Search

Background The function of H3F3A G43W mutation, which has been observed in almost all GCTB, remains poorly characterized. Breakthrough in malignant GCTB has been trapped by the lack of clinical available drugs, limited canonical patient samples and paucity of fidelity preclinical models. Methods Tumor samples obtained from a malignant GCTB was implanted in immunodeficient mice for the generation of PDX. Histological examination and short tandem repeat (STR) were used for inherited features analyses. An epigenetic/transcriptional targeted compound library was selected for drug screening. The in vivo effects of selected drug were validated in PDX model. Results We established the PDX model with recurrent malignant GCTB specimens, histological examination and STR analyses revealed that PDX and their corresponding parental patients shared the same STRs and histologic features, suggesting common origins. ITF-2357 was the most significant compound with an IC50 lower than 0.1 uM. The results of the drug screening and in vivo PDX validation demonstrated that ITF-2357 might be a promising drug targeted H3F3A G34W mutation MGCTBs. Conclusion Our study demonstrates that PDX model maintained the same histologic and genetic features as those in the original patient. targeting HDAC through ITF-2357 effectively overcomes malignant GCTB progression in vitro and in vivo. Translational potential statement As PDX retain the principal histologic and genetic characteristics of the primary tumors, mad it a valuable research tool in predictive clinical efficacy. In this study, we first established a malignant GCTB PDX model, which might further accelerate the progress of drug development in malignant GCTB., Highlights • PDX model were established from a malignant GCTB patient. • PDCs and PDX maintained same oncohiston mutations as those in the original patient. • ITF-2357 inhibits malignant GCTB progression in vitro and in vivo.

Compared with traditional endonasal endoscope, Virtual endonasal endoscope (VEE) is a computerized alternative solution with the advantages of being non-invasive, affordable, no perforation, low risk of infection, and high degree of sensitivity. A Central path extraction algorithm based on Pre-planning of the roaming area (CPE-PRA) is proposed to extract the central path of the nasal cavity model efficiently. And a B-spline curve fitting algorithm based on Relative center deviation (RCD) is introduced to fit a smooth curve to the extracted path, so that the virtual camera could have both a steady turning speed and a broad vision. A series of comparison tests were conducted to evaluate the effectiveness and efficiency of the proposed algorithms.

To investigate the potential benefits of acarbose therapy on cardiovascular events (CVD) in Type 2 diabetes (T2DM) in an urban community over 10-year follow-up. The study population of Beijing Community Diabetes Study (BCDS) were type 2 diabetes (T2DM) living in 21 communities in Beijing. All patients received comprehensive intervention in accordance with the Chinese guidelines for the prevention and treatment of diabetes. Professors in endocrinology from top tier hospitals regularly visited the communities for consultations, which was a feature of this study. A total of 1797 T2DM in BCDS study had complete screening data, including blood glucose, blood pressure, lipid profiles and acarbose continuous therapy. After 10-year follow-up, the risks of CVD outcomes were assessed according to whether patients had received acarbose therapy or not. All patients were followed-up to assess the long-term effects of the multifactorial interventions. At baseline, compared with the acarbose therapy free in T2DM, there was no significant difference in achieving the joint target control in patients with acarbose therapy. From the beginning of 8th year follow-up, the joint target control rate in patients with acarbose therapy was significantly higher than that of acarbose therapy free. During the 10-year follow-up, a total of 446 endpoint events occurred, including all-cause death, cardiovascular events, cerebrovascular events. The incidences of myocardial infarction (from the 4th year of follow-up) and all-cause death (from the 2nd year of follow-up) in patients who received acarbose therapy were significantly lower than that of acarbose therapy free respectively. In Cox multivariate analyses, there were significant differences in incidences of myocardial infarction and all-cause death between afore two groups during the 10-year follow-up, and the adjusted HRs were 0.50 and 0.52, respectively. After multifactorial interventions, T2DM with acarbose therapy revealed significant reductions of myocardial infarction and all-cause death. The long-term effects of with acarbose therapy on improving joint target control might be one of the main reasons of myocardial infarction and all-cause death reduction.Trial Registration: ChiCTR-TRC-13003978, ChiCTR-OOC-15006090.

The CYP4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at individual patients' level to capture the possible effect of ethnicity, gene-gene interaction or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95%CI 7-10%), with a higher effect in females, in patients taking acenocoumarol and in Whites. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived. This article is protected by copyright. All rights reserved.

ObjectiveTumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic indicators from pathological images challenging.DesignAn interpretable, weakly supervised deep learning framework incorporating prior knowledge was proposed to analyse hepatocellular carcinoma (HCC) and explore new prognostic phenotypes on pathological whole-slide images (WSIs) from the Zhongshan cohort of 1125 HCC patients (2451 WSIs) and TCGA cohort of 320 HCC patients (320 WSIs). A ‘tumour risk score (TRS)’ was established to evaluate patient outcomes, and then risk activation mapping (RAM) was applied to visualise the pathological phenotypes of TRS. The multi-omics data of The Cancer Genome Atlas(TCGA) HCC were used to assess the potential pathogenesis underlying TRS.ResultsSurvival analysis revealed that TRS was an independent prognosticator in both the Zhongshan cohort (ppredictive ability of TRS was superior to and independent of clinical staging systems, and TRS could evenly stratify patients into up to five groups with significantly different prognoses. Notably, sinusoidal capillarisation, prominent nucleoli and karyotheca, the nucleus/cytoplasm ratio and infiltrating inflammatory cells were identified as the main underlying features of TRS. The multi-omics data of TCGA HCC hint at the relevance of TRS to tumour immune infiltration and genetic alterations such as the FAT3 and RYR2 mutations.ConclusionOur deep learning framework is an effective and labour-saving method for decoding pathological images, providing a valuable means for HCC risk stratification and precise patient treatment.

