Author: "Wen, Xin" / Topic: business.industry - Searchworks@Jio Institute Digital Library Search Results

294 results on '"Wen, Xin"'

1. Principal Component Analysis for Big Data

Author: Qiang Sun, Ziwei Zhu, Wen-Xin Zhou, and Jianqing Fan
Subjects: FOS: Computer and information sciences, business.industry, Computer science, Dimensionality reduction, 05 social sciences, Big data, Nonlinear dimensionality reduction, Mixture model, Machine learning, computer.software_genre, 01 natural sciences, Methodology (stat.ME), 010104 statistics & probability, ComputingMethodologies_PATTERNRECOGNITION, Ranking, Analytics, 0502 economics and business, Principal component analysis, Statistical inference, Artificial intelligence, 0101 mathematics, business, computer, Statistics - Methodology, 050205 econometrics
Abstract: Big data is transforming our world, revolutionizing operations and analytics everywhere, from financial engineering to biomedical sciences. The complexity of big data often makes dimension reduction techniques necessary before conducting statistical inference. Principal component analysis, commonly referred to as PCA, has become an essential tool for multivariate data analysis and unsupervised dimension reduction, the goal of which is to find a lower dimensional subspace that captures most of the variation in the dataset. This article provides an overview of methodological and theoretical developments of PCA over the last decade, with focus on its applications to big data analytics. We first review the mathematical formulation of PCA and its theoretical development from the view point of perturbation analysis. We then briefly discuss the relationship between PCA and factor analysis as well as its applications to large covariance estimation and multiple testing. PCA also finds important applications in many modern machine learning problems, and we focus on community detection, ranking, mixture model and manifold learning in this paper., review article, in press with Wiley StatsRef
Published: 2022

2. Fatigue life prediction for the main spar with wrinkle defects of a wind turbine blade

Author: Fangai Yu, Wen Xin, Xueyan Zhang, and Bo Zhou
Subjects: Materials science, Turbine blade, business.industry, Mechanical Engineering, Structural engineering, law.invention, Mechanics of Materials, law, medicine, General Materials Science, Spar, medicine.symptom, business, Wrinkle
Published: 2021
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3. MicroRNA-328-3p facilitates the progression of gastric cancer via KEAP1/NRF2 axis

Author: Ruicheng Yan, Jiasheng Liu, Wen-Xin Dao, Yong-Bin Zheng, Wenhong Deng, Jianfei Luo, and Zhe Xiao
Subjects: 0301 basic medicine, Small interfering RNA, NF-E2-Related Factor 2, medicine.disease_cause, Biochemistry, 03 medical and health sciences, Stomach Neoplasms, microRNA, medicine, Humans, Viability assay, Kelch-Like ECH-Associated Protein 1, 030102 biochemistry & molecular biology, business.industry, Cancer, General Medicine, medicine.disease, KEAP1, MicroRNAs, 030104 developmental biology, Apoptosis, Cancer cell, Disease Progression, Cancer research, business, Oxidative stress, Signal Transduction
Abstract: Gastric cancer is a common lethal malignancy and causes great cancer-related mortality worldwide. MicroRNA (miR)-328-3p is implicated in the progression of various human cancers; however, its role and mechanism in the progression of gastric cancer remain unclear.Human gastric cancer cells were incubated with miR-328-3p mimic, inhibitor or the matched negative control. Cell viability, colony formation, migrative and invasive capacity, cell apoptosis and oxidative stress were measured. To clarify the involvement of nuclear factor-E2-related factor 2 (NRF2) and kelch-like ECH-associated protein 1 (KEAP1), small interfering RNA was used. miR-328-3p was upregulated in human gastric cancer cells and tissues, and its level positively correlated with the progression of gastric cancer. miR-328-3p promoted cell viability, colony formation, migration and invasion, thereby facilitating the progression of gastric cancer. miR-328-3p mimic reduced, while miR-328-3p inhibitor increased apoptosis and oxidative stress of human gastric cancer cells. Mechanistically, miR-328-3p upregulated NRF2 via targeting KEAP1to attenuate excessive free radical production and cell apoptosis. miR-328-3p functions as an oncogenic gene and inhibiting miR-328-3p may help to develop novel therapeutic strategies of human gastric cancer.
Published: 2021
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4. The interplay of students’ regulation learning and their collective decision-making performance in a SSI context

Author: Ying Shao Hsu and Wen Xin Zhang
Subjects: Knowledge management, business.industry, 05 social sciences, 050301 education, 0501 psychology and cognitive sciences, Collaborative learning, Context (language use), Psychology, business, 0503 education, 050104 developmental & child psychology, Education, Group decision-making
Abstract: This study designed a decision-making learning module to engage students in collective decision-making in a collaborative learning environment. The purpose of this study was to explore the interpla...
Published: 2021
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5. Identification of Potential Biomarkers using Improved Ranked Guided Iterative Feature Elimination

Author: Wen Xin Ng and Weng Howe Chan
Subjects: Computer science, business.industry, Pattern recognition, Context (language use), Feature selection, Filter (signal processing), Identification (information), ComputingMethodologies_PATTERNRECOGNITION, Feature (computer vision), Classifier (linguistics), Redundancy (engineering), Artificial intelligence, business, Selection (genetic algorithm)
Abstract: In healthcare, biomarkers serve an important role in disease classification. Many existing works are focusing in identifying potential biomarkers from gene expression. Moreover, the large number of redundant features in a high dimensional dataset such as gene expression would introduce bias in the classifier and reduce the classifierâ€™s performance. Embedded feature selection methods such as ranked guided iterative feature elimination have been widely adopted owing to the good performance in identification of informative features. However, method like ranked guided iterative feature elimination does not consider the redundancy of the features. Thus, this paper proposes an improved ranked guided iterative feature elimination method by introducing an additional filter selection based on minimum redundancy maximum relevance to filter out redundant features and maintain the relevant feature subset to be ranked and used for classification. Experiments are done using two gene expression datasets for prostate cancer and central nervous system. The performance of the classification is measured in terms of accuracy and compared with existing methods. Meanwhile, biological context verification of the identified features is done through available knowledge databases. Our method shows improved classification accuracy, and the selected genes were found to have relationship with the diseases.
Published: 2021
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6. A Tracking Registration Method for Augmented Reality Based on Multi-modal Template Matching and Point Clouds

Author: Wei-Ping Ma, Peng-Xia Cao, and Wen-Xin Li
Subjects: Computer science, business.industry, Applied Mathematics, Template matching, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Graphics processing unit, Point cloud, Iterative closest point, RANSAC, Computer Science Applications, Control and Systems Engineering, Robustness (computer science), Computer Science::Computer Vision and Pattern Recognition, Modeling and Simulation, Key frame, Computer vision, Augmented reality, Artificial intelligence, business
Abstract: In order to overcome the defects where the surface of the object lacks sufficient texture features and the algorithm cannot meet the real-time requirements of augmented reality, a markerless augmented reality tracking registration method based on multi-modal template matching and point clouds is proposed. The method first adapts the linear parallel multi-modal LineMod template matching method with scale invariance to identify the texture-less target and obtain the reference image as the key frame that is most similar to the current perspective. Then, we can obtain the initial pose of the camera and solve the problem of re-initialization because of tracking registration interruption. A point cloud-based method is used to calculate the precise pose of the camera in real time. In order to solve the problem that the traditional iterative closest point (ICP) algorithm cannot meet the real-time requirements of the system, Kd-tree (k-dimensional tree) is used under the graphics processing unit (GPU) to replace the part of finding the nearest points in the original ICP algorithm to improve the speed of tracking registration. At the same time, the random sample consensus (RANSAC) algorithm is used to remove the error point pairs to improve the accuracy of the algorithm. The results show that the proposed tracking registration method has good real-time performance and robustness.
Published: 2021
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7. Clinical characteristics and plasma antibody titer of patients with COVID-19 in Zhejiang, China

Author: Dan ying Qiu, Wen xin Li, Jing jing Cheng, Fei hang Ge, Lian peng Wu, Zhen Wang, Dong Chen, Wei Zhang, Wei ling Xiang, and Bingyu Chen
Subjects: Adult, Male, 0301 basic medicine, China, Convalescent plasma, Coronavirus disease 2019 (COVID-19), Antibodies, Viral, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 0302 clinical medicine, Correspondence, Humans, Medicine, General Pharmacology, Toxicology and Pharmaceutics, COVID-19 Serotherapy, Aged, Antibody titer, Clinical characteristics, General Veterinary, business.industry, Immunization, Passive, COVID-19, General Medicine, Middle Aged, Antibodies, Neutralizing, 030104 developmental biology, Immunoglobulin M, Immunoglobulin G, 030220 oncology & carcinogenesis, Immunology, Female, business
Abstract: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first affected humans in China on December 31, 2019 (Shi et al., 2020). Coronaviruses generally cause mild, self-limiting upper respiratory tract infections in humans, such as the common cold, pneumonia, and gastroenteritis (To et al., 2013; Berry et al., 2015; Chan et al., 2015). According to the Report of the World Health Organization (WHO)-China Joint Mission on COVID-19 (WHO, 2020), the case fatality rate of COVID-19 increases with age, while the rate among males is higher than that among females (4.7% and 2.8%, respectively). Since an effective vaccine and specific anti-viral drugs are still under development, passive immunization using the convalescent plasma (CP) of recovered COVID-19 donors may offer a suitable therapeutic strategy for severely ill patients in the meantime. So far, several studies have shown therapeutic efficacy of CP transfusion in treating COVID-19 cases. A pilot study first reported that transfusion of CP with neutralizing antibody titers above 1:640 was well tolerated and could potentially improve clinical outcomes through neutralizing viremia in severe COVID-19 cases (Chen et al., 2020). Immunoglobulin G (IgG) and IgM are the most abundant and important antibodies in protecting the human body from viral attack (Arabi et al., 2015; Marano et al., 2016). Our study aimed to understand the aspects of plasma antibody titer levels in convalescent patients, as well as assessing the clinical characteristics of normal, severely ill, and critically ill patients, and thus provide a basis for guiding CP therapy. We also hoped to find indicators which could serve as a reference in predicting the progression of the disease.
Published: 2020
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8. Saliency Detection via Manifold Ranking Based on Robust Foreground

Author: Peng-Xia Cao, Wen-Xin Li, Wei-Ping Ma, and Jin-Chuan Sun
Subjects: Convex hull, 0209 industrial biotechnology, Boosting (machine learning), business.industry, Computer science, Applied Mathematics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Corner detection, Regular polygon, Pattern recognition, 02 engineering and technology, Computer Science Applications, Improved performance, 020901 industrial engineering & automation, Binary segmentation, Control and Systems Engineering, Computer Science::Computer Vision and Pattern Recognition, Modeling and Simulation, Hull, 0202 electrical engineering, electronic engineering, information engineering, Manifold ranking, 020201 artificial intelligence & image processing, Artificial intelligence, business
Abstract: The graph-based manifold ranking saliency detection only relies on the boundary background to extract foreground seeds, resulting in a poor saliency detection result, so a method that obtains robust foreground for manifold ranking is proposed in this paper. First, boundary connectivity is used to select the boundary background for manifold ranking to get a preliminary saliency map, and a foreground region is acquired by a binary segmentation of the map. Second, the feature points of the original image and the filtered image are obtained by using color boosting Harris corners to generate two different convex hulls. Calculating the intersection of these two convex hulls, a final convex hull is found. Finally, the foreground region and the final convex hull are combined to extract robust foreground seeds for manifold ranking and getting final saliency map. Experimental results on two public image datasets show that the proposed method gains improved performance compared with some other classic methods in three evaluation indicators: precision-recall curve, F-measure and mean absolute error.
Published: 2020
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9. A Cohort Study on Associations between Fundus/intraocular Pressure Abnormality and Medical Check-up Items

Author: Dongying Yao, Changmin Ke, Juan Wang, Chu-na Zheng, Jianglin Wu, Xiaojuan Fang, Wen-Xin Luo, and Peiping Wang
Subjects: Adult, Male, Intraocular pressure, medicine.medical_specialty, genetic structures, Arteriosclerosis, Fundus Oculi, Blood Pressure, Hyperlipidemias, Fundus (eye), behavioral disciplines and activities, Cohort Studies, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Heart Rate, Risk Factors, Ophthalmology, Humans, Medicine, Physical Examination, Intraocular Pressure, Aged, Diabetic Retinopathy, Hematologic Tests, business.industry, Middle Aged, humanities, eye diseases, Sensory Systems, Cholesterol, Cross-Sectional Studies, Hypertension, Myopia, Degenerative, 030221 ophthalmology & optometry, Female, Ocular Hypertension, sense organs, Abnormality, business, 030217 neurology & neurosurgery, Cohort study
Abstract: To evaluate the associations between medical check-up items (MCI) for fundus and intraocular pressure abnormality (FIPA) diseases in the Department of Health Management Centre, the Fifth Affiliated Hospital of Sun Yat-sen University (DHMC-FHS).Individuals who visited DHMC-FHS and underwent MCI between June 2017 to May 2019 were included, 3237 subjects. A total of 356 participants were diagnosed as FIPA and enrolled. The general clinical characteristics were collected. Diseases for FIPA diagnosed included five cohort, high intraocular pressure, diabetic retinopathy, hypertension fundus arteriosclerosis, large eye cup, and high myopia fundus changes. Possible impact factors of MCI included blood routine, B-ultrasound, heart rate, hypertension, hyperlipidemia, standard vision, cerebral arteriosclerosis, body mass, arterial/carotid arteriosclerosis, etc. Further, the Pearson's correlation coefficients and logistic regression analyses were used to examine associations between MCI and FIPA.The weighted study population who belonged to FIPA included 356 subjects. There were significant differences in age, IOP, habitual exercise, smoking, sleep duration (Of FIPA participants, high intraocular pressure, hypertension fundus arteriosclerosis and high myopia fundus changes were shown a positive relationship with MCI. Control IOP, habitual exercise and less frequent smoking were regarded as positive associations with decreased FIPA. These findings could help us prevent and diagnose FIPA diseases in time via MCI.
Published: 2020
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10. P‐177: A Novel OLED Pixel Circuit for High‐Resolution or High‐Frequency Application

Author: Ying-teng Zhai, Hua Gong, Xu Qian, Wei-qiang Yang, Yue He, and Wen-xin Jiang
Subjects: Materials science, Pixel, business.industry, OLED, Optoelectronics, High resolution, business
Published: 2020
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11. Serum PIWI-Interacting RNAs piR-020619 and piR-020450 Are Promising Novel Biomarkers for Early Detection of Colorectal Cancer

Author: Yongxia Chen, Haiping Zhao, Jun-Qing Liang, Yongfeng Jia, Ma Daguang, Zhenfei Wang, Wen Xin, Hao Qin, Hao Yang, Yongping Mu, Li Feng, Wu Yingcai, and Tan Xiaohui
Subjects: Male, 0301 basic medicine, Oncology, endocrine system, medicine.medical_specialty, Lung Neoplasms, Epidemiology, Colorectal cancer, Piwi-interacting RNA, Breast Neoplasms, Colorectal adenoma, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Stomach Neoplasms, Internal medicine, Biomarkers, Tumor, Humans, Medicine, RNA, Small Interfering, Lung cancer, Early Detection of Cancer, Aged, Sequence Analysis, RNA, urogenital system, business.industry, Gene Expression Profiling, Cancer, Middle Aged, medicine.disease, Gene Expression Regulation, Neoplastic, 030104 developmental biology, Real-time polymerase chain reaction, Case-Control Studies, 030220 oncology & carcinogenesis, Biomarker (medicine), Female, Colorectal Neoplasms, business, Cell-Free Nucleic Acids
Abstract: Background: Early diagnosis can significantly reduce colorectal cancer deaths. We sought to identify serum PIWI-interacting RNAs (piRNAs) that could serve as sensitive and specific noninvasive biomarkers for early colorectal cancer detection. Methods: We screened the piRNA expression profile in sera from 7 patients with colorectal cancer and 7 normal controls using small RNA sequencing. Differentially expressed piRNAs were measured in a training cohort of 140 patients with colorectal cancer and 140 normal controls using reverse transcription quantitative PCR. The identified piRNAs were evaluated in two independent validation cohorts of 180 patients with colorectal cancer and 180 normal controls. Finally, the diagnostic value of the identified piRNAs for colorectal adenoma (CRA) was assessed, and their expression was measured in 50 patients with lung cancer, 50 with breast cancer, and 50 with gastric cancer. Results: The piRNAs piR-020619 and piR-020450 were consistently elevated in sera of patients with colorectal cancer as compared with controls. A predicative panel based on the two piRNAs was established that displayed high diagnostic accuracy for colorectal cancer detection. The two-piRNA panel could detect small-size and early-stage colorectal cancer with an area under the ROC curve of 0.863 and 0.839, respectively. Combined use of the two piRNAs could effectively distinguish CRA from controls. Aberrant elevation of the two piRNAs was not observed in sera of patients with lung, breast, and gastric cancer. Conclusions: Serum piR-020619 and piR-020450 show a strong potential as colorectal cancer-specific early detection biomarkers. Impact: The field of circulating piRNAs could allow for novel tumor biomarker development.
Published: 2020
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12. Efficacy of amisulpride on postoperative nausea and vomiting: a systematic review and meta-analysis

Author: Chao-Fan Zhang, Yang Liu, Dan-Dan Tian, Long He, Lu-Feng Zhang, Yan-Qiu Ai, and Wen-Xin Tang
Subjects: medicine.medical_specialty, medicine.drug_class, Placebo, 030226 pharmacology & pharmacy, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Humans, Antiemetic, Pharmacology (medical), 030212 general & internal medicine, Amisulpride, Adverse effect, Randomized Controlled Trials as Topic, Pharmacology, business.industry, General Medicine, Confidence interval, Relative risk, Meta-analysis, Postoperative Nausea and Vomiting, Dopamine Antagonists, medicine.symptom, business, Postoperative nausea and vomiting, medicine.drug
Abstract: Postoperative nausea and vomiting (PONV) remains a significant clinical problem for surgical patients. Amisulpride is a well-studied D2/D3 antagonist that has the potential to be used for preventing and treating PONV. Our aim was to assess the efficacy and safety of amisulpride for prevention and treatment of PONV through a systematic review and meta-analysis. A systematic literature search was performed using MEDLINE, EMBASE, PUBMED, clinicaltrials.gov, and the Cochrane Central Register of Controlled Trials from their inception to Feb 15th, 2019. The efficacy outcome was the incidence of complete response, defined as no emesis and no rescue antiemetic use in a 24-h period after study drug administration. The safety outcomes were the adverse effects associated with amisulpride. Five studies comprising 3243 patients met inclusion critieria. Compared with placebo, amisulpride showed a significantly improved incidence of complete response [relative risk (RR): 1.30; 95% confidence interval (CI): 1.20–1.41; P
Published: 2020
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13. Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching

Author: Wei-Ping Ma, Wen-Xin Li, and Peng-Xia Cao
Subjects: 0209 industrial biotechnology, Cross-correlation, Pixel, Computer science, business.industry, Applied Mathematics, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Stereo matching, 02 engineering and technology, Computer Science Applications, 020901 industrial engineering & automation, Control and Systems Engineering, Robustness (computer science), Modeling and Simulation, 0202 electrical engineering, electronic engineering, information engineering, Robot, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Robotic arm, Binocular vision, 3d coordinates
Abstract: In order to improve the low positioning accuracy and execution efficiency of the robot binocular vision, a binocular vision positioning method based on coarse-fine stereo matching is proposed to achieve object positioning. The random fern is used in the coarse matching to identify objects in the left and right images, and the pixel coordinates of the object center points in the two images are calculated to complete the center matching. In the fine matching, the right center point is viewed as an estimated value to set the search range of the right image, in which the region matching is implemented to find the best matched point of the left center point. Then, the similar triangle principle of the binocular vision model is used to calculate the 3D coordinates of the center point, achieving fast and accurate object positioning. Finally, the proposed method is applied to the object scene images and the robotic arm grasping platform. The experimental results show that the average absolute positioning error and average relative positioning error of the proposed method are 8.22 mm and 1.96% respectively when the object's depth distance is within 600 mm, the time consumption is less than 1.029 s. The method can meet the needs of the robot grasping system, and has better accuracy and robustness.
Published: 2020
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14. Broadband White-Light Emission in One-Dimensional Organic–Inorganic Hybrid Silver Halide

Author: Cheng-Yang Yue, Xiao-Wu Lei, Wen-Li He, Ya-Hui Guo, Zhi-Hong Jing, Wen-Xin Chu, Hang-Xin Che, Chen Sun, and Yun Yuan
Subjects: Silver halide, 010405 organic chemistry, business.industry, 010402 general chemistry, 01 natural sciences, 0104 chemical sciences, law.invention, Inorganic Chemistry, chemistry.chemical_compound, Metal halides, chemistry, law, Broadband, Organic inorganic, White light, Optoelectronics, Light emission, Physical and Theoretical Chemistry, business, Light-emitting diode, Diode
Abstract: In the past few decades, organic-inorganic hybrid metal halides acting as single-component white light emission diodes (LEDs) have attracted extensive attentions, but most of the studies concentrate on the low-dimensional lead perovskites. Here, by using the nontoxic silver as optically active metal center, a series of hybrid silver halides based on one-dimensional structures were constructed and realized broadband white light emission. Compounds [H
Published: 2020
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15. Effects of mindfulness meditation on anxiety, depression, stress, and mindfulness in nursing students: a meta-analysis and trial sequential analysis of randomized controlled trials

Author: Wen-Xin Sun, Xiu-Jie Sun, Bin Yuan, Bei-Li Jia, Juan Sun, Dong-Mei Yang, and Yu-Feng Li
Subjects: mindfulness, Mindfulness, meditation, education, Anxiety depression, RT1-120, Nursing, Education, law.invention, stress, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Stress (linguistics), Medicine, 030212 general & internal medicine, General Nursing, nursing students, 030504 nursing, business.industry, anxiety, meta-analysis, Meta-analysis, depression, Mindfulness meditation, 0305 other medical science, business, trial sequential analysis, Clinical psychology
Abstract: Objective The aim of this study was to assess the effectiveness of mindfulness meditation (MM) on anxiety, depression, stress and mindfulness in nursing students. Methods A comprehensive search and screening procedures were conducted to locate all MM interventions implemented with nursing students. For randomized controlled trials (RCTs) in accordance with the inclusion criteria, a search was conducted in PubMed, Embase, Web of Science, Medline, PsycINFO, Cumulative Index to Nursing and Allied Health (CINAHL), Cochrane Central Register of Controlled Trials (CENTRAL), China Biology Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI) and Wanfang. Databases were retrieved from inception through August 2018. Additional studies were identified through hand searches and Internet searches. Two reviewers collected relevant data of eligible articles according to the data extraction tables. Based on Cochrane Handbook, critical appraisal of the methodological quality was assessed by two other reviewers. An Excel form was used to extract main characteristics of included RCTs. Meta-analysis and trial sequential analysis (TSA) were carried out using software RevMan 5.3 and TSA 0.9. Results Five RCTs with 257 nursing students were included. Only two studies were assessed as high quality and three studies were evaluated as moderate quality. Meta-analysis showed that, comparing with the control group, MM could significantly improve anxiety (SMD = −0.45, 95% CI −0.73 to −0.17, P = 0.001) and stress (SMD = −0.69, 95% CI −0.97 to −0.40, P < 0.001). TSA results confirmed that the outcome of the merger is credible. It could also significantly improve depression level of nursing students after 8 weeks intervention duration (SMD = −0.70, 95% CI −1.14 to −0.26, P = 0.002). However, there was no beneficial effect on depression level of nursing students with 1 week intervention duration (SMD = 0.09, 95% CI −0.42 to 0.59, P = 0.74) and its effects on mindfulness level of nursing students also did not show statistical significance (SMD = 0.37, 95% CI −0.04 to 0.77, P = 0.07). No definitive conclusions were drawn from the TSA. Conclusions The results of this meta-analysis indicated that MM could effectively reduce the level of anxiety and stress of nursing students. TSA confirmed that the results of meta-analysis are credible. For depression, it could also significantly improve depression of nursing students with 8 weeks intervention, but there was no significant effect on nursing students with 1 week intervention duration. There was also no beneficial effect on mindfulness level of nursing students. However, TSA indicated that the accumulated evidence is still inconclusive. We suggest that more well-designed clinical trials with large sample and higher quality would be required in future to draw a definitive conclusion.
Published: 2020
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16. Visible and near-infrared driven Yb3+/Tm3+ co-doped InVO4 nanosheets for highly efficient photocatalytic applications

Author: Weiya Huang, Kailian Zhang, Xiaoxiao Li, Changlin Yu, Yu Xie, Jie Guan, Wen-Xin Dai, Ping Mu, Laixi Zou, and Kai Yang
Subjects: Tafel equation, Materials science, business.industry, Environmental pollution, Overpotential, Photochemistry, Photon upconversion, Inorganic Chemistry, chemistry.chemical_compound, Semiconductor, chemistry, Methyl orange, Photocatalysis, Irradiation, business
Abstract: To effectively enhance the utilization of clean sunlight energy, harvesting a large percentage of near infrared (NIR) light is significant. One of the commonly used effective methods for modifying semiconductors is by co-doping upconversion materials on semiconductors to heighten the photocatalytic efficiency. In this work, Yb3+/Tm3+ co-doped InVO4 nanosheets were synthesized by a facile hydrothermal path, and the crystal phases, morphologies, surface chemical compositions, as well as optical properties were characterized. Yb3+/Tm3+ co-doped InVO4 revealed significantly enhanced photoactivity towards chromium(VI) reduction and methyl orange oxidation under visible or NIR light irradiation. Furthermore, 5YT-IV presented the highest electrocatalytic performance and photocatalytic production of H2O2 under visible light irradiation, requiring low overpotential and low Tafel slope (390 mV dec−1) for hydrogen evolution reaction than that of the bare InVO4 (731 mV dec−1), and as well improved the yield of photocatalytic H2O2 production by about 3.5 times. This was primarily ascribed to intensive light absorption resulting from the benign upconversion energy transfer of Yb3+/Tm3+ and the boosted charge separation caused by the intermediate energy states. Moreover, the presence of h+ and ˙O2− as the main oxidative species played a significant role during the photocatalytic oxidation process of methyl orange and electrons played a decisive role in Cr(VI) reduction. This study provides a promising platform for efficiently utilizing the visible-NIR energy of sunlight in the field of photocatalytic H2O2 production and for alleviating environmental pollution in future.
Published: 2020
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17. Pd/BiOBr tetragonal platelets with controllable facets by the decoration of La dopant enabling highly efficient photocatalytic activity

Author: Xin Chen, Qizhe Fan, Kai Yang, Yanming Yang, Changlin Yu, Wen-Xin Dai, Weiya Huang, and Kailian Zhang
Subjects: Materials science, Dopant, business.industry, Doping, General Chemistry, Crystal structure, Condensed Matter Physics, Ion, Crystal, Tetragonal crystal system, Semiconductor, Chemical engineering, Photocatalysis, General Materials Science, business
Abstract: The charge transfer between semiconductors and metals is greatly dependent on the crystal structure and properties of the interface. It is well known that Schottky junctions formed by depositing Pd nanoparticles on BiOBr nanosheets can accelerate the transfer and separation of carriers. However, the stability of the crystal structure and the exposed crystal surface with high performance both decrease in the process of photo-deposition. In the present work, Pd/BiOBr photocatalysts decorated with an La dopant were fabricated by a two-step synthesis with solvothermal and photo-deposition methods. Interestingly, Pd/BiOBr crystals could be reconstructed by doping with La ions, such as the regrowth of facets with UV light irradiation. The instability of the crystal structure and lower photocatalytic performance could be reversed by doping with La ions. La-Doping refined the crystal structure and strengthened the charge transfer and separation of carriers over Pd/BiOBr, exhibiting enhanced photocatalytic activity toward the degradation of acid orange II (AO II). Moreover, the reason for the effects of the La ions was investigated by density functional theory calculations.
Published: 2020
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18. Outcome prediction using the Mortality in Emergency Department Sepsis score combined with procalcitonin for influenza patients

Author: Wen-Xin Liu, Fei Teng, Ji-Fei Cai, Shu-Bin Guo, Tian-Tian Wan, Xuan Qi, and Xin Liu
Subjects: Male, medicine.medical_specialty, Time Factors, Logistic regression, Procalcitonin, Sepsis, 03 medical and health sciences, 0302 clinical medicine, Predictive Value of Tests, Internal medicine, Influenza, Human, medicine, Humans, 030212 general & internal medicine, Aged, Retrospective Studies, Receiver operating characteristic, business.industry, General Medicine, Emergency department, Odds ratio, Middle Aged, Prognosis, medicine.disease, Female, SOFA score, Observational study, Emergency Service, Hospital, business, Biomarkers
Abstract: Background Severe influenza is often associated with bacterial coinfection and can trigger sepsis, which increases the severity, complexity and mortality of the disease. To determine an effective method for predicting 28-day mortality of emergency department (ED) patients with influenza, we investigated the Mortality in Emergency Department Sepsis (MEDS) score, procalcitonin (PCT) and other relevant biomarkers. Methods We conducted a retrospective, observational, monocentric study, and the endpoint was 28-day mortality. Independent predictors were identified and a new combination predictive model was created both by logistic regression, and the model was evaluated by a receiver operating characteristic (ROC) curve. Results A total of 364 consecutive ED admitted patients with influenza were enrolled and 45 patients died within 28 days. For predicting 28-day mortality, the MEDS score and PCT were independent predictors with adjusted odds ratio of 1.318 (95% CI 1.206–1.439) and 1.038 (95% CI 1.010–1.065), and with AUCs of 0.817 (95% CI 0.756–0.878) and 0.793 (95% CI 0.725–0.861), respectively. The new combination of the MEDS score with PCT significantly improved the efficacy for predicting 28-day mortality with an AUC of 0.857 (95% CI 0.809–0.905), and was superior to the SOFA score with an AUC of 0.837 (95% CI 0.779–0.894). Conclusion The MEDS score and PCT, especially when combined, perform well for predicting mortality of ED admitted patients with influenza.
Published: 2019
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19. Developing a multivariable risk prediction model to predict prolonged viral clearance in patients with COVID-19

Author: Xuan Zhang, Jian Fei Luo, Zong An Liang, Dan Liu, Ji Wang, Xiao Ju Tang, Ting Wang, Jia Liu, Nian Li, Gang Wang, Xin Zhang, Feng Ming Luo, Weimin Li, Ying Liu, Min Li, Wen Xin Luo, and Yong Zao Zhou
Subjects: 0301 basic medicine, Microbiology (medical), 2019-20 coronavirus outbreak, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Multivariable calculus, 030106 microbiology, COVID-19, prediction model, 03 medical and health sciences, 0302 clinical medicine, Infectious Diseases, Internal medicine, medicine, In patient, 030212 general & internal medicine, business, Letter to the Editor, viral clearance
Abstract: Highlights • In this study, a multivariable risk prediction model was developed that may help predict a patient's risk of prolonged SARS-CoV-2 RNA clearance. • Time from illness onset to admission, haemoptysis, diarrhea, use of glucocorticoids, leukopenia and elevated alanine transaminase were independent risk factors for prolonged duration of viral clearance • Estimating these risk factors could promote individual precision therapy and optimizing the use of medical resources.
Published: 2021
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20. Associations of Childcare Arrangements with Adiposity Measures in a Multi-Ethnic Asian Cohort: The GUSTO Study

Author: Shiao-Yng Chan, Airu Chia, Lynette Pei-Chi Shek, Yap Seng Chong, Carla Costa Lança, Fabian Yap, Wen Lun Yuan, Yung Seng Lee, Keith M. Godfrey, Jia Ying Toh, Mary Foong-Fong Chong, Johan G. Eriksson, Falk Müller-Riemenschneider, Beverly Wen-Xin Wong, Kok Hian Tan, Mya Thway Tint, Ray Sugianto, Natarajan Padmapriya, Seang-Mei Saw, Clinicum, Research Programs Unit, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Helsinki University Hospital Area, Lee Kong Chian School of Medicine (LKCMedicine), KK Women’s and Children’s Hospital, and Graduate Medical School, Duke-National University of Singapore
Subjects: Pediatric Obesity, Asia, Health, Toxicology and Mutagenesis, Psychological intervention, Ethnic group, 030209 endocrinology & metabolism, Overweight, Childhood obesity, Article, Body Mass Index, 03 medical and health sciences, Screen time, 0302 clinical medicine, medicine, Humans, Medicine [Science], 030212 general & internal medicine, Child Care, Child, Preschool, Children, Adiposity, Asian, business.industry, Childcare, Public Health, Environmental and Occupational Health, Grandparent, Caregiver type, Anthropometry, medicine.disease, 3142 Public health care science, environmental and occupational health, Skinfold Thickness, Child, Preschool, 3121 General medicine, internal medicine and other clinical medicine, Cohort, Medicine, medicine.symptom, business, Demography, childcare, adiposity, preschool, caregiver type
Abstract: Childcare arrangements shape behavioural patterns that influence the risk of childhood obesity. However, little is known of its influence on childhood obesity in Singapore. We aim to examine the associations between childcare arrangements at the age of 5 years and childhood adiposity at age 6 years. Children from the GUSTO study were grouped into three childcare arrangements at age 5: full-time centre-based childcare (FC), partial centre-based with parental care (PCP), and partial centre-based with non-parents (grandparents and domestic helpers) as caregivers (PCN). Diet, physical activity and sedentary behaviour information were collected at age 5, while anthropometric measurements were collected at age 6. Associations were analysed using multivariable regression models. Among 540 children, those in PCN had higher BMI z-scores (β: 0.34; 95% CI: 0.01, 0.66), greater sum of skinfold thicknesses (mm) (β: 3.75; 95% CI: 0.53, 6.97) and were 3.55 times (95% CI: 1.78, 7.05) more likely to be overweight/obese than those in FC. Adiposity measures in PCP children did not differ from those in FC. PCN children were reported to have more screen time and greater fast-food intake. Children in PCN tended to have higher adiposity measures. Greater engagement of non-parental caregivers should be considered in interventions targeting child obesity. Agency for Science, Technology and Research (A*STAR) Ministry of Health (MOH) National Medical Research Council (NMRC) Published version The GUSTO cohort study was funded by the Singapore National Research Foundation’s Translational and Clinical Research (TCR) Flagship Programme and was administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC), Singapore—NMRC/TCR/004- NUS/2008; NMRC/TCR/012-NUHS/2014. Additional funding was given by the Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore. KMG is supported by the UK Medical Research Council (MC_UU_12011/4), the National Institute for Health Research (NIHR Senior Investigator NF-SI-0515-10042), NIHR Southampton 1000DaysPlus Global Nutrition Research Group (17/63/154) and NIHR Southampton Biomedical Research Centre (IS-BRC1215-20004), the British Heart Foundation (RG/15/17/3174) and by the European Union (Erasmus+ Programme Early Nutrition eAcademy Southeast Asia-573651-EPP-1-2016-1-DE-EPPKA2-CBHE-JP and ImpENSA.
Published: 2021
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21. A Narrative Review of Human Clinical Trials on the Impact of Phenolic-Rich Plant Extracts on Prediabetes and Its Subgroups

Author: Cheryl S Gammon, Rachel Page, Wen Xin Janice Lim, Pamela R. von Hurst, and Lynne Chepulis
Subjects: medicine.medical_specialty, endocrine system diseases, Review, Glycemic Control, Prediabetic State, Impaired glucose tolerance, functional food, Insulin resistance, Phenols, impaired fasting glucose, Internal medicine, medicine, Humans, TX341-641, Prediabetes, Glycemic, Clinical Trials as Topic, Nutrition and Dietetics, biology, Plant Extracts, business.industry, Nutrition. Foods and food supply, Diospyros kaki, nutritional and metabolic diseases, food and beverages, impaired glycemic control, medicine.disease, Impaired fasting glucose, biology.organism_classification, polyphenol, Treatment Outcome, Endocrinology, Postprandial, impaired glucose tolerance, Artemisia, business, Food Science
Abstract: Phenolic-rich plant extracts have been demonstrated to improve glycemic control in individuals with prediabetes. However, there is increasing evidence that people with prediabetes are not a homogeneous group but exhibit different glycemic profiles leading to the existence of prediabetes subgroups. Prediabetes subgroups have been identified as: isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), and combined impaired fasting glucose and glucose intolerance (IFG/IGT). The present review investigates human clinical trials examining the hypoglycemic potential of phenolic-rich plant extracts in prediabetes and prediabetes subgroups. Artemisia princeps Pampanini, soy (Glycine max (L.) Merrill) leaf and Citrus junos Tanaka peel have been demonstrated to improve fasting glycemia and thus may be more useful for individuals with IFG with increasing hepatic insulin resistance. In contrast, white mulberry (Morus alba Linn.) leaf, persimmon (Diospyros kaki) leaf and Acacia. Mearnsii bark were shown to improve postprandial glycemia and hence may be preferably beneficial for individuals with IGT with increasing muscle insulin resistance. Elaeis guineensis leaf was observed to improve both fasting and postprandial glycemic measures depending on the dose. Current evidence remains scarce regarding the impact of the plant extracts on glycemic control in prediabetes subgroups and therefore warrants further study.
Published: 2021

22. A new classification of congenital abnormalities of UPVS: sonographic appearances, screening strategy and clinical significance

Author: Dandan Luo, Yan Ding, Wen Xin, Meiling Liang, Mengyu Zhang, Huaxuan Wen, Tan Ying, Shengli Li, Yue Qin, Ying Yuan, Yimei Liao, and Qing Zeng
Subjects: medicine.medical_specialty, medicine.diagnostic_test, Postnatal management, business.industry, Umbilical–portal venous system, Ultrasonographic characteristics, R895-920, Fetal heart, Interventional radiology, New comprehensive classification, Screening strategy, Medical physics. Medical radiology. Nuclear medicine, Blood circulation, Embryology, medicine, Etiology, Radiology, Nuclear Medicine and imaging, Clinical significance, Normal blood, Radiology, business, Educational Review, Neuroradiology
Abstract: The umbilical–portal venous system (UPVS) plays an important role in embryonic development, as well as a significant blood circulation system to ensure the normal blood supply of fetal heart and brain and other vital organs. Congenital anomalies of UPVS contain many subtypes with a broad spectrum of manifestations and prognoses. Furthermore, because of fetal small lumen of UPVS, the sonographic evaluation remains difficult in utero. Appreciation of normal embryology and anatomy of UPVS is essential to an understanding of sonographic characteristics of anomalies of UPVS and fetal sequential changes. Through reviewing previous references and our experience with congenital abnormalities of UPVS, a new comprehensive classification is proposed. The new classification identifies three types of congenital abnormalities of UPVS based on morphological abnormalities and shunts. The embryology and etiology, sonographic, clinical and prognostic characteristics of each subtype of the new classification are described in detail. Knowledge of congenital abnormalities of UPVS can give sonographers a clue and aid prenatal sonographic diagnosis. The purpose of this article is to help the sonographers to understand the new classification of congenital abnormalities of UPVS, master the sonographic characteristics of each subtype and prenatal ultrasonographic screening strategy, and guide subsequent appropriate counseling and management.
Published: 2021
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23. Measuring In-Building Spatial-Temporal Human Distribution through Monocular Image Data Considering Deep Learning–Based Image Depth Estimation

