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2. Retina-Brain Homology: The Correlation Between Ophthalmic or Retinal Artery Occlusion and Ischemic Stroke

Author

Yao Y, Song Q, Zhang J, Wen Y, and Dou X

Subjects
retina, brain, ophthalmic artery occlusion, retinal artery occlusion, stroke, thrombolysis, Ophthalmology, RE1-994, Neurology. Diseases of the nervous system, RC346-429
Abstract

Yufeng Yao,1,2 Qiyuan Song,3 Jingnan Zhang,2,4 Yingying Wen,2,4 Xiaoyan Dou2 1Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 2Department of Ophthalmology, Shenzhen Second People’s Hospital, the First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong Province, People’s Republic of China; 3Department of Ophthalmology, Shenzhen Children’s Hospital, Shenzhen, Guangdong Province, People’s Republic of China; 4Shenzhen University Medical College, No.1066 Xueyuan Road, Shenzhen University, Shenzhen, Guangdong Province, People’s Republic of ChinaCorrespondence: Xiaoyan Dou, Email douxy08@163.comAbstract: The retina’s similar structure and function to the brain make it a unique visual “window” for studying cerebral disorders. Ophthalmic artery occlusion (OAO) or retinal artery occlusion (RAO) is a severe ophthalmic emergency that significantly affects visual acuity. Studies have demonstrated that patients with OAO or RAO face a notably higher risk of future acute ischemic stroke (AIS). However, ophthalmologists often overlook multidisciplinary approach involving the neurologist, to evaluate the risk of AIS and devise clinical treatment strategies for patients with OAO or RAO. Unlike the successful use of thrombolysis in AIS, the application of thrombolysis for OAO or RAO remains limited and controversial due to insufficient reliable evidence. In this review, we aim to summarize the anatomical and functional connections between the retina and the brain, and the clinical connection between OAO or RAO and AIS, compare and review recent advances in the effectiveness and safety of intravenous and intra-arterial thrombolysis therapy in patients with OAO or RAO, and discuss future research directions for OAO or RAO. Our goal is to advance the development of multidisciplinary diagnosis and treatment strategies for the disease, as well as to establish expedited pathways or thrombolysis guidelines for vascular intervention.Keywords: retina, brain, ophthalmic artery occlusion, retinal artery occlusion, stroke, thrombolysis

Published
2024

3. Nonlinear Relationship Between Low Density Lipoprotein and the Probability of Diabetic Macular Edema

Author

Yao Y, Lin Z, Ye B, Long T, Li S, Liang H, Luo T, and Dou X

Subjects
low density lipoprotein, diabetic macular edema, nonlinearity, association, Ophthalmology, RE1-994
Abstract

Yufeng Yao,1,2 Zhenli Lin,3 Baikang Ye,1 Tingxi Long,1,4 Suting Li,1,4 Huixian Liang,1,4 Tianyi Luo,1,4 Xiaoyan Dou1 1Department of Ophthalmology, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong Province, People’s Republic of China; 2Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 3Department of Ophthalmology, Shenzhen University General Hospital, Shenzhen, Guangdong Province, People’s Republic of China; 4Shenzhen University Medical College, Shenzhen University, Shenzhen, Guangdong Province, People’s Republic of ChinaCorrespondence: Xiaoyan Dou, Department of Ophthalmology, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, No. 3002 Sungang West Road, Futian District, Shenzhen, Guangdong Province, 518035, People’s Republic of China, Tel/Fax +86 13600169183, Email douxy08@163.comPurpose: Previous studies simply linearized the relationship between low density lipoprotein (LDL) and diabetic macular edema’s (DME) probability, ignoring the possibility of a nonlinear relationship between them. We aimed to investigate the nonlinear relationship between LDL and DME probability in patients with type 2 diabetes mellitus (T2DM).Patients and methods: The study recruited 431 T2DM patients who attended Guangdong Provincial People’s Hospital from December 2017 to November 2018. A multivariate logistic regression model was conducted to evaluate the association between LDL and DME probability. The nonlinear relationship was identified by generalized additive model. Subgroup analyses were performed to assess the consistency of the association in different subgroups.Results: LDL was positively associated with DME probability (OR=1.60, 95% CI: 1.10~2.34, P=0.0145) after adjusting for covariates. A nonlinear relationship between LDL and DME probability was discovered, with an inflection point for LDL around 4.85 mmol/L (95% CI: 4.18~4.93, P=0.037). The effect sizes and the confidence intervals on the left and right sides of inflection point were 2.17 (1.31 to 3.58) and 0.26 (0.04 to 1.77), respectively. Subgroup analyses revealed other variables had no effect on the association between them.Conclusion: Our finding suggested LDL was positively correlated with DME probability in T2DM patients. And the relationship between LDL and DME probability was nonlinear. Our findings need to be confirmed by further causal researches.Keywords: low density lipoprotein, diabetic macular edema, nonlinearity, association

Published
2024

4. Prevalence and Determinants of Anxiety and Depression Among Healthcare Workers in Liaoning Province, China

Author

Lu J, Dou X, Yi Y, Yu Y, and Zhou L

Subjects
anxiety, depression, cross-sectional study, healthcare workers, Public aspects of medicine, RA1-1270
Abstract

Jiachen Lu, Xiaofeng Dou, Yaohui Yi, Yingying Yu, Ling Zhou School of Public Health, Dalian Medical University, Dalian, People’s Republic of ChinaCorrespondence: Ling Zhou, Email zhouling0609@163.comPurpose: To assess the anxiety and depression and their predictors among healthcare workers in Liaoning Province, China.Methods: In order to explore the influencing factors and prevalence of anxiety and depression among healthcare workers, a cross-sectional research design was used to survey 500 healthcare workers using the 14-item Hospital Anxiety Depression Scale (HADS), the Rosenberg Self-Esteem Scale (RSES), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Survey of Perceived Organizational Support (SPOS).Results: About 47.12% of the healthcare workers suffered from anxiety and 71.63% suffered from depression. In our study, we found that the health status (OR: 0.540, 95% CI: 0.298– 0.976), self-esteem (OR: 0.395, 95% CI: 0.251– 0.619), PSS (OR: 0.621, 95% CI: 0.388– 0.994), organizational support (OR: 0.533, 95% CI. 0.333– 0.854) were protective factors for healthcare workers suffering from anxiety, and resistance to COVID-19 (OR: 1.703, 95% CI: 1.082– 2.681) was a risk factor for healthcare workers suffering from anxiety, while good quality of life (OR: 0.385, 95% CI: 0.206– 0.719) self-esteem (OR: 0.187, 95% CI: 0.110– 0.317), and PSS (OR: 0.475, 95% CI: 0.267– 0.847) were protective factors for healthcare workers suffering from depression, and at the age of 35– 40 years (OR: 2.475, 95% CI: 1.140– 5.369) and resistance to COVID-19 (OR: 2.219, 95% CI: 1.313– 3.751) were risk factors for healthcare workers suffering from depression.Conclusion: The anxiety and depression status of healthcare workers in China is poor, and hospital administrators should take positive measures to support healthcare workers and give positive expectations to alleviate negative emotions such as anxiety and depression.Keywords: anxiety, depression, cross-sectional study, healthcare workers

Published
2024

5. Psychometric Characteristics of the Chinese Version of the Tuberculosis Related-Stigma Scale in a Population of Medical Students and Its Correlation with Selected Demographic Characteristics

Author

Yi Y, Sun M, Lu J, Dou X, Yu Y, and Zhou L

Subjects
tuberculosis related-stigma scale, medical student, psychometrics, determinants, Public aspects of medicine, RA1-1270
Abstract

Yaohui Yi, Meng Sun, Jiachen Lu, Xiaofeng Dou, Yingying Yu, Ling Zhou School of Public Health, Dalian Medical University, Dalian City, Liaoning Province, People’s Republic of ChinaCorrespondence: Ling Zhou, School of Public Health, Dalian Medical University, Dalian City, Liaoning Province, People’s Republic of China, Tel +86-411-8611-0368, Email zhouling0609@163.comBackground: As future health workers, medical students’ attitudes towards tuberculosis (TB) patients can impact TB control. However, in China, there is a lack of well-quantified assessment regarding the stigma among medical students towards TB patients. Therefore, this study aimed to validate the Chinese version of the Tuberculosis related-Stigma Scale (TSS) in medical students and to apply the scale to measure stigma and its determinants.Methods: A total of 1035 eligible medical students participated in the cross-sectional questionnaire. Exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) were first conducted to test Chinese version of the TSS construct validity, and then internal consistency was assessed using Cronbach’s α. Finally, multiple linear regression analyses were conducted to identify predictors of stigma.Results: EFA extracted two factors (“Social distance” and “Exclusionary sentiments”). The CFA further confirmed the two-factor construct. The internal consistency, convergent and divergent validity of the adapted Chinese version of the TSS was acceptable. Furthermore, Whether one has received TB health education and whether know a person with TB are associated with all dimensions of TB stigma, while differences in sex and place of residence play different roles in influencing the different dimensions of stigma.Conclusion: The adapted Chinese version of the TSS can be used to assess the level of stigma among medical students in China towards tuberculosis patients. When implementing future interventions to reduce stigma associated with TB, special attention should be given to medical students from urban areas, of male gender, who have not received TB health education, and no know a person with TB. However, these two dimensions (“Social distance” and “Exclusionary sentiments”) are impacted by different determinants and should therefore be addressed separately when designing, implementing, and evaluating measures to reduce stigma.Keywords: tuberculosis related-stigma scale, medical student, psychometrics, determinants

Published
2024

6. The Patients’ Presupposed Distrust to Doctors in China: An Explanatory Sequential Mixed Methods Study

Author

Li Y, Wei Y, Liang X, and Dou X

Subjects
patients, presupposed distrust, root cause analysis, cross-sectional investigation, qualitative research, Medicine (General), R5-920
Abstract

Yan Li,1 Yanbin Wei,1 Xueping Liang,1 Xinman Dou1,2 1School of Nursing, Lanzhou University, Lanzhou, People’s Republic of China; 2Second Clinical Medical College, Lanzhou University, Lanzhou, People’s Republic of ChinaCorrespondence: Xinman Dou, Second Clinical Medical College, Lanzhou University, No. 82 Cuiyingmen, Chengguan District, Lanzhou, 730000, People’s Republic of China, Tel +86-13909318916, Email douxm@lzu.edu.cnPurpose: The aim of this study was to investigate the current status of patients’ presupposed distrust, and to clarify the causes of high presupposed distrust.Patients and Methods: An explanatory sequential mixed methods study was conducted using a two-stage design. The first phase was a quantitative cross-sectional survey, a total of 384 patients by convenience sampling completed the survey. Study instruments including demographic and clinical characteristics sheet, patients’ presupposed distrust scale. In the qualitative phase, 16 patients on the basis of their mean score for all PPDS items were higher than 4 were identified as extreme cases participated in one-to-one semi-structured interviews.Results: The total item mean score for all patients on PPDS was 3.59(3.18, 4.09), which above the median range of the PPDS (item mean score of 3). Personal income level and educational level were significant predictive influencing factors of patients’ presupposed distrust, which could explain 17.347% of the variance. The reasons of high patients’ presupposed distrust were as follows: moral character, health knowledge, patient perceptions, and the social circumstance.Conclusion: The level of patients’ presupposed distrust was high, which needs to be further decreased. Demographic and clinical variables (personal income level, educational level) are identified to be the major contributing factors. The main causes for the formation of the high patients’ presupposed distrust are patients internal factors and social circumstance.Keywords: patients, presupposed distrust, root cause analysis, cross-sectional investigation, qualitative research

Published
2024

7. A new approach to slice analysis via slice topology

Author

Dou, X., Jin, M., Ren, G., and Sabadini, I.