Introduction To date, research is lacking on the development of a cardiovascular disease (CVD) risk assessment tool for people with diabetes mellitus, in general, and for Chinese patients with diabetes in particular. We have explored CVD risk assessment tools for Chinese patients with diabetes. Here, we report our investigation of cardiovascular risk assessment using the improved Framingham Risk Score (I-FRS) in patients with type 2 diabetes mellitus (T2DM) in Beijing communities. Methods A total of 3232 patients with T2DM attending Beijing community health centers were enrolled in this study. FRS were used to predict CVD risk in all patients at baseline using the following risk scores for glycated hemoglobin (HbA1c) categories: 0 = HbA1c ≤ 7.0%; 1 = 7.0% 9.0%. The I-FRS was use to stratify all patients into low (I-FRS 20%) FRS strata. All treatments administered in the Beijing Communities Diabetes Study were in accordance with national guidelines for T2DM in China, and patients regularly attended clinical consultations with professors in endocrinology, who were experts in their respective speciality, from top tier hospitals. After 10 years, patients were followed-up to assess the long-term effects of the multifactorial interventions. Statistical analysis was performed using SAS® software (SAS Institute, Inc., Cary, NC, USA). Results The receiver operating characteristic curve of the I-FRS showed significant prediction accuracy for the actual incidence of CVD events. At baseline, subjects in the high FRS stratum for diabetes were more prone to be elderly and to have a longer duration of T2DM, higher systolic blood pressure, and higher lipid profiles. Subjects in the medium and high FRS strata had a higher incidence of CVD events than those in the no-complications group (DM group with no blood pressure issues) (P 20% was 12.5-fold higher than that of patients with I-FRS score

Background In the process of drug development, computational drug repositioning is effective and resource-saving with regards to its important functions on identifying new drug–disease associations. Recent years have witnessed a great progression in the field of data mining with the advent of deep learning. An increasing number of deep learning-based techniques have been proposed to develop computational tools in bioinformatics. Methods Along this promising direction, we here propose a drug repositioning computational method combining the techniques of Sigmoid Kernel and Convolutional Neural Network (SKCNN) which is able to learn new features effectively representing drug–disease associations via its hidden layers. Specifically, we first construct similarity metric of drugs using drug sigmoid similarity and drug structural similarity, and that of disease using disease sigmoid similarity and disease semantic similarity. Based on the combined similarities of drugs and diseases, we then use SKCNN to learn hidden representations for each drug-disease pair whose labels are finally predicted by a classifier based on random forest. Results A series of experiments were implemented for performance evaluation and their results show that the proposed SKCNN improves the prediction accuracy compared with other state-of-the-art approaches. Case studies of two selected disease are also conducted through which we prove the superior performance of our method in terms of the actual discovery of potential drug indications. Conclusion The aim of this study was to establish an effective predictive model for finding new drug–disease associations. These experimental results show that SKCNN can effectively predict the association between drugs and diseases.

Obesity increases the risk of developing cardiovascular disease and other metabolic diseases. We intended to compare three different anthropometric indicators of obesity, in predicting the incidence of cardiovascular events in Chinese type 2 diabetes. Beijing Community Diabetes Study was a prospective multi-center study conducted in Beijing community health centers. Type 2 diabetes patients from fourteen community health centers were enrolled at baseline. The primary endpoint was cardiovascular events. The upper quartile of neck circumference (NC) was set as greater NC. A total of 3299 diabetes patients were enrolled. In which, 941 (28.52%) had cardiovascular disease at baseline. Logistic analysis showed that central obesity (waist circumference (WC) above 90 cm in men and 85 cm in women) and greater NC were all related to baseline cardiovascular disease (adjusted OR = 1.49, and 1.55). After 10-year follow-up, 340 (10.31%) had cardiovascular events. Compared with patients without cardiovascular events, those having cardiovascular events had higher BMI, larger WC and NC. Cox regression analysis showed that greater WC and NC were all associated with the occurrence of cardiovascular events (adjusted HR = 1.41, and 1.38). A higher NC and WC might increase the risk of cardiovascular events by about 40% in type 2 diabetes patients in Beijing communities.

WFOV (wide field of view) imaging mode is used to provide an ultrasound image much larger than the normal probe field of view, which is achieved by compounding successive frames in a sequence as the probe moves and scans. The eraser feature in this paper is designed to erase the undesirable part of panorama image with reverse probe movement. To implement the eraser function we propose a method which is a three step process composed of probe movement detection, pixel erasing and smooth connection of added field of view image. Here we compute the position of real-time image relative to the static prior image based on image registration and spatial transformation for detecting probe motion. The fine-tuning in Y-direction and line fusion based on persistence method are used for smooth connection between prior WFOV image and added field-of view image.

Introduction. Distinct from other diseases, as cancer progresses, both the symptoms and treatments evolve, resulting in a complex, time-dependent relationship. Many competing risk factors influence the outcome of cancer. An improved method was used to evaluate the data from 6 non-small-cell lung cancer (NSCLC) clinical trials combined in our center since 2016 to deal with the bias caused by competing risk factors. Material and Methods. Data of 118 lung cancer patients were collected from 2016 to 2020. Fine and Gray’s model for competing risk was used to evaluate survival of different treatment group compares with the classic survival analysis model. Results. Immunotherapy had better progression-free survival than chemotherapy. (HR: 0.62, 95% CI: 0.41-0.95, p = 0.0260 ). However, there were no significant differences in patients who withdrew due to treatment-related adverse events from different groups. ( Z = 0.0508 , p = 0.8217 ). The PD-1/PD-L1 inhibitors in our study did not significantly improve overall survival compared with chemotherapy (HR:0.77, 95% CI:0.48-1.24, p = 0.2812 ), estimated 1-year overall survival rates were 55% and 46%, and 3-year overall survival rates were 17% and 10%, respectively. Conclusion. When the outcome caused by competing risk exists, the corresponding competing risk model method should be adopted to eliminate the bias caused by the classic survival analysis.

