEO and implement the refueling operations for GEO client satellites. If the vehicles run out of fuel, they arrive at the station to be refueled. The weight and orbital altitude of fuel storage station, the number, weight, orbital altitude and orbital phase of refueling vehicles are the key parameters of the orbit deployment scheme. The mathematical model for optimizing the scheme was constructed, which takes shorten the refueling response time and lower the cost of OOS system as multi-objective. The calculation process of the optimization was explained. By analyzing the optimization results, the optimal orbit deployment scheme of OOS system containing 1 fuel storage station and 4 to 6 refueling vehicles was proposed.
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- 2019
49. Effects of blockage ratio and Reynolds number on particle deposition in duct airflow over a forward-facing step
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Li-zhi Zhang and Hao Lu
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Materials science ,Turbulence ,business.industry ,Airflow ,0211 other engineering and technologies ,Reynolds number ,02 engineering and technology ,Building and Construction ,Reynolds stress ,Mechanics ,Computational fluid dynamics ,symbols.namesake ,021105 building & construction ,symbols ,Duct (flow) ,021108 energy ,Particle size ,business ,Energy (miscellaneous) ,Particle deposition - Abstract
Deposition processes of particles in duct airflow over a forward-facing step (FFS) were numerically studied by computational fluid dynamics method. Reynolds stress model with velocity fluctuation modification and discrete particle model with turbulent particle dispersion were developed to predict airflow fields and particle motions respectively. After grid independence study and numerical validation, the effects of different Reynolds numbers and blockage ratios on particle deposition characteristics were investigated. Particle deposition velocities, deposition efficiency and deposition mechanisms in duct with a forward-facing step were analyzed and discussed. The results showed that particle deposition velocity in FFS duct keeps monotonically increasing as particle diameter increases. Moreover, particle deposition profile in FFS duct increases as blockage ratio and Reynolds number increases. Deposition efficiency is higher for small particles (dp 10 µm) than uniform duct case. When air velocity is fixed as 5.5 m/s, the maximum deposition efficiency of FFS duct can reach 84 when λ = 0.25 and particle size is 1 µm. Moreover, when air velocity increases, the deposition efficiency will increase. Reduction of deposition distance, production of high TKE region and interception of windward surface by FFS are dominant mechanisms to increase particle deposition rates. Moreover, the “particle free zone” appears when particle diameter is more than 10 um and blockage ratio is 0.5.
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- 2019
50. Effect of moxibustion on VEGF and EGF expressions in tumor tissues of rats with gastric tumor
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Li-zhi Ouyang, Jun-lin Shi, Zhuo-jun Peng, Jing Tan, Huan Zhao, Yu-pan Chen, and Ya-ping Lin
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medicine.medical_specialty ,medicine.medical_treatment ,0211 other engineering and technologies ,02 engineering and technology ,Moxibustion ,Zusanli ,Metastasis ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Epidermal growth factor ,Internal medicine ,021105 building & construction ,medicine ,business.industry ,Stomach ,Cancer ,medicine.disease ,030205 complementary & alternative medicine ,Vascular endothelial growth factor ,medicine.anatomical_structure ,Endocrinology ,Complementary and alternative medicine ,chemistry ,Cancer cell ,business - Abstract
To explore the inhibitory effect of moxibustion on tumor growth and metastasis, and also its possible mechanism, in gastric tumor-bearing rats by investigating the expressions of vascular endothelial growth factor (VEGF) and epidermal growth factor (EGF). Fifty healthy Sprague-Dawley (SD) rats (half male and half female) were routinely housed for 1 week. A total of 20 rats were randomly divided into a blank group and a sham operation group, with 10 rats in each group. The remaining 30 rats were used to make gastric cancer models by implantation of ascites-type Walker-256 cancer cells. After successful modeling, rats were randomly divided into a model group, a moxibustion group and an infrared group, with 10 rats in each group. From the day of modeling, the body weight of each group was weighed every 4 days. Warm moxibustion was alternately performed at two-group acupoints [Zhongwan (CV 12), Guanyuan (CV 4) and bilateral Zusanli (ST 36) in one group, and bilateral Pishu (BL 20) and Weishu (BL 21) in another group] in the moxibustion group. The body surface projection area of the stomach was irradiated with short-wave infrared rays in the infrared group, once a day, 20 min per time for 21 d. At the end of the treatment, the gastric tumor was completely dissected, and the tumor volume and tumor growth inhibition rate were calculated. Then the gastric tumor cell metastasis was recorded. The levels of VEGF and EGF in rat gastric tumor tissues were determined by enzyme-linked immunosorbent assay (ELISA). Compared with the blank group, the body weight of the model group decreased significantly after modeling (P
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- 2019
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