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Surface Processes Driving Intracontinental Basin Subsidence in the Context of India–Eurasia Collision:Evidence from Flexural Subsidence Modeling of the Cenozoic Southern Tarim Basin along the west Kunlun Foreland,NW Tibetan Plateau

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Acta Geologica Sinica(English Edition) 2023年第6期97卷 1778-1786页

作者： HUANG Hao LIN Xiubin AN Kaixuan ZHANG Yuqing CHEN Hanlin CHENG Xiaogan LI Chunyang Key Laboratory of Geoscience big data and Deep Resources of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310027China Research center for Structures in Oil and Gas-Bearing Basins Ministry of EducationHangzhou 310027China Research Institute of Petroleum Exploration and Development PetroChinaBeijing 100083China Research Institute of Petroleum Exploration and Development Sinopec Southwest Oil and Gas CompanyChengdu 610041China

The India–Eurasia collision has produced a number of Cenozoic deep intracontinental basins,which bear important information for revealing the far-afield responses to the remote collision.Despite their significance,their subsiding mechanism remains the subject of debate,with end-member models attributing it to either orogenic or sedimentary load.In this study,we conduct flexural subsidence modeling with a two-dimensional finite elastic plate model on the Hotan-Mazatagh section along the southern Tarim Basin,which defines a key region in the foreland of the west Kunlun Orogen,along the NW margin of the Tibetan Plateau.The modeling results indicate that the orogenic load of west Kunlun triggers the southern Tarim Basin to subside by up to less than ~6 km,with its impact weakening towards the basin interiors until ~230 km north from the Karakax fault.The sedimentary load,consisting of Cenozoic strata,forces the basin to subside by ~2 to~7 km.In combination with the retreat of the proto-Paratethys Sea and the paleogeographic reorganization of the Tarim Basin,we propose that surface processes,in particular a shift from an exorheic to an endorheic drainage system associated with the consequent thick sedimentary load,played a decisive role in forming deep intracontinental basins in the context of the India-Eurasia collision.

关键词： flexural subsidence modeling India-Eurasia collision west Kunlun Tarim Basin Northwest Tibetan Plateau

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Postpartum depression and major depressive disorder:the same or not?Evidence from resting-state functional MRI

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Psychoradiology 2022年第3期2卷 121-128页

作者： Bochao Cheng Yi Guo Xijian Chen Bin Lv Yi Liao Haibo Qu Xiao Hu Haoxiang Yang Yajing Meng Wei Deng Jiaojian Wang Department of Radiology West China Second University Hospital of Sichuan UniversityChengdu 610041China Key Laboratory of Birth Defects and Related Diseases of Women and Children(Sichuan University) Ministry of EducationChengdu 610041China Department of Gynecology and Obstetrics West China Second University HospitalSichuan UniversityChengdu 610041China Department of Rehabilitation Medicine West China Second University HospitalSichuan UniversityChengdu 610041China Department of Psychiatry West China Hospital of Sichuan UniversityChengdu 610041China Affiliated Mental Health center&Hangzhou Seventh People’s Hospital Zhejiang University School of MedicineHangzhouZhejiang 310063China State Key Laboratory of Primate biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Primate biomedical Research KunmingYunnan 650500China

Background Although postpartum depression(PPD)and non-peripartum major depressive disorder(MDD)occurring within and outside the postpartum period share many clinical characteristics,whether PPD and MDD are the same or not remains controversial.Methods The current study was devoted to identify the shared and different neural circuits between PPD and MDD by resting-state functionalmagnetic resonance imaging data from 77 participants(22 first-episodic drug-naleMDD,26 drug-nale PPD,and 29 healthy controls(HC)).Results Both the PPD andMDD groups exhibited higher fractional amplitude of low-frequency fluctuation(fALFF)in left temporal pole relative to the HC group;the MDD group showed specifically increased degree centrality in the right cerebellum while PPD showed specifically decreased fALFF in the left supplementary motor area and posterior middle temporal gyrus(pMTG_L),and specifically decreased functional connectivities between pMTG and precuneus and between left subgeneual anterior cingulate cortex(sgACC_L)and right sgACC.Moreover,sgACC and left thalamus showed abnormal regional homogeneity of functional activities between any pair of HC,MDD,and PPD.Conclusions These results provide initial evidence that PPD and MDD have common and distinct neural circuits,which may facilitate understanding the neurophysiological basis and precision treatment for PPD.