The CRISPR/Cas9 system has been used in a wide range of applications in the production of gene-edited animals and plants. Most efforts to insert genes have relied on homology-directed repair (HDR)-mediated integration, but this strategy remains inefficient for the production of gene-edited livestock, especially monotocous species such as cattle. Although efforts have been made to improve HDR efficiency, other strategies have also been proposed to circumvent these challenges. Here we demonstrate that a homology-mediated end-joining (HMEJ)-based method can be used to create gene-edited cattle that displays precise integration of a functional gene at the ROSA26 locus. We found that the HMEJ-based method increased the knock-in efficiency of reporter genes by eightfold relative to the traditional HDR-based method in bovine fetal fibroblasts. Moreover, we identified the bovine homology of the mouse Rosa26 locus that is an accepted genomic safe harbor and produced three live-born gene-edited cattle with higher rates of pregnancy and birth, compared with previous work. These gene-edited cattle exhibited predictable expression of the functional gene natural resistance-associated macrophage protein-1 (NRAMP1), a metal ion transporter that should and, in our experiments does, increase resistance to bovine tuberculosis, one of the most detrimental zoonotic diseases. This research contributes to the establishment of a safe and efficient genome editing system and provides insights for gene-edited animal breeding.

Background The prediction of potential drug-target interactions (DTIs) not only provides a better comprehension of biological processes but also is critical for identifying new drugs. However, due to the disadvantages of expensive and high time-consuming traditional experiments, only a small section of interactions between drugs and targets in the database were verified experimentally. Therefore, it is meaningful and important to develop new computational methods with good performance for DTIs prediction. At present, many existing computational methods only utilize the single type of interactions between drugs and proteins without paying attention to the associations and influences with other types of molecules. Methods In this work, we developed a novel network embedding-based heterogeneous information integration model to predict potential drug-target interactions. Firstly, a heterogeneous multi-molecuar information network is built by combining the known associations among protein, drug, lncRNA, disease, and miRNA. Secondly, the Large-scale Information Network Embedding (LINE) model is used to learn behavior information (associations with other nodes) of drugs and proteins in the network. Hence, the known drug-protein interaction pairs can be represented as a combination of attribute information (e.g. protein sequences information and drug molecular fingerprints) and behavior information of themselves. Thirdly, the Random Forest classifier is used for training and prediction. Results In the results, under the five-fold cross validation, our method obtained 85.83% prediction accuracy with 80.47% sensitivity at the AUC of 92.33%. Moreover, in the case studies of three common drugs, the top 10 candidate targets have 8 (Caffeine), 7 (Clozapine) and 6 (Pioglitazone) are respectively verified to be associated with corresponding drugs. Conclusions In short, these results indicate that our method can be a powerful tool for predicting potential drug-target interactions and finding unknown targets for certain drugs or unknown drugs for certain targets.

Drug-disease association is an important piece of information which participates in all stages of drug repositioning. Although the number of drug-disease associations identified by high-throughput technologies is increasing, the experimental methods are time consuming and expensive. As supplement to them, many computational methods have been developed for an accurate in silico prediction for new drug-disease associations. In this work, we present a novel computational model combining sparse auto-encoder and rotation forest (SAEROF) to predict drug-disease association. Gaussian interaction profile kernel similarity, drug structure similarity and disease semantic similarity were extracted for exploring the association among drugs and diseases. On this basis, a rotation forest classifier based on sparse auto-encoder is proposed to predict the association between drugs and diseases. In order to evaluate the performance of the proposed model, we used it to implement 10-fold cross validation on two golden standard datasets, Fdataset and Cdataset. As a result, the proposed model achieved AUCs (Area Under the ROC Curve) of Fdataset and Cdataset are 0.9092 and 0.9323, respectively. For performance evaluation, we compared SAEROF with the state-of-the-art support vector machine (SVM) classifier and some existing computational models. Three human diseases (Obesity, Stomach Neoplasms and Lung Neoplasms) were explored in case studies. As a result, more than half of the top 20 drugs predicted were successfully confirmed by the Comparative Toxicogenomics Database(CTD database). This model is a feasible and effective method to predict drug-disease correlation, and its performance is significantly improved compared with existing methods.

MotivationPIWI proteins and Piwi-Interacting RNAs (piRNAs) are commonly detected in human cancers, especially in germline and somatic tissues, and correlates with poorer clinical outcomes, suggesting that they play a functional role in cancer. As the problem of combinatorial explosions between ncRNA and disease exposes out gradually, new bioinformatics methods for large-scale identification and prioritization of potential associations are therefore of interest. However, in the real world, the network of interactions between molecules is enormously intricate and noisy, which poses a problem for efficient graph mining. This study aims to make preliminary attempts on bionetwork based graph mining.ResultsIn this study, we present a method based on graph attention network to identify potential and biologically significant piRNA-disease associations (PDAs), called GAPDA. The attention mechanism can calculate a hidden representation of an association in the network based on neighbor nodes and assign weights to the input to make decisions. In particular, we introduced the attention-based Graph Neural Networks to the field of bio-association prediction for the first time, and proposed an abstract network topology suitable for small samples. Specifically, we combined piRNA sequence information and disease semantic similarity with piRNA-disease association network to construct a new attribute network. In the experiment, GAPDA performed excellently in five-fold cross-validation with the AUC of 0.9038. Not only that, but it still has superior performance compared to methods based on collaborative filtering and attribute features. The experimental results show that GAPDA ensures the prospect of the graph neural network on such problems and can be an excellent supplement for future biomedical research.Contactzhuhongyou@ms.xjb.ac.cn;leiwang@ms.xjb.ac.cnSupplementary informationSupplementary data are available at Bioinformatics online.

Identification of drug-disease association is crucial for drug development and reposition. However, discovering drugs which are associated with diseases from in vitro testing is costly and time-consuming. Accumulating evidence showed that computational approaches can complement biological and clinical experiments for this identification task. In this work, we propose a novel computational method Node2Bio for predicting drug-disease associations using a highly efficient biomolecular network representation model. Specifically, we first construct a large-scale biomolecular association network (BAN) by integrating the associations among drugs, diseases, proteins, miRNAs and lncRNAs. Then, the network embedding model node2vec is used to extract network behavior features of drug and disease nodes. Finally, the feature vectors are taken as inputs for the XGboost classifier to predict potential drug-disease associations. To evaluate the prediction performance of the proposed method, five-fold cross-validation tests are performed on a widely used SCMFDD-S dataset. The experimental results demonstrate that our method achieves competitive performance with a high AUC value of 0.8569, which suggests that our method is a useful tool for identification of drug-disease associations.