Subjects
Mathematics - Complex Variables
Abstract

In this paper we summarize some known facts on slice topology in the quaternionic case, and we deepen some of them by proving new results and discussing some examples. We then show, following [18], how this setting allows us to generalize slice analysis to the general case of functions with values in a real left alternative algebra, which includes the case of slice monogenic functions with values in Clifford algebra. Moreover, we further extend slice analysis, in one and several variables, to functions with values in a Euclidean space of even dimension. In this framework, we study the domains of slice regularity, we prove some extension properties and the validity of a Taylor expansion for a slice regular function., Comment: Modified the definition of $\widetilde{P_I}(z,r)$ in 8.2. The Version of Record of this article is published in Adv. Appl. Clifford Algebras, and is available online at https://doi.org/10.1007/s00006-021-01170-3

Published
2021
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8. The Effect of Low-Dose Esketamine on Postoperative Neurocognitive Dysfunction in Elderly Patients Undergoing General Anesthesia for Gastrointestinal Tumors: A Randomized Controlled Trial

Author

Ma J, Wang F, Wang J, Wang P, Dou X, Yao S, and Lin Y

Subjects
esketamine, postoperative neurocognitive dysfunction, elderly patients, gastrointestinal surgery, Therapeutics. Pharmacology, RM1-950
Abstract

Jiamin Ma,1– 3,&ast; Fuquan Wang,1,2,&ast; Jingxu Wang,1,2,&ast; Pengcheng Wang,4 Xiaoke Dou,1,2 Shanglong Yao,1,2 Yun Lin1,2 1Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China; 2Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People’s Republic of China; 3Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, 201620, People’s Republic of China; 4Department of Anesthesiology, Zhumadian Central Hospital, Zhumadian, 463000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yun Lin, Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277, Jiefang Avenue, Wuhan, Hubei, 430022, People’s Republic of China, Tel/Fax +86 02785351606, Email franklinyun@hust.edu.cnPurpose: This study aims to evaluate the effects of the intraoperative application of low-dose esketamine on postoperative neurocognitive dysfunction (PND) in elderly patients undergoing general anesthesia for gastrointestinal tumors.Methods: Sixty-eight elderly patients were randomly allocated to two groups: the esketamine group (group Es) (0.25 mg/kg loading, 0.125mg/kg/h infusion) and the control group (group C) (received normal saline). The primary outcome was the incidence of delayed neurocognitive recovery (DNR). The secondary outcomes were intraoperative blood loss, the total amount of fluid given during surgery, propofol and remifentanil consumption, cardiovascular adverse events, use of vasoactive drugs, operating and anesthesia time, the number of cases of sufentanil remedial analgesia, the incidence of postoperative delirium (POD), the intraoperative hemodynamics, bispectral index (BIS) value at 0, 1, 2 h after operation and numeric rating scale (NRS) pain scores within 3 d after surgery.Results: The incidence of DNR in group Es (16.13%) was lower than in group C (38.71%) (P < 0.05). The intraoperative remifentanil dosage and the number of cases of dopamine used in group Es were lower than in group C (P < 0.05). Compared with group C, DBP was higher at 3 min after intubation, and MAP was lower at 30 min after extubation in group Es (P

Published
2023

9. Extracellular Vesicles Derived circSH3PXD2A Inhibits Chemoresistance of Small Cell Lung Cancer by miR-375-3p/YAP1

Author

Chao F, Zhang Y, Lv L, Wei Y, Dou X, Chang N, Yi Q, and Li M

Subjects
circsh3pxd2a, extracellular vesicles, mir-375-3p, yap1, chemoresistance, small cell lung cancer, Medicine (General), R5-920
Abstract

Fengmei Chao,1,&ast; Yang Zhang,2,3,&ast; Lei Lv,1 Yaqin Wei,2,3 Xiaoyan Dou,2,3 Na Chang,4 Qiyi Yi,5 Ming Li2,3 1Department of Cancer Epigenetics Program, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230031, People’s Republic of China; 2Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230031, People’s Republic of China; 3Core Unit of National Clinical Research Center for Laboratory Medicine of China, Hefei, Anhui, 230001, People’s Republic of China; 4Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230031, People’s Republic of China; 5School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ming Li; Qiyi Yi, Email lm831216@ustc.edu.cn; yiqiyi@ahmu.edu.cnIntroduction: Small cell lung cancer (SCLC) is a subtype of lung cancer with high malignancy and poor prognosis. Rapid acquisition of chemoresistance is one of the main reasons leading to clinical treatment failure of SCLC. Studies have indicated that circRNAs participate in multiple processes of tumor progression, including chemoresistance. However, the molecular mechanisms of circRNAs driving the chemoresistance of SCLC are not well specified.Methods: The differentially expressed circRNAs were screened by transcriptome sequencing of chemoresistant and chemosensitive SCLC cells. The EVs of SCLC cells were isolated and identified by ultracentrifugation, Western blotting, transmission electron microscopy, nanoparticle tracking analysis and EVs uptake assays. The expression levels of circSH3PXD2A in serum and EVs of SCLC patients and healthy individuals were detected by qRT‒PCR. The characteristics of circSH3PXD2A were detected by Sanger sequencing, RNase R assay, nuclear-cytoplasmic fraction assay, and fluorescence in situ hybridization assay. The mechanisms of circSH3PXD2A inhibiting SCLC progression were studied by bioinformatics analysis, chemoresistance assay, proliferation assay, apoptosis assay, transwell assay, pull-down assay, luciferase reporting assay, and mouse xenograft assay.Results: It was identified that the circSH3PXD2A was a prominently downregulated circRNA in chemoresistant SCLC cells. The expression level of circSH3PXD2A in EVs of SCLC patients was negatively associated with chemoresistance, and the combination of EVs-derived circSH3PXD2A and serum ProGRP (Progastrin-releasing peptide) levels had better indications for DDP-resistant SCLC patients. CircSH3PXD2A inhibited the chemoresistance, proliferation, migration, and invasion of SCLC cells through miR-375-3p/YAP1 axis in vivo and in vitro. SCLC cells cocultured with EVs secreted by circSH3PXD2A-overexpressing cells exhibited decreased chemoresistance and cell proliferation.Conclusion: Our results manifest that EVs-derived circSH3PXD2A inhibits the chemoresistance of SCLC through miR-375-3p/YAP1 axis. Moreover, EVs-derived circSH3PXD2A may serve as a predictive biomarker for DDP-resistant SCLC patients.Keywords: circSH3PXD2A, extracellular vesicles, miR-375-3p, YAP1, chemoresistance, small cell lung cancer

Published
2023

10. Single-photon distributed free-space spectroscopy

Author

Yu, S., Zhang, Z., Xia, H., Dou, X., Li, M., Wei, T., Wang, L., Jiang, P., Wu, Y., Zhang, C., You, L., Hu, Y., Wu, T., Zhao, L., Shangguan, M., Tao, L., and Qiu, J.

Subjects
Physics - Atmospheric and Oceanic Physics, Physics - Optics
Abstract

Spectroscopy is a well-established nonintrusive tool that has played an important role in identifying substances and quantifying their compositions, from quantum descriptions to chemical and biomedical diagnostics. Challenges exist in accurate measurements in dynamic environments, especially for understanding chemical reactions in arbitrary free-space. We develop a distributed free-space spectroscopy realized by a comb-referenced frequency-scanning single-photon lidar, providing multidimensional (time-range-spectrum) remote sensing. A continuous field experiment over 72 hours is deployed to obtain the spectra of multiple molecules (CO2 and HDO) in free-space over 6 km, with a range resolution of 60 m and a time resolution of 10 min over a spectrum span of 30 GHz. The CO2 and HDO concentrations are retrieved from the spectra acquired. This distributed free-space spectroscopy holds much promise for increasing knowledge of atmospheric environments and chemistry research, especially for complex molecular spectra evolution in any location over large areas., Comment: 5 pages, 5 figures

Published
2020

11. Selenium Nanoparticles-Enriched Lactobacillus casei ATCC 393 Prevents Cognitive Dysfunction in Mice Through Modulating Microbiota-Gut-Brain Axis

Author

Qiao L, Chen Y, Song X, Dou X, and Xu C

Subjects
neurodegenerative disease, gut microbiota, oxidative stress, neuroinflammation, Medicine (General), R5-920
Abstract

Lei Qiao, Yue Chen, Xiaofan Song, Xina Dou, Chunlan Xu The Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of ChinaCorrespondence: Chunlan Xu, The Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of China, Tel +86 29-88460543, Fax +86 29-88460332, Email clxu@nwpu.edu.cnPurpose: The bidirectional communication between the gut and the central nervous system mediated by gut microbiota is closely related to the occurrence and development of neurodegenerative diseases, including Alzheimer’s disease (AD). Selenium (Se) has been identified as playing a role against AD. Probiotics have beneficial effects on host brain function and behavior by modulating the microbiota-gut-brain axis. Herein, we evaluated the protective effects of Lactobacillus casei ATCC 393 (L. casei ATCC 393) and selenium nanoparticles-enriched L. casei ATCC 393 (L. casei ATCC 393-SeNPs) against D-galactose/aluminum chloride-induced AD model mice.Methods: The Morris Water Maze (MWM) test was used to assess cognitive function of mice. The morphology and histopathological changes, antioxidant capacity and immune responses in the brain and ileum were evaluated. The alterations in intestinal permeability of the mice were determined using FITC-dextran. Gut microbiota composition was assessed using 16s rRNA sequencing.Results: Thirteen weeks intervention with L. casei ATCC 393 or L. casei ATCC 393-SeNPs significantly improved cognitive dysfunction, and minimized amyloid beta (Aβ) aggregation, hyperphosphorylation of TAU protein, and prevented neuronal death by modulating Akt/cAMP-response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) signaling pathway. Moreover, compared with L. casei ATCC 393, L. casei ATCC 393-SeNPs further effectively mitigated intestinal barrier dysfunction by improving antioxidant capacity, regulating immune response, restoring gut microbiota balance, and increasing the level of short-chain fatty acids and neurotransmitters, thereby inhibiting the activation of microglia and protecting brain neurons from neurotoxicity such as oxidative stress and neuroinflammation.Conclusion: These findings indicated that targeting the microbiota-gut-brain axis with L. casei ATCC 393-SeNPs may have therapeutic potential for the deficits of cognitive function in the AD model mice. Thus, we anticipate that L. casei ATCC 393-SeNPs may be a promising and safe Se nutritional supplement for use as a food additive to prevent the neurodegenerative disease.Graphical Abstract: Keywords: neurodegenerative disease, gut microbiota, oxidative stress, neuroinflammation