Author: Jen-Yu Han, Wen-Xin Qiu, and Albert Y. Chen
Subjects: Distribution (number theory), Computer science, business.industry, Deep learning, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Demand estimation, Computer Science Applications, Image (mathematics), Image sensing, Monocular image, Video tracking, Computer vision, Artificial intelligence, business, Cluster analysis, Civil and Structural Engineering
Abstract: This research estimated the spatial-temporal distribution of humans in buildings through image sensing. Inputs were the in-building network, image sequences recording the movement of human,...
Published: 2021
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24. Immunotherapy-related toxicity in lung cancer: clinical characteristics and managing strategy

Author: Wen-Xin Luo, Lan Yang, Wei-Min Li, and Pei-Fang Wei
Subjects: Oncology, medicine.medical_specialty, Lung Neoplasms, business.industry, medicine.medical_treatment, MEDLINE, General Medicine, Immunotherapy, medicine.disease, Text mining, Internal medicine, Toxicity, medicine, Humans, Medicine, business, Lung cancer, Medical Progress
Published: 2021
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25. Correlation of 18F-FDG PET/CT SUVmax with clinical features, D-dimer and LDH in patients with primary intestinal lymphoma

Author: Chong Huo, Guo-bao Chen, Shuo Zhou, Mei-fu Lin, Xueming Du, Wen-xin Chen, and Cailong Chen
Subjects: Fluorine Radioisotopes, Medicine (General), Lymphoma, Standardized uptake value, positron emission tomography/computed tomography, tomography, Biochemistry, 030218 nuclear medicine & medical imaging, fluorodeoxyglucose F18, Fibrin Fibrinogen Degradation Products, 03 medical and health sciences, 0302 clinical medicine, R5-920, Positron Emission Tomography Computed Tomography, D-dimer, Intestinal Neoplasms, non-Hodgkin, medicine, Humans, In patient, Retrospective Studies, medicine.diagnostic_test, L-Lactate Dehydrogenase, business.industry, Biochemistry (medical), Cell Biology, General Medicine, medicine.disease, Intestinal lymphoma, Positron emission tomography, 030220 oncology & carcinogenesis, Positron-Emission Tomography, Fdg pet ct, Tomography, Radiopharmaceuticals, business, Nuclear medicine, Intestinal tumor, Retrospective Clinical Research Report
Abstract: Objective To investigate the characteristics of fluorine-18-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) maximum standardized uptake value (SUVmax) in primary intestinal lymphoma (PIL) and its correlation with D-dimer and lactate dehydrogenase (LDH). Methods Fifty-two patients diagnosed with PIL from June 2016 to December 2019 were analyzed. All patients underwent 18F-FDG PET/CT. The relationships between SUVmax and different pathological subtypes, clinical stages and risk grades were analyzed. The correlations between SUVmax and Ki-67, LDH and D-dimer were determined. Additionally, PET/CT imaging results were collected from 35 patients with primary intestinal cancer (PIC) and compared with the imaging features of PIL. Results SUVmax was significantly different between PIL and PIC groups and various PIL pathological subgroups. Patients in the high-risk PIL group had markedly higher SUVmax values than the intermediate-risk and low-risk groups. A significant positive correlation was observed between SUVmax and Ki-67 in patients with PIL. SUVmax was significantly different between the elevated and normal D-dimer groups. D-dimer showed a positive correlation with SUVmax. Conclusion 18F-FDG PET/CT SUVmax reflects the aggressiveness of lymphoma to a certain degree, is correlated with Ki-67 and determines the risk grades of PIL. Moreover, it facilitates differential diagnosis, clinical staging and treatment based on D-dimer levels.
Published: 2021

26. Key Factors Affecting Farmers’ Choice of Corn Reduction under the China’s New Agriculture Policy in the ‘Liandaowan’ Areas, Northeast China

Author: HE Xiuli, Liu Shiwei, Liu Wen-xin, and Zhang Ping-yu
Subjects: Government, 010504 meteorology & atmospheric sciences, business.industry, Structural adjustment, Geography, Planning and Development, Subsidy, 010501 environmental sciences, 01 natural sciences, Agricultural economics, Crop diversity, Agriculture, General Earth and Planetary Sciences, Farmland preservation, China, business, Agricultural extension, 0105 earth and related environmental sciences
Abstract: Farmers are the main land managers, and their production decisions crucially affect crop outputs and farmland preservation. Understanding the motivations and factors underlying farmers’ decision making is a fundamental to implementation polices of government. This study analyzed factors that influence farmers’ choice of corn reduction under the China’s new agriculture policy in the ‘Liandaowan’ areas of Northeast China. This study collected data from 106 randomly selected households in 34 villages in ‘Liandaowan’ areas of Northeast China using a semi-structured questionnaire. Results showed that the Chinese corn structural adjustment plan confronted with many constraints, and most of farmers insist on planting corn. Drought and low accumulated temperature, no suitable substitution crop, farmers’ preferences, farmers’ education and age, relatively high comparative benefit of corn, the availability of machinery and technical assistance, subsidies and low family incomes all influence farmers’ choice of corn substitution. Based on our experimental results, we derived important policy implications for promoting corn structural adjustment incorporate increase crop diversity, promote soybean and corn rotation, provide adequate agricultural extension services, and increase the corn substitution subsidies and improve farmers’ income.
Published: 2019
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27. Assessment of angiogenesis in rabbit orthotropic liver tumors using three-dimensional dynamic contrast-enhanced ultrasound compared with two-dimensional DCE-US

Author: Fu-shun Pan, Xiaoyan Xie, Zhu Wang, Qiao Zheng, Wen-Xin Wu, Ming-De Lu, Wei Wang, Jian-Chao Zhang, Yu-Chen Zhang, Quan-Yuan Shan, Li-Da Chen, Si-Min Ruan, and Wei Li
Subjects: Liver tumor, Angiogenesis, Intraclass correlation, Contrast Media, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, chemistry.chemical_compound, Imaging, Three-Dimensional, 0302 clinical medicine, medicine, Animals, Humans, Radiology, Nuclear Medicine and imaging, skin and connective tissue diseases, Ultrasonography, Reproducibility, Neovascularization, Pathologic, business.industry, Liver Neoplasms, Ultrasound, Area under the curve, Reproducibility of Results, Image Enhancement, medicine.disease, Vascular endothelial growth factor, Disease Models, Animal, Liver, chemistry, 030220 oncology & carcinogenesis, Rabbits, Bolus (digestion), Nuclear medicine, business
Abstract: To evaluate quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) in the assessment of tumor angiogenesis using an orthotropic liver tumor model. Nine New Zealand white rabbits with liver orthotropic VX2 tumors were established and imaged by two-dimensional (2D) and 3D DCE-US after SonoVue® bolus injections. The intraclass correlation coefficients of perfusion parameters, including peak intensity (PI), mean transit time, time to peak, and area under the curve, were calculated based on time-intensity curve. The percentage area of microvascular (PAMV) and the expression of vascular endothelial growth factor (VEGF) were both evaluated by immunohistochemical analysis and weighted by the tumor activity area ratio. Correlations between quantitative and histologic parameters were analyzed. The reproducibility of 3D DCE-US quantitative parameters was excellent (ICC 0.91–0.99); but only PI showed high reproducibility (ICC 0.97) in 2D. None of the parameters of quantitative 2D DCE-US were significantly correlated with weighted PAMV or VEGF. For 3D DCE-US, there was a positive correlation between PI and weighted PAMV (r = 0.74, P = 0.04) as well as VEGF (r = 0.79, P = 0.02). Quantitative parameters of 3D DCE-US show feasibility, higher reproducibility and accuracy for the assessment of tumor angiogenesis using an orthotropic liver tumor model compared with 2D DCE-US.
Published: 2019
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28. A novel firefly algorithm based on gender difference and its convergence

Author: Chun-Feng Wang and Wen-Xin Song
Subjects: education.field_of_study, Hardware_MEMORYSTRUCTURES, Markov chain, business.industry, Computer science, 020209 energy, Population, 02 engineering and technology, ComputerSystemsOrganization_PROCESSORARCHITECTURES, Local optimum, Convergence (routing), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Firefly algorithm, Local search (optimization), Artificial intelligence, Focus (optics), business, education, Time complexity, Software
Abstract: Firefly algorithm is a population-based algorithm, because the search process is simple and easy to implement, it has received extensive attention from scholars. However, the algorithm has low accuracy and is easy to fall into local optimum. Therefore, an improved firefly algorithm based on gender difference (GDFA) is proposed to enhance the performance of the algorithm in this paper. In the basic firefly algorithm, fireflies have no gender distinction, which is not consistent with reality. According to this point, fireflies are divided into two subgroups based on gender. In addition, different update equations are designed for two subgroups on the basis of their moving ways. Male fireflies are guided by two randomly selected female fireflies to focus on global search and female fireflies move to the best male firefly to implement local search, which aim to balance the exploration and exploitation of the algorithm. To further improve the search accuracy, the chaos search is conducted near the best position of the population. Several simulation experiments and constrained optimization problems are carried out to verify the effectiveness of GDFA, and the time complexity of GDFA is analyzed. Finally, the convergence analysis of proposed algorithm is given based on Markov chain theory.
Published: 2019
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29. Large Conjugated Organic Cations Sensitized Hybrid Lead Halides as Visible Light Driven Photocatalysts

Author: Yun Yuan, Wen-Xin Chu, Hui-Fang Zhao, Ya-Hui Guo, Xiao-Wu Lei, Hang-Xin Che, Jing-Zhao Li, Zhi-Hong Jing, Cheng-Yang Yue, and Hao Jiang
Subjects: Materials science, Composite oxide, 010405 organic chemistry, business.industry, Halide, General Chemistry, Conjugated system, 010402 general chemistry, Condensed Matter Physics, Photochemistry, 01 natural sciences, 0104 chemical sciences, chemistry.chemical_compound, Semiconductor, Metal halides, chemistry, General Materials Science, business, Visible spectrum
Abstract: Visible light driven photocatalysts based on crystalline metal halides received much less attention compared with dense or composite oxide semiconductors due to low photochemical stabilities. Here,...
Published: 2019
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30. Application of a DPSIR Modeling Framework to Assess Spatial-Temporal Differences of Water Poverty in China

Author: Caizhi Sun, Yong-jie Wu, Min-juan Zhao, and Wen-xin Liu
Subjects: Ecology, Poverty, business.industry, DPSIR, Environmental resource management, Water resources, Geography, Variation (linguistics), Water poverty, Sustainability, Spatial variability, business, China, Earth-Surface Processes, Water Science and Technology
Published: 2019
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31. Follicular dendritic cell sarcoma detected in hepatogastric ligament: A case report and review of the literature

Author: Ping Zhang, Xingkai Liu, Youxi Yu, Wen-Xin Yan, and Yan Li
Subjects: Pathology, medicine.medical_specialty, Hepatogastric ligament, Spleen, 03 medical and health sciences, 0302 clinical medicine, Case report, medicine, Computed tomography, business.industry, Stomach, Soft tissue, General Medicine, medicine.disease, Curvatures of the stomach, Immunohistochemistry, medicine.anatomical_structure, Cervical lymph nodes, 030220 oncology & carcinogenesis, Follicular dendritic cell sarcoma, 030211 gastroenterology & hepatology, business, Pancreas
Abstract: The most common organ where follicular dendritic cell sarcoma (FDCS) occurs is in cervical lymph nodes, while few cases are found in extranodal organs such as liver, spleen, and soft tissue. This is a case report that FDCS occurs in the hepatogastric ligament. To our knowledge, there is no such case that has been reported previously. A 47-year-old male patient was found to have an intraabdominal mass during an annual physical examination. Computed tomography showed a 4.2 cm × 4.1 cm mass located at the lesser curvature of the stomach, above the pancreas. During operation, a tumor mass was found in the hepatogastric ligament and a radical resection was performed. The tumor was diagnosed as FDCS by pathology and immunohistochemical testing. The patient had a favorable recovery, and no obvious abnormality was found 3 months post-operation.
Published: 2019

32. A near-infrared fluorescent probe for accurately diagnosing cancer by sequential detection of cysteine and H

Author: Yongfei Li, Zhi-Qing Wang, Wen-Xin Wang, Guo-Jiang Mao, Wen-Li Jiang, Zun-Pan She, and Chun-Yan Li
Subjects: Catalysis, Cell Line, Mice, Text mining, In vivo, Neoplasms, Materials Chemistry, medicine, Animals, Humans, Cysteine, Fluorescent Dyes, Molecular Structure, business.industry, Chemistry, Optical Imaging, Metals and Alloys, Cancer, General Chemistry, Hydrogen-Ion Concentration, medicine.disease, Fluorescence, Molecular biology, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Spectrometry, Fluorescence, Cancer cell, Ceramics and Composites, business
Abstract: A near-infrared fluorescent probe, CyAc, is synthesized for accurately diagnosing cancer in vivo by sequential detection of Cys and H+. CyAc can not only discriminate normal cells and cancer cells, but also distinguish normal mice from tumor mice.
Published: 2021

33. Efficacy and safety of surgical ablation concomitant to coronary artery bypass grafting for atrial fibrillation: a meta-analysis

Author: Wei Wang, Kang Yi, Jie Gao, Shao-E He, Xiao-Min Xu, Tao You, Jian-Guo Xu, Yu-Hu Ma, and Wen-Xin Wang
Subjects: medicine.medical_specialty, Bypass grafting, business.industry, Atrial fibrillation, medicine.disease, medicine.anatomical_structure, Meta-analysis, Internal medicine, Concomitant, Cardiology, Medicine, business, Surgical ablation, Artery
Published: 2021
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34. New-onset lesions on MRI-DWI and cerebral blood flow changes on 3D-pCASL after carotid artery stenting

Author: Xin Lou, Ting Wang, Zhenghui Sun, Lin Ma, Ge-Sheng Wang, and Wen-Xin Wang
Subjects: Male, medicine.medical_specialty, Science, Hemodynamics, Article, Temporal lobe, Medical research, Internal medicine, medicine, Humans, Carotid Stenosis, Aged, Multidisciplinary, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, Middle Aged, medicine.disease, Stenosis, Diffusion Magnetic Resonance Imaging, Blood pressure, Neurology, Cerebral blood flow, Cardiology, Medicine, Stents, business, Perfusion, Neuroscience, Diffusion MRI
Abstract: This study aimed to investigate the relationship between the new-onset hyperintense lesions on diffusion-weighted images (DWI) and the changes of cerebral blood flow (CBF) before and after carotid artery stenting (CAS) in patients with symptomatic unilateral carotid artery stenosis. Twenty-four patients with symptomatic unilateral carotid stenosis (50–99%) were enrolled. Routine head magnetic resonance imaging and three-dimensional pseudo-continuous arterial spin labeling were taken 7 days before the surgery and for four consecutive days post CAS. While the incidence of new DWI lesions were high (17/24, 70.8%) and 176 lesions were observed among the 17 cases, there was only one subject showing the symptoms. The majority of the lesions were located at the cortex/subcortex of the ipsilateral frontal and parietal lobes (60.8%) with 92.6% of the lesions size being less than 3 mm. The CBFs in this area were significantly higher than that of the temporal lobe on the first 3 days post stenting (p
Published: 2021
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35. Early combined rehabilitation intervention to improve the prognosis of premature infants

Author: Zhi-hui Zhao, Wen-xin Deng, Ling-ling Chen, Yang Liu, Bei-bei Liu, Zheng-feng Li, Tao-jun Du, Yun-huan Zhong, and Yong Zhang
Subjects: medicine.medical_specialty, business.industry, Physical therapy, medicine, business, Rehabilitation interventions
Abstract: Background: To explore the clinical effect of early combined rehabilitation intervention on premature infants in the neonatal intensive care unit (NICU) Methods: Premature infants with gestational ages less than 32 weeks or birth weights less than 1500 g were included in the present study.The participants were divided into the intervention group and control group. All infants received the current routine treatment based on the clinical guidelines, and the intervention group was additionally treated by visual and auditory stimulation, oral motor function, respiratory function and neurodevelopmental training. The following clinical outcomes were compared: durations of oxygen supplementation and indwelling gastric tube use; incidences of retinopathy of prematurity (ROP) and neonatal necrotizing enterocolitis (NEC); Sliverman scores; incidences of bronchopulmonary dysplasia (BPD) and intraventricular haemorrhage; days of hospitalization; and neurodevelopmental outcomes. Datas were analysed using the following statistical tests: the chi-square test, the independent samples or paired t test, repeated measures ANOVA, and the Wilcoxon rank sum test.Results: Compared with those in the control group, premature infants in the intervention group had shorter durations of oxygen supplementation and indwelling gastric tube use, fewer hospitalization days and lower incidences of ROP, BPD, and NEC.The intervention group had lower Sliverman scores and higher Ballard neuromuscular scores than the control group.Conclusion Early combined rehabilitation intervention can improve the short-term clinical outcomes of premature infants.
Published: 2021
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36. Corrigendum: MicroRNA-608 Promotes Apoptosis in Non-Small Cell Lung Cancer Cells Treated With Doxorubicin Through the Inhibition of TFAP4

Author: Yi-Fei Wang, Xiang Ao, Ying Liu, Dan Ding, Wen-Jie Jiao, Zhuang Yu, Wen-Xin Zhai, Sheng-Hua Dong, Yu-Qi He, Hang Guo, and Jian-Xun Wang
Subjects: lcsh:QH426-470, Single-nucleotide polymorphism, single nucleotide polymorphisms, microRNA, medicine, Genetics, Doxorubicin, Lung cancer, Transcription factor, Gene, Genetics (clinical), non-small cell lung cancer, Original Research, business.industry, apoptosis, Correction, medicine.disease, respiratory tract diseases, lcsh:Genetics, microRNA-608, Apoptosis, Cancer research, TFAP4, Molecular Medicine, business, transcription factor activating enhancer-binding protein 4, medicine.drug
Abstract: Lung cancer is the most commonly diagnosed type of cancer and the leading cause of cancer-associated death worldwide. MicroRNAs (miRNAs) are non-coding single-stranded RNA molecules of ∼20–25 nucleotides in length. Single nucleotide polymorphisms are a class of genetic variation in the human genome, which when present in miRNA genes are associated with the risk of developing cancer. This study aimed to identify whether the miRNA (miR)-608 polymorphism rs4919510 influenced the incidence of lung cancer, and to explore the underlying mechanisms of miR-608 in the pathogenesis of the disease. A total of 37 patients with non-small cell lung cancer (NSCLC) were selected to determine the expression levels of miR-608; 96 NSCLC patients and 136 cancer-free healthy controls were recruited to determine the incidence of miR-608 rs4919510 in lung cancer patients. Additionally, the impact of miR-608 on the expression of predicted target genes, cell migration, viability, proliferation, and apoptosis was also assessed. We found that the presence of miR-608 rs4919510 did not affect the susceptibility of patients to NSCLC or the maturation of miR-608. miR-608 expression levels were found to be downregulated in NSCLC tissues. Furthermore, overexpression of miR-608 promoted doxorubicin-induced apoptosis in NSCLC cell lines A549 and HCC4006 by inhibiting the expression of transcription factor activating enhancer-binding protein 4 (TFAP4), and high expression levels of TFAP4 were observed in NSCLC tissues. Therefore, our results may provide valuable insights for the chemotherapeutical treatment of NSCLC.
Published: 2021
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37. Relationship between chronic kidney disease and sarcopenia