Xue-Lian Zhang,1 Ming-Xia Yuan,1 Gang Wan,2 Guang-Ran Yang,1 Dong-Mei Li,3 Han-Jing Fu,1 Liang-Xiang Zhu,1 Rong-Rong Xie,1 Jian-Dong Zhang,4 Yu-Jie Lv,5 Yu-Ling Li,6 Xue-Ping Du,7 Zi-Ming Wang,8 Xue-Li Cui,9 De-Yuan Liu,10 Ying Gao,11 Shu-Yan Cheng,12 Qian Wang,13 Yu Ji,14 Guang-Wei Li,15,16 Shen-Yuan Yuan1 1Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Medical Records and Statistics Department, Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China; 3Clinical and Translational Science Institute, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA; 4Department of General Practice, Jinsong Community Health Service Center, Beijing, People’s Republic of China; 5Department of General Practice, Cuigezhuang Community Health Service Center, Beijing, People’s Republic of China; 6Department of General Practice, Xinjiekou Community Health Service Center, Beijing, People’s Republic of China; 7Department of General Practice, Yuetan Community Health Service Center of Fuxing Hospital, Capital Medical University, Beijing, People’s Republic of China; 8Department of General Practice, Jiangtai Community Health Service Center, Beijing, People’s Republic of China; 9Department of General Practice, Sanlitun Community Health Service Center, Beijing, People’s Republic of China; 10Department of General Practice, Zuojiazhuang Community Health Service Center, Beijing, People’s Republic of China; 11Department of General Practice, The First People’s Hospital of Chongwen District, Beijing, People’s Republic of China; 12Department of General Practice, Balizhuang Community Health Service Center, Beijing, People’s Republic of China; 13Department of General Practice, Majiapu Community Health Service Center, Beijing, People’s Republic of China; 14Department of Endocrinology, Beijing Aerospace General Hospital, Beijing, People’s Republic of China; 15Department of Endocrinology, China-Japan Friendship Hospital, Beijing, People’s Republic of China; 16Center of Endocrinology and Cardiovascular Disease, Department of Endocrinology, National Center of Cardiology and Fuwai Hospital, Beijing, People’s Republic of China Objective: It is well known that diabetic kidney disease is a risk factor for cardiovascular diseases (CVD) in patients with type 2 diabetes mellitus (T2DM). In this study, the effects of urine albumin excretion rate (AER) and estimated glomerular filtration rate (eGFR) on CVD outcomes were analyzed in a population of T2DM. Methods: The study was carried out using recorded information of a cohort study. A total of 1,914 patients with T2DM with no prevalent CVD were enrolled in an 8 years prospective study and received multifactorial intervention. The risk of CVD outcomes was assessed according to chronic kidney disease staging, which was categorized using AER (mg/d) and eGFR (mL/min/1.73 m2). The effects of AER and eGFR on risk of CVD onset were also analyzed. Results: During the follow-up period (median 6.8 years), 71 CVD events occurred. At baseline, those with AER ≥300 mg/d and coexisting eGFR 60–89 mL/min/ 1.73 m2 or

INTRODUCTION Breast reconstruction is an integral part of breast cancer management with the aim of restoring a breast to its natural form. There is increasing awareness among women that it is a safe procedure and its benefits extend beyond aesthetics. Our aim was to establish the rate of breast reconstruction and provide an overview of the patients who underwent breast reconstruction at National University Hospital (NUH), Singapore. METHODS We evaluated factors that impact a patient's decision to proceed with breast reconstruction, such as ethnicity, age, time and type of implant. We retrospectively reviewed the medical records of women who had breast cancer and underwent breast surgery at NUH between 2001 and 2010. RESULTS The breast reconstruction rate in this study was 24.3%. There were 241 patients who underwent breast reconstruction surgeries (including delayed and immediate procedures) among 993 patients for whom mastectomies were done for breast cancer. Chinese patients were the largest ethnic group who underwent breast reconstruction after mastectomy (74.3%). Within a single ethnic patient group, Malay women had the largest proportion of women undergoing breast reconstruction (60.0%). The youngest woman in whom cancer was detected in our study was aged 20 years. Malay women showed the greatest preference for autologous tissue breast reconstruction (92.3%). The median age at cancer diagnosis of our cohort was 46 years. CONCLUSION We noted increases in the age of patients undergoing breast reconstruction and the proportion of breast reconstruction cases over the ten-year study period.

Background: Our previous studies have shown that Tongxinluo (TXL), a compound Chinese medicine, can decrease myocardial ischemia-reperfusion injury, protect capillary endothelium function, and lessen cardiac ventricle reconstitution in animal models. The aim of this study was to illuminate whether TXL can improve hypercholesterolemia-impaired heart function by protecting artery endothelial function and increasing microvascular density (MVD) in heart. Furthermore, we will explore the underlying molecular mechanism of TXL cardiovascular protection. Methods: After intragastric administration of TXL (0.1 ml/10 g body weight) to C57BL/6J wild-type mice (n = 8) and ApoE-／- mice (n = 8), total cholesterol, high-density lipoprotein-cholesterol, very-low-density lipoprotein (VLDL)-cholesterol, triglyceride, and blood glucose levels in serum were measured. The parameters of heart rate (HR), left ventricular diastolic end diameter, and left ventricular systolic end diameter were harvested by ultrasonic cardiogram. The left ventricular ejection fraction, stroke volume, cardiac output, and left ventricular fractional shortening were calculated. Meanwhile, aorta peak systolic flow velocity (PSV), end diastolic flow velocity, and mean flow velocity (MFV) were measured. The pulsatility index (PI) and resistant index were calculated in order to evaluate the vascular elasticity and resistance. The endothelium-dependent vasodilatation was evaluated by relaxation of aortic rings in response to acetylcholine. Western blotting and real-time quantitative reverse transcription polymerase chain reaction were performed for protein and gene analyses of vascular endothelial growth factor (VEGF). Immunohistochemical detection was performed for myocardial CD34 expression. Data in this study were compared by one-way analysis of variance between groups. A value of P < 0.05 was considered statistically significant. Results: Although there was no significant decrease of cholesterol level (F = 2.300, P = 0.240), TXL inhibited the level of triglyceride and VLDL (F = 9.209, P = 0.024 and F = 9.786, P = 0.020, respectively) in ApoE-／- mice. TXL improved heart function of ApoE-／- mice owing to the elevations of LVEF, SV, CO, and LVFS (all P < 0.05). TXL enhanced aortic PSV and MFV (F = 10.774, P = 0.024 and F = 11.354, P = 0.020, respectively) and reduced PI of ApoE-／- mice (1.41 ± 0.17 vs. 1.60 ± 0.17; P = 0.037). After incubation with 10 μmol/L acetylcholine, the ApoE-／- mice treated with TXL aortic segment relaxed by 44% ± 3%, significantly higher than control group mice (F = 9.280, P = 0.040). TXL also restrain the angiogenesis of ApoE-／- mice aorta (F = 21.223, P = 0.010). Compared with C57BL/6J mice, the MVD was decreased in heart tissue of untreated ApoE-／- mice (54.0 ± 3.0/mm2 vs. 75.0 ± 2.0/mm2; F = 16.054, P = 0.010). However, TXL could significantly enhance MVD (65.0 ± 5.0/mm2 vs. 54.0 ± 3.0/mm2; F = 11.929, P = 0.020) in treated ApoE-／- mice. In addition, TXL obviously increased the expression of VEGF protein determined by Western blot (F = 20.247, P = 0.004). Conclusions: TXL obviously improves the ApoE-／- mouse heart function from different pathways, including reduces blood fat to lessen atherosclerosis; enhances aortic impulsivity, blood supply capacity, and vessel elasticity; improves endothelium-dependent vasodilatation; restraines angiogenesis of aorta-contained plaque; and enhances MVD of heart. The molecular mechanism of MVD enhancement maybe relate with increased VEGF expression. Key words: Heart Function; Microvascular Protection; Tongxinluo