Published
2022

12. Drug Resistance Patterns and Trends in Patients with Suspected Drug-Resistant Tuberculosis in Dalian, China: A Retrospective Study

Author

Pan Y, Yu Y, Lu J, Yi Y, Dou X, and Zhou L

Subjects
mycobacterium tuberculosis, dr-tb, rr-/mdr-tb, prevalence, associated factors, Infectious and parasitic diseases, RC109-216
Abstract

Yuanping Pan, Yingying Yu, Jiachen Lu, Yaohui Yi, Xiaofeng Dou, Ling Zhou School of Public Health, Dalian Medical University, Dalian, 116000, People’s Republic of ChinaCorrespondence: Ling Zhou, School of Public Health, Dalian Medical University, 9 West Section, Lvshun South Road, Dalian, Liaoning Province, People’s Republic of China, Tel +86 411 8611 0368, Email zhouling0609@163.comPurpose: The emergence of drug-resistant tuberculosis (DR-TB) represents a threat to the control of tuberculosis. This study aimed to estimate the patterns and trends of DR-TB in patients with suspected DR-TB. In addition, risk factors for multidrug-resistant tuberculosis (MDR-TB) were identified among suspected DR-TB patients in Dalian, China.Patients and Methods: A total of 5661 patients with suspected DR-TB from Jan 1, 2013 to Dec 31, 2020 were included in the final analysis. The resistance pattern of all resistant strains was determined by drug susceptibility testing (DST) using the conventional Lowenstein-Jensen Proportion Method (LJ). DR-TB trends were estimated from 2013 to 2020. During the research period, the chi-square test was employed to analyze the significance of linear drug-resistance trends across time. Bivariate and multivariate logistic regression were performed to assess factors associated with MDR-TB.Results: From 2013 to 2020, the resistance rates of rifampicin (RFP) and isoniazid (INH) decreased significantly, whereas the resistance rates of ethambutol (EMB) and streptomycin (SM) increased in patients with suspected DR-TB. From 2013 to 2020, the prevalence of DR-TB decreased in all patients from 34.71% to 28.01% with an average annual decrease of 3.02%. Among new cases, from 2013 to 2020, the prevalence of DR-TB (from 26.67% to 24.75%), RFP-resistant TB (RR-TB) (from 15.09% to 3.00%) and MDR-TB (from 6.08% to 2.62%) showed a significant downward trend. Among patients with a previous treatment history, DR-TB (from 54.70% to 37.50%), RR-TB (from 44.16% to 11.49%) and MDR-TB (from 26.90% to 10.34%) showed a significant downward trend from 2013 to 2020. Males (AOR 1.28, 95% CI 1.035– 1.585), patients 45 to 64 years of age (AOR 1.75, 95% CI 1.342– 2.284), patients 65 years and older (AOR 1.65, 95% CI 1.293– 2.104), rural residents (AOR 1.24, 95% CI 1.014– 1.519) and a previous treatment history (AOR 3.94, 95% CI 3.275– 4.741) were risk factors for MDR-TB.Conclusion: The prevalence of DR-TB, RR-TB and MDR-TB was significantly reduced from 2013 to 2020. Considerable progress has been made in the prevention and treatment of DR-TB during this period. However, the increasing rate of drug resistance in EMB and SM should be taken seriously. Suspected DR-TB patients who are male, older than 45 years of age, live in rural areas, and have a history of TB treatment should be given priority by health care providers.Keywords: Mycobacterium tuberculosis, DR-TB, RR-/MDR-TB, prevalence, associated factors

Published
2022

13. Comparisons of Outcomes Between Adolescent and Young Adult with Older Patients After Radical Resection of Pancreatic Ductal Adenocarcinoma by Propensity Score Matching: A Single-Center Study

Author

Tang N, Dou X, You X, Liu G, Ou Z, and Zai H

Subjects
adolescent and young adult (aya), pancreatic ductal adenocarcinoma (pdac), propensity score matching (psm), total pancreaticoduodenectomy (tpd), overall survival (os)., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Neng Tang,1,2 Xiaolin Dou,1,2 Xing You,1,2 Guodong Liu,1,2 Zhenglin Ou,1,2,&ast; Hongyan Zai1,2,&ast; 1Department of General Surgery, Xiangya Hospital Central South University, Changsha, 410008, Hunan Province, People’s Republic of China; 2National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, 410008, Hunan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhenglin Ou; Hongyan ZaiDepartment of General Surgery, Xiangya Hospital Central South University, 87 Xiangya Road, Changsha, 410008, Hunan Province, People’s Republic of ChinaEmail zhenglinou@163.com; zaihy@csu.edu.cnPurpose: Adolescent and young adult (AYA) pancreatic ductal adenocarcinoma (PDAC) occurs in patients below 40 years old. Whether AYA patients have worse outcomes compared with older patients is still controversial. The purpose of this study is to compare the outcomes of AYA patients and older patients after radical surgery for PDAC.Methods: A single-center, retrospective, cohort study was conducted in patients who underwent radical surgery for PDAC in Xiangya Hospital Central South University from January 2007 to December 2019. The clinicopathological data and results of patients with PDAC were collected and analyzed retrospectively. They were divided into AYA group and older group based on age (< 40, AYA group; ≥ 40, older group). Based on all the considered covariates except age, we estimated 1:2 case propensity score matching (PSM).Results: A total of 1033 cases were enrolled, 46 cases (4.45%) in the AYA group. Both before and after PSM, the AYA patients have a higher preoperative CA19-9 than the older patients (P < 0.001) and (P < 0.001). Pathological results showed that AYA group had a higher microvascular invasion rate (P < 0.001 and P = 0.045) than older group. The median time of overall survival (OS) in AYA group and older group were 13 months (95% CI = 11.50– 14.50) and 14 months (95% CI = 13.50– 14.50), respectively. Additionally, AYA group have a worse 2-year OS rate than older group (8.70% vs 25.23%, P = 0.011 and 8.70% vs 25.00%, P = 0.023). According to the Log rank test, AYA group have a worse cumulative OS rate than older group (P = 0.002) and (P = 0.030), respectively.Conclusion: PDAC might be more aggressive in AYA, and the cumulative OS after radical PDAC surgery in AYA patients is worse than that in older patients.Keywords: adolescent and young adult, AYA, pancreatic ductal adenocarcinoma, PDAC, propensity score matching, PSM, total pancreaticoduodenectomy, TPD, overall survival, OS

Published
2021

17. Incidence and Risk Factors of Post-Operative Depression in Patients Undergoing Transurethral Resection of Prostate for Benign Prostatic Hyperplasia

Author

Zhu D, Gao J, Dou X, Peng D, Zhang Y, and Zhang X

Subjects
benign prostate hyperplasia, bph, transurethral resection of the prostate, turp, depression, prevalence rate, risk factors, Medicine (General), R5-920
Abstract

Daofang Zhu,1 Jingjing Gao,1 Xianming Dou,2 Dangwei Peng,1 Yao Zhang,1 Xiansheng Zhang1 1Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, People’s Republic of China; 2Department of Urology, Anhui No. 2 Provincial People’s Hospital, Heifei, 230041, People’s Republic of ChinaCorrespondence: Xiansheng Zhang Tel +86- 551-62922114Email xshzhang1013@126.comBackground: Benign prostatic hyperplasia (BPH) is a frequent-occurring disease in middle-aged and elderly men. This work is a prospective study and aims at exploring the incidence of post-operative depression and the potential risk factors of depression in a cohort of patients with BPH in China.Methods: In this survey, 611 men who underwent transurethral resection of the prostate (TURP) were strictly selected at our institution from January 2016 to August 2019. Zung Self-rating Depression Scale was used for evaluation of depressive symptoms. Sociodemographic, clinical and other data were also collected.Results: We found that 152/611 (24.9%) patients suffered from different degree of depression at 6 months after TURP, including mild symptoms (20.9%) and moderate/severe symptoms (3.9%). A total of 421 (68.9%) patients developed post-TURP erectile dysfunction (ED). The occurrence of depression was closely associated with marital status, education level, cigarette smoking, alcohol consumption, severity of lower urinary tract symptoms (LUTS), duration of BPH, erectile function, and comorbidities (such as diabetes, dyslipidaemia and bladder stone). The risk factors related to the severity of depression included widowed or single marital status, frequent alcohol consumption, moderate or severe LUTS, longer duration (> 5 years) of BPH, ED, urinary continence, and comorbidities such as diabetes and bladder stone.Conclusion: Many risk factors are related to the occurrence of depression in patients undergoing TURP. Widowed or single marital status, frequent alcohol consumption, moderate or severe LUTS, longer duration of BPH, ED, urinary incontinence and comorbidities such as diabetes and bladder stone are connected with the increase odds of moderate or severe depressive symptom.Keywords: benign prostate hyperplasia, BPH, transurethral resection of the prostate, TURP, depression, prevalence rate, risk factors

Published
2021

18. Structured light assisted coherent fourier scatterometry for physical parameter retrieval of nanostructures

Author

Dou, X. (author) and Dou, X. (author)

Abstract

In the semiconductor industry, the minimumelement size has stepped into nanometer level. To keep the functionality of fabricated nanostructures, there is a huge demand of a technique that can provide non-destructive inspection and allow for in-line or in-situ monitoring during the manufacturing process. Optical scatterometry, which uses the far-field optical scattering information to retrieve the geometrical features of a structure, is a suitable method. As a non-imaging technique, optical scatterometry does not produce images of the illuminated object. Optical scatterometry relies on retrieving nanostructure profile parameters by continuously comparing the given set of predicted signatures expected from a scattering experiment with the actual measured ones. Because we parametrize the structure with a limited set of parameters (i.e. we use prior knowledge of the structure), we can reconstruct the structure with a resolution beyond the diffraction limit. This technique is particularly valuable for characterizing micro- and nano-scale structures that are commonly found in semiconductor devices and integrated circuits ...., ImPhys/Pereira group

Published
2024

19. Second-order correlation function from asymmetric to symmetric transitions due to spectrally indistinguishable biexciton cascade emission

Author

Wu, X. F., Dou, X. M., Ding, K., Zhou, P. Y., Ni, H. Q., Niu, Z. C., Zhu, H. J., Jiang, D. S., Zhao, C. L., and Sun, B. Q.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Other Condensed Matter
Abstract

We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exciton photon is not spectrally distinguishable from biexciton photon, and either of them can trigger the start in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton the photon statistics becomes asymmetric and a cross-bunching lineshape is obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of second-order correlation function measurements.

