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Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A data-driven Perspective

Genomics, Proteomics & Bioinformatics 2023年第1期21卷 164-176页

作者： Jianlei Gu Jiawei Dai Hui Lu Hongyu Zhao SJTU-Yale Joint Center for Biostatistics and Data Science Department of Bioinformatics and BiostatisticsSchool of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China Center for Biomedical Informatics Shanghai Engineering Research Center for Big Data in Pediatric Precision MedicineShanghai Children’s HospitalShanghai 200040China Department of Biostatistics Yale UniversityNew HavenCT 06511USA

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human *** expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an *** is known that many human genes are broadly expressed across ***,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG *** this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human *** results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression *** further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.

关键词： Ubiquitous expression Housekeeping gene Disallowed gene Expression specificity Expression variability

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Short-Term Effects of Ambient Air Pollutants on Outpatient Visits for Childhood Allergic Diseases in Shanghai,China

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Journal of Shanghai Jiaotong university(science) 2024年第6期29卷 979-994页

作者： HU Yi GU Jianlei WU Dan WANG Xiaolei LU Hui YU Guangjun Center for Biomedical Informatics Shanghai Children’s HospitalShanghai Jiao Tong University School of MedicineShanghai 200040China SJTU-Yale Joint Center for Biostatistics and Data Science Department of Bioinformatics and BiostatisticsShanghai Jiao Tong UniversityShanghai 200240China Shanghai Engineering Research Center for Big Data in Pediatric Precision Medicine Shanghai 200040China

This study aims to investigate the short-term effects of ambient air pollutants on outpatient visits for childhood allergic *** data on ambient air pollutants(NO2,SO2,CO and PM2.5)and outpatient visits for childhood allergic diseases(asthma,atopic dermatitis and allergic rhinitis)were obtained in Shanghai,China from 2013 to *** effects of ambient air pollutants were estimated for total outpatient visits for childhood allergic diseases,gender and age stratification and disease classification by using distributed lag non-linear model(DLNM).We found positive associations between short-term exposure to air pollutants and childhood allergic *** and children aged 7 years old were more likely to be sensitive to ambient air ***2 and SO2 showed stronger effects on asthma and atopic dermatitis,*** study provides evidence that short-term exposure to ambient air pollutants can increase the risk of childhood allergic diseases.

关键词： childhood allergic diseases ambient air pollutant nitrogen dioxide(NO2) sulfur dioxide(SO2) particulate matter<2.5μm in diameter(PM2.5)

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Human mobility and the infectious disease transmission:a systematic review

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地球空间信息科学学报（英文版） 2024年第6期27卷中插6,1824-1851页

作者： M.Naser Lessani Zhenlong Li Fengrui Jing Shan Qiao Jiajia Zhang Bankole Olatosi Xiaoming Li Geoinformation and Big Data Research Lab Department of GeographyUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Health Promotion Educationand BehaviorUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Epidemiology and Biostatistics Arnold School of Public HealthUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Health Services Policy and Management Arnold School of Public HealthUniversity of South CarolinaColumbiaSCUSA

Recent decades have witnessed several infectious disease outbreaks,including the coronavirus disease(COVID-19)pandemic,which had catastrophic impacts on societies around the *** the same time,the twenty-first century has experienced an unprecedented era of techno-logical development and demographic changes:exploding population growth,increased air-line flights,and increased rural-to-urban migration,with an estimated 281 million international migrants worldwide in 2020,despite COVID-19 movement *** this review,we synthesized 195 research articles that examined the association between human movement and infectious disease outbreaks to understand the extent to which human mobility has increased the risk of infectious disease *** article covers eight infectious diseases,ranging from respiratory illnesses to sexually transmitted and vector-borne *** review revealed a strong association between human mobility and infectious disease spread,particularly strong for respiratory illnesses like COVID-19 and *** significant research into the relationship between infectious diseases and human mobility,four knowl-edge gaps were identified based on reviewed literature in this study:1)although some studies have used big data in investigating infectious diseases,the efforts are limited(with the exception of COVID-19 disease),2)while some research has explored the use of multiple data sources,there has been limited focus on fully integrating these data into comprehensive analyses,3)limited research on the global impact of mobility on the spread of infectious disease with most studies focusing on local or regional outbreaks,and 4)lack of standardiza-tion in the methodology for measuring the impacts of human mobility on infectious disease *** tackling the recognized knowledge gaps and adopting holistic,interdisciplinary methods,forthcoming research has the potential to substantially enhance our comprehension of the intricate inter