Author: Wen-Xin Chen, Ming-Dian Yu, Hui-Zhen Zhang, Yu Zhang, Sheng-Ping Yang, Yan-Min Zhang, Jiabin Wu, Miao Lin, and Fuyuan Hong
Subjects: Male, medicine.medical_specialty, Sarcopenia, Science, Renal function, Physical examination, Physical strength, Logistic regression, urologic and male genital diseases, Severity of Illness Index, Article, Medical research, Internal medicine, medicine, Humans, Prospective Studies, Renal Insufficiency, Chronic, Multidisciplinary, medicine.diagnostic_test, Muscle loss, business.industry, Middle Aged, medicine.disease, female genital diseases and pregnancy complications, Preferred walking speed, Nephrology, Case-Control Studies, Medicine, Female, business, Kidney disease, Glomerular Filtration Rate
Abstract: Few studies have investigated the relationship between sarcopenia and mild to moderate renal decline. This study aimed to investigate the relationship between chronic kidney disease (CKD) and sarcopenia. In total, 123 patients hospitalized with CKD and 57 healthy volunteers who underwent physical examination during the same period (control group) were analyzed. Body compositions were measured by dual-energy X-ray absorptiometry, and the relative appendicular skeletal muscle index (RASMI) was calculated. Muscular strength was evaluated using a pinch meter. Walking speed within 6 m was measured for muscular function assessment. Single-photon emission computed tomography was performed to measure the glomerular filtration rate (GFR) of CKD patients, who were then divided into CKD1 (55 patients in CKD stages 1 and 2) and CKD2 (68 patients in CKD stages 3-5). The incidence rates of sarcopenia were significantly higher in the CKD1 (40.0%) and CKD2 (55.9%) groups than in the control group (19.3%) (P
Published: 2021

38. Early combined rehabilitation intervention to improve the short-term prognosis of premature infants

Author: Wen-xin Deng, Zhi-hui Zhao, Zheng-feng Li, Tao-jun Du, Yong Zhang, Yun-huan Zhong, Ling-ling Chen, Bei-bei Liu, and Yang Liu
Subjects: Pediatrics, medicine.medical_specialty, Neonatal intensive care unit, Wilcoxon signed-rank test, Gestational Age, Infant, Premature, Diseases, RJ1-570, 03 medical and health sciences, 0302 clinical medicine, 030225 pediatrics, medicine, Humans, Respiratory function, Retinopathy of Prematurity, Bronchopulmonary Dysplasia, business.industry, Premature infants, Infant, Newborn, Repeated measures design, Infant, Retinopathy of prematurity, Infant, Low Birth Weight, medicine.disease, Prognosis, Bronchopulmonary dysplasia, Pediatrics, Perinatology and Child Health, Gestation, Early rehabilitation comprehensive intervention treatment, business, Rehabilitation interventions, 030217 neurology & neurosurgery, Infant, Premature, Research Article
Abstract: Background To explore the clinical effect of early combined rehabilitation intervention on premature infants in the neonatal intensive care unit (NICU). Methods Premature infants with gestational ages less than 32 weeks or birth weights less than 1500 g were included in the present study.The participants were divided into the intervention group and control group. All infants received the current routine treatment based on the clinical guidelines, and the intervention group was additionally treated by visual and auditory stimulation, oral motor function, respiratory function and neurodevelopmental training. The following clinical outcomes were compared: durations of oxygen supplementation and indwelling gastric tube use; incidences of retinopathy of prematurity (ROP) and neonatal necrotizing enterocolitis (NEC); Sliverman scores; incidences of bronchopulmonary dysplasia (BPD) and intraventricular haemorrhage; days of hospitalization; and neurodevelopmental outcomes. Datas were analysed using the following statistical tests: the chi-square test, the independent samples or paired t test, repeated measures ANOVA, and the Wilcoxon rank sum test. Results Compared with those in the control group, premature infants in the intervention group had shorter durations of oxygen supplementation and indwelling gastric tube use, fewer hospitalization days and lower incidences of ROP, BPD, and NEC.The intervention group had lower Sliverman scores and higher Ballard neuromuscular scores than the control group. Conclusion Early combined rehabilitation intervention can improve the short-term clinical outcomes of premature infants.
Published: 2021

39. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1

Author: Klionsky, Daniel, Abdel-Aziz, Amal Kamal, Abdelfatah, Sara, Abdellatif, Mahmoud, Abdoli, Asghar, Abel, Steffen, Abeliovich, Hagai, Abildgaard, Marie, Abudu, Yakubu Princely, Acevedo-Arozena, Abraham, Adamopoulos, Iannis, Adeli, Khosrow, Adolph, Timon, Adornetto, Annagrazia, Aflaki, Elma, Agam, Galila, Agarwal, Anupam, Aggarwal, Bharat, Agnello, Maria, Agostinis, Patrizia, Agrewala, Javed, Agrotis, Alexander, Aguilar, Patricia, Ahmad, S Tariq, Ahmed, Zubair, Ahumada-Castro, Ulises, Aits, Sonja, Aizawa, Shu, Akkoc, Yunus, Akoumianaki, Tonia, Akpinar, Hafize Aysin, Al-Abd, Ahmed, Al-Akra, Lina, Al-Gharaibeh, Abeer, Alaoui-Jamali, Moulay, Alberti, Simon, Alcocer-Gómez, Elísabet, Alessandri, Cristiano, Ali, Muhammad, Alim Al-Bari, M Abdul, Aliwaini, Saeb, Alizadeh, Javad, Almacellas, Eugènia, Almasan, Alexandru, Alonso, Alicia, Alonso, Guillermo, Altan-Bonnet, Nihal, Altieri, Dario, Álvarez, Élida, Alves, Sara, Alves Da Costa, Cristine, Alzaharna, Mazen, Amadio, Marialaura, Amantini, Consuelo, Amaral, Cristina, Ambrosio, Susanna, Amer, Amal, Ammanathan, Veena, An, Zhenyi, Andersen, Stig, Andrabi, Shaida, Andrade-Silva, Magaiver, Andres, Allen, Angelini, Sabrina, Ann, David, Anozie, Uche, Ansari, Mohammad, Antas, Pedro, Antebi, Adam, Antón, Zuriñe, Anwar, Tahira, Apetoh, Lionel, Apostolova, Nadezda, Araki, Toshiyuki, Araki, Yasuhiro, Arasaki, Kohei, Araújo, Wagner, Araya, Jun, Arden, Catherine, Arévalo, Maria-Angeles, Arguelles, Sandro, Arias, Esperanza, Arikkath, Jyothi, Arimoto, Hirokazu, Ariosa, Aileen, Armstrong-James, Darius, Arnauné-Pelloquin, Laetitia, Aroca, Angeles, Arroyo, Daniela, Arsov, Ivica, Artero, Rubén, Asaro, Dalia Maria Lucia, Aschner, Michael, Ashrafizadeh, Milad, Ashur-Fabian, Osnat, Atanasov, Atanas, Au, Alicia, Auberger, Patrick, Auner, Holger, Aurelian, Laure, Autelli, Riccardo, Avagliano, Laura, Ávalos, Yenniffer, Aveic, Sanja, Aveleira, Célia Alexandra, Avin-Wittenberg, Tamar, Aydin, Yucel, Ayton, Scott, Ayyadevara, Srinivas, Azzopardi, Maria, Baba, Misuzu, Backer, Jonathan, Backues, Steven, Bae, Dong-Hun, Bae, Ok-Nam, Bae, Soo Han, Baehrecke, Eric, Baek, Ahruem, Baek, Seung-Hoon, Baek, Sung Hee, Bagetta, Giacinto, Bagniewska-Zadworna, Agnieszka, Bai, Hua, Bai, Jie, Bai, Xiyuan, Bai, Yidong, Bairagi, Nandadulal, Baksi, Shounak, Balbi, Teresa, Baldari, Cosima, Balduini, Walter, Ballabio, Andrea, Ballester, Maria, Balazadeh, Salma, Balzan, Rena, Bandopadhyay, Rina, Banerjee, Sreeparna, Banerjee, Sulagna, Bánréti, Ágnes, Bao, Yan, Baptista, Mauricio, Baracca, Alessandra, Barbati, Cristiana, Bargiela, Ariadna, Barilà, Daniela, Barlow, Peter, Barmada, Sami, Barreiro, Esther, Barreto, George, Bartek, Jiri, Bartel, Bonnie, Bartolome, Alberto, Barve, Gaurav, Basagoudanavar, Suresh, Bassham, Diane, Bast, Robert, Basu, Alakananda, Batoko, Henri, Batten, Isabella, Baulieu, Etienne, Baumgarner, Bradley, Bayry, Jagadeesh, Beale, Rupert, Beau, Isabelle, Beaumatin, Florian, Bechara, Luiz, Beck, George, Beers, Michael, Begun, Jakob, Behrends, Christian, Behrens, Georg, Bei, Roberto, Bejarano, Eloy, Bel, Shai, Behl, Christian, Belaid, Amine, Belgareh-Touzé, Naïma, Bellarosa, Cristina, Belleudi, Francesca, Belló Pérez, Melissa, Bello-Morales, Raquel, Beltran, Jackeline Soares de Oliveira, Beltran, Sebastián, Benbrook, Doris Mangiaracina, Bendorius, Mykolas, Benitez, Bruno, Benito-Cuesta, Irene, Bensalem, Julien, Berchtold, Martin, Berezowska, Sabina, Bergamaschi, Daniele, Bergami, Matteo, Bergmann, Andreas, Berliocchi, Laura, Berlioz-Torrent, Clarisse, Bernard, Amélie, Berthoux, Lionel, Besirli, Cagri, Besteiro, Sebastien, Betin, Virginie, Beyaert, Rudi, Bezbradica, Jelena, Bhaskar, Kiran, Bhatia-Kissova, Ingrid, Bhattacharya, Resham, Bhattacharya, Sujoy, Bhattacharyya, Shalmoli, Bhuiyan, Md Shenuarin, Bhutia, Sujit Kumar, Bi, Lanrong, Bi, Xiaolin, Biden, Trevor, Bijian, Krikor, Billes, Viktor, Binart, Nadine, Bincoletto, Claudia, Birgisdottir, Asa, Bjorkoy, Geir, Blanco, Gonzalo, Blas-Garcia, Ana, Blasiak, Janusz, Blomgran, Robert, Blomgren, Klas, Blum, Janice, Boada-Romero, Emilio, Boban, Mirta, Boesze-Battaglia, Kathleen, Boeuf, Philippe, Boland, Barry, Bomont, Pascale, Bonaldo, Paolo, Bonam, Srinivasa Reddy, Bonfili, Laura, Bonifacino, Juan, Boone, Brian, Bootman, Martin, Bordi, Matteo, Borner, Christoph, Bornhauser, Beat, Borthakur, Gautam, Bosch, Jürgen, Bose, Santanu, botana, luis, Botas, Juan, Boulanger, Chantal, Boulton, Michael, Bourdenx, Mathieu, Bourgeois, Benjamin, Bourke, Nollaig, Bousquet, Guilhem, Boya, Patricia, Bozhkov, Peter, Bozi, Luiz, Bozkurt, Tolga, Brackney, Doug, Brandts, Christian, Braun, Ralf, Braus, Gerhard, Bravo-Sagua, Roberto, Bravo-San Pedro, José, Brest, Patrick, Bringer, Marie-Agnès, Briones-Herrera, Alfredo, Broaddus, V Courtney, Brodersen, Peter, Brodsky, Jeffrey, Brody, Steven, Bronson, Paola, Bronstein, Jeff, Brown, Carolyn, Brown, Rhoderick, Brum, Patricia, Brumell, John, Brunetti-Pierri, Nicola, Bruno, Daniele, Bryson-Richardson, Robert, Bucci, Cecilia, Buchrieser, Carmen, Bueno, Marta, Buitrago-Molina, Laura Elisa, Buraschi, Simone, Buch, Shilpa, Buchan, J Ross, Buckingham, Erin, Budak, Hikmet, Budini, Mauricio, Bultynck, Geert, Burada, Florin, Burgoyne, Joseph, Burón, M Isabel, Bustos, Victor, Büttner, Sabrina, Butturini, Elena, Byrd, Aaron, Cabas, Isabel, Cabrera-Benitez, Sandra, Cadwell, Ken, Cai, Jingjing, Cai, Lu, Cai, Qian, Cairó, Montserrat, Calbet, Jose, Caldwell, Guy, Caldwell, Kim, Call, Jarrod, Calvani, Riccardo, Calvo, Ana, Calvo-Rubio Barrera, Miguel, Camara, Niels OS, Camonis, Jacques, Camougrand, Nadine, Campanella, Michelangelo, Campbell, Edward, Campbell-Valois, François-Xavier, Campello, Silvia, Campesi, Ilaria, Campos, Juliane, Camuzard, Olivier, Cancino, Jorge, Candido de Almeida, Danilo, Canesi, Laura, Caniggia, Isabella, Canonico, Barbara, Cantí, Carles, Cao, Bin, Caraglia, Michele, Caramés, Beatriz, Carchman, Evie, Cardenal-Muñoz, Elena, Cardenas, Cesar, Cardenas, Luis, Cardoso, Sandra, Carew, Jennifer, Carle, Georges, Carleton, Gillian, Carloni, Silvia, Carmona-Gutierrez, Didac, Carneiro, Leticia, Carnevali, Oliana, Carosi, Julian, Carra, Serena, Carrier, Alice, Carrier, Lucie, Carroll, Bernadette, Carter, A Brent, Carvalho, Andreia Neves, Casanova, Magali, Casas, Caty, Casas, Josefina, Cassioli, Chiara, Castillo, Eliseo, Castillo, Karen, Castillo-Lluva, Sonia, Castoldi, Francesca, Castori, Marco, Castro, Ariel, Castro-Caldas, Margarida, Castro-Hernandez, Javier, Castro-Obregon, Susana, Catz, Sergio, Cavadas, Claudia, Cavaliere, Federica, Cavallini, Gabriella, Cavinato, Maria, Cayuela, Maria, Cebollada Rica, Paula, Cecarini, Valentina, Cecconi, Francesco, Cechowska-Pasko, Marzanna, Cenci, Simone, Ceperuelo-Mallafré, Victòria, Cerqueira, João, Cerutti, Janete, Cervia, Davide, Cetintas, Vildan Bozok, Cetrullo, Silvia, Chae, Han-Jung, Chagin, Andrei, Chai, Chee-Yin, Chakrabarti, Gopal, Chakrabarti, Oishee, Chakraborty, Tapas, Chakraborty, Trinad, Chami, mounia, Chamilos, Georgios, Chan, David, Chan, Edmond, Chan, Edward, Chan, H.Y. Edwin, Chan, Helen, Chan, Hung, Chan, Matthew, Chan, Yau Sang, Chandra, Partha, Chang, Chih-Peng, Chang, Chunmei, Chang, Hao-Chun, Chang, Kai, Chao, Jie, Chapman, Tracey, Charlet-Berguerand, Nicolas, Chatterjee, Samrat, Chaube, Shail, Chaudhary, Anu, Chauhan, Santosh, Chaum, Edward, Checler, Frédéric, Cheetham, Michael, Chen, Chang-Shi, Chen, Guang-Chao, Chen, Jian-Fu, Chen, Liam, Chen, Leilei, Chen, Lin, Chen, Mingliang, Chen, Mu-Kuan, Chen, Ning, Chen, Quan, Chen, Ruey-Hwa, Chen, Shi, Chen, Wei, Chen, Weiqiang, Chen, Xin-Ming, Chen, Xiong-Wen, Chen, Xu, Chen, Yan, Chen, Ye-Guang, Chen, Yingyu, Chen, Yongqiang, Chen, Yu-Jen, Chen, Yue-Qin, Chen, Zhefan Stephen, Chen, Zhi, Chen, Zhi-Hua, Chen, Zhijian, Chen, Zhixiang, Cheng, Hanhua, Cheng, Jun, Cheng, Shi-Yuan, Cheng, Wei, Cheng, Xiaodong, Cheng, Xiu-Tang, Cheng, Yiyun, Cheng, Zhiyong, Chen, Zhong, Cheong, Heesun, Cheong, Jit Kong, Chernyak, Boris, Cherry, Sara, Cheung, Chi Fai Randy, Cheung, Chun Hei Antonio, Cheung, King-Ho, Chevet, Eric, Chi, Richard, Chiang, Alan Kwok Shing, Chiaradonna, Ferdinando, Chiarelli, Roberto, Chiariello, Mario, Chica, Nathalia, Chiocca, Susanna, Chiong, Mario, Chiou, Shih-Hwa, Chiramel, Abhilash, Chiurchiù, Valerio, Cho, Dong-Hyung, Choe, Seong-Kyu, Choi, Augustine, Choi, Mary, Choudhury, Kamalika Roy, Chow, Norman, Chu, Charleen, Chua, Jason, Chua, John Jia En, Chung, Hyewon, Chung, Kin Pan, Chung, Seockhoon, Chung, So-Hyang, Chung, Yuen-Li, Cianfanelli, Valentina, Ciechomska, Iwona, Cifuentes, Mariana, Cinque, Laura, Cirak, Sebahattin, Cirone, Mara, Clague, Michael, Clarke, Robert, Clementi, Emilio, Coccia, Eliana, Codogno, Patrice, Cohen, Ehud, Cohen, Mickael, Colasanti, Tania, Colasuonno, Fiorella, Colbert, Robert, Colell, Anna, Čolić, Miodrag, Coll, Nuria, Collins, Mark, Colombo, María, Colón-Ramos, Daniel, Combaret, Lydie, Comincini, Sergio, Cominetti, Márcia, Consiglio, Antonella, Conte, Andrea, Conti, Fabrizio, Contu, Viorica Raluca, Cookson, Mark, Coombs, Kevin, Coppens, Isabelle, Corasaniti, Maria Tiziana, Corkery, Dale, Cordes, Nils, Cortese, Katia, Costa, Maria do Carmo, Costantino, Sarah, Costelli, Paola, Coto-Montes, Ana, Crack, Peter, Crespo, Jose, Criollo, Alfredo, Crippa, Valeria, Cristofani, Riccardo, Csizmadia, Tamas, Cuadrado, Antonio, Cui, Bing, Cui, Jun, Cui, Yixian, Cui, Yong, Culetto, Emmanuel, Cumino, Andrea, Cybulsky, Andrey, Czaja, Mark, Czuczwar, Stanislaw, D'Adamo, Stefania, D'Amelio, Marcello, D'Arcangelo, Daniela, D'Lugos, Andrew, D'Orazi, Gabriella, da Silva, James, Dafsari, Hormos Salimi, Dagda, Ruben, Dagdas, Yasin, Daglia, Maria, Dai, Xiaoxia, Dai, Yun, Dai, Yuyuan, Dal Col, Jessica, Dalhaimer, Paul, Dalla Valle, Luisa, Dallenga, Tobias, Dalmasso, Guillaume, Damme, Markus, Dando, Ilaria, Dantuma, Nico, Darling, April, Das, Hiranmoy, Dasarathy, Srinivasan, Dasari, Santosh, Dash, Srikanta, Daumke, Oliver, Dauphinee, Adrian, Davies, Jeffrey, Dávila, Valeria, Davis, Roger, Davis, Tanja, Dayalan Naidu, Sharadha, De Amicis, Francesca, De Bosscher, Karolien, De Felice, Francesca, De Franceschi, Lucia, De Leonibus, Chiara, de Mattos Barbosa, Mayara, De Meyer, Guido, De Milito, Angelo, De Nunzio, Cosimo, De Palma, Clara, De Santi, Mauro, De Virgilio, Claudio, De Zio, Daniela, Debnath, Jayanta, DeBosch, Brian, Decuypere, Jean-Paul, Deehan, Mark, Deflorian, Gianluca, DeGregori, James, Dehay, Benjamin, Del Rio, Gabriel, Delaney, Joe, Delbridge, Lea, Delorme-Axford, Elizabeth, Delpino, M Victoria, Demarchi, Francesca, Dembitz, Vilma, Demers, Nicholas, Deng, Hongbin, Deng, Zhiqiang, Dengjel, Joern, Dent, Paul, Denton, Donna, DePamphilis, Melvin, Der, Channing, Deretic, Vojo, Descoteaux, Albert, Devis, Laura, Devkota, Sushil, Devuyst, Olivier, Dewson, Grant, Dharmasivam, Mahendiran, Dhiman, Rohan, di Bernardo, Diego, Di Cristina, Manlio, Di Domenico, Fabio, Di Fazio, Pietro, Di Fonzo, Alessio, Di Guardo, Giovanni, Di Guglielmo, Gianni, Di Leo, Luca, Di Malta, Chiara, Di Nardo, Alessia, Di Rienzo, Martina, Di Sano, Federica, Diallinas, George, Diao, Jiajie, Diaz-Araya, Guillermo, Díaz-Laviada, Inés, Dickinson, Jared, Diederich, Marc, Dieudé, Mélanie, Dikic, Ivan, Ding, Shiping, Ding, Wen-Xing, Dini, Luciana, Dinić, Jelena, Dinic, Miroslav, Dinkova-Kostova, Albena, Dionne, Marc, Distler, Jörg, Diwan, Abhinav, Dixon, Ian, Djavaheri-Mergny, Mojgan, Dobrinski, Ina, Dobrovinskaya, Oxana, Dobrowolski, Radek, Dobson, Renwick, Đokić, Jelena, Dokmeci Emre, Serap, Donadelli, Massimo, Dong, Bo, Dong, Xiaonan, Dong, Zhiwu, Dorn Ii, Gerald, Dotsch, Volker, Dou, Huan, Dou, Juan, Dowaidar, Moataz, Dridi, Sami, Drucker, Liat, Du, Ailian, Du, Caigan, Du, Guangwei, Du, Hai-Ning, Du, Li-Lin, du Toit, André, Duan, Shao-Bin, Duan, Xiaoqiong, Duarte, Sónia, Dubrovska, Anna, Dunlop, Elaine, Dupont, Nicolas, Durán, Raúl, Dwarakanath, Bilikere, Dyshlovoy, Sergey, Ebrahimi-Fakhari, Darius, Eckhart, Leopold, Edelstein, Charles, Efferth, Thomas, Eftekharpour, Eftekhar, Eichinger, Ludwig, Eid, Nabil, Eisenberg, Tobias, Eissa, N Tony, Eissa, Sanaa, Ejarque, Miriam, El Andaloussi, Abdeljabar, El-Hage, Nazira, El-Naggar, Shahenda, Eleuteri, Anna Maria, El-Shafey, Eman, Elgendy, Mohamed, Eliopoulos, Aristides, Elizalde, María, Elks, Philip, Elsasser, Hans-Peter, Elsherbiny, Eslam, Emerling, Brooke, Emre, N., Eng, Christina, Engedal, Nikolai, Engelbrecht, Anna-Mart, Engelsen, Agnete, Enserink, Jorrit, Escalante, Ricardo, Esclatine, Audrey, Escobar-Henriques, Mafalda, Eskelinen, Eeva-Liisa, Espert, Lucile, Eusebio, Makandjou-Ola, Fabrias, Gemma, Fabrizi, Cinzia, Facchiano, Antonio, Facchiano, Francesco, Fadeel, Bengt, Fader, Claudio, Faesen, Alex, Fairlie, W Douglas, Falcó, Alberto, Falkenburger, Bjorn, Fan, Daping, Fan, Jie, Fan, Yanbo, Fang, Evandro, Fang, Yanshan, Fang, Yognqi, Fanto, Manolis, Farfel-Becker, Tamar, Faure, Mathias, Fazeli, Gholamreza, Fedele, Anthony, Feldman, Arthur, Feng, Du, Feng, Jiachun, Feng, Lifeng, Feng, Yibin, Feng, Yuchen, Feng, Wei, Fenz Araujo, Thais, Ferguson, Thomas, Fernández, Álvaro, Fernandez-Checa, Jose, Fernández-Veledo, Sonia, Fernie, Alisdair, Ferrante, Anthony, Ferraresi, Alessandra, Ferrari, Merari, Ferreira, Julio, Ferro-Novick, Susan, Figueras, Antonio, Filadi, Riccardo, Filigheddu, Nicoletta, Filippi-Chiela, Eduardo, Filomeni, Giuseppe, Fimia, Gian Maria, Fineschi, Vittorio, Finetti, Francesca, Finkbeiner, Steven, Fisher, Edward, Fisher, Paul, Flamigni, Flavio, Fliesler, Steven, Flo, Trude, Florance, Ida, Florey, Oliver, Florio, Tullio, Fodor, Erika, Follo, Carlo, Fon, Edward, Forlino, Antonella, Fornai, Francesco, Fortini, Paola, Fracassi, Anna, Fraldi, Alessandro, Franco, Brunella, Franco, Rodrigo, Franconi, Flavia, Frankel, Lisa, Friedman, Scott, Fröhlich, Leopold, Frühbeck, Gema, Fuentes, Jose, Fujiki, Yukio, Fujita, Naonobu, Fujiwara, Yuuki, Fukuda, Mitsunori, Fulda, Simone, Furic, Luc, Furuya, Norihiko, Fusco, Carmela, Gack, Michaela, Gaffke, Lidia, Galadari, Sehamuddin, Galasso, Alessia, Galindo, Maria, Gallolu Kankanamalage, Sachith, Galluzzi, Lorenzo, Galy, Vincent, Gammoh, Noor, Gan, Boyi, Ganley, Ian, Gao, Feng, Gao, Hui, Gao, Minghui, Gao, Ping, Gao, Shou-Jiang, Gao, Wentao, Gao, Xiaobo, Garcera, Ana, Garcia, Maria Noé, Garcia, Verónica, García-del Portillo, Francisco, Garcia-Escudero, Vega, Garcia-Garcia, Aracely, Garcia-Macia, Marina, García-Moreno, Diana, Garcia-Ruiz, Carmen, García-Sanz, Patricia, Garg, Abhishek, Gargini, Ricardo, Garofalo, Tina, Garry, Robert, Gassen, Nils, Gatica, Damian, Ge, Liang, Ge, Wanzhong, Geiss-Friedlander, Ruth, Gelfi, Cecilia, Genschik, Pascal, Gentle, Ian, Gerbino, Valeria, Gerhardt, Christoph, Germain, Kyla, Germain, Marc, Gewirtz, David, Ghasemipour Afshar, Elham, Ghavami, Saeid, Ghigo, Alessandra, Ghosh, Manosij, Giamas, Georgios, Giampietri, Claudia, Giatromanolaki, Alexandra, Gibson, Gary, Gibson, Spencer, Ginet, Vanessa, Giniger, Edward, Giorgi, Carlotta, Girao, Henrique, Girardin, Stephen, Giridharan, Mridhula, Giuliano, Sandy, Giulivi, Cecilia, Giuriato, Sylvie, Giustiniani, Julien, Gluschko, Alexander, Goder, Veit, Goginashvili, Alexander, Golab, Jakub, Goldstone, David, Golebiewska, Anna, Gomes, Luciana, Gomez, Rodrigo, Gómez-Sánchez, Rubén, Gomez-Puerto, Maria Catalina, Gomez-Sintes, Raquel, Gong, Qingqiu, Goni, Felix, González-Gallego, Javier, Gonzalez-Hernandez, Tomas, Gonzalez-Polo, Rosa, Gonzalez-Reyes, Jose, González-Rodríguez, Patricia, Goping, Ing Swie, Gorbatyuk, Marina, Gorbunov, Nikolai, Görgülü, Kıvanç, Gorojod, Roxana, Gorski, Sharon, Goruppi, Sandro, Gotor, Cecilia, Gottlieb, Roberta, Gozes, Illana, Gozuacik, Devrim, Graef, Martin, Gräler, Markus, Granatiero, Veronica, Grasso, Daniel, Gray, Joshua, Green, Douglas, Greenhough, Alexander, Gregory, Stephen, Griffin, Edward, Grinstaff, Mark, Gros, Frederic, Grose, Charles, Gross, Angelina, Gruber, Florian, Grumati, Paolo, Grune, Tilman, Gu, Xueyan, Guan, Jun-Lin, Guardia, Carlos, Guda, Kishore, Guerra, Flora, Guerri, Consuelo, Guha, Prasun, Guillén, Carlos, Gujar, Shashi, Gukovskaya, Anna, Gukovsky, Ilya, Gunst, Jan, Günther, Andreas, Guntur, Anyonya, Guo, Chuanyong, Guo, Chun, Guo, Hongqing, Guo, Lian-Wang, Guo, Ming, Gupta, Pawan, Gupta, Shashi Kumar, Gupta, Swapnil, Gupta, Veer Bala, Gupta, Vivek, Gustafsson, Asa, Gutterman, David, H B, Ranjitha, Haapasalo, Annakaisa, Haber, James, Hać, Aleksandra, Hadano, Shinji, Hafrén, Anders, Haidar, Mansour, Hall, Belinda, Halldén, Gunnel, Hamacher-Brady, Anne, Hamann, Andrea, Hamasaki, Maho, Han, Weidong, Hansen, Malene, Hanson, Phyllis, Hao, Zijian, Harada, Masaru, Harhaji-Trajkovic, Ljubica, Hariharan, Nirmala, Haroon, Nigil, Harris, James, Hasegawa, Takafumi, Hasima Nagoor, Noor, Haspel, Jeffrey, Haucke, Volker, Hawkins, Wayne, Hay, Bruce, Haynes, Cole, Hayrabedyan, Soren, Hays, Thomas, He, Congcong, He, Qin, He, Rong-Rong, He, You-Wen, He, Yu-Ying, Heakal, Yasser, Heberle, Alexander, Hejtmancik, J Fielding, Helgason, Gudmundur Vignir, Henkel, Vanessa, Herb, Marc, Hergovich, Alexander, Herman-Antosiewicz, Anna, Hernández, Agustín, Hernandez, Carlos, Hernandez-Diaz, Sergio, Hernandez-Gea, Virginia, Herpin, Amaury, Herreros, Judit, Hervás, Javier, Hesselson, Daniel, Hetz, Claudio, Heussler, Volker, Higuchi, Yujiro, Hilfiker, Sabine, Hill, Joseph, Hlavacek, William, Ho, Emmanuel, Ho, Idy, Ho, Philip Wing-Lok, Ho, Shu-Leong, Ho, Wan Yun, Hobbs, G Aaron, Hochstrasser, Mark, Hoet, Peter, Hofius, Daniel, Hofman, Paul, Höhn, Annika, Holmberg, Carina, Hombrebueno, Jose, Yi-Ren Hong, Chang-Won Hong, Hooper, Lora, Hoppe, Thorsten, Horos, Rastislav, Hoshida, Yujin, Hsin, I-Lun, Hsu, Hsin-Yun, Hu, Bing, Hu, Dong, Hu, Li-Fang, Hu, Ming Chang, Hu, Ronggui, Hu, Wei, Hu, Yu-Chen, Hu, Zhuo-Wei, Hua, Fang, Hua, Jinlian, Hua, Yingqi, Huan, Chongmin, Huang, Canhua, Huang, Chuanshu, Huang, Chuanxin, Huang, Chunling, Huang, Haishan, Huang, Kun, Huang, Michael, Huang, Rui, Huang, Shan, Huang, Tianzhi, Huang, Xing, Huang, Yuxiang Jack, Huber, Tobias, Hubert, Virginie, Hubner, Christian, Hughes, Stephanie, Hughes, William, Humbert, Magali, Hummer, Gerhard, Hurley, James, Hussain, Sabah, Hussain, Salik, Hussey, Patrick, Hutabarat, Martina, Hwang, Hui-Yun, Hwang, Seungmin, Ieni, Antonio, Ikeda, Fumiyo, Imagawa, Yusuke, Imai, Yuzuru, Imbriano, Carol, Imoto, Masaya, Inman, Denise, Inoki, Ken, Iovanna, Juan, Iozzo, Renato, Ippolito, Giuseppe, Irazoqui, Javier, Iribarren, Pablo, Ishaq, Mohd, ISHIKAWA, Makoto, Ishimwe, Nestor, Isidoro, Ciro, Ismail, Nahed, Issazadeh-Navikas, Shohreh, Itakura, Eisuke, Ito, Daisuke, Ivankovic, Davor, Ivanova, Saška, Iyer, Anand Krishnan V, Izquierdo, José, Izumi, Masanori, Jäättelä, Marja, Jabir, Majid Sakhi, Jackson, William, Jacobo-Herrera, Nadia, Jacomin, Anne-Claire, Jacquin, Elise, Jadiya, Pooja, Jaeschke, Hartmut, Jagannath, Chinnaswamy, Jakobi, Arjen, Jakobsson, Johan, Janji, Bassam, Jansen-Dürr, Pidder, Jansson, Patric, Jantsch, Jonathan, Januszewski, Sławomir, Jassey, Alagie, Jean, Steve, Jeltsch-David, Hélène, Jendelova, Pavla, Jenny, Andreas, Jensen, Thomas, Jessen, Niels, Jewell, Jenna, Ji, Jing, Jia, Lijun, Jia, Rui, Jiang, Liwen, Jiang, Qing, Jiang, Richeng, Jiang, Teng, Jiang, Xuejun, Jiang, Yu, Jimenez-Sanchez, Maria, Jin, Eun-Jung, Jin, Fengyan, Jin, Hongchuan, Jin, Li, Jin, Luqi, Jin, Meiyan, Jin, Si, Jo, Eun-Kyeong, Joffre, Carine, Johansen, Terje, Johnson, Gail, Johnston, Simon, Jokitalo, Eija, Jolly, Mohit Kumar, Joosten, Leo, Jordan, Joaquin, Joseph, Bertrand, Ju, Dianwen, Ju, Jeong-Sun, Ju, Jingfang, Juárez, Esmeralda, Judith, Delphine, Juhász, Gábor, Jun, Youngsoo, Jung, Chang Hwa, Jung, Sung-Chul, Jung, Yong Keun, Jungbluth, Heinz, Jungverdorben, Johannes, Just, Steffen, Kaarniranta, Kai, Kaasik, Allen, Kabuta, Tomohiro, Kaganovich, Daniel, Kahana, Alon, Kain, Renate, Kajimura, Shinjo, Kalamvoki, Maria, Kalia, Manjula, Kalinowski, Danuta, Kaludercic, Nina, Kalvari, Ioanna, Kaminska, Joanna, Kaminskyy, Vitaliy, Kanamori, Hiromitsu, Kanasaki, Keizo, Kang, Chanhee, Kang, Rui, Kang, Sang Sun, Kaniyappan, Senthilvelrajan, 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Humberto, Roelofs, Jeroen, Rogers, Robert, Rogov, Vladimir, ROJO, Ana, Rolka, Krzysztof, Romanello, Vanina, Romani, Luigina, Romano, Alessandra, Romano, Patricia, Romeo-Guitart, David, Romero, Luis, Romero, Montserrat, Roney, Joseph, Rongo, Christopher, Roperto, Sante, Rosenfeldt, Mathias, Rosenstiel, Philip, Rosenwald, Anne, Roth, Kevin, Roth, Lynn, Roth, Steven, Rouschop, Kasper, Roussel, Benoit, Roux, Sophie, Rovere-Querini, Patrizia, Roy, Ajit, Rozieres, Aurore, Ruano, Diego, Rubinsztein, David, Rubtsova, Maria, Ruckdeschel, Klaus, Ruckenstuhl, Christoph, Rudolf, Emil, Rudolf, Rüdiger, Ruggieri, Alessandra, Ruparelia, Avnika Ashok, Rusmini, Paola, Russell, Ryan, Russo, Gian Luigi, Russo, Maria, Russo, Rossella, Ryabaya, Oxana, Ryan, Kevin, Ryu, Kwon-Yul, Sabater-Arcis, Maria, Sachdev, Ulka, Sacher, Michael, Sachse, Carsten, Sadhu, Abhishek, Sadoshima, Junichi, Safren, Nathaniel, Saftig, Paul, Sagona, Antonia, Sahay, Gaurav, Sahebkar, Amirhossein, Sahin, Mustafa, Sahin, Ozgur, Sahni, Sumit, Saito, Nayuta, Saito, Shigeru, Saito, Tsunenori, Sakai, Ryohei, Sakai, Yasuyoshi, Sakamaki, Jun-Ichi, Saksela, Kalle, Salazar, Gloria, Salazar-Degracia, Anna, Salekdeh, Ghasem, Saluja, Ashok, Sampaio-Marques, Belém, Sanchez, Maria Cecilia, Sanchez-Alcazar, Jose, Sanchez-Vera, Victoria, Sancho-Shimizu, Vanessa, Sanderson, J Thomas, Sandri, Marco, Santaguida, Stefano, Santambrogio, Laura, Santana, Magda, Santoni, Giorgio, Sanz, Alberto, Sanz, Pascual, Saran, Shweta, Sardiello, Marco, Sargeant, Timothy, Sarin, Apurva, Sarkar, Chinmoy, Sarkar, Sovan, Sarrias, Maria-Rosa, Sarkar, Surajit, Sarmah, Dipanka Tanu, Sarparanta, Jaakko, Sathyanarayan, Aishwarya, Sathyanarayanan, Ranganayaki, Scaglione, K Matthew, Scatozza, Francesca, Schaefer, Liliana, Schafer, Zachary, Schaible, Ulrich, Schapira, Anthony, Scharl, Michael, Schatzl, Hermann, Schein, Catherine, Scheper, Wiep, Scheuring, David, Schiaffino, Maria Vittoria, Schiappacassi, Monica, Schindl, Rainer, Schlattner, Uwe, Schmidt, Oliver, Schmitt, Roland, Schmidt, Stephen, Schmitz, Ingo, Schmukler, Eran, Schneider, Anja, Schneider, Bianca, Schober, Romana, Schoijet, Alejandra, Schott, Micah, Schramm, Michael, Schröder, Bernd, Schuh, Kai, Schüller, Christoph, Schulze, Ryan, Schürmanns, Lea, Schwamborn, Jens, Schwarten, Melanie, Scialo, Filippo, Sciarretta, Sebastiano, Scott, Melanie, Scotto, Kathleen, Scovassi, A Ivana, Scrima, Andrea, Scrivo, Aurora, Sebastian, David, Sebti, Salwa, Sedej, Simon, Segatori, Laura, Segev, Nava, Seglen, Per, Seiliez, Iban, Seki, Ekihiro, Selleck, Scott, Sellke, Frank, Selsby, Joshua, Sendtner, Michael, Senturk, Serif, Seranova, Elena, Sergi, Consolato, Serra-Moreno, Ruth, Sesaki, Hiromi, Settembre, Carmine, Setty, Subba Rao Gangi, Sgarbi, Gianluca, Sha, Ou, Shacka, John, Shah, Javeed, Shang, Dantong, Shao, Changshun, Shao, Feng, Sharbati, Soroush, Sharkey, Lisa, Sharma, Dipali, Sharma, Gaurav, Sharma, Kulbhushan, Sharma, Pawan, Sharma, Surendra, Shen, Han-Ming, Shen, Hongtao, Shen, Jiangang, Shen, Ming, Shen, Weili, Shen, Zheni, Sheng, Rui, Sheng, Zhi, Sheng, Zu-Hang, Shi, Jianjian, Shi, Xiaobing, Shi, Ying-Hong, Shiba-Fukushima, Kahori, Shieh, Jeng-Jer, Shimada, Yohta, Shimizu, Shigeomi, Shimozawa, Makoto, Shintani, Takahiro, Shoemaker, Christopher, Shojaei, Shahla, Shoji, Ikuo, Shravage, Bhupendra, Shridhar, Viji, Shu, Chih-Wen, Shu, Hong-Bing, Shui, Ke, Shukla, Arvind, Shutt, Timothy, Sica, Valentina, Siddiqui, Aleem, Sierra, Amanda, Sierra-Torre, Virginia, Signorelli, Santiago, Sil, Payel, Silva, Bruno, Silva, Johnatas, Silva-Pavez, Eduardo, Silvente-Poirot, Sandrine, Simmonds, Rachel, Simon, Anna Katharina, Simon, Hans-Uwe, Simons, Matias, Singh, Anurag, Singh, Lalit, Singh, Rajat, Singh, Shivendra, Singh, Shrawan, Singh, Sudha, Singh, Sunaina, Singh, Surinder Pal, Sinha, Debasish, Sinha, Rohit Anthony, Sinha, Sangita, Sirko, Agnieszka, Sirohi, Kapil, Sivridis, Efthimios, Skendros, Panagiotis, Skirycz, Aleksandra, Slaninová, Iva, Smaili, Soraya, Smertenko, Andrei, Smith, Matthew, Soenen, Stefaan, Sohn, Eun Jung, Sok, Sophia, Solaini, Giancarlo, Soldati, Thierry, Soleimanpour, Scott, Soler, Rosa, Solovchenko, Alexei, Somarelli, Jason, Sonawane, Avinash, Song, Fuyong, Song, Hyun Kyu, Song, Ju-Xian, Song, Kunhua, Song, Zhiyin, Soria, Leandro, Sorice, Maurizio, Soukas, Alexander, Soukup, Sandra-Fausia, Sousa, Diana, Sousa, Nadia, Spagnuolo, Paul, Spector, Stephen, Srinivas Bharath, M., St Clair, Daret, Stagni, Venturina, Staiano, Leopoldo, Stalnecker, Clint, Stankov, Metodi, Stathopulos, Peter, Stefan, Katja, Stefan, Sven Marcel, Stefanis, Leonidas, Steffan, Joan, Steinkasserer, Alexander, Stenmark, Harald, Sterneckert, Jared, Stevens, Craig, Stoka, Veronika, Storch, Stephan, Stork, Björn, Strappazzon, Flavie, Strohecker, Anne