Published
2015
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21. Regulation of E2F Transcription Factor 3 by microRNA-152 Modulates Gastric Cancer Invasion and Metastasis

Author

Shi L, Zhu H, Shen Y, Dou X, Guo H, Wang P, Zhang S, Zhou L, and Zou X

Subjects
mir-152, e2f3, plk1, metastasis, gastric cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Liangliang Shi, 1–3,* Hao Zhu, 1–3,* Yonghua Shen, 1–3,* Xiaotan Dou, 1–3 Huimin Guo, 1–3 Pin Wang, 1–3 Shu Zhang, 1–3 Lin Zhou, 1–3 Xiaoping Zou 1–3 1Department of Gastroenterology, Drum Tower Clinical Medical College of Nanjing Medical University, Nanjing 210008, People’s Republic of China; 2Department of Gastroenterology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, People’s Republic of China; 3Jiangsu Clinical Medical Center of Digestive Disease, Nanjing 210008, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaoping Zou; Lin ZhouDepartment of Gastroenterology, Nanjing Drum Tower Hospital, No. 321 Zhongshan Road, Nanjing 210008, People’s Republic of ChinaTel +86 25-68182222Fax +86 25-83304616Email 13770771661@163.com; zhoulin1105@163.comBackground: The transcription factor, E2F transcription factor 3 (E2F3), has been proved to modulate metastasis in multiple human cancers. The present study was aimed to expound the function and specific mechanism of E2F3 in gastric cancer (GC) progression.Materials and Methods: The expression of E2F3, microRNA-152 (miR-152) and PLK1 (polo-like kinase 1) in GC cell lines was detected by quantitative RT-PCR and Western blot. The roles of E2F3 and miR-152 in GC metastasis were classified using gain-of-function and loss-of-function assays. The miRNAs directly targeting E2F3 were identified by bioinformatics analysis and luciferase reporter experiment. Chromatin immunoprecipitation was carried out to reveal the correlation between E2F3 and PLK1.Results: E2F3 expression was frequently up-regulated in GC tissues, and its high expression might imply poor prognosis. Downregulation of E2F3 restrained GC migration and invasion in vitro and in vivo. Interestingly, we proved that miR-152 was an upstream regulator of E2F3. Moreover, miR-152 reduced E2F3 expression by directly targeting its 3ʹ-UTR, and then modulated GC metastasis via polo-like kinase 1 (PLK1) mediated protein kinase B (AKT) and extracellular signal-regulated kinase (ERK) signals.Conclusion: E2F3 plays a crucial role in GC progression and the newly discovered miR-152/E2F3/PLK1 axis provides a new underlying target for therapy of metastasis in GC patients.Keywords: miR-152, E2F3, PLK1, metastasis, gastric cancer

Published
2020

22. Effectiveness and Feasibility of Complementary Lung-RADS Version 1.1 in Risk Stratification for pGGN in LDCT Lung Cancer Screening in a Chinese Population

Author

Meng Q, Ren P, Gao P, Dou X, Chen X, Guo L, and Song Y

Subjects
low-dose computed tomography, lung neoplasms, lung-rads, mass screening, ground-glass nodules., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Qingcheng Meng,1,* Pengfei Ren,2,* Pengrui Gao,1 Xinmin Dou,1 Xuejun Chen,1 Lanwei Guo,3 Yongping Song4 1Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 2Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 3Department of Cancer Prevention Office, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 4Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yongping SongDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, People’s Republic of ChinaTel/Fax +86 371 65587016Email songyongping001@126.comPurpose: To evaluate the effectiveness of using a modified lung imaging reporting and data system (Lung-RADS) for risk stratification of pure ground-glass nodules (pGGNs) in low-dose computed tomography (LDCT) for lung cancer (LC) screenings in China.Patients and Methods: Eight subjects with nine pGGNs originating from a Cancer Screening Program were enrolled as training set and 32 asymptomatic subjects with 35 pGGNs were selected as validation set from November 2013 to October 2018. The complementary Lung-RADS categories were set based on the GGN-vessel relationship (GVR). The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed.Results: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. The combined incidence of invasive adenocarcinoma in type III and IV was more than that of benign and preinvasive diseases (30% vs 75%, P=0.013). Type II GVR between two benign (66.7%), seven preinvasive (53.8%), and six invasive (21.4%) GGN cases was statistically significant (χ2=5.415, P=0.019). GGN pathological groups and GVR had a significant correlation (r=0.584, P=0.00). Compared to Lung-RADS 1.1, complementary Lung-RADS 1.1 had better performance in the training set, with its sensitivity increased from 33.3% to 88.9%, accuracy increased from 44.4% to 88.9%, false-negative proportion (FNP) decreased from 66.7% to 11.1%, and the sensitivity to predict malignant nodules increased from 13.8% to 93.1%, accuracy increased from 28.6% to 80.0%, and FNP decreased from 86.2% to 6.9% in validation set. The detection rate of preinvasive disease and adenocarcinoma was increased from 12.5% to 90.6% and that of missed diagnosis decreased from 87.5% to 9.4% in the validation set, P=0.004.Conclusion: Complementary Lung-RADS 1.1 is superior to Lung-RADS 1.1 and would be beneficial for LC screening of LDCT in China.Keywords: low-dose computed tomography, lung neoplasms, lung-RADS, mass screening, ground-glass nodules

Published
2020

23. Measurements of a fast nuclear spin dynamics in a single InAs quantum dot with positively charged exciton

Author

Dou, X. M., Sun, B. Q., Jiang, D. S., Ni, H. Q., and Niu, Z. C.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

By using highly time-resolved spectroscopy with an alternative {\sigma}+/{\sigma} - laser pulse modulation technique, we are able to measure the fast buildup and decay times of the dynamical nuclear spin polarization (DNSP) at 5 K for a single InAs quantum dot (QD) with positively charged exciton. It is shown that the nuclear dipole-dipole interaction can efficiently depolarize DNSP with a typical time constant of 500 {\mu}s in the absence of external magnetic field. By using an external field of 8 mT to suppress the nuclear dipolar interaction, the decay time turns to be mainly induced by interaction with unpaired electron and extends to about 5 ms. In addition, it is found that the time constant of hole-induced depolarization of nuclear spin is about 112 ms., Comment: 5 pages, 3 figures

Published
2012
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24. Temperature dependence of electron-spin relaxation in a single InAs quantum dot at zero applied magnetic field

Author

Dou, X. M., Sun, B. Q., Jiang, D. S., Ni, H. Q., and Niu, Z. C.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The temperature-dependent electron spin relaxation of positively charged excitons in a single InAs quantum dot (QD) was measured by time-resolved photoluminescence spectroscopy at zero applied magnetic fields. The experimental results show that the electron-spin relaxation is clearly divided into two different temperature regimes: (i) T < 50 K, spin relaxation depends on the dynamical nuclear spin polarization (DNSP) and is approximately temperature-independent, as predicted by Merkulov et al. (ii) T > about 50 K, spin relaxation speeds up with increasing temperature. A model of two LO phonon scattering process coupled with hyperfine interaction is proposed to account for the accelerated electron spin relaxation at higher temperatures., Comment: 10 pages, 4 figures

Published
2012
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25. Singularity and entropy of the viscosity dark energy model

Author

Meng, X. H. and Dou, X.

Subjects
Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

In this paper bulk viscosity is introduced to describe the effects of cosmic non-perfect fluid on the cosmos evolution and to build the unified dark energy (DE) with (dark) matter models. Also we derive a general relation between the bulk viscosity form and Hubble parameter that can provide a procedure for the viscosity DE model building. Especially, a redshift dependent viscosity parameter $\zeta\propto\lambda_{0}+\lambda_{1}(1+z)^{n}$ proposed in the previous work by X.H.Meng and X.Dou in 2009\cite{md} is investigated extensively in this present work. Further more we use the recently released supernova dataset (the Constitution dataset) to constrain the model parameters. In order to differentiate the proposed concrete dark energy models from the well known $\Lambda$CDM model, statefinder diagnostic method is applied to this bulk viscosity model, as a complementary to the $Om$ parameter diagnostic and the deceleration parameter analysis performed by us before. The DE model evolution behavior and tendency are shown in the plane of the statefinder diagnostic parameter pair \{$r,s$\} where the fixed point represents the $\Lambda$CDM model. The possible singularity property in this bulk viscosity cosmology is also discussed to which we can conclude that in the different parameter regions chosen properly, this concrete viscosity DE model can have various late evolution behaviors and the late time singularity could be avoided. We also calculate the cosmic entropy in the bulk viscosity dark energy frame, and find that the total entropy in the viscosity DE model increases monotonously with respect to the scale factor evolution, thus this monotonous increasing property can indicate an arrow of time in the universe evolution, though the quantum version of the arrow of time is still puzzling., Comment: 5 figs

Published
2009

27. Friedmann cosmology with bulk viscosity: a concrete model for dark energy

Author

Meng, X H and Dou, X

Subjects
Astrophysics
Abstract

The universe content is considered as a non-perfect fluid with bulk viscosity and can be described by a general equation of state (endowed some deviation from the conventionally assumed cosmic perfect fluid model). An explicitly bulk viscosity dark energy model is proposed to confront consistently with the current observational data sets by statistical analysis and is shown consistent with (not deviated away much from) the concordant $\Lambda$ Cold Dark Matter (CDM) model by comparing the decelerating parameter. Also we compare our relatively simple viscosity dark energy model with a more complicated one by contrast with the concordant $\Lambda$CDM model and find our model improves for the viscosity dark energy model building. Finally we discuss the perspectives of dark energy probes for the coming years with observations., Comment: 6ps

Published
2008
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28. Biogenic selenium nanoparticles synthesized by Lactobacillus casei ATCC 393 alleviate intestinal epithelial barrier dysfunction caused by oxidative stress via Nrf2 signaling-mediated mitochondrial pathway

Author

Xu C, Qiao L, Ma L, Guo Y, Dou X, Yan S, Zhang B, and Roman A

Subjects
Lactobacillus casei, SeNPs, Mitochondrial, Antioxidant, ROS, Intestinal barrier, Medicine (General), R5-920
Abstract