关键词： Human mobility geography infectious diseases sexually transmitted diseases systematic review

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Neural Generalized Ordinary Differential Equations with Layer-Varying Parameters

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Journal of data science 2024年第1期22卷 10-24页

作者： Yu, Duo Miao, Hongyu Wu, Hulin Department of Population Health The University of Texas Austin United States College of Nursing Florida State University United States Department of Biostatistics and Data Science The University of Texas Health Science Center Houston United States

Deep residual networks (ResNets) have shown state-of-the-art performance in various real-world applications. Recently, the ResNets model was reparameterized and interpreted as solutions to a continuous ordinary differential equation or Neural-ODE model. In this study, we propose a neural generalized ordinary differential equation (Neural-GODE) model with layer-varying parameters to further extend the Neural-ODE to approximate the discrete ResNets. Specifically, we use nonparametric B-spline functions to parameterize the Neural-GODE so that the tradeoff between the model complexity and computational efficiency can be easily balanced. It is demonstrated that ResNets and Neural-ODE models are special cases of the proposed Neural-GODE model. Based on two benchmark datasets, MNIST and CIFAR-10, we show that the layer-varying Neural-GODE is more flexible and general than the standard Neural-ODE. Furthermore, the Neural-GODE enjoys the computational and memory benefits while performing comparably to ResNets in prediction accuracy. © 2024 The Author(s).

关键词： B-splines deep residual networks neural ordinary differential equations

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Decoding Consciousness in Artificial Intelligence

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Journal of data science 2024年第1期22卷 1-9页

作者： Xiong, Momiao Department of Biostatistics and Data Science School of Public Health The University of Texas Health Science Center at Houston Houston 77030 TX United States Society of Artificial Intelligence Research Houston 77030 TX United States

The exploration of whether artificial intelligence (AI) can evolve to possess consciousness is an intensely debated and researched topic within the fields of philosophy, neuroscience, and artificial intelligence. Understanding this complex phenomenon hinges on integrating two complementary perspectives of consciousness: the objective and the subjective. Objective perspectives involve quantifiable measures and observable phenomena, offering a more scientific and empirical approach. This includes the use of neuroimaging technologies such as electrocorticography (ECoG), EEG, and fMRI to study brain activities and patterns. These methods allow for the mapping and understanding of neural representations related to language, visual, acoustic, emotional, and semantic information. However, the objective approach may miss the nuances of personal experience and introspection. On the other hand, subjective perspectives focus on personal experiences, thoughts, and feelings. This introspective view provides insights into the individual nature of consciousness, which cannot be directly measured or observed by others. Yet, the subjective approach is often criticized for its lack of empirical evidence and its reliance on personal interpretation, which may not be universally applicable or reliable. Integrating these two perspectives is essential for a comprehensive understanding of consciousness. By combining objective measures with subjective reports, we can develop a more holistic understanding of the mind. © 2024 The Author(s).