关键词： postpartum depression major depressive disorder resting-state fMRI functional activity functional connectivity

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GTB-PPI:Predict Protein-protein Interactions Based on L1-regularized Logistic Regression and Gradient Tree Boosting

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Genomics, Proteomics & Bioinformatics 2020年第5期18卷 582-592页

作者： Bin Yu Cheng Chen Hongyan Zhou Bingqiang Liu Qin Ma School of Life Sciences University of Science and Technology of ChinaHefei 230027China College of Mathematics and Physics Qingdao University of Science and TechnologyQingdao 266061China Artificial Intelligence and biomedical big data Research center Qingdao University of Science and TechnologyQingdao 266061China School of Mathematics Shandong UniversityJinan 250100China Department of biomedical Informatics College of MedicineThe Ohio State UniversityColumbusOH 43210USA

Protein-protein interactions(PPIs)are of great importance to understand genetic mechanisms,delineate disease pathogenesis,and guide drug design.With the increase of PPI data and development of machine learning technologies,prediction and identification of PPIs have become a research hotspot in proteomics.In this study,we propose a new prediction pipeline for PPIs based on gradient tree boosting(GTB).First,the initial feature vector is extracted by fusing pseudo amino acid composition(Pse AAC),pseudo position-specific scoring matrix(Pse PSSM),reduced sequence and index-vectors(RSIV),and autocorrelation descriptor(AD).Second,to remove redundancy and noise,we employ L1-regularized logistic regression(L1-RLR)to select an optimal feature subset.Finally,GTB-PPI model is constructed.Five-fold cross-validation showed that GTB-PPI achieved the accuracies of 95.15% and 90.47% on Saccharomyces cerevisiae and Helicobacter pylori datasets,respectively.In addition,GTB-PPI could be applied to predict the independent test datasets for Caenorhabditis elegans,Escherichia coli,Homo sapiens,and Mus musculus,the one-core PPI network for CD9,and the crossover PPI network for the Wnt-related signaling pathways.The results show that GTB-PPI can significantly improve accuracy of PPI prediction.The code and datasets of GTB-PPI can be downloaded from https://***/QUST-AIBBDRC/GTB-PPI/.

关键词： Protein-protein interaction Feature fusion L1-regularized logistic regression Gradient tree boosting Machine learning

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Current status and future prospects of stomatology research

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2023年第10期24卷 853-867,I0001页

作者： Qianming CHEN Yahui WANG Jing SHUAI Stomatology Hospital School of StomatologyZhejiang University School of MedicineClinical Research Center for Oral Diseases of Zhejiang ProvinceKey Laboratory of Oral Biomedical Research of Zhejiang ProvinceCancer Center of Zhejiang UniversityHangzhou 310006China

Research in stomatology(dental medicine)continues to expand globally and is oriented towards solving clinical issues,focusing on clarifying the clinical relevance and potential mechanisms of oral–systemic connections via clinical epidemiology,oral microecological characterization,and the establishment of animal models.Interdisciplinary integration of materials science and tissue engineering with stomatology is expected to lead to the creation of innovative materials and technologies to better resolve the most prevalent and challenging clinical issues such as peri-implantitis,soft and hard tissue defects,and dentin hypersensitivity.With the rapid development of artificial intelligence(AI),5th generation mobile communication technology(5G),and big data applications,“intelligent stomatology”is emerging to build models for better clinical diagnosis and management,accelerate the reform of education,and support the growth and advancement of scientific research.Here,we summarized the current research status,and listed the future prospects and limitations of these three aspects,aiming to provide a basis for more accurate etiological exploration,novel treatment methods,and abundant big data analysis in stomatology to promote the translation of research achievements into practical applications for both clinicians and the public.

关键词： Stomatology Dental medicine Systemic disease Material Innovative technique

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IRES-mediated cap-independent translation,a path leading to hidden proteome

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Journal of Molecular Cell Biology 2019年第10期11卷 911-919页

作者： Yun Yang Zefeng Wang CAS Key Laboratory of Computational Biology Biomedical Big Data CenterCAS-MPG Partner Institute for Computational BiologyShanghai Institute of Nutrition and HealthChinese Academy of SciencesShanghai 200031China University of Chinese Academy of Sciences Chinese Academy of SciencesShanghai 200031China CAS center for Excellence in Molecular Cell Science Chinese Academy of SciencesShanghai 200031China