Chunlan Xu, Lei Qiao, Li Ma, Yu Guo, Xina Dou, Shuqi Yan, Baohua Zhang, Alexandra RomanThe Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, Shaanxi, People’s Republic of ChinaBackground: Selenium (Se) can exert antioxidative activity and prevent the body from experiencing oxidative injury. Biogenic Se nanoparticles (SeNPs) synthesized by probiotics possess relatively strong chemical stability, high bioavailability, and low toxicity, this makes them potential Se supplements. Previously, we demonstrated that SeNPs synthesized by Lactobacillus casei ATCC 393 can alleviate hydrogen peroxide (H2O2)-induced human and porcine intestinal epithelial cells’ oxidative damage. However, the antioxidant mechanism remains unclear.Methods: The possible antioxidant mechanism and protective effect of SeNPs on intestinal epithelial permeability and mitochondrial function were evaluated by establishing an H2O2-induced oxidative damage model of human colon mucosal epithelial cells (NCM460) and conducting Nrf2 inhibitor interference experiments. Mitochondrial membrane potential (MMP), mitochondrial DNA content, adenosine triphosphate (ATP), ROS, and protein expression levels of Nrf2-related genes were determined. Mitochondrial ultrastructure was visualized by transmission electron microscopy.Results: An amount of 4 μg Se/mL of SeNPs synthesized by L. casei ATCC 393 alleviated increase of ROS, reduced ATP and MMP, and maintained intestinal epithelial permeability in NCM460 cells challenged by H2O2. In addition, SeNPs improved the protein levels of Nrf2, HO-1, and NQO-1. Moreover, SeNPs attenuated the damage of mitochondrial ultrastructure caused by oxidative stress. Nrf2 inhibitor (ML385) abolished the regulatory effect of SeNPs on intracellular ROS production.Conclusion: Data suggest that biogenic SeNPs synthesized by L. casei ATCC 393 can protect the intestinal epithelial barrier function against oxidative damage by alleviating ROS-mediated mitochondrial dysfunction via Nrf2 signaling pathway. Biogenic SeNPs are an attractive candidate for potential Se supplement agent in preventing oxidative stress-related intestinal disease by targeting mitochondria.Keywords: Lactobacillus casei, selenium nanoparticles, mitochondrial, antioxidant, reactive oxygen species, intestinal barrier

Published
2019

30. A global DNA methylation and gene expression analysis of early human B-cell development reveals a demethylation signature and transcription factor network

Author

Wiemels, Joseph, Wiencke, John, Lee, ST, Xiao, Y, Muench, MO, Xiao, J, Fomin, ME, Wiencke, JK, Zheng, S, Dou, X, De, A, and Chokkalingam, A

Abstract

The epigenetic changes during B-cell development relevant to both normal function and hematologic malignancy are incompletely understood. We examined DNA methylation and RNA expression status during early B-cell development by sorting multiple replicates o

