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Article ; Online: A Bayesian genomic selection approach incorporating prior feature ordering and population structures with application to coronary artery disease.

Dai, Xiaotian / Lu, Xuewen / Chekouo, Thierry

2023 Volume 32, Issue 8, Page(s) 1616–1629

Abstract: Coronary artery disease is one of the most common types of cardiovascular disease. Death from coronary heart disease is influenced by genetic factors in both women and men. In this article, we propose a novel Bayesian variable selection framework for the ...

Abstract	Coronary artery disease is one of the most common types of cardiovascular disease. Death from coronary heart disease is influenced by genetic factors in both women and men. In this article, we propose a novel Bayesian variable selection framework for the identification of important genetic variants associated with coronary artery disease disease status. Instead of treating each feature independently as in conventional Bayesian variable selection methods, we propose an innovative prior for the inclusion probabilities of genetic variants that accounts for their ordering structure. We assume that neighboring variants are more likely to be selected together as they tend to be highly correlated and have similar biological functions. Additionally, we propose to group participating subjects based on underlying population structure and fit separate regressions, so that the regression coefficients can better reflect different disease risks in different population groups. Our approach borrows strength across regression models through an innovative prior inspired by the Markov random fields. The proposed framework can improve variable selection and prediction performances as demonstrated in the simulation studies. We also apply the proposed framework to the CATHeterization GENetics data with binary Coronary artery disease disease status.
MeSH term(s)	Male ; Humans ; Female ; Bayes Theorem ; Coronary Artery Disease/genetics ; Computer Simulation ; Genomics
Language	English
Publishing date	2023-06-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1136948-6
ISSN	1477-0334 ; 0962-2802
ISSN (online)	1477-0334
ISSN	0962-2802
DOI	10.1177/09622802231181231
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Discussion of tumor mutation burden as an indicator to predict efficacy of immune checkpoint inhibitors: A case report.

Wu, Mingrui / Liang, Lan / Dai, Xiaotian

Frontiers in oncology

2022 Volume 12, Page(s) 939022

Abstract: There are many treatment options for advanced lung cancer, among which immunotherapy has developed rapidly and benefited a lot of patients. However, immunotherapy can only benefit a subgroup of patients, and how to select patients suitable for this ... ...

Abstract	There are many treatment options for advanced lung cancer, among which immunotherapy has developed rapidly and benefited a lot of patients. However, immunotherapy can only benefit a subgroup of patients, and how to select patients suitable for this therapy is critical. Tumor mutation burden (TMB) is one of the important reference indicators for immune checkpoint inhibitors (ICIs). However, there are many factors influencing the usage of this indicator, which will lead to considerable consequences if not treated well. In this study, we performed a case study on a male advanced lung squamous cell carcinoma patient of age 83. The patient suffered from "cough and sputum", and did chest
Language	English
Publishing date	2022-08-03
Publishing country	Switzerland
Document type	Case Reports
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2022.939022
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Article: Statistical Learning Methods Applicable to Genome-Wide Association Studies on Unbalanced Case-Control Disease Data

Dai, Xiaotian / Fu, Guifang / Zhao, Shaofei / Zeng, Yifei

Genes. 2021 May 13, v. 12, no. 5

2021

Abstract: Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health ... ...

Abstract	Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health records have enabled the collection of thousands of phenotypes from large cohorts, in particular for diseases with low prevalence. The unbalanced binary traits pose serious challenges to traditional statistical methods in terms of both genomic selection and disease prediction. For example, the well-established linear mixed models (LMM) yield inflated type I error rates in the presence of unbalanced case-control ratios. In this article, we review multiple statistical approaches that have been developed to overcome the inaccuracy caused by the unbalanced case-control ratio, with the advantages and limitations of each approach commented. In addition, we also explore the potential for applying several powerful and popular state-of-the-art machine-learning approaches, which have not been applied to the GWAS field yet. This review paves the way for better analysis and understanding of the unbalanced case-control disease data in GWAS.
Keywords	artificial intelligence ; marker-assisted selection ; prediction ; telemedicine
Language	English
Dates of publication	2021-0513
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12050736
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Statistical Learning Methods Applicable to Genome-Wide Association Studies on Unbalanced Case-Control Disease Data.