As important test equipment to carry out full-scale structure testing and components failure mechanisms research, super structural testing machines have developed rapidly all over the world in recent years. The authors of this paper investigated, compared and analyzed the construction and the development trends of super structural testing machines in China. The test functions, the test space, the maximum tonnage and other technical indexes of super structural testing machines, which have been built in China, were described. The functions and the typical tests of a multi-functional structure test loading system (40,000 kN) installed in the Beijing University of Technology were also discussed. The vibrations caused by the failure of brittle test pieces on this super structural testing machine were analyzed, and some suggestions to reduce the vibrations were given. It would be valuable for further development and the improvement of other super structural testing machines.

Background Endothelial microparticles (EMPs) are small vesicles released by endothelial cells (ECs); they are considered biomarkers for endothelial dysfunction and therapeutic targets in diabetes-related vascular disease. Sirtuins have also been shown to play important roles in diabetes by regulating endothelial dysfunction. However, the effect of sirtuin-incorporated EMPs on their parental ECs remains unknown. Aim The present study aims to investigate the diagnostic value of EMPs in diabetes and detect the protective effects of sirtuin 6 (Sirt6) mRNA -incorporated EMPs on endothelial dysfunction. Methods EMPs were prepared from cultured HUVECs and venous blood from patients with diabetes (n=10) and from healthy volunteers (n=6) after sequential centrifugation. Adv-Sirt6 or Sirt6 siRNA was used to alter Sirt6 expression. EC angiogenesis, inflammatory phenotypes, nitric oxide (NO) formation and eNOS phosphorylation were used to evaluate endothelial dysfunction. Results The levels of EMPs in diabetic patients and high glucose-cultured HUVECs are high, whereas Sirt6 expression in plasma and EMPs is low. EMPs generated from diabetic patients or high glucose-cultured HUVECs increase inflammatory chemokine release and blunt EC angiogenesis. Furthermore, EMPs enriched with Sirt6 mRNA induces EC angiogenesis, increases eNOS phosphorylation and impedes inflammatory chemokine release. Inhibition of Sirt6 mRNA expression in EMPs by siRNA hinders angiogenesis and eNOS phosphorylation but increases cellular inflammation. Conclusion The Sirt6 mRNA-carrying EMPs may ameliorate endothelial dysfunction in diabetic patients.

To investigate the expression of enzymes involved in chondroitin sulfate (CS) sulfation in the articular cartilage isolated from adult patients with osteoarthritis (OA) and Kashin-Beck disease (KBD), using normal adults as controls.Articular cartilage samples were collected from normal, OA and KBD adults aged 38-60 years old, and divided into three groups with six individual subjects in each group. The morphology and pathology grading of knee joint cartilage was examined by Safranin O staining. The localization and expression of enzymes involved in CS sulfation (CHST-3, CHST-11, CHST-12, CHST-13, carbohydrate (N-acetylgalactosamine 4-sulfate 6-O) sulfotransferase 15 - CHST-15, and uronyl 2-O-sulfotransferase - UST) were examined by immunohistochemical (IHC) staining and semi-quantitative analysis.Positive staining rates for anabolic enzymes CHST-3, CHST-12, CHST-15, and UST were lower in the KBD and OA groups than those in the control group. Meanwhile, reduced levels of CHST-11, and CHST-13 in KBD group were observed, in contrast to those in OA and control groups. The expressions of all six CS sulfation enzymes were less detected in the superficial and deep zones of KBD cartilage compared with control and OA cartilage.The reduced expression of the CS structure modifying sulfotransferases in the chondrocytes of both KBD and OA adult patients may provide explanations for their cartilage damages, and therapeutic targets for their treatment.

In the field of electromagnetic launch or other military research, the requirements for the power density of high-voltage capacitor charging power supply (CCPS) are increasing. The design of the cooling system becomes more difficult, especially in the intermittent operation mode, when the power supply exists transient heating process. As the main heating element of CCPS, the inverter unit is the key factor to influence the power density. In this paper, the main factors that influence the temperature rise of the device are analyzed, including the material and size of the heat sink. The rules between the above factors and the transient temperature rise are analyzed by Matlab simulation software. Then, the architecture model of inverter unit is established through ICEPAK software for simulation, which proves the accuracy of the regular. A basis for designing system level power supplies working in intermittent operating mode is provided through the transient thermal design of inverter unit’D The accuracy of the rule is verified through some load short circuit experiments with a 30-kW/6 kV charging power supply.