Published
2012

35. Global multi-stakeholder endorsement of the MAFLD definition

Author

Mendez-Sanchez, N, Bugianesi, E, Gish, R, Lammert, F, Tilg, H, Nguyen, M, Sarin, S, Fabrellas, N, Zelber-Sagi, S, Fan, J, Shiha, G, Targher, G, Zheng, M, Chan, W, Vinker, S, Kawaguchi, T, Castera, L, Yilmaz, Y, Korenjak, M, Spearman, C, Ungan, M, Palmer, M, El-Shabrawi, M, Gruss, H, Dufour, J, Dhawan, A, Wedemeyer, H, George, J, Valenti, L, Fouad, Y, Romero-Gomez, M, Eslam, M, Abate, M, Abbas, B, Abbassy, A, Abd El Ghany, W, Abd Elkhalek, A, Abd ElMajeed, E, Abdalgaber, M, Abdallah, M, Abdallah, N, Abdelaleem, S, Abdelghani, Y, Abdelghany, W, Abdelhalim, S, Abdelhamid, W, Abdelhamid, N, Abdelkader, N, Abdelkreem, E, Abdelmohsen, A, Abdelrahman, A, Abd-elsalam, S, Abdeltawab, D, Abduh, A, Abdulhakam, N, Abdulla, M, Abedpoor, N, Abenavoli, L, Aberg, F, Ablack, O, Abo elftouh, M, Abo-Amer, Y, Aboubkr, A, Aboud, A, Abouelnaga, A, Aboufarrag, G, Aboutaleb, A, Abundis, L, Adali, G, Adames, E, Adams, L, Adda, D, Adel, N, Adel Sayed, M, Afaa, T, Afredj, N, Aghayeva, G, Aghemo, A, Aguilar-Salinas, C, Ahlenstiel, G, Ahmady, W, Ahmed, W, Ahmed, A, Ahmed, S, Ahmed, H, Ahmed, R, Aigner, E, Akarsu, M, Akroush, M, Akyuz, U, Al Mahtab, M, Al Qadiri, T, Al Rawahi, Y, AL rubaee, R, Al Saffar, M, Alam, S, Al-Ani, Z, Albillos, A, Alboraie, M, Al-Busafi, S, Al-Emam, M, Alharthi, J, Ali, K, Ali, B, Ali, M, Ali, R, Alisi, A, AL-Khafaji, A, Alkhatry, M, Aller, R, Almansoury, Y, Al-Naamani, K, Alnakeeb, A, Alonso, A, Alqahtani, S, Alrabadi, L, Alswat, K, Altaher, M, Altamimi, T, Altamirano, J, Alvares-da-Silva, M, Aly, E, Alzahaby, A, Alzamzamy, A, Amano, K, Amer, M, Amin, M, Amin, S, Amir, A, Ampuero, J, Anas, N, Andreone, P, Andriamandimby, S, Anees, M, Angela, P, Antonios, M, Arafat, W, Araya, J, Armendariz-Borunda, J, Armstrong, M, Ashktorab, H, Aspichueta, P, Assal, F, Atef, M, Attia, D, Atwa, H, Awad, R, Awad, M, Awny, S, Awolowo, O, Awuku, Y, Ayada, I, Aye, T, Ayman, S, Ayman, H, Ayoub, H, Azmy, H, Babaran, R, Badreldin, O, Badry, A, Bahcecioglu, I, Bahour, A, Bai, J, Balaban, Y, Balasubramanyam, M, Bamakhrama, K, Banales, J, Bangaru, B, Bao, J, Barahona, J, Barakat, S, Barbalho, S, Barbra, B, Barranco, B, Barrera, F, Baumann, U, Bazeed, S, Bech, E, Benayad, A, Benesic, A, Bernstein, D, Bessone, F, Birney, S, Bisseye, C, Blake, M, Bobat, B, Bonfrate, L, Bordin, D, Bosques-Padilla, F, Boursier, J, Boushab, B, Bowen, D, Bravo, P, Brennan, P, Bright, B, Broekaert, I, Buque, X, Burgos-Santamaria, D, Burman, J, Busetto, L, Byrne, C, Cabral-Prodigalidad, P, Cabrera-Alvarez, G, Cai, W, Cainelli, F, Caliskan, A, Canbay, A, Cano-Contreras, A, Cao, H, Cao, Z, Carrion, A, Carubbi, F, Casanovas, T, Castellanos Fernandez, M, Chai, J, Chan, S, Charatcharoenwitthaya, P, Chavez-Tapia, N, Chayama, K, Chen, J, Chen, L, Chen, Z, Chen, H, Chen, S, Chen, Q, Chen, Y, Chen, G, Chen, E, Chen, F, Chen, P, Cheng, R, Cheng, W, Chieh, J, Chokr, I, Cholongitas, E, Choudhury, A, Chowdhury, A, Chukwudike, E, Ciardullo, S, Clayton, M, Clement, K, Cloa, M, Coccia, C, Collazos, C, Colombo, M, Cosar, A, Cotrim, H, Couillerot, J, Coulibaly, A, Crespo, G, Crespo, J, Cruells, M, Cua, I, Dabbous, H, Dalekos, G, D'Alia, P, Dan, L, Dao, V, Darwish, M, Datz, C, Davalos-Moscol, M, Dawoud, H, de Careaga, B, de Knegt, R, de Ledinghen, V, de Silva, J, Debzi, N, Decraecker, M, Del Pozo, E, Delgado, T, Delgado-Blanco, M, Dembinski, L, Depina, A, Derbala, M, Desalegn, H, Desbois-Mouthon, C, Desoky, M, Dev, A, Di Ciaula, A, Diago, M, Diallo, I, Diaz, L, Dirchwolf, M, Dongiovanni, P, Dorofeyev, A, Dou, X, Douglas, M, Doulberis, M, Dovia, C, Doyle, A, Dragojevic, I, Drenth, J, Duan, X, Dulskas, A, Dumitrascu, D, Duncan, O, Dusabejambo, V, Dwawhi, R, Eiketsu, S, El Amrousy, D, El Deeb, A, El Deriny, G, El Din, H, El Kamshishy, S, El Kassas, M, El Raziky, M, Elagamy, O, Elakel, W, Elalfy, D, Elaraby, H, Elawady, H, Elbadawy, R, Eldash, H, Eldefrawy, M, Elecharri, C, Elfaramawy, A, Elfatih, M, Elfiky, M, Elgamsy, M, Elgendy, M, El-Guindi, M, Elhussieny, N, Eliwa, A, Elkabbany, Z, El-Khayat, H, El-Koofy, N, Elmetwalli, A, Elrabat, A, El-Raey, F, Elrashdy, F, Elsahhar, M, Elsaid, E, Elsayed, S, Elsayed, H, Elsayed, A, El-Serafy, M, Elsharkawy, A, Elsheemy, R, Elshemy, E, Elsherbini, S, Eltoukhy, N, Elwakil, R, Emad, O, Emad, S, Embabi, M, Ergenc, I, Ermolova, T, Esmat, G, Esmat, D, Estupinan, E, Ettair, S, Eugen, T, Ezz-Eldin, M, Falcon, L, Fan, Y, Fandari, S, Farag, M, Farahat, T, Fares, E, Fares, M, Fassio, E, Fathy, H, Fathy, D, Fathy, W, Fayed, S, Feng, D, Feng, G, Fernandez-Bermejo, M, Ferreira, C, Ferrer, J, Forbes, A, Fouad, R, Fouad, H, Frisch, T, Fujii, H, Fukunaga, S, Fukunishi, S, Fulya, H, Furuhashi, M, Gaber, Y, Galang, A, Gallardo, J, Galloso, R, Gamal, M, Gamal, R, Gamal, H, Gan, J, Ganbold, A, Gao, X, Garas, G, Garba, T, Garcia-Cortes, M, Garcia-Monzon, C, Garcia-Samaniego, J, Gastaldelli, A, Gatica, M, Gatley, E, Gegeshidze, T, Geng, B, Ghazinyan, H, Ghoneem, S, Giacomelli, L, Giannelli, G, Giannini, E, Giefer, M, Gines, P, Girala, M, Giraudi, P, Goh, G, Gomaa, A, Gong, B, Gonzales, D, Gonzalez, H, Gonzalez-Huezo, M, Graupera, I, Grgurevic, I, Gronbaek, H, Gu, X, Guan, L, Gueye, I, Guingane, A, Gul, O, Gul, C, Guo, Q, Gupta, P, Gurakar, A, Gutierrez, J, Habib, G, Hafez, A, Hagman, E, Halawa, E, Hamdy, O, Hamed, A, Hamed, D, Hamid, S, Hamoudi, W, Han, Y, Haridy, J, Haridy, H, Harris, D, Hart, M, Hasan, F, Hashim, A, Hassan, I, Hassan, A, Hassan, E, Hassan, M, Hassanin, F, Hassnine, A, Haukeland, J, Hawal, A, He, J, He, Q, He, Y, He, F, Hegazy, M, Hegazy, A, Henegil, O, Hernandez, N, Hernandez-Guerra, M, Higuera-de-la-Tijera, F, Hindy, I, Hirota, K, Ho, L, Hodge, A, Hosny, M, Hou, X, Huang, J, Huang, Y, Huang, Z, Huang, A, Huang, X, Hui-ping, S, Hunyady, B, Hussein, M, Hussein, O, Hussien, S, Ibanez-Samaniego, L, Ibdah, J, Ibrahim, L, Ibrahim, M, Ibrahim, I, Icaza-Chavez, M, Idelbi, S, Idilman, R, Ikeda, M, Indolfi, G, Invernizzi, F, Irshad, I, Isa, H, Iskandar, N, Ismaiel, A, Ismail, M, Ismail, Z, Ismail, F, Iwamoto, H, Jack, K, Jacob, R, Jafarov, F, Jafri, W, Jahshan, H, Jalal, P, Jancoriene, L, Janicko, M, Jayasena, H, Jefferies, M, Jha, V, Ji, F, Ji, Y, Jia, J, Jiang, C, Jiang, N, Jiang, Z, Jin, X, Jin, Y, Jing, X, Jingyu, Q, Jinjolava, M, Jong, F, Jucov, A, Julius, I, Kaddah, M, Kamada, Y, Kamal, A, Kamal, E, Kamel, A, Kao, J, Karin, M, Karlas, T, Kashwaa, M, Katsidzira, L, Kaya, E, Kayasseh, M, Keenan, B, Keklikkiran, C, Keml, W, Khalaf, D, Khalefa, R, Khamis, S, Khater, D, Khattab, H, Khavkin, A, Khlynova, O, Khmis, N, Kobyliak, N, Koffas, A, Koike, K, Kok, K, Koller, T, Komas, N, Korochanskaya, N, Koulla, Y, Koya, S, Kraft, C, Kraja, B, Krawczyk, M, Kuchay, M, Kulkarni, A, Kumar, A, Kumar, M, Lakoh, S, Lam, P, Lan, L, Lange, N, Lankarani, K, Lanthier, N, Lapshyna, K, Lashen, S, Laure, K, Lazebnik, L, Lebrec, D, Lee, S, Lee, W, Lee, Y, Leeming, D, Leite, N, Leon, R, Lesmana, C, Li, J, Li, Q, Li, Y, Li, L, Li, M, Liang, H, Lijuan, T, Lim, S, Lim, L, Lin, S, Lin, H, Lin, R, Lithy, R, Liu, Y, Liu, X, Liu, 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M., Palle S., Pan Z., Pan X. -Y., Pan Q., Papaefthymiou A., Paquissi F. C., Par G., Parkash A., Payawal D., Peltekian K. M., Peng X., Peng L., Peng Y., Pengoria R., Perez M., Perez J. L., Perez N. M., Persico M., Pessoa M. G., Petta S., Philip M., Plaz Torres M. C., Polavarapu N., Poniachik J., Portincasa P., Pu C., Purnak T., Purwanto E., Qi X., Qian Z., Qiang Z., Qiao Z., Qiao L., Queiroz A., Rabiee A., Radwan M., Rahetilahy A. M., Ramadan Y., Ramadan D., Ramli A. S., Ramm G. A., Ran A., Rankovic I., RAO H., Raouf S., Ray S., Reau N., Refaat A., Reiberger T., Remes-Troche J. M., Reyes E. C., Richardson B., Ridruejo E., Riestra Jimenez S., Rizk I., Roberts S., Roblero J. P., Robles J. A. P., Rockey D., Rodriguez M., Rodriguez Hernandez H., Roman E., Romeiro F. G., Romeo S., Rosales-Zabal J. M., Roshdi G. R., Rosso N., Ruf A., Ruiz P. C., Runes N. R., Ruzzenente A., Ryan M., Saad A., Sabbagh E. B., Sabbah M., Saber S., Sabrey R., Sabry R., Saeed M. A., Said D., Said E. M., Sakr M. A., Salah Y., Salama R. M., Salama A., Saleh H., Saleh A., Salem A., Salem A. T., Salifou A., Salih A. F., Salman A., Samouda H., Sanai F., Sanchez-Avila J. F., Sanker L., Sano T., Sanz M., Saparbu T., Sawhney R., Sayed F., Sayed S. A., Sayed A. O., Sayed M., Sebastiani G., Secadas L., Sediqi K. Q., Seif S., Semida N., Senates E., Serban E. D., Serfaty L., Seto W. -K., Sghaier I., Sha M., Shabaan H. M., Shalaby L., Shaltout I., Sharara A. I., Sharma V., Shawa I. T., Shawkat A., Shawky N., Shehata O., Sheils S., Shewaye A. B., Shi G., Shi J., Shimose S., Shirono T., Shou L., Shrestha A., Shui G., Sievert W., Sigurdardottir S., Sira M. M., Siradj R., Sison C., Smyth L., Soliman R., Sollano J. D., Sombie R., Sonderup M., Sood S., Soriano G., Stedman C. A. M., Stefanyuk O., Stimac D., Strasser S., Strnad P., Stuart K., Su W., Su M., Sumida Y., Sumie S., Sun D. -Q., Sun J., Suzuki H., Svegliati-Baroni G., Swar M. O., TAHARBOUCHT S., Taher Z., Takamura S., Tan L., Tan S. -S., Tanwandee T., Tarek S., Tatiana G., Tavaglione F., Tecson G. Y., Tee H. -P., Teschke R., Tharwat M., Thong V. D., Thursz M., Tine T., Tiribelli C., Tolmane I., Tong J., Tongo M., Torkie M., Torre A., Torres E. A., Trajkovska M., Treeprasertsuk S., Tsutsumi T., Tu T., Tur J. A., Turan D., Turcan S., Turkina S., Tutar E., Tzeuton C., Ugiagbe R., Uygun A., Vacca M., Vajro P., Van der Poorten D., Van Kleef L. A., Vashakidze E., Velazquez C. M., Velazquez M. I., Vento S., Verhoeven V., Vespasiani-Gentilucci U., Vethakkan S. R., Vilaseca J., Vitek L., Volkanovska A., Wallace M., Wan W., Wang Y., Wang X., Wang C., Wang M., Wangchuk P., Weltman M., White M., Wiegand J., Wifi M. -N., Wigg A., Wilhelmi M., William R., Wittenburg H., Wu S., Wubeneh A. M., Xia H., Xiao J., Xiao X., Xiaofeng W., Xiong W., Xu L., Xu J., Xu W., Xu J. -H., Xu K., Xu Y., Xu S. -H., Xu M., Xu A., Xu C., Yan H., Yang J., Yang R. -X., Yang Y., Yang Q., Yang N., Yao J., Yara J., Yaras S., Yilmaz N., Younes R., younes H., Young S., Youssef F., Yu Y., Yu M. -L., Yuan J., Yue Z., Yuen M. -F., Yun W., Yurukova N., Zakaria S., Zaky S., Zaldastanishvili M., Zapata R., Zare N., Zerem E., Zeriban N., Zeshuai X., Zhang H., Zhang X., Zhang Y., Zhang W. -H., Zhang Y. -P., Zhang Z. -Q., Zhao J., Zhao R. -R., Zhao H., Zheng C., Zheng Y., Zheng R., Zheng T. -L., Zheng K., Zhou X. Q., Zhou Y., Zhou Y. -J., Zhou H., Zhou L., Zhu L. D., Zhu Y. F., Zhu Y., Zhu P. -W., Ziada E., Ziring D., Ziyi L., Zou S., Zou Z., Zou H., Zuart Ruiz R., Mendez-Sanchez, N, Bugianesi, E, Gish, R, Lammert, F, Tilg, H, Nguyen, M, Sarin, S, Fabrellas, N, Zelber-Sagi, S, Fan, J, Shiha, G, Targher, G, Zheng, M, Chan, W, Vinker, S, Kawaguchi, T, Castera, L, Yilmaz, Y, Korenjak, M, Spearman, C, Ungan, M, Palmer, M, El-Shabrawi, M, Gruss, H, Dufour, J, Dhawan, A, Wedemeyer, H, George, J, Valenti, L, Fouad, Y, Romero-Gomez, M, Eslam, M, Abate, M, Abbas, B, Abbassy, A, Abd El Ghany, W, Abd Elkhalek, A, Abd ElMajeed, E, Abdalgaber, M, Abdallah, M, Abdallah, N, Abdelaleem, S, Abdelghani, Y, Abdelghany, W, Abdelhalim, S, Abdelhamid, W, Abdelhamid, N, Abdelkader, N, Abdelkreem, E, Abdelmohsen, A, Abdelrahman, A, Abd-elsalam, S, Abdeltawab, D, Abduh, A, Abdulhakam, N, Abdulla, M, Abedpoor, N, Abenavoli, L, Aberg, F, Ablack, O, Abo elftouh, M, Abo-Amer, Y, Aboubkr, A, Aboud, A, Abouelnaga, A, Aboufarrag, G, Aboutaleb, A, Abundis, L, Adali, G, Adames, E, Adams, 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I, Isa, H, Iskandar, N, Ismaiel, A, Ismail, M, Ismail, Z, Ismail, F, Iwamoto, H, Jack, K, Jacob, R, Jafarov, F, Jafri, W, Jahshan, H, Jalal, P, Jancoriene, L, Janicko, M, Jayasena, H, Jefferies, M, Jha, V, Ji, F, Ji, Y, Jia, J, Jiang, C, Jiang, N, Jiang, Z, Jin, X, Jin, Y, Jing, X, Jingyu, Q, Jinjolava, M, Jong, F, Jucov, A, Julius, I, Kaddah, M, Kamada, Y, Kamal, A, Kamal, E, Kamel, A, Kao, J, Karin, M, Karlas, T, Kashwaa, M, Katsidzira, L, Kaya, E, Kayasseh, M, Keenan, B, Keklikkiran, C, Keml, W, Khalaf, D, Khalefa, R, Khamis, S, Khater, D, Khattab, H, Khavkin, A, Khlynova, O, Khmis, N, Kobyliak, N, Koffas, A, Koike, K, Kok, K, Koller, T, Komas, N, Korochanskaya, N, Koulla, Y, Koya, S, Kraft, C, Kraja, B, Krawczyk, M, Kuchay, M, Kulkarni, A, Kumar, A, Kumar, M, Lakoh, S, Lam, P, Lan, L, Lange, N, Lankarani, K, Lanthier, N, Lapshyna, K, Lashen, S, Laure, K, Lazebnik, L, Lebrec, D, Lee, S, Lee, W, Lee, Y, Leeming, D, Leite, N, Leon, R, Lesmana, C, Li, J, Li, Q, Li, Y, Li, L, Li, M, 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Zuart Ruiz, R, Mendez-Sanchez N., Bugianesi E., Gish R. G., Lammert F., Tilg H., Nguyen M. H., Sarin S. K., Fabrellas N., Zelber-Sagi S., Fan J. -G., Shiha