关键词： artificial general intelligence artificial intelligence consciousness mortal computation

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Association between Serum Uric Acid and the Early Marker of Kidney Function Decline among Chinese Middle-Aged and Older Population:Evidence from the China Health and Retirement Longitudinal Study

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Biomedical and Environmental sciences 2023年第3期36卷 231-240页

作者： TANG Xu XU Lu MENG Ruo Gu DU Yi Qing LIU Shi Jun ZHAN Si Yan XU Tao Department of Urology Peking University People’s HospitalBeijing 100044China Research Center of Clinical Epidemiology Peking University Third HospitalBeijing 100191China National Institute of Health Data Science Center for Data Science in Health and MedicinePeking UniversityBeijing 100191China Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100191China Center for Intelligent Public Health Institute for Artificial IntelligencePeking UniversityBeijing 100191China

Objective To evaluate the association between serum uric acid(SUA)and kidney function *** data was obtained from the China Health and Retirement Longitudinal Study on the Chinese middle-aged and older population for *** kidney function decline was defined as an annual estimated glomerular filtration rate(e GFR)decrease by>3 mL/min per 1.73 m^(2).Multivariable logistic regression was applied to determine the association between SUA and kidney function *** shape of the association was investigated by restricted cubic *** A total of 7,346 participants were included,of which 1,004 individuals(13.67%)developed kidney function decline during the follow-up of 4 years.A significant dose-response relation was recorded between SUA and the kidney function decline(OR 1.14,95%CI 1.03-1.27),as the risk of kidney function decline increased by 14%per 1 mg/d L increase in *** the subgroup analyses,such a relation was only recorded among women(OR 1.22,95%CI 1.03-1.45),those aged<60 years(OR 1.22,95%CI 1.05-1.42),and those without hypertension and without diabetes(OR 1.22,95%CI 1.06-1.41).Although the dose-response relation was not observed in men,the high level of SUA was related to kidney function decline(OR 1.83,95%CI 1.05-3.17).The restricted cubic spline analysis indicated that SUA>5 mg/dL was associated with a significantly higher risk of kidney function *** The SUA level was associated with kidney function *** elevation of SUA should therefore be addressed to prevent possible kidney impairment and dysfunction.

关键词： Uric acid Glomerular filtration rate Kidney function decline

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Using a Bayesian model of the joint distribution of pain and time on medication to decide on pain medication for neuropathy

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Communications in Statistics Case Studies data Analysis and Applications 2023年第3期9卷 252-269页

作者： Gao, Guangyi Wick, Jo A. Brown, Alexandra R. Barohn, Richard J. Gajewski, Byron J. Department of Biostatistics & Data Science University of Kansas Medical Center Kansas City KS United States Department of Neurology University of Missouri Columbia MO United States

The PAIN-CONTRoLS trial compared four medications in treating Cryptogenic sensory polyneuropathy. The primary outcome was a utility function that combined two outcomes, patients’ pain score reduction and patients’ quit rate. However, additional analysis of the individual outcomes could also be leveraged to inform selecting an optimal medication for future patients. We demonstrate how joint modeling of longitudinal and time-to-event data from PAIN-CONTRoLS can be used to predict the effects of medication in a patient-specific manner and helps to make patient-focused decisions. A joint model was used to evaluate the two outcomes while accounting for the association between the longitudinal process and the time-to-event processes. Results suggested no significant association between the patients’ pain scores and time to the medication quit in the PAIN-CONTRoLS study, but the joint model still provided robust estimates and a better model fit. Using the model estimates, given patients’ baseline characteristics, a drug profile on both the pain reduction and medication time could be obtained for each drug, providing information on how likely they would quit and how much pain reduction they should expect. Our analysis suggested that drugs viable for one patient may not be beneficial for others. © 2023 Taylor & Francis Group, LLC.

关键词： Bayesian approach decision making joint model longitudinal data time-to-event data

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Workplace Quality and Exposure to Bullying During a Crisis: The Inhibiting Role of Positive Leadership in Nursing

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International Journal of Bullying Prevention 2025年 1-18页

作者： Georganta, Katerina Nikolakopoulos, Stavros Glaveli, Niki Department of Psychology School of Social Sciences University of Ioannina University Campus Ioannina 45110 Greece Department of Data Science & Biostatistics Julius Center University Medical Center Utrecht Utrecht Netherlands Department of Business Administration School of Business University of the Aegean Chios Greece