Marie, Stupack, Dwayne, Su, Huanxing, Su, Ling-Yan, Su, Longxiang, Suarez-Fontes, Ana, Subauste, Carlos, Subbian, Selvakumar, Subirada, Paula, Sudhandiran, Ganapasam, Sue, Carolyn, Sui, Xinbing, Summers, Corey, Sun, Guangchao, Sun, Jun, SUN, Kang, Sun, Meng-xiang, Sun, Qiming, Sun, Yi, Sun, Zhongjie, Sunahara, Karen, Sundberg, Eva, Susztak, Katalin, Sutovsky, Peter, Suzuki, Hidekazu, Sweeney, Gary, Symons, J David, Sze, Stephen Cho Wing, Szewczyk, Nathaniel, Tabęcka-Łonczynska, Anna, Tabolacci, Claudio, Tacke, Frank, Taegtmeyer, Heinrich, Tafani, Marco, Tagaya, Mitsuo, Tai, Haoran, Tait, Stephen, Takahashi, Yoshinori, Takats, Szabolcs, Talwar, Priti, Tam, Chit, Tam, Shing Yau, Tampellini, Davide, Tamura, Atsushi, Tan, Chong Teik, Tan, Eng-King, Tan, Ya-Qin, Tanaka, Masaki, Tanaka, Motomasa, Tang, Daolin, Tang, Jingfeng, Tang, Tie-Shan, Tanida, Isei, Tao, Zhipeng, Taouis, Mohammed, Tatenhorst, Lars, Tavernarakis, Nektarios, Taylor, Allen, Taylor, Gregory, Taylor, Joan, Tchetina, Elena, Tee, Andrew, Tegeder, Irmgard, Teis, David, Teixeira, Natercia, Teixeira-Clerc, Fatima, Tekirdag, Kumsal, Tencomnao, Tewin, Tenreiro, Sandra, Tepikin, Alexei, Testillano, Pilar, Tettamanti, Gianluca, Tharaux, Pierre-Louis, Thedieck, Kathrin, Thekkinghat, Arvind, Thellung, Stefano, Thinwa, Josephine, Thirumalaikumar, V.P., Thomas, Sufi Mary, Thomes, Paul, Thorburn, Andrew, Thukral, Lipi, Thum, Thomas, Thumm, Michael, Tian, Ling, Tichy, Ales, Till, Andreas, Timmerman, Vincent, Titorenko, Vladimir, Todi, Sokol, Todorova, Krassimira, Toivonen, Janne, Tomaipitinca, Luana, Tomar, Dhanendra, Tomas-Zapico, Cristina, Tomić, Sergej, Tong, Benjamin Chun-Kit, Tong, Chao, Tong, Xin, Tooze, Sharon, Torgersen, Maria, Torii, Satoru, Torres-López, Liliana, Torriglia, Alicia, Towers, Christina, Towns, Roberto, Toyokuni, Shinya, Trajkovic, Vladimir, Tramontano, Donatella, Tran, Quynh-Giao, Travassos, Leonardo, Trelford, Charles, Tremel, Shirley, Trougakos, Ioannis, Tsao, Betty, Tschan, Mario, Tse, Hung-Fat, Tse, Tak Fu, Tsugawa, Hitoshi, Tsvetkov, Andrey, Tumbarello, David, Tumtas, Yasin, Tuñón, María, Turcotte, Sandra, Turk, Boris, Turk, Vito, Turner, Bradley, Tuxworth, Richard, Tyler, Jessica, Tyutereva, Elena, Uchiyama, Yasuo, Ugun-Klusek, Aslihan, Uhlig, Holm, Ułamek-Kozioł, Marzena, Ulasov, Ilya, Umekawa, Midori, Ungermann, Christian, Unno, Rei, Urbe, Sylvie, Uribe-Carretero, Elisabet, Üstün, Suayib, Uversky, Vladimir, Vaccari, Thomas, Vaccaro, Maria, Vahsen, Björn, Vakifahmetoglu-Norberg, Helin, Valdor, Rut, Valente, Maria, Valko, Ayelén, Vallee, Richard, Valverde, Angela, Van Den Berghe, Greet, van der Veen, Stijn, Van Kaer, Luc, van Loosdregt, Jorg, van Wijk, Sjoerd, Vandenberghe, Wim, Vanhorebeek, Ilse, Vannier-Santos, Marcos, Vannini, Nicola, Vanrell, M Cristina, Vantaggiato, Chiara, Varano, Gabriele, Varela-Nieto, Isabel, Varga, Máté, Vasconcelos, M Helena, Vats, Somya, Vavvas, Demetrios, Vega-Naredo, Ignacio, Vega-Rubin-de-Celis, Silvia, Velasco, Guillermo, Velázquez, Ariadna, Vellai, Tibor, Vellenga, Edo, Velotti, Francesca, Verdier, Mireille, Verginis, Panayotis, Vergne, Isabelle, Verkade, Paul, Verma, Manish, Verstreken, Patrik, Vervliet, Tim, Vervoorts, Jörg, Vessoni, Alexandre, Victor, Victor, Vidal, Michel, Vidoni, Chiara, Vieira, Otilia, Vierstra, Richard, Viganó, Sonia, Vihinen, Helena, Vijayan, Vinoy, Vila, Miquel, Vilar, Marçal, Villalba, José, Villalobo, Antonio, Villarejo-Zori, Beatriz, Villarroya, Francesc, Villarroya, Joan, Vincent, Olivier, Vindis, Cecile, Viret, Christophe, Viscomi, Maria Teresa, Visnjic, Dora, Vitale, Ilio, Vocadlo, David, Voitsekhovskaja, Olga, Volonté, Cinzia, Volta, Mattia, Vomero, Marta, Von Haefen, Clarissa, Vooijs, Marc, Voos, Wolfgang, Vucicevic, Ljubica, Wade-Martins, Richard, Waguri, Satoshi, Waite, Kenrick, Wakatsuki, Shuji, Walker, David, Walker, Mark, Walker, Simon, Walter, Jochen, Wandosell, Francisco, Wang, Bo, Wang, Chao-Yung, Wang, Chen, Wang, Chenran, Wang, Chenwei, Wang, Cun-Yu, Wang, Dong, Wang, Fangyang, Wang, Feng, Wang, Fengming, Wang, Guansong, Wang, Han, Wang, Hao, Wang, Hexiang, Wang, Hong-Gang, Wang, Jianrong, Wang, Jigang, Wang, Jiou, Wang, Jundong, Wang, Kui, Wang, Lianrong, Wang, Liming, Wang, Maggie Haitian, Wang, Meiqing, Wang, Nanbu, Wang, PengWei, Wang, PeiPei, Wang, Ping, Wang, Qing Jun, Wang, Qing, Wang, Qing Kenneth, Wang, Qiong, Wang, Wen-Tao, Wang, Wuyang, Wang, Xinnan, Wang, Xuejun, Wang, Yan, Wang, Yanchang, Wang, Yanzhuang, Wang, Yen-Yun, Wang, Yihua, Wang, Yipeng, Wang, Yu, wang, yuqi, Wang, Zhe, Wang, Zhenyu, Wang, Zhouguang, Warnes, Gary, Warnsmann, Verena, Watada, Hirotaka, Watanabe, Eizo, Watchon, Maxinne, Wawrzyńska, Anna, Weaver, Timothy, Wegrzyn, Grzegorz, Wehman, Ann, Wei, Huafeng, Wei, Lei, Wei, Taotao, Wei, Yongjie, Weiergräber, Oliver, Weihl, Conrad, Weindl, Günther, Weiskirchen, Ralf, Wells, Alan, Wen, Runxia, Wen, Xin, Werner, Antonia, Weykopf, Beatrice, Wheatley, Sally, Whitton, J Lindsay, Whitworth, Alexander, Wiktorska, Katarzyna, Wildenberg, Manon, Wileman, Tom, Wilkinson, Simon, Willbold, Dieter, Williams, Brett, Williams, Robin, Williams, Roger, Williamson, Peter, Wilson, Richard, Winner, Beate, Winsor, Nathaniel, Witkin, Steven, Wodrich, Harald, Woehlbier, Ute, Wollert, Thomas, Wong, Esther, Wong, Jack Ho, Wong, Richard, Wong, Vincent Kam Wai, Wong, W Wei-Lynn, Wu, An-Guo, Wu, Chengbiao, Wu, Jian, Wu, Junfang, Wu, Kenneth, Wu, Min, Wu, Shan-Ying, Wu, Shengzhou, Wu, Shu-Yan, Wu, Shufang, Wu, William, Wu, Xiaohong, Wu, Xiaoqing, Wu, Yao-Wen, Wu, Yihua, Xavier, Ramnik, Xia, Hongguang, Xia, Lixin, Xia, Zhengyuan, Xiang, Ge, Xiang, Jin, Xiang, Mingliang, Xiang, Wei, Xiao, Bin, Xiao, Guozhi, Xiao, Hengyi, Xiao, Hong-tao, Xiao, Jian, Xiao, Lan, Xiao, Shi, Xiao, Yin, Xie, Baoming, Xie, Chuan-Ming, Xie, Min, Xie, Yuxiang, Xie, Zhiping, Xie, Zhonglin, Xilouri, Maria, Xu, Congfeng, Xu, En, Xu, Haoxing, Xu, Jing, Xu, Jinrong, Xu, Liang, Xu, Wen Wen, Xu, Xiulong, Xue, Yu, Yakhine-Diop, Sokhna, Yamaguchi, Masamitsu, Yamaguchi, Osamu, Yamamoto, Ai, Yamashina, Shunhei, Yan, Shengmin, Yan, Shian-Jang, Yan, Zhen, Yanagi, Yasuo, Yang, Chuanbin, Yang, Dun-Sheng, Yang, Huan, Yang, Huang-Tian, Yang, Hui, Yang, Jin-Ming, Yang, Jing, Yang, Jingyu, Yang, Ling, Yang, Liu, Yang, Ming, Yang, Pei-Ming, Yang, Qian, Yang, Seungwon, Yang, Shu, Yang, Shun-Fa, Yang, Wannian, Yang, Wei Yuan, Yang, Xiaoyong, Yang, Xuesong, Yang, Yi, Yang, Ying, Yao, Honghong, Yao, Shenggen, Yao, Xiaoqiang, Yao, Yong-Gang, Yao, Yong-Ming, Yasui, Takahiro, Yazdankhah, Meysam, Yen, Paul, Yi, Cong, Yin, Xiao-Ming, Yin, Yanhai, Yin, Zhangyuan, Yin, Ziyi, Ying, Meidan, Ying, Zheng, Yip, Calvin, Yiu, Stephanie Pei Tung, Yoo, Young, Yoshida, Kiyotsugu, Yoshii, Saori, Yoshimori, Tamotsu, Yousefi, Bahman, Yu, Boxuan, Yu, Haiyang, Yu, Jun, Yu, Li, Yu, Ming-Lung, Yu, Seong-Woon, Yu, Victor, Yu, W Haung, Yu, Zhengping, Yu, Zhou, Yuan, Junying, Yuan, Ling-Qing, Yuan, Shilin, Yuan, Shyng-Shiou, Yuan, Yanggang, Yuan, Zengqiang, Yue, Jianbo, Yue, Zhenyu, Yun, Jeanho, Yung, Raymond, Zacks, David, Zaffagnini, Gabriele, Zambelli, Vanessa, Zanella, Isabella, Zang, Qun, Zanivan, Sara, Zappavigna, Silvia, Zaragoza, Pilar, Zarbalis, Konstantinos, Zarebkohan, Amir, Zarrouk, Amira, Zeitlin, Scott, Zeng, Jialiu, Zeng, Ju-deng, Žerovnik, Eva, Zhan, Lixuan, Zhang, Bin, Zhang, Donna, Zhang, Hanlin, Zhang, Hong, Zhang, Honghe, Zhang, Huafeng, Zhang, Huaye, Zhang, Hui, Zhang, Hui-Ling, Zhang, Jianbin, Zhang, Jianhua, Zhang, Jing-Pu, Zhang, Kalin, Zhang, Leshuai, Zhang, Lin, Zhang, Lisheng, Zhang, Lu, Zhang, Luoying, Zhang, Menghuan, Zhang, Peng, Zhang, Sheng, Zhang, Wei, Zhang, Xiangnan, Zhang, Xiao-Wei, Zhang, Xiaolei, Zhang, Xiaoyan, Zhang, Xin, Zhang, Xinxin, Zhang, Xu Dong, Zhang, Yang, Zhang, Yanjin, Zhang, Yi, Zhang, Ying-Dong, Zhang, Yingmei, Zhang, Yuan-Yuan, Zhang, Yuchen, Zhang, Zhe, Zhang, Zhengguang, Zhang, Zhibing, Zhang, Zhihai, Zhang, Zhiyong, Zhang, Zili, Zhao, Haobin, Zhao, Lei, Zhao, Shuang, Zhao, Tongbiao, Zhao, Xiao-Fan, Zhao, Ying, Zhao, Yongchao, Zhao, Yongliang, Zhao, Yuting, Zheng, Guoping, Zheng, Kai, Zheng, Ling, Zheng, Shizhong, Zheng, Xi-Long, Zheng, Yi, Zheng, Zu-Guo, Zhivotovsky, Boris, Zhong, Qing, Zhou, Ao, Zhou, Ben, Zhou, Cefan, ZHOU, Gang, Zhou, Hao, Zhou, Hong, Zhou, Hongbo, Zhou, Jie, Zhou, Jing, Zhou, Jiyong, Zhou, Kailiang, Zhou, Rongjia, Zhou, Xu-jie, Zhou, Yanshuang, Zhou, Yinghong, Zhou, Yubin, Zhou, Zheng-Yu, Zhou, Zhou, Zhu, Binglin, Zhu, Changlian, Zhu, Guo-Qing, Zhu, Haining, Zhu, Hongxin, Zhu, Hua, Zhu, Wei-Guo, Zhu, Yanping, Zhu, Yushan, Zhuang, Haixia, Zhuang, Xiaohong, Zientara-Rytter, Katarzyna, Zimmermann, Christine, Ziviani, Elena, Zoladek, Teresa, Zong, Wei-Xing, Zorov, Dmitry, Zorzano, Antonio, Zou, Weiping, Zou, Zhen, Zou, Zhengzhi, Zuryn, Steven, Zwerschke, Werner, Brand-Saberi, Beate, Dong, X Charlie, Kenchappa, Chandra Shekar, Li, Zuguo, Lin, Yong, Oshima, Shigeru, Rong, Yueguang, Sluimer, Judith, Stallings, Christina, Tong, Chun-Kit, Ahmad, S. Tariq, Alim Al-Bari, M. Abdul, Bechara, Luiz R.G., Behrens, Georg M.N., Bhuiyan, Md. Shenuarin, Broaddus, V. Courtney, Buchan, J. Ross, Burón, M. Isabel, Carter, A. Brent, Chan, Matthew T.V., Choi, Augustine M.K., D’Adamo, Stefania, D’Amelio, Marcello, D’Arcangelo, Daniela, D’Lugos, Andrew, D’Orazi, Gabriella, De Meyer, Guido R.Y., Delpino, M. Victoria, Distler, Jörg H.W., Dixon, Ian M.C., Dobson, Renwick C.J., 2nd Dorn, Gerald, Eissa, N. Tony, Engelsen, Agnete S.T., Fairlie, W. Douglas, Ferreira, Julio C.B., H.B., Ranjitha, Hanson, Phyllis I., Hejtmancik, J. Fielding, Ho, Idy H.T., Hobbs, G. Aaron, Hoet, Peter H.M., Huang, Michael L.H., Iyer, Anand Krishnan V., Johnson, Gail V.W., Joosten, Leo A.B., Karim, Md. Razaul, Kaufmann, Stefan H.E., Ko, Ben C.B., Leck, Lionel Y.W., Lima, Thania R.R., Livingston, J. Andrew, Martin, Alexandre P.J., Montes, L. Ruth, Murphy, J. Patrick, Ng, Charlene C.W., Nicolao, M. 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Charlie, Ain Shams University [ASU], Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University [JGU], Medical University Graz, Centre de Recherche des Cordeliers [CRC (UMR_S_1138 / U1138)], Institut Pasteur d'Iran, Leibniz Institute of Plant Biochemistry [IPB], The University of Texas M.D. Anderson Cancer Center [Houston], Institut de pharmacologie moléculaire et cellulaire [IPMC], Lipides - Nutrition - Cancer [Dijon - U1231] [LNC], Centre méditerranéen de médecine moléculaire [C3M], Institut de Biologie Valrose [IBV], Petites Molécules de neuroprotection, neurorégénération et remyélinisation, Signalisation Hormonale, Physiopathologie Endocrinienne et Métabolique, Institut Cochin [IC UM3 (UMR 8104 / U1016)], Institut NeuroMyoGène [INMG], Paris-Centre de Recherche Cardiovasculaire [PARCC (UMR_S 970/ U970)], Marqueurs cardiovasculaires en situation de stress [MASCOT (UMR_S_942 / U942)], Institut de Recherche sur le Cancer et le Vieillissement [IRCAN], Centre de Recherche en Cancérologie de Marseille [CRCM], Centre for Integrative Biology - CBI [Inserm U964 - CNRS UMR7104 - IGBMC], Oncogenesis, Stress, Signaling [OSS], Institut Necker Enfants-Malades [INEM - UM 111 (UMR 8253 / U1151)], Institut de Biologie Intégrative de la Cellule [I2BC], Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte [M2iSH], Centre de Recherches en Cancérologie de Toulouse [CRCT], Physiopathologie et traitement des maladies du foie, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 [CIIL], Institut de Génétique et de Biologie Moléculaire et Cellulaire [IGBMC], Laboratoire Bio-PeroxIL. Biochimie du peroxysome, inflammation et métabolisme lipidique [Dijon] [BIO-PEROXIL], Centre de recherche sur l'Inflammation [CRI (UMR_S_1149 / ERL_8252 / U1149)], Unité de génétique et biologie des cancers [U830], Laboratoire d'Optique et Biosciences [LOB], Institut des Maladies Métaboliques et Casdiovasculaires [UPS/Inserm U1297 - I2MC], Différenciation et communication neuronale et neuroendocrine [DC2N], Institut de Recherche en Cancérologie de Montpellier [IRCM - U1194 Inserm - UM], Centre d'Immunologie de Marseille - Luminy [CIML], Physiopathologie et imagerie des troubles neurologiques [PhIND], Laboratory of Fundamental and Applied Bioenergetics = Laboratoire de bioénergétique fondamentale et appliquée [LBFA], Imagine - Institut des maladies génétiques (IHU) [Imagine - U1163], Institut Mondor de Recherche Biomédicale [IMRB], Franco-czech Laboratory for clinical research on obesity, University of Michigan [Ann Arbor], University of Michigan System, Institut de pharmacologie moléculaire et cellulaire (IPMC), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Université Côte d'Azur (UCA), Lipides - Nutrition - Cancer [Dijon - U1231] (LNC), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre méditerranéen de médecine moléculaire (C3M), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA), Institut de Biologie Valrose (IBV), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Sud - Paris 11 (UP11), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université de Paris (UP), Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Nutrition, Métabolisme, Aquaculture (NuMéA), Université de Pau et des Pays de l'Adour (UPPA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut NeuroMyoGène (INMG), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Institut de Recherche sur le Cancer et le Vieillissement (IRCAN), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre de Recherche en Cancérologie de Marseille (CRCM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), Centre for Integrative Biology - CBI (Inserm U964 - CNRS UMR7104 - IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institute of genetics and molecular and cellular biology-Centre National de la Recherche Scientifique (CNRS), Chemistry, Oncogenesis, Stress and Signaling (COSS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-CRLCC Eugène Marquis (CRLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Necker Enfants-Malades (INEM - UM 111 (UMR 8253 / U1151)), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte (M2iSH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre de Recherche en Nutrition Humaine d'Auvergne (CRNH d'Auvergne)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Centre International de Recherche en Infectiologie - UMR (CIRI), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie et Génomique des Poissons (LPGP), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Laboratoire Bio-PeroxIL. Biochimie du peroxysome, inflammation et métabolisme lipidique [Dijon] (BIO-PEROXIL), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre de recherche sur l'Inflammation (CRI (UMR_S_1149 / ERL_8252 / U1149)), Institut Jean-Pierre Bourgin (IJPB), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de génétique et biologie des cancers (U830), Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Optique et Biosciences (LOB), École polytechnique (X)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Différenciation et communication neuronale et neuroendocrine (DC2N), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Laboratory of Fundamental and Applied Bioenergetics = Laboratoire de bioénergétique fondamentale et appliquée (LBFA), Université Grenoble Alpes (UGA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epithelial biology and disease - Liliane Bettencourt Chair of Developmental Biology (Equipe Inserm U1163), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Biomécanique cellulaire et respiratoire (BCR), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Charles University [Prague]-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was supported by the National Institute of General Medical Sciences [GM131919]., Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM), Marqueurs cardiovasculaires en situation de stress (MASCOT (UMR_S_942 / U942)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie des Adaptations Nutritionnelles (PhAN), Université de Nantes (UN)-Institut National de la Recherche Agronomique (INRA), Département Plateforme (PF I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut Gustave Roussy (IGR), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Chinese Academy of Medical Sciences [Suzhou, Chine] (CAMS), Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], Department of Women's and Children's Health [Stockholm, Sweden], Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École polytechnique (X), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, FHU OncoAge - Pathologies liées à l’âge [CHU Nice] (OncoAge), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Institut de Pharmacologie Moléculaire et Cellulaire [UNIV Côte d'Azur] (UPMC), Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM), Life Sciences Institute [Ann Arbor, MI, USA], University of Michigan System-University of Michigan System, European Institute of Oncology IRCCS [Milan, Italy] (EIO), Ain Shams University (ASU), Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Réseau International des Instituts Pasteur (RIIP), Leibniz Institute of Plant Biochemistry (IPB), Hebrew University of Jerusalem, Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Oncogenesis, Stress, Signaling (OSS), Institut des Maladies Métaboliques et Casdiovasculaires (UPS/Inserm U1297 - I2MC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Charles University [Prague] (CU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Klionsky, D. J., Abdel-Aziz, A. K., Abdelfatah, S., Abdellatif, M., Abdoli, A., Abel, S., Abeliovich, H., Abildgaard, M. H., Abudu, Y. P., Acevedo-Arozena, A., Adamopoulos, I. E., Adeli, K., Adolph, T. E., Adornetto, A., Aflaki, E., Agam, G., Agarwal, A., Aggarwal, B. B., Agnello, M., Agostinis, P., Agrewala, J. N., Agrotis, A., Aguilar, P. V., Ahmad, S. T., Ahmed, Z. M., Ahumada-Castro, U., Aits, S., Aizawa, S., Akkoc, Y., Akoumianaki, T., Akpinar, H. A., Al-Abd, A. M., Al-Akra, L., Al-Gharaibeh, A., Alaoui-Jamali, M. A., Alberti, S., Alcocer-Gomez, E., Alessandri, C., Ali, M., Alim Al-Bari, M. A., Aliwaini, S., Alizadeh, J., Almacellas, E., Almasan, A., Alonso, A., Alonso, G. D., Altan-Bonnet, N., Altieri, D. C., Alvarez, E. M. C., Alves, S., Alves da Costa, C., Alzaharna, M. M., Amadio, M., Amantini, C., Amaral, C., Ambrosio, S., Amer, A. O., Ammanathan, V., An, Z., Andersen, S. U., Andrabi, S. A., Andrade-Silva, M., Andres, A. M., Angelini, S., Ann, D., Anozie, U. C., Ansari, M. Y., Antas, P., Antebi, A., Anton, Z., Anwar, T., Apetoh, L., Apostolova, N., Araki, T., Araki, Y., Arasaki, K., Araujo, W. L., Araya, J., Arden, C., Arevalo, M. -A., Arguelles, S., Arias, E., Arikkath, J., Arimoto, H., Ariosa, A. R., Armstrong-James, D., Arnaune-Pelloquin, L., Aroca, A., Arroyo, D. S., Arsov, I., Artero, R., Asaro, D. M. L., Aschner, M., Ashrafizadeh, M., Ashur-Fabian, O., Atanasov, A. G., Au, A. K., Auberger, P., Auner, H. W., Aurelian, L., Autelli, R., Avagliano, L., Avalos, Y., Aveic, S., Aveleira, C. A., Avin-Wittenberg, T., Aydin, Y., Ayton, S., Ayyadevara, S., Azzopardi, M., Baba, M., Backer, J. M., Backues, S. K., Bae, D. -H., Bae, O. -N., Bae, S. H., Baehrecke, E. H., Baek, A., Baek, S. -H., Baek, S. H., Bagetta, G., Bagniewska-Zadworna, A., Bai, H., Bai, J., Bai, X., Bai, Y., Bairagi, N., Baksi, S., Balbi, T., Baldari, C. T., Balduini, W., Ballabio, A., Ballester, M., Balazadeh, S., Balzan, R., Bandopadhyay, R., Banerjee, S., Banreti, A., Bao, Y., Baptista, M. S., Baracca, A., Barbati, C., Bargiela, A., Barila, D., Barlow, P. G., Barmada, S. J., Barreiro, E., Barreto, G. E., Bartek, J., Bartel, B., Bartolome, A., Barve, G. R., Basagoudanavar, S. H., Bassham, D. C., Bast, R. C., Basu, A., Batoko, H., Batten, I., Baulieu, E. E., Baumgarner, B. L., Bayry, J., Beale, R., Beau, I., Beaumatin, F., Bechara, L. R. G., Beck, G. R., Beers, M. F., Begun, J., Behrends, C., Behrens, G. M. N., Bei, R., Bejarano, E., Bel, S., Behl, C., Belaid, A., Belgareh-Touze, N., Bellarosa, C., Belleudi, F., Bello Perez, M., Bello-Morales, R., Beltran, J. S. D. O., Beltran, S., Benbrook, D. M., Bendorius, M., Benitez, B. A., Benito-Cuesta, I., Bensalem, J., Berchtold, M. W., Berezowska, S., Bergamaschi, D., Bergami, M., Bergmann, A., Berliocchi, L., Berlioz-Torrent, C., Bernard, A., Berthoux, L., Besirli, C. G., Besteiro, S., Betin, V. M., Beyaert, R., Bezbradica, J. S., Bhaskar, K., Bhatia-Kissova, I., Bhattacharya, R., Bhattacharya, S., Bhattacharyya, S., Bhuiyan, M. S., Bhutia, S. K., Bi, L., Bi, X., Biden, T. J., Bijian, K., Billes, V. A., Binart, N., Bincoletto, C., Birgisdottir, A. B., Bjorkoy, G., Blanco, G., Blas-Garcia, A., Blasiak, J., Blomgran, R., Blomgren, K., Blum, J. S., Boada-Romero, E., Boban, M., Boesze-Battaglia, K., Boeuf, P., Boland, B., Bomont, P., Bonaldo, P., Bonam, S. R., Bonfili, L., Bonifacino, J. S., Boone, B. A., Bootman, M. D., Bordi, M., Borner, C., Bornhauser, B. C., Borthakur, G., Bosch, J., Bose, S., Botana, L. M., Botas, J., Boulanger, C. M., Boulton, M. E., Bourdenx, M., Bourgeois, B., Bourke, N. M., Bousquet, G., Boya, P., Bozhkov, P. V., Bozi, L. H. M., Bozkurt, T. O., Brackney, D. E., Brandts, C. H., Braun, R. J., Braus, G. H., Bravo-Sagua, R., Bravo-San Pedro, J. M., Brest, P., Bringer, M. -A., Briones-Herrera, A., Broaddus, V. 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P., Whitton, J. L., Whitworth, A. J., Wiktorska, K., Wildenberg, M. E., Wileman, T., Wilkinson, S., Willbold, D., Williams, B., Williams, R. S. B., Williams, R. L., Williamson, P. R., Wilson, R. A., Winner, B., Winsor, N. J., Witkin, S. S., Wodrich, H., Woehlbier, U., Wollert, T., Wong, E., Wong, J. H., Wong, R. W., Wong, V. K. W., Wong, W. W. -L., Wu, A. -G., Wu, C., Wu, J., Wu, K. K., Wu, M., Wu, S. -Y., Wu, S., Wu, W. K. K., Wu, X., Wu, Y. -W., Wu, Y., Xavier, R. J., Xia, H., Xia, L., Xia, Z., Xiang, G., Xiang, J., Xiang, M., Xiang, W., Xiao, B., Xiao, G., Xiao, H., Xiao, H. -T., Xiao, J., Xiao, L., Xiao, S., Xiao, Y., Xie, B., Xie, C. -M., Xie, M., Xie, Y., Xie, Z., Xilouri, M., Xu, C., Xu, E., Xu, H., Xu, J., Xu, L., Xu, W. W., Xu, X., Xue, Y., Yakhine-Diop, S. M. S., Yamaguchi, M., Yamaguchi, O., Yamamoto, A., Yamashina, S., Yan, S., Yan, S. -J., Yan, Z., Yanagi, Y., Yang, C., Yang, D. -S., Yang, H., Yang, H. -T., Yang, J. -M., Yang, J., Yang, L., Yang, M., Yang, P. -M., Yang, Q., Yang, S., Yang, S. -F., Yang, W., Yang, W. Y., Yang, X., Yang, Y., Yao, H., Yao, S., Yao, X., Yao, Y. -G., Yao, Y. -M., Yasui, T., Yazdankhah, M., Yen, P. M., Yi, C., Yin, X. -M., Yin, Y., Yin, Z., Ying, M., Ying, Z., Yip, C. K., Yiu, S. P. T., Yoo, Y. H., Yoshida, K., Yoshii, S. R., Yoshimori, T., Yousefi, B., Yu, B., Yu, H., Yu, J., Yu, L., Yu, M. -L., Yu, S. -W., Yu, V. C., Yu, W. H., Yu, Z., Yuan, J., Yuan, L. -Q., Yuan, S., Yuan, S. -S. F., Yuan, Y., Yuan, Z., Yue, J., Yue, Z., Yun, J., Yung, R. L., Zacks, D. N., Zaffagnini, G., Zambelli, V. O., Zanella, I., Zang, Q. S., Zanivan, S., Zappavigna, S., Zaragoza, P., Zarbalis, K. S., Zarebkohan, A., Zarrouk, A., Zeitlin, S. O., Zeng, J., Zeng, J. -D., Zerovnik, E., Zhan, L., Zhang, B., Zhang, D. D., Zhang, H., Zhang, H. -L., Zhang, J., Zhang, J. -P., Zhang, K. Y. B., Zhang, L. W., Zhang, L., Zhang, M., Zhang, P., Zhang, S., Zhang, W., Zhang, X., Zhang, X. -W., Zhang, X. D., Zhang, Y., Zhang, Y. -D., Zhang, Y. -Y., Zhang, Z., Zhao, H., Zhao, L., Zhao, S., Zhao, T., Zhao, X. -F., Zhao, Y., Zheng, G., Zheng, K., Zheng, L., Zheng, S., Zheng, X. -L., Zheng, Y., Zheng, Z. -G., Zhivotovsky, B., Zhong, Q., Zhou, A., Zhou, B., Zhou, C., Zhou, G., Zhou, H., Zhou, J., Zhou, K., Zhou, R., Zhou, X. -J., Zhou, Y., Zhou, Z. -Y., Zhou, Z., Zhu, B., Zhu, C., Zhu, G. -Q., Zhu, H., Zhu, W. -G., Zhu, Y., Zhuang, H., Zhuang, X., Zientara-Rytter, K., Zimmermann, C. M., Ziviani, E., Zoladek, T., Zong, W. -X., Zorov, D. B., Zorzano, A., Zou, W., Zou, Z., Zuryn, S., Zwerschke, W., Brand-Saberi, B., Dong, X. C., Kenchappa, C. S., Lin, Y., Oshima, S., Rong, Y., Sluimer, J. C., Stallings, C. L., Tong, C. -K., and Centre National de la Recherche Scientifique (CNRS)
Subjects: 0301 basic medicine, Programmed cell death, Settore BIO/06, Autophagosome, Autolysosome, [SDV]Life Sciences [q-bio], lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Autophagy-Related Proteins, Review, Computational biology, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, Biology, Settore MED/04, 03 medical and health sciences, stress, Chaperone-mediated autophagy, ddc:570, Autophagy, LC3, Animals, Humans, cancer, Settore BIO/10, flux, lysosome, macroautophagy, neurodegeneration, phagophore, vacuole, Set (psychology), Molecular Biology, 030102 biochemistry & molecular biology, business.industry, Interpretation (philosophy), Autophagosomes, Cell Biology, Multicellular organism, 030104 developmental biology, Knowledge base, Biological Assay, Lysosomes, business, Biomarkers, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: Contains fulltext : 232759.pdf (Publisher’s version ) (Closed access) In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
Published: 2021
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40. Cell adhesion molecule-mediated therapeutic strategies in atherosclerosis: From a biological basis and molecular mechanism to drug delivery nanosystems

