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Bing Zhang

Bio: Bing Zhang is an academic researcher from Nanjing University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 58, co-authored 320 publications receiving 11185 citations. Previous affiliations of Bing Zhang include Zhejiang University & University of Wisconsin-Madison.


Papers
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Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper conducted an eco-efficiency analysis for regional industrial systems in China by developing data envelopment analysis (DEA) based models, which showed that Tianjing, Shanghai, Guangdong, Beijing, Hainan and Qinghai are relatively eco-efficient.

431 citations

Journal ArticleDOI
01 Dec 1998-Neuron
TL;DR: It is shown that a mutation that eliminates an AP180 homolog (LAP) in Drosophila severely impairs the efficiency of synaptic vesicle endocytosis and alters the normal localization of clathrin in nerve terminals.

430 citations

Journal ArticleDOI
TL;DR: Clinical characteristics and outcomes of intensive care patients, data on whom are scarce but are of paramount importance to reduce mortality, are focused on.
Abstract: With the dramatic increase of confirmed cases of coronavirus disease (COVID-19) and the increasing death toll in China, timely and effective management of severely and critically ill patients appears to be particularly important. Previous studies on COVID-19 mainly described the general features of patients (1). However, little attention has been paid to clinical characteristics and outcomes of intensive care patients, data on whom are scarce but are of paramount importance to reduce mortality. Some of the results of these studies have been previously reported in the form of an abstract (2).

428 citations

Journal ArticleDOI
TL;DR: Global sampling of microbial communities associated with wastewater treatment plants and application of ecological theory revealed a small, core bacterial community associated with performance and provides insights into the community dynamics in this environment.
Abstract: Microorganisms in wastewater treatment plants (WWTPs) are essential for water purification to protect public and environmental health. However, the diversity of microorganisms and the factors that control it are poorly understood. Using a systematic global-sampling effort, we analysed the 16S ribosomal RNA gene sequences from ~1,200 activated sludge samples taken from 269 WWTPs in 23 countries on 6 continents. Our analyses revealed that the global activated sludge bacterial communities contain ~1 billion bacterial phylotypes with a Poisson lognormal diversity distribution. Despite this high diversity, activated sludge has a small, global core bacterial community (n = 28 operational taxonomic units) that is strongly linked to activated sludge performance. Meta-analyses with global datasets associate the activated sludge microbiomes most closely to freshwater populations. In contrast to macroorganism diversity, activated sludge bacterial communities show no latitudinal gradient. Furthermore, their spatial turnover is scale-dependent and appears to be largely driven by stochastic processes (dispersal and drift), although deterministic factors (temperature and organic input) are also important. Our findings enhance our mechanistic understanding of the global diversity and biogeography of activated sludge bacterial communities within a theoretical ecology framework and have important implications for microbial ecology and wastewater treatment processes.

423 citations

Journal ArticleDOI
14 Feb 2002-Neuron
TL;DR: A novel role for BMP signaling in regulating Drosophila neuromuscular junction synapse assembly and activity is revealed and may indicate that similar pathways could govern vertebrate synapse development.

342 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal ArticleDOI
TL;DR: Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development.
Abstract: Background Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. Methods To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. Results Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. Conclusions Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.)

6,672 citations

Book ChapterDOI
01 Jan 2010

5,842 citations

01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

Posted Content
TL;DR: In this paper, the authors provide a unified and comprehensive theory of structural time series models, including a detailed treatment of the Kalman filter for modeling economic and social time series, and address the special problems which the treatment of such series poses.
Abstract: In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

4,252 citations