G., Targher G., Zheng M. -H., Chan W. -K., Vinker S., Kawaguchi T., Castera L., Yilmaz Y., Korenjak M., Spearman C. W., Ungan M., Palmer M., El-Shabrawi M., Gruss H. -J., Dufour J. -F., Dhawan A., Wedemeyer H., George J., Valenti L., Fouad Y., Romero-Gomez M., Eslam M., Abate M. L., Abbas B., Abbassy A. A., Abd El Ghany W., Abd Elkhalek A., Abd ElMajeed E., Abdalgaber M., AbdAllah M., Abdallah M., Abdallah N., Abdelaleem S., Abdelghani Y., Abdelghany W., Abdelhalim S. M., Abdelhamid W., Abdelhamid N., Abdelkader N. A., Abdelkreem E., Abdelmohsen A. M., Abdelrahman A. A., Abd-elsalam S. M., Abdeltawab D., Abduh A., Abdulhakam N., Abdulla M., Abedpoor N., Abenavoli L., Aberg F., Ablack O., Abo elftouh M., Abo-Amer Y. E. -E., Aboubkr A., Aboud A., Abouelnaga A. M., Aboufarrag G. A., Aboutaleb A., Abundis L., Adali G., Adames E., Adams L., Adda D., Adel N., Adel Sayed M., Afaa T. J., Afredj N., Aghayeva G., Aghemo A., Aguilar-Salinas C. A., Ahlenstiel G., Ahmady W., Ahmed W., Ahmed A., Ahmed S. N., Ahmed H. M., Ahmed R., Aigner E., Akarsu M., Akroush M., Akyuz U., Al Mahtab M., Al Qadiri T., Al Rawahi Y., AL rubaee R., Al Saffar M., Alam S., Al-Ani Z., Albillos A., Alboraie M., Al-Busafi S., Al-Emam M., Alharthi J., Ali K., Ali B. A., Ali M., Ali R. A. R., Alisi A., AL-Khafaji A. R., Alkhatry M., Aller R., Almansoury Y., Al-Naamani K., Alnakeeb A., Alonso A., Alqahtani S. A., Alrabadi L., Alswat K., Altaher M., Altamimi T., Altamirano J., Alvares-da-Silva M. R., Aly E. A. M., Alzahaby A., Alzamzamy A., Amano K., Amer M. A., Amin M. A., Amin S. A., Amir A. A., Ampuero J., Anas N., Andreone P., Andriamandimby S. F., Anees M., Angela P., Antonios M., Arafat W., Araya J. M., Armendariz-Borunda J., Armstrong M. J., Ashktorab H., Aspichueta P., Assal F., Atef M., Attia D., Atwa H., Awad R., Awad M. A. E., Awny S., Awolowo O., Awuku Y. A., Ayada I., Aye T. T., Ayman S., Ayman H., Ayoub H., Azmy H. M., Babaran R. P., Badreldin O., Badry A., Bahcecioglu I. H., Bahour A., Bai J., Balaban Y., Balasubramanyam M., Bamakhrama K., Banales J. M., Bangaru B., Bao J., Barahona J. S., Barakat S., Barbalho S. M., Barbra B., Barranco B., Barrera F., Baumann U., Bazeed S., Bech E., Benayad A., Benesic A., Bernstein D., Bessone F., Birney S., Bisseye C., Blake M., Bobat B., Bonfrate L., Bordin D. S., Bosques-Padilla F., Boursier J., Boushab B. M., Bowen D., Bravo P. M., Brennan P. N., Bright B., Broekaert I., Buque X., Burgos-Santamaria D., Burman J., Busetto L., Byrne C. D., Cabral-Prodigalidad P. A. I., Cabrera-Alvarez G., Cai W., Cainelli F., Caliskan A. R., Canbay A., Cano-Contreras A., Cao H. -X., Cao Z., Carrion A., Carubbi F., Casanovas T., Castellanos Fernandez M. I., Chai J., Chan S. P., Charatcharoenwitthaya P., Chavez-Tapia N., Chayama K., Chen J., Chen L., Chen Z. -W., Chen H., Chen S. -D., Chen Q., Chen Y., Chen G., Chen E. -Q., Chen F., Chen P. -J., Cheng R., Cheng W., Chieh J. T. W., Chokr I., Cholongitas E., Choudhury A., Chowdhury A., Chukwudike E. S., Ciardullo S., Clayton M., Clement K., Cloa M. M., Coccia C., Collazos C., Colombo M., Cosar A. M., Cotrim H. P., Couillerot J., Coulibaly A., Crespo G., Crespo J., Cruells M., Cua I. H. Y., Dabbous H. K., Dalekos G. N., D'Alia P., Dan L., Dao V. H., Darwish M., Datz C., Davalos-Moscol M. B., Dawoud H., de Careaga B. O., de Knegt R., de Ledinghen V., de Silva J., Debzi N., Decraecker M., Del Pozo E., Delgado T. C., Delgado-Blanco M., Dembinski L., Depina A., Derbala M., Desalegn H., Desbois-Mouthon C., Desoky M., Dev A., Di Ciaula A., Diago M., Diallo I., Diaz L. A., Dirchwolf M., Dongiovanni P., Dorofeyev A., Dou X., Douglas M. W., Doulberis M., Dovia C. K., Doyle A., Dragojevic I., Drenth J. P., Duan X., Dulskas A., Dumitrascu D. L., Duncan O., Dusabejambo V., Dwawhi R. S. N. A., Eiketsu S., El Amrousy D., El Deeb A., El Deriny G., El Din H. S., El Kamshishy S., El Kassas M., El Raziky M., Elagamy O. A., Elakel W., Elalfy D., Elaraby H., ElAwady H., Elbadawy R., Eldash H. H., Eldefrawy M. S., Elecharri C. L., Elfaramawy A., Elfatih M., Elfiky M., Elgamsy M., Elgendy M., El-Guindi M. A., Elhussieny N., Eliwa A. M., Elkabbany Z., El-Khayat H., El-Koofy N. M., Elmetwalli A., Elrabat A., El-Raey F., Elrashdy F., Elsahhar M., Elsaid E. M., Elsayed S., Elsayed H., Elsayed A., Elsayed A. M., El-Serafy M., Elsharkawy A. M., Elsheemy R. Y., Elshemy E. E., Elsherbini S., Eltoukhy N., Elwakil R., Emad O., Emad S., Embabi M., Ergenc I., Ermolova T., Esmat G., Esmat D. M., Estupinan E. C., Ettair S., Eugen T., Ezz-Eldin M., Falcon L. P. V., Fan Y. -C., Fandari S., Farag M., Farahat T. M., Fares E. M., Fares M., Fassio E., Fathy H., Fathy D., Fathy W., Fayed S., Feng D., Feng G., Fernandez-Bermejo M., Ferreira C. T., Ferrer J. D., Forbes A., Fouad R., Fouad H. M., Frisch T., Fujii H., Fukunaga S., Fukunishi S., Fulya H., Furuhashi M., Gaber Y., Galang A. J. G., Gallardo J. C., Galloso R., Gamal M., Gamal R., Gamal H., Gan J., Ganbold A., Gao X., Garas G., Garba T., Garcia-Cortes M., Garcia-Monzon C., Garcia-Samaniego J., Gastaldelli A., Gatica M., Gatley E., Gegeshidze T., Geng B., Ghazinyan H., Ghoneem S., Giacomelli L., Giannelli G., Giannini E. G., Giefer M., Gines P., Girala M., Giraudi P. J., Goh G. B. -B., Gomaa A. A., Gong B., Gonzales D. H. C., Gonzalez H. C., Gonzalez-Huezo M. S., Graupera I., Grgurevic I., Gronbaek H., Gu X., Guan L., Gueye I., Guingane A. N., Gul O. O., Gul C. B., Guo Q., Gupta P. P., Gurakar A., Gutierrez J. C. R., Habib G., Hafez A., Hagman E., Halawa E., Hamdy O., Hamed A. E., Hamed D. H., Hamid S., Hamoudi W., Han Y., Haridy J., Haridy H., Harris D. C. H. H., Hart M., Hasan F., Hashim A., Hassan I., Hassan A., Hassan E. A., Hassan A. A., Hassan M. S., Hassanin F., Hassnine A., Haukeland J. W., Hawal A. I. M., He J., He Q., He Y., He F. -P., Hegazy M., Hegazy A., Henegil O., Hernandez N., Hernandez-Guerra M., Higuera-de-la-Tijera F., Hindy I., Hirota K., Ho L. C., Hodge A., Hosny M., Hou X., Huang J. -F., Huang Y., Huang Z., Huang A., Huang X. -P., Hui-ping S., Hunyady B., Hussein M. A., Hussein O., Hussien S. M., Ibanez-Samaniego L., Ibdah J., Ibrahim L., Ibrahim M., Ibrahim I., Icaza-Chavez M. E., Idelbi S., Idilman R. I., Ikeda M., Indolfi G., Invernizzi F., Irshad I., Isa H. M. A., Iskandar N. J., Ismaiel A., Ismail M., Ismail Z., Ismail F., Iwamoto H., Jack K., Jacob R., Jafarov F., Jafri W., Jahshan H., Jalal P. K., Jancoriene L., Janicko M., Jayasena H., Jefferies M., Jha V., Ji F., Ji Y., Jia J., Jiang C., Jiang N., Jiang Z. -Z., Jin X., Jin Y., Jing X., Jingyu Q., Jinjolava M., Jong F. H. H., Jucov A., Julius I., Kaddah M., Kamada Y., kamal A., Kamal E. M., Kamel A. S., Kao J. -H., Karin M., Karlas T., Kashwaa M., Katsidzira L., Kaya E., Kayasseh M. A., Keenan B., Keklikkiran C., Keml W., Khalaf D. K., Khalefa R., Khamis S., Khater D., khattab H., Khavkin A., Khlynova O., Khmis N., Kobyliak N., Koffas A., Koike K., Kok K. Y. Y., Koller T., Komas N. P., Korochanskaya N. V., Koulla Y., Koya S., Kraft C., Kraja B., Krawczyk M., Kuchay M. S., Kulkarni A. V., Kumar A., Kumar M., Lakoh S., Lam P., Lan L., Lange N. F., Lankarani K. B., Lanthier N., Lapshyna K., Lashen S. A., Laure K. N. J., Lazebnik L., Lebrec D., Lee S. S., Lee W. S., Lee Y. Y., Leeming D. J., Leite N. C., Leon R., Lesmana C. R. A., Li J., Li Q., Li Y. -Y., Li Y., Li L., Li M., li Y., Liang H., Lijuan T., Lim S. G., Lim L. -L., Lin S., Lin H. -C., Lin R., Lithy R., Liu Y., Liu X., Liu W. -Y., Liu S., Liu K., Liu T., Lonardo A., Lopez M. B., Lopez-Benages E., Lopez-Jaramillo P., Lu H., Lu L. G., Lu Y., Lubel J., Lui R., Lupasco I., Luzina E., Lv X. -H., Lynch K., Ma H. -L., Machado M. V., Maduka N., Madzharova K., Magdaong R., Mahadeva S., Mahfouz A., Mahmood N. R. K. N., Mahmoud E., Mahrous M., Maiwall R., Majeed A., Majumdar A., Mak L., Maklouf M. M., Malekzadeh R., Mandato C., Mangia A., Mann J., Mansour H. H., Mansouri A., Mantovani A., Mao J. Q., Maramag F., Marchesini G., Marcus C., Marinho R. A. R. T., Martinez-Chantar M. L., Martins A. A. S., Marwan R., Mason K. F., Masoud G., Massoud M. N., Matamoros M. A., Mateos R. M., Mawed A., Mbanya J. C., Mbendi C., McColaugh L., McLeod D., Medina J. F. R., Megahed A., Mehrez M., Memon I., Merat S., Mercado R., Mesbah A., Meskini T., Metwally M., Metwaly R., Miao L., Micah E., Miele L., Milivojevic V., Milovanovic T., Mina Y. L., Mishkovik M., Mishriki A., Mitchell T., Mohamed A., Mohamed M., Mohamed S., Mohammed S., Mohammed A., Mohan V., Mohie S., Mokhtar A., Moniem R., Montilla M. S., Morales J. A. O., Morata M. M. S., Moreno-Planas J. M., Morise S., Mosaad S., Moselhy M., Mostafa A. M., Mostafa E., Mouane N., Mousa N., Moustafa H. M., Msherif A., Muller K., Munoz C., Munoz-Urribarri A. B., Murillo O. A., Mustapha F. I., Muzurovic E., Nabil Y., Nafady S., Nagamatsu A., Nakajima A., Nakano D., Nan Y., Nascimbeni F., Naseef M. S., Nashat N., Natalia T., Negro F., Nersesov A. V., Neuman M., Ng'wanasayi M., Ni Y., Nicoll A., Niizeki T., Nikolova D., Ningning W., Niriella M., Nogoibaeva K. A., Nordien R., O Sullivan C., O'Beirne J., Obekpa S., Ocama P., Ochwoto M., Ogolodom M. P., Ojo O., Okrostsvaridze N., Oliveira C. P., Omana R. C., Omar O. M., Omar H., Omar M., Omran S., Omran R., Osman M. M., Owise N., Owusu-Ansah T., Padilla- Machaca P. M., Palle S., Pan Z., Pan X. -Y., Pan Q., Papaefthymiou A., Paquissi F. C., Par G., Parkash A., Payawal D., Peltekian K. M., Peng X., Peng L., Peng Y., Pengoria R., Perez M., Perez J. L., Perez N. M., Persico M., Pessoa M. G., Petta S., Philip M., Plaz Torres M. C., Polavarapu N., Poniachik J., Portincasa P., Pu C., Purnak T., Purwanto E., Qi X., Qian Z., Qiang Z., Qiao Z., Qiao L., Queiroz A., Rabiee A., Radwan M., Rahetilahy A. M., Ramadan Y., Ramadan D., Ramli A. S., Ramm G. A., Ran A., Rankovic I., RAO H., Raouf S., Ray S., Reau N., Refaat A., Reiberger T., Remes-Troche J. M., Reyes E. C., Richardson B., Ridruejo E., Riestra Jimenez S., Rizk I., Roberts S., Roblero J. P., Robles J. A. P., Rockey D., Rodriguez M., Rodriguez Hernandez H., Roman E., Romeiro F. G., Romeo S., Rosales-Zabal J. M., Roshdi G. R., Rosso N., Ruf A., Ruiz P. C., Runes N. R., Ruzzenente A., Ryan M., Saad A., Sabbagh E. B., Sabbah M., Saber S., Sabrey R., Sabry R., Saeed M. A., Said D., Said E. M., Sakr M. A., Salah Y., Salama R. M., Salama A., Saleh H., Saleh A., Salem A., Salem A. T., Salifou A., Salih A. F., Salman A., Samouda H., Sanai F., Sanchez-Avila J. F., Sanker L., Sano T., Sanz M., Saparbu T., Sawhney R., Sayed F., Sayed S. A., Sayed A. O., Sayed M., Sebastiani G., Secadas L., Sediqi K. Q., Seif S., Semida N., Senates E., Serban E. D., Serfaty L., Seto W. -K., Sghaier I., Sha M., Shabaan H. M., Shalaby L., Shaltout I., Sharara A. I., Sharma V., Shawa I. T., Shawkat A., Shawky N., Shehata O., Sheils S., Shewaye A. B., Shi G., Shi J., Shimose S., Shirono T., Shou L., Shrestha A., Shui G., Sievert W., Sigurdardottir S., Sira M. M., Siradj R., Sison C., Smyth L., Soliman R., Sollano J. D., Sombie R., Sonderup M., Sood S., Soriano G., Stedman C. A. M., Stefanyuk O., Stimac D., Strasser S., Strnad P., Stuart K., Su W., Su M., Sumida Y., Sumie S., Sun D. -Q., Sun J., Suzuki H., Svegliati-Baroni G., Swar M. O., TAHARBOUCHT S., Taher Z., Takamura S., Tan L., Tan S. -S., Tanwandee T., Tarek S., Tatiana G., Tavaglione F., Tecson G. Y., Tee H. -P., Teschke R., Tharwat M., Thong V. D., Thursz M., Tine T., Tiribelli C., Tolmane I., Tong J., Tongo M., Torkie M., Torre A., Torres E. A., Trajkovska M., Treeprasertsuk S., Tsutsumi T., Tu T., Tur J. A., Turan D., Turcan S., Turkina S., Tutar E., Tzeuton C., Ugiagbe R., Uygun A., Vacca M., Vajro P., Van der Poorten D., Van Kleef L. A., Vashakidze E., Velazquez C. M., Velazquez M. I., Vento S., Verhoeven V., Vespasiani-Gentilucci U., Vethakkan S. R., Vilaseca J., Vitek L., Volkanovska A., Wallace M., Wan W., Wang Y., Wang X., Wang C., Wang M., Wangchuk P., Weltman M., White M., Wiegand J., Wifi M. -N., Wigg A., Wilhelmi M., William R., Wittenburg H., Wu S., Wubeneh A. M., Xia H., Xiao J., Xiao X., Xiaofeng W., Xiong W., Xu L., Xu J., Xu W., Xu J. -H., Xu K., Xu Y., Xu S. -H., Xu M., Xu A., Xu C., Yan H., Yang J., Yang R. -X., Yang Y., Yang Q., Yang N., Yao J., Yara J., Yaras S., Yilmaz N., Younes R., younes H., Young S., Youssef F., Yu Y., Yu M. -L., Yuan J., Yue Z., Yuen M. -F., Yun W., Yurukova N., Zakaria S., Zaky S., Zaldastanishvili M., Zapata R., Zare N., Zerem E., Zeriban N., Zeshuai X., Zhang H., Zhang X., Zhang Y., Zhang W. -H., Zhang Y. -P., Zhang Z. -Q., Zhao J., Zhao R. -R., Zhao H., Zheng C., Zheng Y., Zheng R., Zheng T. -L., Zheng K., Zhou X. Q., Zhou Y., Zhou Y. -J., Zhou H., Zhou L., Zhu L. D., Zhu Y. F., Zhu Y., Zhu P. -W., Ziada E., Ziring D., Ziyi L., Zou S., Zou Z., Zou H., and Zuart Ruiz R.