Author: Yi-Fan Fang, Jingwei Shao, Fang Yang, Ming-Yue Yang, Wen-Xin Ni, Jingqing Le, Meng-Die Yin, Jia-Li Jiang, Bang-Yue Luo, Zhenhua Deng, and Chao Li
Subjects: 0301 basic medicine, Endothelium, Inflammation, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Drug Delivery Systems, Fibrinolytic Agents, medicine, Cell Adhesion, Animals, Humans, Pharmacology, business.industry, Cell adhesion molecule, Plaque rupture, Atherosclerosis, Human morbidity, Nanostructures, 030104 developmental biology, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Drug delivery, Cancer research, Molecular mechanism, Lipid lowering, Endothelium, Vascular, medicine.symptom, business, Cell Adhesion Molecules
Abstract: Atherosclerosis (AS), characterized by pathological constriction of blood vessels due to chronic low-grade inflammation and lipid deposition, is a leading cause of human morbidity and mortality worldwide. Cell adhesion molecules (CAMs) have the ability to regulate the inflammatory response and endothelial function, as well as potentially driving plaque rupture, which all contribute to the progression of AS. Moreover, recent advances in the development of clinical agents in the cardiovascular field are based on CAMs, which show promising results in the fight against AS. Here, we review the current literature on mechanisms by which CAMs regulate atherosclerotic progression from the earliest induction of inflammation to plaques formation. In particular, we focused on therapeutic strategies based on CAMs inhibitors that prevent leukocyte from migrating to endothelium, including high-affinity antibodies and antagonists, nonspecific traditional medicinal formulas and lipid lowering drugs. The CAMs-based drug delivery nanosystem and the available data on the more reasonable and effective clinical application of CAMs inhibitors have been emphasized, raising hope for further progress in the field of AS therapy.
Published: 2020