Most eukaryotic mRNAs are translated in a cap-dependent fashion;however,under stress conditions,the cap-independent translation driven by internal ribosomal entry sites(IRESs)can serve as an alternative mechanism for protein production.Many IRESs have been discovered from viral or cellular mRNAs to promote ribosome assembly and initiate translation by recruiting different trons-acting factors.Although the mechanisms of translation initiation driven by viral IRESs are relatively well understood,the existence of cellular IRESs is still under debate due to the limitations of translation reporter systems used to assay IRES activities.A recent screen identified>1000 putative IRESs from viral and human mRNAs,expanding the scope and mechanism for capindependent translation.Additionally,a large number of circular RNAs lacking free ends were identified in eukaryotic cells,many of which are found to be translated through IRESs.These findings suggest that IRESs may play a previously unappreciated role in driving translation of the new type of mRNA,implying a hidden proteome produced from cap-independent translation.

关键词： IRES ITAF translation bicistronic system circular RNA

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High-Quality Development of Stomatology under the National Strategy

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Chinese Medical Sciences Journal 2022年第2期37卷 95-97页

作者： Xuedong Zhou State Key Laboratory of Oral Diseases National Clinical Research Center for Oral DiseasesWest China Hospital of StomatologySichuan UniversityChengdu 610041China

The 19th National Congress of the Communist Party of china has proposed a national strategy for a healthy china,which includes the formulation of a new plan to promote high-quality development.Oral diseases have been included in the national“Medium-and Long-term Plan for the Prevention and Treatment of Chronic Diseases”.chinas national oral health strategy provides great opportunities for advancements in stomatology and for the improvement of the people s oral health.This article discusses these opportunities for advancement in the field of stomatology in china from six aspects:societal needs of oral health;advances in science and technology;changed diagnosis and treatment modes;application of big data;multidistiplinary integration;and talent training.

关键词： stomatology Healthy china strategy high-quality development

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White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging

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Neuroscience Bulletin 2019年第5期35卷 867-876页

作者： Sugai Liang Qiang Wang Xiangzhen Kong Wei Deng Xiao Yang Xiaojing Li Zhong Zhang Jian Zhang Chengcheng Zhang Xin-min Li Xiaohong Ma Junming Shao Andrew J. Greenshaw Tao Li Mental Health Centre West China Hospital Sichuan University Chengdu 610041 China Huaxi Brain Research Centre West China Hospital Sichuan University Chengdu 610041 China Language and Genetics Department Max Planck Institute for Psycholinguistics 6525 XD Nijmegen Netherlands big data Research center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Psychiatry University of Alberta Edmonton T6G 2B7 Canada

Identifying data-driven biotypes of major depressive disorder(MDD) has promise for the clarification of diagnostic heterogeneity. However, few studies have focused on white-matter abnormalities for MDD subtyping. This study included 116 patients with MDD and118 demographically-matched healthy controls assessed by diffusion tensor imaging and neurocognitive evaluation.Hierarchical clustering was applied to the major fiber tracts, in conjunction with tract-based spatial statistics, to reveal white-matter alterations associated with MDD.Clinical and neurocognitive differences were compared between identified subgroups and healthy controls. With fractional anisotropy extracted from 20 fiber tracts, cluster analysis revealed 3 subgroups based on the patterns of abnormalities. Patients in each subgroup versus healthy controls showed a stepwise pattern of white-matter alterations as follows: subgroup 1(25.9% of patient sample),widespread white-matter disruption;subgroup 2(43.1% of patient sample), intermediate and more localized abnormalities in aspects of the corpus callosum and left cingulate;and subgroup 3(31.0% of patient sample),possible mild alterations, but no statistically significant tract disruption after controlling for family-wise error. The neurocognitive impairment in each subgroup accompanied the white-matter alterations: subgroup 1, deficits in sustained attention and delayed memory;subgroup 2, dysfunction in delayed memory;and subgroup 3, no significant deficits. Three subtypes of white-matter abnormality exist in individuals with major depression, those having widespread abnormalities suffering more neurocognitive impairments, which may provide evidence for parsing the heterogeneity of the disorder and help optimize typespecific treatment approaches.