Published
2022

39. Analysis of pressure oscillations and wall heat flux due to hydrogen auto-ignition in a confined domain

Author

Dou, X, Talei, M, Yang, Y, Dou, X, Talei, M, and Yang, Y

Abstract

This study investigates the impact of the near-wall temperature gradient on hydrogen auto-ignition characteristics using one-dimensional (1D) fully resolved simulations. Ten cases are simulated, one featuring normal combustion and the other nine simulating auto-ignitive combustion with different initial pressures, equivalence ratios, and near-wall temperature gradients. The simulations show that the near-wall temperature gradient greatly affects the onset and intensity of the auto-ignition event. For cases with the initial conditions of 833.3 K and 15 bar, a small near-wall temperature gradient delays the timing of auto-ignition and places the auto-ignition kernel further away from the wall, facilitating deflagration-to-detonation transition of the auto-ignitive flame. This leads to a large increase in pressure oscillations within the domain and heat flux to the wall. When the initial conditions are changed to 900 K and 20 bar, the magnitude of the near-wall temperature gradient also affects the number of auto-ignition events, leading to a significant impact on the wall heat flux. The results suggest that an accurate modeling of the near-wall temperature gradient is necessary for the simulations of hydrogen end-gas auto-ignition. This requires special considerations in the near-wall region and a careful selection of the wall heat transfer model in Computational Fluid Dynamics (CFD) tools, such as Reynolds-Averaged Navier–Stokes (RANS) and Large-Eddy Simulation (LES).

Published
2023

40. Global Carbon Budget 2023

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2023

41. Proceedings of the Eighteenth DOE Solar Photochemistry Research Conference

Author

Allan, C.B., Allison, D.P., Anderson, D.J., Aukett, T., Baba, A.I., Bally, T., Barbara, P.F., Barkigia, K.M., Barkoff, A., Baxley, G., Bedja, I., Bevilacqua, J.M., Biczok, L., Blankenship, R.E., Blatter, F., Bobrowski, K., Borguet, E., Brigham, E.S., Brunschwig, B.S., Calvin, M., Cao, T., Castner, E.W., Chandler, D., Chang, H.-C., Chang, Y.J., Chen, L.X., Chen, Y., Chidsey, C.E.D., Chin, T.T., Chipman, D.M., Chumanov, G., Connolly, J.S., Cook, W., Cormier, R.A., Cortes, E., Cotton, T.M., Creutz, C., Crosby, G.A., Cummings, S., Curtis, C.J., Derr, D.L., Djurovich, P.I., Dou, X., Dutta, P.K., Eckert, A., Eisenberg, R., Eisenthal, K.B., Elliot, C.M., Endicott, J.F., Fajer, J., Fayer, M.D., Feldberg, S.W., Ferraudi, G., Ferrere, S., Fessenden, R.W., Fox, M.A., Frank, A.J., Frei, H., Friesner, R.A., Fujita, E., Gahan, S.L., Gao, G., Gentemann, S., Gosztola, D., Gratzel, M., Greenbaum, E., Gregg, B.A., Grodkowski, J., Groner, M., Gust, D., Hansen, D., Hayes, J., Hill, J.E., Hoffman, M.Z., Holten, D., Hotchandani, S., Howard, J., Hsiao, J.-S., Hu, S., Huang, N.-T., Hug, G.L., Hung, S.-C., Hupp, J.T., Hurst, J.K., Isied, S.S., Jankowiak, R., Jeevarajan, A.S., Jeevarajan, J.A., Jones, G., Joshi, R., Kamat, P.V., Kapoor, S., Karki, L., Kartha, S., Kasha, M., Keller, S.W., Kelley, D.F., Kenyon, C.N., Kevan, L., and Kim, K.J.

Published
1994

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