41. Onboard absolute radiometric calibration and validation of the satellite calibration spectrometer on HY-1C

Author: Si Xiaolong, Chen Hongyao, Li-ming Zhang, He-yu Xu, Wen-xin Huang, Li Xin, Xu Weiwei, and Qing-jun Song
Subjects: Optics, Spectrometer, Ocean color, Calibration (statistics), business.industry, Environmental science, Satellite, Moderate-resolution imaging spectroradiometer, business, Radiometric calibration, Diffuser (optics), Atomic and Molecular Physics, and Optics, Interpolation
Abstract: As the reference radiometric calibration standard of sensors on the Haiyang-1C (HY-1C) satellite platform, the satellite calibration spectrometer (SCS) is equipped with an onboard calibration system composed of double solar diffusers and an erbium-doped diffuser to monitor the postlaunch radiometric response change. Herein, through onboard calibration data analysis, the calibration diffuser performance remains stable without degradation, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra is adopted as a reference to repeatedly verify onboard radiometric calibration results by selecting different dates and reflectance scenes. The SCS equivalent reflectance is obtained by combining the mean digital number (DN) of the SCS crossing area image with the radiometric calibration coefficient. The spectral reflectance is obtained via interpolation and iteration, which is adopted as the actual MODIS incident pupil spectral reflectance because the small imaging time interval can be ignored and almost vertically observed, and it is convoluted with the MODIS spectral response function to obtain the predicted equivalent reflectance. Validation is completed by comparing the predicted MODIS equivalent reflectance to the measured value based on the onboard calibration coefficient. The results show that (1) the difference between the measured and predicted MODIS band equivalent reflectance is between -0.00466 and 0.0039, and (2) the percentage difference between the measured and predicted MODIS band equivalent reflectance ranges from 4.17% and 1.24%, indicating that the calibration system carried on HY-1C can perform high-precision SCS radiometric calibration, meeting the cross-calibration accuracy requirements of other loads on the same platform.
Published: 2020

42. Delayed hospital admission and high-dose corticosteroids potentially prolong SARS-CoV-2 RNA detection duration of patients with COVID-19

Author: Sijia Li, Jianwu Hu, Wen Xin Li, Xiaoqi Xiong, Jun Jiang, Ailan Yang, Xinyu Song, and Zhigang Hu
Subjects: 0301 basic medicine, Adult, Male, Microbiology (medical), medicine.medical_specialty, Multivariate statistics, Time Factors, Adolescent, Binomial regression, 030106 microbiology, Antiviral Agents, Lesion, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Interquartile range, Risk Factors, Internal medicine, medicine, Corticosteroids, Humans, 030212 general & internal medicine, Glucocorticoids, Aged, Proportional Hazards Models, Aged, 80 and over, Noninvasive Ventilation, Proportional hazards model, business.industry, SARS-CoV-2, Confounding, Oxygen Inhalation Therapy, RNA, COVID-19, General Medicine, Middle Aged, Hospital admission, Respiration, Artificial, Hypokalemia, Virus Shedding, Hospitalization, Thymosin, Logistic Models, Infectious Diseases, RNA, Viral, Original Article, Female, medicine.symptom, business
Abstract: Coronavirus disease 2019 (COVID-19) with the infection of SARS-CoV-2 has become a serious pandemic worldwide. However, only few studies focused on risk factors of prolonged SARS-CoV-2 RNA detection among patients with COVID-19. We included 206 adult patients with laboratory-confirmed COVID-19 from two hospitals between 23 Jan and 1 April 2020. Least absolute shrinkage and selection operator (LASSO) analysis was used to screen out independent risk factors of SARS-CoV-2 RNA detection. By multivariate binomial logistic regression analysis and Cox regression analysis, we further determined the associations between SARS-CoV-2 RNA detection and potential risk factors. All patients had two negative SARS-CoV-2 tests with 33 days of median duration of SARS-CoV-2 RNA detection (interquartile range: 25.2-39 days). LASSO and binomial logistic regression analyses suggested that delayed hospital admission (adjusted OR = 3.70, 95% CI: 1.82-7.50), hypokalemia, and subpleural lesion (adjusted OR = 4.32, 95% CI: 1.10-16.97) were associated with prolonged SARS-CoV-2 RNA detection. By LASSO and multivariate Cox regression analyses, we observed that delayed hospital admission, subpleural lesion, and high-dose corticosteroid use were independent risk factors of prolonged SARS-CoV-2 RNA detection. Early hospital admission shortened 5.73 days of mean duration of SARS-CoV-2 RNA detection than delayed hospital admission after adjusting confounding factors. Our study demonstrated that delayed hospital admission and subpleural lesion were associated with prolonged SARS-CoV-2 RNA detection among patients with COVID-19. The use of high-dose corticosteroids should be interpreted with extreme caution in treating COVID-19.
Published: 2020
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43. Predictive value of ultrasound diagnosis of aberrant right subclavian artery with non-recurrent laryngeal nerve

Author: Qin Ye, Xueying Lin, Zhen-Hu Lin, Rongxi Liang, Ensheng Xue, Bo Wang, Zhi-Yong Chen, Zhikui Chen, You-Jia Lin, and Wen-Xin Zhao
Subjects: medicine.medical_specialty, business.industry, Ultrasound, Recurrent laryngeal nerve, Medicine, Aberrant right subclavian artery, General Medicine, Radiology, Ultrasonography, business, Predictive value
Abstract: IntroductionThis study aims to evaluate the predictive value of color Doppler ultrasound for the diagnosis of aberrant right subclavian artery (ARSA) with a co-occurring non-recurrent right laryngeal nerve (NRLN).Material and methodsIn the present study, 58 patients with ARSA (ARSA group) and 1,280 patients without ARSA (controls) were diagnosed by ultrasonography. In addition, 32 patients with ARSA (ARSA operation group) and controls underwent thyroidectomy with surgical exploration with or without NRLN. Then, the incidence of NRLN was analyzed. The right common carotid artery (RCCA) and right subclavian artery (RSA) trends were observed by ultrasound, and classified into two types: RCCA and RSA originating from the innominate artery (IA) (type I), and IA could not be detected (type II).ResultsA total of 32 cases of NRLN were found in the ARSA operation group, but no case was found in controls, and the difference was statistically significant (p = 0.0006). The difference in the constituent ratio of type I and type II was statistically significant between the ARSA group and controls (p = 0.0002). That is, the IA could not be detected in the ARSA group, which was accompanied by the RCCA that originated from the aortic arch, while the IA was detected in most patients in the control group at the level of the sternoclavicular joints.ConclusionsAberrant right subclavian artery can be rapidly detected by ultrasonography. Aberrant right subclavian artery occurs when the RCCA originates from the aortic arch during detection. Patients with ARSA sometimes have co-occurring NRLN. Hence, vigilance in protecting the NRLN is needed during an operation.
Published: 2020
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44. Machine Speed Condition Monitoring using Statistical Time-Domain Features Modeled with Graph

Author: Guoliang Lu, Zhenjie Zhu, Xinlai Ye, and Wen Xin
Subjects: Vibration, Computer science, business.industry, Feature extraction, Condition monitoring, Graph (abstract data type), Pattern recognition, Time domain, Artificial intelligence, F1 score, business, Signal, Statistical hypothesis testing
Abstract: The most important part of speed condition monitoring for industrial machinery is to find the structural changes in dynamic running status. The existing detection methods mainly rely on the time-domain or frequency-domain analysis of the collected operation signals to detect the change. In this paper, the time-domain features and the structural graph similarity are combined to detect the dynamic speed conditions. For the condition signal, we firstly divide it into time-sequential segments. Secondly, extract statistical features from each segment, and modeled as graph to characterize the dynamic behavior of machine speed condition. A common hypothesis testing based on the 30 criterion is finally used to make the change decision. We have investigated the proposed method based on an experimental setup. Experimental results show that compared with the time-domain features, the precision and F score are improved by more than 10%, which shows the effectiveness of our method.
Published: 2020
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45. Muscle Fatigue Enhance Beta Band EMG-EMG Coupling of Antagonistic Muscles in Patients With Post-stroke Spasticity

Author: Le-Jun Wang, Xiao-Ming Yu, Qi-Neng Shao, Ce Wang, Hua Yang, Shang-Jun Huang, and Wen-Xin Niu
Subjects: 0301 basic medicine, medicine.medical_specialty, Histology, Contraction (grammar), lcsh:Biotechnology, Biomedical Engineering, Bioengineering, 02 engineering and technology, Isometric exercise, antagonist muscle, Biceps, Muscle coactivation, 03 medical and health sciences, Physical medicine and rehabilitation, coactivation, EMG, lcsh:TP248.13-248.65, medicine, Spasticity, Original Research, Muscle fatigue, business.industry, Bioengineering and Biotechnology, 021001 nanoscience & nanotechnology, Coactivation, post-stroke spasticity, 030104 developmental biology, medicine.anatomical_structure, muscle fatigue, medicine.symptom, 0210 nano-technology, business, Biotechnology, Motor cortex
Abstract: There is a significant influence of muscle fatigue on the coupling of antagonistic muscles while patients with post-stroke spasticity are characterized by abnormal antagonistic muscle coactivation activities. This study was designed to verify whether the coupling of antagonistic muscles in patients with post-stroke spasticity is influenced by muscle fatigue. Ten patients with chronic hemipare and spasticity and 12 healthy adults were recruited to participate in this study. Each participant performed a fatiguing isometric elbow flexion of the paretic side or right limb at 30% maximal voluntary contraction (MVC) level until exhaustion while surface electromyographic (sEMG) signals were collected from the biceps brachii (BB) and triceps brachii (TB) muscles during the sustained contraction. sEMG signals were divided into the first (minimal fatigue) and second halves (severe fatigue) of the contraction. The power and coherence between the sEMG signals of the BB and TB in the alpha (8–12 Hz), beta (15–35 Hz), and gamma (35–60 Hz) frequency bands associated with minimal fatigue and severe fatigue were calculated. The coactivation ratio of the antagonistic TB muscle was also determined during the sustained fatiguing contraction. The results demonstrated that there was a significant decrease in maximal torque during the post-fatigue contraction compared to that during the pre-fatigue contraction in both stroke and healthy group. In the stroke group, EMG-EMG coherence between the BB and TB in the alpha and beta frequency bands was significantly increased in severe fatigue compared to minimal fatigue, while coactivation of antagonistic muscle increased progressively during the sustained fatiguing contraction. In the healthy group, coactivation of the antagonistic muscle showed no significant changes during the fatiguing contraction and no significant coherence was found in the alpha, beta and gamma frequency bands between the first and second halves of the contraction. Therefore, the muscle fatigue significantly increases the coupling of antagonistic muscles in patients with post-stroke spasticity, which may be related to the increased common corticospinal drive from motor cortex to the antagonistic muscles. The increase in antagonistic muscle coupling induced by muscle fatigue may provide suggestions for the design of training program for patients with post-stroke spasticity.
Published: 2020
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46. A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN

Author: Jullian Yapeter, De Rong Loh, Wen Xin Yong, Karupppasamy Subburaj, and Rajesh Chandramohanadas
Subjects: Standardization, Computer science, Health Informatics, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Deep Learning, Minimum bounding box, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Microscopy, Radiological and Ultrasound Technology, business.industry, Deep learning, Pattern recognition, Cell counting, Computer Graphics and Computer-Aided Design, Object detection, Visualization, Malaria, Feature (computer vision), Computer Vision and Pattern Recognition, Artificial intelligence, Neural Networks, Computer, business, 030217 neurology & neurosurgery
Abstract: Accurate and early diagnosis is critical to proper malaria treatment and hence death prevention. Several computer vision technologies have emerged in recent years as alternatives to traditional microscopy and rapid diagnostic tests. In this work, we used a deep learning model called Mask R-CNN that is trained on uninfected and Plasmodium falciparum-infected red blood cells. Our predictive model produced reports at a rate 15 times faster than manual counting without compromising on accuracy. Another unique feature of our model is its ability to generate segmentation masks on top of bounding box classifications for immediate visualization, making it superior to existing models. Furthermore, with greater standardization, it holds much potential to reduce errors arising from manual counting and save a significant amount of human resources, time, and cost.
Published: 2020

47. Identification of biomarkers of clear cell renal cell carcinoma by bioinformatics analysis

Author: Alimujiang Abudurexiti, wei Sang, ning Zhang, Zhilu Gan, Xiaogang Hu, and wen-xin Chen
Subjects: differentially expressed genes, genetic structures, Databases, Factual, Epidemiology, Computational biology, Kaplan-Meier Estimate, clear cell renal cell carcinoma, KIF23, Genome, 03 medical and health sciences, 0302 clinical medicine, Meta-Analysis of Observational Studies in Epidemiology, medicine, Biomarkers, Tumor, Humans, 030212 general & internal medicine, KEGG, Gene, Carcinoma, Renal Cell, business.industry, Gene Expression Profiling, Computational Biology, General Medicine, survival prognosis, medicine.disease, GREB1, Gene expression profiling, Clear cell renal cell carcinoma, Observational Studies as Topic, 030220 oncology & carcinogenesis, Adenocarcinoma, business, Adenocarcinoma, Clear Cell, Research Article
Abstract: Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer, and more and more researches find that the occurrence of ccRCC is associated with genetic changes, but the molecular mechanism still remains unclear. The present study aimed to identify aggregation trend of differentially expressed genes (DEGs) in ccRCC, which would be beneficial to the treatment of ccRCC and provide research ideas using a series of bioinformatics approach. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) analysis were used to get the enrichment trend of DEGs of GSE53757 and GSE16449. Draw Venn Diagram was applied for co-expression of DEGs. Cytoscape with the Retrieval of Interacting Gene (STRING) datasets and Molecular Complex Detection (MCODE) were performed protein-protein interaction (PPI) of DEGs. The Kaplan–Meier Plotter analysis of top 15 upregulated and top 15 downregulated were selected in Gene Expression Profiling Interactive Analysis (GEPIA). Then, the expression level of hub genes between normal renal tissue and different pathological stages of ccRCC tissue, which significantly correlated with overall survival in ccRCC patients, were also analyzed by Ualcan based on The Cancer Genome Atlas (TCGA) database. In this study, we got 167 co-expression DEGs, including 72 upregulated DEGs and 95 downregulated DEGs. We identified 11 hub genes had significantly correlated with overall survival in ccRCC patients. Among them, KIF23, APLN, ADCY1, GREB1, TLR4, IRF8, CXCL1, CXCL2, deserved our attention.
Published: 2020

48. Blue laser imaging combined with JNET (Japan NBI Expert Team) classification for pathological prediction of colorectal laterally spreading tumors

Author: Jun Wu, Yu Chen, Qun Peng, Liang-Dou Lin, Weiguang Qiao, Haitao Qing, Zhi-Bin Lu, Wen-xin Tan, Silin Huang, Wen-Hua Zhang, and Qiang Zhang
Subjects: medicine.medical_specialty, business.industry, Lasers, Colonoscopy, Hepatology, 03 medical and health sciences, Narrow Band Imaging, 0302 clinical medicine, Hyperplastic Polyp, Multicenter study, Japan, 030220 oncology & carcinogenesis, Internal medicine, medicine, Humans, 030211 gastroenterology & hepatology, Surgery, In patient, Radiology, business, Colorectal Neoplasms, Pathological, Retrospective Studies
Abstract: Blue laser imaging (BLI) can provide useful information on colorectal laterally spreading tumors (LSTs) by visualizing the surface and vessel patterns in detail. The present research aimed to evaluate the diagnostic performance of BLI-combined JNET (Japan NBI Expert Team) classification for identifying LSTs. This retrospective, multicenter study included 172 LSTs consisted of 6 hyperplastic polyps/sessile serrated polyps, 94 low-grade dysplasias (LGD), 60 high-grade dysplasias (HGD), 6 superficial submucosal invasive (m-SMs) carcinomas, and 4 deep submucosal invasive carcinomas. The relationship between the JNET classification and the histologic findings of these lesions were then analyzed. For all LSTs, non-experts and experts had a 79.7% and 90.7% accuracy for Type 2A (P = 0.004), a sensitivity of 94.7% and 96.8% (P = 0.718), and a specificity of 61.5% and 83.3% (P = 0.002) for prediction of LGD, respectively. The results also demonstrated 80.8% and 91.3% accuracy for Type 2B (P = 0.005), a sensitivity of 65.2% and 83.3% (P = 0.017), and a specificity of 90.6% and 96.2% (P = 0.097) for predicting HGD or m-SMs. For LST-granular (LST-G) lesions, Type 2A in experts had higher specificity (65.6% vs. 83.6%, P = 0.022) and accuracy (81.8% vs. 91.2%, P = 0.022). Type 2B in experts only had higher accuracy (82.5% vs. 92.0%, P = 0.019). However, no significant differences were noted for any comparisons between non-experts and experts for LST-non-granular (LST-NG) lesions. BLI combined with JNET classification was an effective method for the precise prediction of pathological diagnosis in patients with LSTs. Diagnostic performance of JNET classification by experts was better than that by non-experts for all examined LST or LST-G lesions when delineating between Type 2A and 2B, but there was no difference for the identification of LST-NG lesions by these two groups.
Published: 2020

49. Measurement of changes in perfusion after carotid endarterectomy by 3D pseudo-continuous arterial spin labeling

Author: Xinguang Yu, Chen Wu, Zheng-hui Sun, Dongsheng Kong, Zhe Xue, and Wen-xin Wang
Subjects: medicine.medical_specialty, nervous system, business.industry, Internal medicine, medicine.medical_treatment, medicine, Cardiology, Continuous arterial spin labeling, Carotid endarterectomy, business, Perfusion
Abstract: Background:Carotid endarterectomy (CEA) is an effective method for treating cerebral ischemia caused by carotid stenosis, but there may be a risk of perfusion pressure breakthrough during early perfusion recovery. As a non-invasive and contrast-free magnetic resonance examination method, arterial spin labeling can be used for continuous observation and measurement in the early postoperative period of carotid endarterectomy. Results: Nineteen patients with severe unilateral carotid stenosis were examined using 3D pseudo-continuous arterial spin labeling before and after CEA, and we found that the pattern of dynamic cerebral blood flow changes is not the same in different regions.Conclusions: 3D pseudo-continuous arterial spin labeling might be helpful for the improvement of postoperative treatment and care of severe unilateral carotid stenosis patients.
Published: 2020
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50. Improving Broadband White-Light Emission Performances of 2D Perovskites by Subtly Regulating Organic Cations

Author: Hui-Fang Zhao, Juan Wang, Meng-Fei Han, Wen-Xin Chu, Zhi Wang, Jian-Qiang Zhao, Chang-Qing Jing, Yun Yuan, Xiao-Wu Lei, and Te Xu
Subjects: White emission, Photoluminescence, 010405 organic chemistry, Chemistry, business.industry, Exciton, Organic Chemistry, Halide, General Chemistry, 010402 general chemistry, 01 natural sciences, Catalysis, 0104 chemical sciences, Characterization (materials science), Broadband, White light, Optoelectronics, Luminescence, business
Abstract: Recently, 2D organic-inorganic hybrid lead halide perovskites have attracted intensive attention in solid-state luminescence fields such as single-component white-light emitters, and rational optimization of the photoluminescence (PL) performance through accurate structural-design strategies is still significant. Herein, by carefully choosing homologous aliphatic amines as templates, isotypical perovskites [DMEDA]PbCl4 (1, DMEDA=N,N-dimethylethylenediamine) and [DMPDA]PbCl4 (2, DMPDA=N,N-dimethyl-1,3-diaminopropane) having tunable and stable broadband bluish white emission properties were rationally designed. The subtle regulation of organic cations leads to a higher degree of distortion of the 2D [PbCl4 ]2- layers and enhanced photoluminescence quantum efficiencies (
Published: 2020

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