The COVID-19 pandemic created an extremely stressful situation for hospitals by intensifying a range of stressors like workload, death and dying, lack of support, inadequate preparation, uncertainty, and conflict. Stressors like these operate as an avenue for the proliferation of bullying. Grounded on Leymann’s Work Environment hypothesis and Baillien’s et al. Three-Way Model which predict that bullying may develop from work-design factors, but at the same time mitigated as a result of the quality of the work environment, it is explored whether positive leadership styles (ethical, supportive, and authentic) would buffer the relationship between the quality of work environment and bullying in hospitals during a crisis. A cross-sectional study was designed collecting data from 234 hospital nurses working in Greece during the COVID-19 pandemic. Moderation analyses showed that leadership styles interacted with stressors in the predicted direction in relation to various types of bullying (work-related, person-related, and physical intimidation). Ethical leadership emerged as the style that significantly interplayed with a range of stressors and buffered their effects on all types of bullying behaviors measured. Theoretical and practical implications in terms of leadership development and its role as a higher-order job resource in the development of high-quality hospital work environments, as well as for proactive crisis management, are discussed. © The Author(s) 2025.

关键词： COVID-19 Crisis Ethical leadership Low quality work environment Positive leadership styles Workplace bullying

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Performance Analysis of Monte Carlo Algorithms in Dense Subgraph Identification

arXiv

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arXiv 2024年

作者： Guo, Wanru Department of Biostatistics and Data Science University of Texas Health Science Center Houston United States

The exploration of network structures through the lens of graph theory has become a cornerstone in understanding complex systems across diverse fields. Identifying densely connected subgraphs within larger networks is crucial for uncovering functional modules in biological systems, cohesive groups within social networks, and critical paths in technological infrastructures. The most representative approach, the SM algorithm, cannot locate subgraphs with large sizes, therefore cannot identify dense subgraphs;while the SA algorithm previously used by researchers combines simulated annealing and efficient moves for the Markov chain. However, the global optima cannot be guaranteed to be located by the simulated annealing methods including SA unless a logarithmic cooling schedule is used. To this end, our study introduces and evaluates the performance of the Simulated Annealing Algorithm (SAA), which combines simulated annealing with the stochastic approximation Monte Carlo algorithm. The performance of SAA against two other numerical algorithms-SM and SA, is examined in the context of identifying these critical subgraph structures using simulated graphs with embeded cliques. We have found that SAA outperforms both SA and SM by 1) the number of iterations to find the densest subgraph and 2) the percentage of time the algorithm is able to find a clique after 10,000 iterations, and 3) computation time. The promising result of the SAA algorithm could offer a robust tool for dissecting complex systems and potentially transforming our approach to solving problems in interdisciplinary fields. © 2024, CC BY.

关键词： Simulated annealing

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UMVUE-DR: Uniformly Minimum Variance Unbiased Doubly Robust Learning with Reduced Bias and Variance for Debiased Recommendation 24

UMVUE-DR: Uniformly Minimum Variance Unbiased Doubly Robust ...

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24th IEEE International Conference on data Mining Workshops, ICDMW 2024

作者： Zheng, Chunyuan Hu, Taojun Zhou, Chuan Zhou, Xiao-Hua Peking University School of Mathematical Sciences Beijing China Peking University Department of Biostatistics Beijing China Center for Data Science Peking University Beijing China Beijing International Center for Mathematical Research Peking University Beijing China

ISBN: (纸本)9798331530631

Recommender systems (RS) are essential for personalized experiences across e-commerce, social media, and various online platforms. due to users are free to choose items to rate, there is a distributional shift between the observed ratings and the ratings among all users and all items, which is also known as the selection bias. Doubly robust (DR) methods have been proposed to address this issue with some promising success. In recent years, many methods have been proposed that aim to further control the bias and variance of the DR approach when learning the propensity model. However, we find that these methods are unable to achieve unbiased estimation of bias and variance and have large estimation errors at either small or large propensity scores. To bridge this gap, this paper proposes a uniformly minimum variance unbiased DR learning method with reduced bias and variance. Experiments on three real-world datasets show the effectiveness of our method. © 2024 IEEE.

关键词： Contrastive Learning

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