Liver fibrosis is the common pathological basis of all chronic liver diseases, and is the necessary stage for the progression of chronic liver disease to cirrhosis. As one of pathogenic factors, inflammation plays a predominant role in liver fibrosis via communication and interaction between inflammatory cells, cytokines, and the related signaling pathways. Damaged hepatocytes induce an increase in pro-inflammatory factors, thereby inducing the development of inflammation. In addition, it has been reported that inflammatory response related signaling pathway is the main signal transduction pathway for the development of liver fibrosis. The crosstalk regulatory network leads to hepatic stellate cell activation and proinflammatory cytokine production, which in turn initiate the fibrotic response. Compared with the past, the research on the pathogenesis of liver fibrosis has been greatly developed. However, the liver fibrosis mechanism is complex and many pathways involved need to be further studied. This review mainly focuses on the crosstalk regulatory network among inflammatory cells, cytokines, and the related signaling pathways in the pathogenesis of chronic inflammatory liver diseases. Moreover, we also summarize the recent studies on the mechanisms underlying liver fibrosis and clinical efforts on the targeted therapies against the fibrotic response.

A miniaturized medium- and long-range antenna is designed in this letter, using in microstrip arrays. This antenna works at 77GHz, which is used in the automotive radar system. The antenna consists of a medium-range array and a long-range array. The former is a $2\times 9$ planar array with low gain and wide beam, the latter is a $10\times 9$ planar array with high gain and narrow beam. These two arrays are switched by switching inside the chip. Both arrays are composed of a series of horizontal linear arrays. Each linear array includes 9 microstrip patches, which are placed interlaced. This structure makes the system achieve the bandwidth of 76-79GHz and a small volume, which resulting in a high range resolution and easy integration.

Background. Neck circumference (NC) was found to be related to the risk factors of cardiovascular disease. However, the effects of NC on cardiovascular disease are still controversial. A prospective study of Chinese patients with type 2 diabetes was performed to evaluate the relationship between NC and cardiovascular disease. Methods. A multicenter prospective study with eight-year follow-up was conducted in Beijing communities. Cardiovascular events were defined as myocardial infarction, unstable angina pectoris, hospitalization for heart failure, coronary revascularization, cardiac death, stroke, transient ischemic attack, and cerebral hemorrhage. Results. A total of 3,009 diabetic patients were recruited. Following an eight-year follow-up, 211 patients with cardiovascular events (105 in men and 106 in women) were identified. All patients were categorized into two groups according to the upper quartile of NC (43 cm in men and 39 cm in women). The prevalence of cardiovascular events in men with an NC >43 cm (16.48%) was higher than that in the group with an NC p=0.007). The prevalence of cardiovascular events in women with the NC >39 cm (10.67%) was higher compared to the group with NC p=0.004). The longitudinal prevalence of cardiovascular events in groups with different NC increased with the increasing duration of follow-up (p<0.001). Cox regression analysis showed that higher NC was associated with the occurrence of cardiovascular events after adjusting for confounding variables (adjusted HR = 2.305 (1.535–3.460)). Conclusions. NC was associated with the occurrence of cardiovascular events in type 2 diabetes in Chinese communities, and greater NC may increase the risk of cardiovascular events by about 2.3-fold.

With the explosive growth of protein sequences generated by biological experiment in the post-genomic era, more and more researchers pay particular attention to the development of approaches for the prediction of protein interactions and functions from sequences. In addition, elucidation of the self-interacting proteins (SIPs) play significant roles in the understanding of cellular process and cell functions. This work explored the use of deep learning model, Long-Short Term Memory (LSTM), for the prediction of SIPs directly from their primary sequences. More specifically, the protein sequence is firstly converted to Position Specific Scoring Matrix (PSSM) by exploiting the Position Specific Iterated BLAST method, in which the evolutionary information is contained. Then, the wavelet transform algorithm is used on PSSM to extract discriminative feature. Finally, based on the knowledge of known self-interacting and non-interacting proteins, LSTM model is trained to recognize SIPs. The prediction performance of the proposed method is evaluated on yeast dataset, which achieved an accuracy rate of 92.21%. The experimental results show that the proposed method outperforms other six existing methods for SIPs prediction. Achieved results demonstrate that the proposed model is an effective architecture with SIPs detection, and would provide a useful supplement for the proteomics research.

MicroRNAs (miRNAs) play critical roles in the development and progression of various diseases. However, traditional experimental approaches are difficult to detect potential human miRNA-disease associations from the vast amount of biological data. Therefore, computational techniques could be of significant value. In this work, we proposed a miRNA sequence similarity calculation model (MISSIM) to large-scale predict miRNA-disease associations by combined Chaos Game Representation (CGR) with Broad Learning System (BLS). In the five-cross-validation experiment, MISSIM achieved ACC of 0.8424 on the HMDD.

The fabrication of thin films comprising ordered nanowire assemblies with emerging, precisely defined properties and adjustable functionalities enables highly integrated technologies in the fields of microelectronics and micro system technology, as well as for efficient power generation, storage, and utilization. Shear force, theoretically, is deemed the most promising method for obtaining in-plane, uniaxial thin films comprising nanowires. The success depends largely on the assembly process, and uniform structural control throughout multiple length scales can be achieved only if a rational strategy is executed. Here, we report that in shearing processes dopants such as lyotropic cellulose nanorods can give rise to the uniaxial alignment of V2O5·nH2O nanowires. Our systematic study indicates that this finding, namely, the nanocombing effect, can be a general principle for the continuous production of uniaxial thin films comprising densely packed nanowires varying in chemical composition and aspect ratios....

This work is mainly done by too many manual operations in the aircraft structure design process resulting in heavy workload, low efficiency and quality, non-standardized processes and procedures. A top-down associated design method employing the template parametric technology is proposed here in order to improve the quality of design and efficiency of aircraft wing structure at the preliminary design stage. The appropriate parametric tool is chosen and the rapid design system of knowledgedriven aircraft wing structure is developed. First, a skeleton model of aircraft wing structure is rapidly built up through the template encapsulated design knowledge. Associated design is then introduced to realize the association between the typical structural part and skeleton model. Finally, the related elements are referenced from skeleton model, and a typical structural part reflecting an automatic response for design changes of the upstream skeleton model is quickly constructed within the template. The rapid design system proposed and developed in this paper is able to formalize the design standardization of aircraft wing structure and thus the rapid generation of different aircraft wing structure programs and achieve the structural design knowledge reuse as well.