Dai, Xiaotian / Fu, Guifang / Zhao, Shaofei / Zeng, Yifei

Genes

2021 Volume 12, Issue 5

Abstract	Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health records have enabled the collection of thousands of phenotypes from large cohorts, in particular for diseases with low prevalence. The unbalanced binary traits pose serious challenges to traditional statistical methods in terms of both genomic selection and disease prediction. For example, the well-established linear mixed models (LMM) yield inflated type I error rates in the presence of unbalanced case-control ratios. In this article, we review multiple statistical approaches that have been developed to overcome the inaccuracy caused by the unbalanced case-control ratio, with the advantages and limitations of each approach commented. In addition, we also explore the potential for applying several powerful and popular state-of-the-art machine-learning approaches, which have not been applied to the GWAS field yet. This review paves the way for better analysis and understanding of the unbalanced case-control disease data in GWAS.
MeSH term(s)	Case-Control Studies ; Genome/genetics ; Genome-Wide Association Study/methods ; Genomics/methods ; Humans ; Linear Models ; Machine Learning ; Phenotype
Language	English
Publishing date	2021-05-13
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12050736
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Article ; Online: Functional random forests for curve response.

Fu, Guifang / Dai, Xiaotian / Liang, Yeheng

Scientific reports

2021 Volume 11, Issue 1, Page(s) 24159

Abstract: The rapid advancement of functional data in various application fields has increased the demand for advanced statistical approaches that can incorporate complex structures and nonlinear associations. In this article, we propose a novel functional random ... ...

Abstract	The rapid advancement of functional data in various application fields has increased the demand for advanced statistical approaches that can incorporate complex structures and nonlinear associations. In this article, we propose a novel functional random forests (FunFor) approach to model the functional data response that is densely and regularly measured, as an extension of the landmark work of Breiman, who introduced traditional random forests for a univariate response. The FunFor approach is able to predict curve responses for new observations and selects important variables from a large set of scalar predictors. The FunFor approach inherits the efficiency of the traditional random forest approach in detecting complex relationships, including nonlinear and high-order interactions. Additionally, it is a non-parametric approach without the imposition of parametric and distributional assumptions. Eight simulation settings and one real-data analysis consistently demonstrate the excellent performance of the FunFor approach in various scenarios. In particular, FunFor successfully ranks the true predictors as the most important variables, while achieving the most robust variable sections and the smallest prediction errors when comparing it with three other relevant approaches. Although motivated by a biological leaf shape data analysis, the proposed FunFor approach has great potential to be widely applied in various fields due to its minimal requirement on tuning parameters and its distribution-free and model-free nature. An R package named 'FunFor', implementing the FunFor approach, is available at GitHub.
Language	English
Publishing date	2021-12-17
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-02265-4
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Article: [Neurobehavioral development of 25 254 children with different gestational ages at birth in three cities of China].

Liu, Ming-Xia / Dai, Xiao-Tian / Hua, Jing

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics

2020 Volume 22, Issue 9, Page(s) 931–935

Abstract: Objective: To study the effect of gestational age at birth on the neurobehavioral development of preschool children.: Methods: A total of 25 254 preschool children from Ma'anshan of Anhui Province, Taizhou of Zhejiang Province, and Yangzhou of ... ...

Abstract	Objective: To study the effect of gestational age at birth on the neurobehavioral development of preschool children. Methods: A total of 25 254 preschool children from Ma'anshan of Anhui Province, Taizhou of Zhejiang Province, and Yangzhou of Jiangsu Province were enrolled. The preschool children were divided into three groups based on their gestational ages at birth: preterm group (2 760 cases; 28-36 Results: The preterm group had significantly lower scores of the five domains of ASQ-3, communication, gross motor, fine motor, problem solving, and personal-social, than the full term group (P<0.05), and significantly lower scores of communication, gross motor, fine motor, and problem solving than the early term group (P<0.05). There were no significant differences in the scores of the five domains of ASQ-3 between the early term and full term groups (P>0.05). The multiple linear regression analysis indicated a significant positive correlation between gestational age and the five domains of ASQ-3 after adjustment for confounding factors including sex, age, body mass index, and parental education level (P<0.01). Conclusions: Children born preterm have poorer neurobehavioral development than those born full term and early term, whereas children born full term and early term have similar neurobehavioral development. Gestational age at birth is an independent influencing factor for neurobehavioral development in preschool children.
MeSH term(s)	Child Behavior ; Child Development ; Child, Preschool ; China ; Cities ; Gestational Age ; Humans ; Infant, Newborn ; Surveys and Questionnaires
Language	Chinese
Publishing date	2020-09-16
Publishing country	China
Document type	Journal Article
ISSN	1008-8830
ISSN	1008-8830
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Article ; Online: Detecting PCOS susceptibility loci from genome-wide association studies via iterative trend correlation based feature screening.