关键词： Major depressive disorder Hierarchal clustering Diffusion tensor imaging Biotype Heterogeneity

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Phenomic Studies on Diseases:Potential and Challenges

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Phenomics 2023年第3期3卷 285-299页

作者： Weihai Ying Med‑X Research Institute and School of biomedical Engineering Shanghai Jiao Tong University1954 Huashan RoadShanghai 200030China Collaborative Innovation center for Genetics and Development Shanghai 200043China

The rapid development of such research field as multi-omics and artificial intelligence(AI)has made it possible to acquire and analyze the multi-dimensional big data of human phenomes.Increasing evidence has indicated that phenomics can pro-vide a revolutionary strategy and approach for discovering new risk factors,diagnostic biomarkers and precision therapies of diseases,which holds profound advantages over conventional approaches for realizing precision medicine:first,the big data of patients'phenomes can provide remarkably richer information than that of the genomes;second,phenomic studies on diseases may expose the correlations among cross-scale and multi-dimensional phenomic parameters as well as the mecha-nisms underlying the correlations;and third,phenomics-based studies are big data-driven studies,which can significantly enhance the possibility and efficiency for generating novel discoveries.However,phenomic studies on human diseases are still in early developmental stage,which are facing multiple major challenges and tasks:first,there is significant deficiency in analytical and modeling approaches for analyzing the multi-dimensional data of human phenomes;second,it is crucial to establish universal standards for acquirement and management of phenomic data of patients;third,new methods and devices for acquirement of phenomic data of patients under clinical settings should be developed;fourth,it is of significance to establish the regulatory and ethical guidelines for phenomic studies on diseases;and fifth,it is important to develop effective international cooperation.It is expected that phenomic studies on diseases would profoundly and comprehensively enhance our capacity in prevention,diagnosis and treatment of diseases.

关键词： Phenomics Diseases big data Precision medicine Diagnosis

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Translational Informatics for Parkinson’s Disease:from big biomedical data to Small Actionable Alterations

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Genomics, Proteomics & Bioinformatics 2019年第4期17卷 415-429页

作者： Bairong Shen Yuxin Lin Cheng Bi Shengrong Zhou Zhongchen Bai Guangmin Zheng Jing Zhou Institutes for Systems Genetics West China HospitalSichuan UniversityChengdu 610041China center for Systems Biology Soochow UniversitySuzhou 215006China center for Translational biomedical Informatics Guizhou University School of MedicineGuiyang 550025China

Parkinson’s disease(PD)is a common neurological disease in elderly people,and its morbidity and mortality are increasing with the advent of global ageing.The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations.To highlight the use of big data for precision PD medicine,we review PD big data and informatics for the translation of basic PD research to clinical applications.We emphasize some key findings in clinically actionable changes,such as susceptibility genetic variations for PD risk population screening,biomarkers for the diagnosis and stratification of PD patients,risk factors for PD,and lifestyles for the prevention of PD.The challenges associated with the collection,storage,and modelling of diverse big data for PD precision medicine and healthcare are also summarized.Future perspectives on systems modelling and intelligent medicine for PD monitoring,diagnosis,treatment,and healthcare are discussed in the end.

关键词： Parkinson’s disease Healthcare Disease biomarker Translational informatics Systems modelling

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Inpatient bed allocation policy under uncertain capacity

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Journal of Management Science and Engineering 2019年第4期4卷 228-251页

作者： Xing Liu Youhua Chen Li Luo Ting Zhu Wenwu Shen TAIWO Enayon Sunday Noah’s Ark Laboratory Huawei TechnologiesShenzhen250012China Business School City University of Hong KongHong KongChina Business School Sichuan UniversitySichuan610064China West China Biomedical Big Data Center West China Hospital/West China School of MedicineSichuan UniversitySichaun610041China Outpatient Department West China HospitalSichuan UniversitySichuan610041China

This paper concerns the problem of inpatient bed allocation for two classes of patients(scheduled and non-scheduled)when there is uncertainty about daily available capacity.In the afternoon of each day,patients from the scheduled class,also called backlogged elective admissions,are selected from a waiting list,for the admission on the next day.The non-scheduled class,also called emergent admissions,are new requests that arise randomly each day with emergent needs.The capacity of available beds for a medical specialty to provide hospitalization services is uncertain when backlogged elective pa-tients are chosen.Admitting too many of elective patients may result in exceeding a day’s capacity,which can potentially necessitate"overflowing"or"postponing"some emergent requests that should be performed as soon as possible.Therefore,the problem faced by the medical specialty facility at the decision-making point of each day is how many of the backlogged elective patients can be admitted.We formulate this problem as a Markov decision process(MDP)and study the structural properties of the model to characterize the nature of the optimal policy.We propose easy-to-implement policies(the fixed quota policy and the best fixed quota policy),which perform well under fitted distributions.By reporting numerical analyses using real data from a Chinese public hospital,we finally compare the improvements that our proposed solutions could bring to the hospital with the existing practices under several different cost structures.

关键词： Bed allocation Markov decision process Emergency reservation Healthcare management

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