To investigate the effects of educational attainment on glucose control and morbid events in patients with type 2 diabetes in Beijing communities.In this prospective multi-center study, 2866 type 2 diabetes patients receiving integrated care from 15 Beijing urban communities were investigated. Educational attainment was categorized into three levels: low, medium, and high. After a 42-month management, glucose control parameters and morbid events were analyzed.At baseline, the percentages of patients with good glucose control (HbA1c ≤ 7.0%) in the low, medium and high educational groups were 49.09%, 54.82% and 62.59%, respectively (P0.001). After the 42-month management, fasting plasma glucose and HbA1c values were the highest in the low educational group (7.51 ± 2.05 mmol/l and 7.20 ± 1.27%, respectively). Percentages of patients with good glucose control in the three groups were 49.6%, 55.83% and 67.23%, respectively, and the incidences of combined morbid events were 4.5%, 2.4% and 1.5%, respectively. Cox regression analysis showed that educational level was related to the incidence of combined morbid events (medium level, HR=0.572; high level, HR=0.351; P0.05).Educational level was associated with long-term glucose control, and seemed to be related to the incidence of combined morbid events in people with type 2 diabetes.

As the basic visual morphological characteristics of molten pool, contour extraction plays an important role in on-line monitoring of welding quality. The limitations of traditional edge detection algorithms make deep learning play a more important role in the task of target segmentation. In this paper, a molten pool visual sensing system in a tungsten inert gas welding (TIG) process environment is established and the corresponding molten pool image data set is made. Based on a residual network, a multi-scale feature fusion semantic segmentation network Res-Seg is designed. In order to further improve the generalization ability of the network model, this paper uses deep convolutional generative adversarial networks (DCGAN) to supplement the molten pool data set, then performs color and morphological data enhancement before network training. By comparing with other traditional edge detection algorithms and semantic segmentation network, it is verified that the scheme has high accuracy and robustness in the actual welding environment. Moreover, a back propagation (BP) neural network is used to predict the weld width, and a fitting test is carried out for the pixel width of the molten pool and its corresponding actual weld width. The average testing error is less than 0.2 mm, which meets the welding accuracy requirements.

Identifying the factors predicting the suitable habitats of invasive alien plants (IAPs) and how these suitable habitats are affected by climate change are important for taking measures to limit the spread of IAPs in China. In this study, an ensemble forecasting approach is used to accurately evaluate the relationships between IAPs distribution and the environmental variables, and to simulate the range shifts of the eleven invasive species under different climate scenarios. All of the AUC and TSS values from ensemble forecasting models are above 0.9, indicating its perfect ability to distinguish actual suitable and unsuitable habitat. Our models show that annual mean temperature and temperature seasonality have strong correlations with alien weeds distribution. The results indicate that all the 11 IAPs ranges will expand northward, which may be due to global climate warming. The prediction shows that a more aggressive climate scenario will be more conducive to the northward expansion of IAPs. The results of this study can provide a new insight for policy makers to monitor and control IAPs.

We investigated the prognostic significance of metabolic risk scores and aspirin with respect to cerebrovascular events.A total of 25 communities of diabetic patients were enrolled in Beijing Community Diabetes Study (BCDS) from 2008. 3413 patients with T2DM in BCDS have complete screening data, including blood glucose, blood pressure, lipid profiles and anti-platelet therapy, which were assigned metabolic score (MS) and add up to the total metabolic score (TMS). According to the total metabolic score (TMS), the patients were divided into four equal groups: Group 1 (24 TMS 40), Group 2 (40 TMS 47), Group 3 (47 TMS 55) and Group 4 (55 TMS 87). After 96 months, patients were followed-up to assess the long-term effects of the multifactorial interventions.During 96-months follow-up, a total of 91 cerebrovascular events occurred, including acute cerebral infarction, acute cerebral hemorrhage and transient ischemic attack (TIA). The incidence of cerebrovascular events was higher in the Group 4 than in the Group 1. In Cox multivariate analyses, there are significant differences in incidences of cerebral infarction events among the four groups during the 96-months follow-up. Cox proportional hazards analysis revealed that, HbA1c (p ≤ 0.001), systolic pressure (p ≤ 0.001), aspirin free treatment (P = 0.0023) are independent predictor for cerebrovascular events in diabetic patients.This study indicates that total metabolic score (TMS) influences the incidence of cerebrovascular events in diabetic patients. In addition to good control of blood glucose, blood pressure and lipid profiles, anti-platelet therapy is important for the prevention of cerebrovascular events in T2DM.ChiCTR-TRC-13003978, ChiCTR-OOC-15006090.

This report presents a silver paste, containing new developed Te-glass, with improved contact resistance on mono-crystalline silicon wafer with ultra-low doped emitters. Its FF and efficiency increase 0.5 and 0.05% respectively. The paste's contact resistivity is around 2 mOhm cm2 on 110 Ohm/sq wafer. The efficiency of the paste is quite stable when firing peak temperature varies from 740 °C to 780 °C. The SEM image reveals that the better contact resistance of the paste is from direct contact between silicon wafer and silver electrode.

In this work, we develop a tractable modeling paradigm for outage probability on device-to-device (D2D) enhanced K-tier heterogeneous cellular network (HCN). To offload traffic in the HCNs, mobile user equipments (UEs) can engage in D2D communications, whose activity is determined by a carrier sensing multiple access (CSMA) scheme. Due to the limited transmit power, the UEs employ a truncated channel inversion power control policy with a cutoff threshold and we show that there exists an optimal threshold for maximizing the probability of success D2D communication. We obtain the expressions for truncation outage probability and signal-to- interference-plus-noise-ratio (SINR) outage probability in the D2D enhanced HCNs. In addition, we evaluate how the D2D communications impact on the system performance.