Dai, Xiaotian / Fu, Guifang / Reese, Randall

BMC bioinformatics

2020 Volume 21, Issue 1, Page(s) 177

Abstract: Background: Feature screening plays a critical role in handling ultrahigh dimensional data analyses when the number of features exponentially exceeds the number of observations. It is increasingly common in biomedical research to have case-control ( ... ...

Abstract	Background: Feature screening plays a critical role in handling ultrahigh dimensional data analyses when the number of features exponentially exceeds the number of observations. It is increasingly common in biomedical research to have case-control (binary) response and an extremely large-scale categorical features. However, the approach considering such data types is limited in extant literature. In this article, we propose a new feature screening approach based on the iterative trend correlation (ITC-SIS, for short) to detect important susceptibility loci that are associated with the polycystic ovary syndrome (PCOS) affection status by screening 731,442 SNP features that were collected from the genome-wide association studies. Results: We prove that the trend correlation based screening approach satisfies the theoretical strong screening consistency property under a set of reasonable conditions, which provides an appealing theoretical support for its outperformance. We demonstrate that the finite sample performance of ITC-SIS is accurate and fast through various simulation designs. Conclusion: ITC-SIS serves as a good alternative method to detect disease susceptibility loci for clinic genomic data.
MeSH term(s)	Case-Control Studies ; Female ; Genetic Predisposition to Disease ; Genome ; Genome-Wide Association Study/methods ; Humans ; Polycystic Ovary Syndrome/diagnosis ; Polycystic Ovary Syndrome/genetics
Language	English
Publishing date	2020-05-04
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-020-3492-z
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Article ; Online: Network Pharmacology Analysis of the Mechanisms of Compound Herba Sarcandrae (Fufang Zhongjiefeng) Aerosol in Chronic Pharyngitis Treatment.

Zhang, Yanping / Yuan, Taohua / Li, Yunsong / Wu, Ning / Dai, Xiaotian

Drug design, development and therapy

2021 Volume 15, Page(s) 2783–2803

Abstract: Purpose: This study aimed to investigate the molecular mechanisms of compound herba Sarcandrae aerosol, also known as the Fufang Zhongjiefeng (FFZJF) aerosol, in treating chronic pharyngitis (CP) using network pharmacology and in vivo experimental ... ...

Abstract	Purpose: This study aimed to investigate the molecular mechanisms of compound herba Sarcandrae aerosol, also known as the Fufang Zhongjiefeng (FFZJF) aerosol, in treating chronic pharyngitis (CP) using network pharmacology and in vivo experimental approaches. Methods: Active compounds and putative targets of five herbs in FFZJF were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Chemistry Database, and Swiss Target Prediction databases. The therapeutic targets of CP were obtained from OMIM, Durgbank, DisGeNT, and GAD databases. The active compounds-target networks were constructed using Cytoscape 3.6.1. The overlapping targets of FFZJF active compounds and CP targets were further analyzed using the String database to construct protein-protein interaction (PPI) network. KEGG pathway and Gene Ontology enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. The predicted targets and pathways were validated in a group A β-hemolytic streptococcus-induced rat CP model. Results: There were 45 active compounds identified from FFZJF and 11 potential protein targets identified for CP treatment. PPI network demonstrated that IL6, PTGS2, TLR-4, and TNF may serve as the key targets of FFZJF for the treatment of CP. The main functional pathways involving these key targets include cytokine secretion, inflammatory response, MyD88-dependent toll-like receptor signaling pathway, toll-like receptor signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. In a rat CP model, the elevation of serum TNF-α, IL1β, and IL6 levels, as well as the upregulation of TLR-4, MyD88, NF-κB P65 in the pharyngeal mucosal tissues could be effectively reduced by FFZJF treatment in a dose-dependent manner. Conclusion: Through a network pharmacology approach and animal study, we predicted and validated the active compounds of FFZJF and their potential targets for CP treatment. The results suggest that FFZJF can markedly alleviate GAS-induced chronic pharyngitis by modulating the TLR-4/MyD88/NF-κB signaling pathways.
MeSH term(s)	Aerosols ; Animals ; Chronic Disease ; Disease Models, Animal ; Dose-Response Relationship, Drug ; Drugs, Chinese Herbal/administration & dosage ; Drugs, Chinese Herbal/pharmacology ; Female ; Male ; Medicine, Chinese Traditional ; Myeloid Differentiation Factor 88/metabolism ; NF-kappa B/metabolism ; Network Pharmacology ; Pharyngitis/drug therapy ; Pharyngitis/physiopathology ; Protein Interaction Maps/drug effects ; Rats ; Rats, Sprague-Dawley ; Toll-Like Receptor 4/metabolism
Chemical Substances	Aerosols ; Drugs, Chinese Herbal ; Myd88 protein, rat ; Myeloid Differentiation Factor 88 ; NF-kappa B ; Tlr4 protein, rat ; Toll-Like Receptor 4 ; uvangoletin
Language	English
Publishing date	2021-06-28
Publishing country	New Zealand
Document type	Journal Article
ZDB-ID	2451346-5
ISSN	1177-8881 ; 1177-8881
ISSN (online)	1177-8881
ISSN	1177-8881
DOI	10.2147/DDDT.S304708
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Discretization and Stabilization of Energy-Based Controller for Period Switching Control and Flexible Scheduling

Tafrishi, Seyed Amir / Dai, Xiaotian / Hirata, Yasuhisa / Burns, Alan

2022

Abstract: Emerging advanced control applications, with increased complexity in software but limited computing resources, suggest that real-time controllers should have adaptable designs. These control strategies also should be designed with consideration of the ... ...

Abstract	Emerging advanced control applications, with increased complexity in software but limited computing resources, suggest that real-time controllers should have adaptable designs. These control strategies also should be designed with consideration of the run-time behavior of the system. One of such research attempts is to design the controller along with the task scheduler, known as control-scheduling co-design, for more predictable timing behavior as well as surviving system overloads. Unlike traditional controller designs, which have equal-distance sampling periods, the co-design approach increases the system flexibility and resilience by explicitly considering timing properties, for example using an event-based controller or with multiple sampling times (non-uniform sampling and control). Within this context, we introduce the first work on the discretization of an energy-based controller that can switch arbitrarily between multiple periods and adjust the control parameters accordingly without destabilizing the system. A digital controller design based on this paradigm for a DC motor with an elastic load as an example is introduced and the stability condition is given based on the proposed Lyapunov function. The method is evaluated with various computer-based simulations which demonstrate its effectiveness. Comment: Accepted to 2022 American Control Conference (ACC), 6 pages, 8 figures
Keywords	Electrical Engineering and Systems Science - Systems and Control ; Computer Science - Robotics ; Mathematics - Optimization and Control
Subject code	629
Publishing date	2022-06-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Autologous transplantation of P63

Wang, Yujia / Meng, Zili / Liu, Ming / Zhou, Yueqing / Chen, Difei / Zhao, Yu / Zhang, Ting / Zhong, Nanshan / Dai, Xiaotian / Li, Shiyue / Zuo, Wei

Science translational medicine

2024 Volume 16, Issue 734, Page(s) eadi3360

Abstract: Adult lung resident stem/progenitor cells, including ... ...

Abstract	Adult lung resident stem/progenitor cells, including P63
MeSH term(s)	Adult ; Humans ; Transplantation, Autologous ; Lung/metabolism ; Pulmonary Disease, Chronic Obstructive/metabolism ; Epithelium/metabolism ; Stem Cells/metabolism
Language	English
Publishing date	2024-02-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	2518854-9
ISSN	1946-6242 ; 1946-6234
ISSN (online)	1946-6242
ISSN	1946-6234
DOI	10.1126/scitranslmed.adi3360
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