Objective: To assess whether multifactorial interventions have long-term effects on the risk of diabetes-related macrovascular complications in patients with type 2 diabetes mellitus living in urban communities of Beijing. Design, setting and participants: A total of 2926 patients with type 2 diabetes from 15 community health centers were divided into a diabetes mellitus (DM) group (n=824), a hypertension (HTN) group (n=1267), and a cardiovascular disease (CVD) group (n=835). By applying Framingham risk scores (FRS), patients in the 3 groups were subdivided into low (FRS 20%) Framingham risk strata. After 48 months, patients were followed-up to assess the long-term effects of the multifactorial interventions. Results: At baseline, the patients’ mean neck circumference (NC) was significantly higher in the HTN and CVD groups than in the DM group (P

Based on the smart home and facial expression recognition, this paper presents a cognitive emotional model for eldercare robot. By combining with Gabor filter, Local Binary Pattern algorithm (LBP) and k-Nearest Neighbor algorithm (KNN) are facial emotional features extracted and recognized. Meanwhile, facial emotional features put influence on robot’s emotion state, which is described in AVS emotion space. Then the optimization of smart home environment on the cognitive emotional model is specially analyzed using simulated annealing algorithm (SA). Finally, transition probability from any emotional state to a state of basic emotions is obtained based on the cognitive reappraisal strategy and Euclidean distance. The simulation and experiment have tested and verified the effective in reducing negative emotional state.

Diabetic retinopathy (DR) is a common and devastating microvascular complication of diabetes and a major cause of acquired blindness in young adults. Advanced glycation end products (AGEs) accumulated under hyperglycemic conditions are thought to play an important role in the pathogenesis of DR. AGEs can exert their deleterious effects by acting directly to induce aberrant crosslinking of extracellular matrix proteins, to increase vascular stiffness, altering vascular structure and function. Moreover, AGEs binding to the receptor for AGEs (RAGE) evokes intensive intracellular signaling cascades that leading to endothelial dysfunction, elaboration of key proinflammatory cytokines and proangiogenic factors, mediating pericyte apoptosis, vascular inflammation and angiogenesis, as well as breakdown of the inner blood-retinal barrier (BRB), the end result of all these events is damage to the neural and vascular components of the retina. Elucidation of AGE-induced mechanisms will help in the understanding of the complex cellular and molecular pathogenesis associated with DR. Novel anti-AGEs agents or AGE crosslink “breakers” are being investigated, it is hoped that in next few years, some of these promising therapies will be successfully applied in clinical context, aiming to reduce the major economical and medical burden caused by DR.

Introduction: Fever of unknown origin (FUO) is a common initial presentation leading to a diagnostic challenge. Patient concerns: A 3-month history of moderate-to-high fever was reported in an otherwise healthy 54-year-old man. Enhanced computed tomography (CT) scans of his chest showed a remarkable progressive enlargement of bilateral cervical, supraclavicular, hilar, and mediastinal lymph nodes within 2 weeks. Bronchofibroscopy manifested obvious luminal stenosis with swelling, thick pale mucosa, and disappearing of structures of trachea cricoid cartilage, followed by a 18F-fluorodeoxyglucose positron-emission tomography–computed tomography (18F-FDG PET/CT) with intense symmetric FDG uptake in larynx, tracheobronchial tree, and hilar, mediastinal, and axillary lymph nodes being demonstrated. Diagnosis: A diagnosis of relapsing polychondritis (RP) was finally reached. Interventions: The patient received methylprednisolone 40 mg daily with a gradual tapering in a 4-month follow-up. Outcomes: The patient experienced no relapse of fever and lymph nodes enlargement in the 4-month follow-up. Lessons: Even though long-term fever with multiple lymphadenectasis usually lead to a diagnosis of lymphoma, the bronchoscopic features and evidence from 18F-FDG PET/CT in this case were much more approximate to RP, indicating an importance of a sensible differential diagnosis of RP in patients who present with nonspecific features such as FUO and lymph nodes enlargement. Keeping a high index of clinical suspicion in these patients can help recognize uncommon of RP and promote diagnosis and treatment. Our case highlights the significance of 18F-FDG PET/CT in helping reaching the diagnosis of RP in this condition. This report provides new data regarding the diagnostic difficulties of this rare type of autoimmune disease, and further investigations are needed as cases accumulate.

Objective The aim of this article is to investigate the prevalence, clinical presentation, prenatal management, and prognosis of mirror syndrome associated with twin–twin transfusion syndrome (TTTS) treated by amnioreduction or selective fetocide. Method A retrospective study of twin pregnancies with TTTS was conducted. The prevalence of mirror syndrome, defined as severe maternal edema related to fetal hydrops and placental edema, was calculated for TTTS, and data on clinical characteristics, treatment, and outcomes of the patients were reviewed. Results We observed mirror syndrome in 4.85% (5/103) of pregnancies with TTTS and 26.32% (5/19) of pregnancies with TTTS Stage IV. Most cases (4/5) of mirror syndrome associated with TTTS were diagnosed before 24 weeks of gestation. The patients manifested edema, anemia, hemodilution, and hypoproteinemia (5/5); proteinuria (4/5); complicated postpartum hemorrhage (4/5); and pulmonary edema and congestive heart failure (2/5). Maternal hemoglobin, hematocrit, and plasma protein dropped after amnioreduction. The perinatal survival rate at 28 days was 28.57% (2/7), and only one infant born after selective feticide survived beyond 18 months. Conclusion TTTS carries a high risk of mirror syndrome, a disease with significant materno-fetal mortality and morbidity. Amnioreduction alone or with selective feticide in mirror syndrome may transiently aggravate anemia and hemodilution and lead to severe maternal complications. © 2014 John Wiley & Sons, Ltd.

周期性亚波长孔阵列的异常透射性质在亚波长光电器件设计中具有重要意义。两层或更多膜层上周期孔阵列结构，由于层之间电磁场的相互作用可以导致新的光学性质。利用时域有限差分方法理论研究了带有矩形孔阵列的Au-介质-Au多层膜的透射特性。结果表明：该结构在近红外波段的透射谱存在多个透射峰，并且透射峰的数量、位置和强度可以通过改变结构的几何参数和介质膜的材料进行调控。详细分析了介质膜的厚度和折射率、孔阵列的周期、矩形孔的边长等因素对多层膜矩形孔阵列透射谱的影响，为利用多个表面等离子共振设计多波长控制器件提供了一定的参考。