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  1. Artikel ; Online: Psychological crisis interventions in Sichuan Province during the 2019 novel coronavirus outbreak.

    Zhou, Xiaobo

    Psychiatry research

    2020  Band 286, Seite(n) 112895

    Schlagwörter covid19
    Sprache Englisch
    Erscheinungsdatum 2020-02-26
    Erscheinungsland Ireland
    Dokumenttyp Letter
    ZDB-ID 445361-x
    ISSN 1872-7123 ; 1872-7506 ; 0925-4927 ; 0165-1781
    ISSN (online) 1872-7123 ; 1872-7506
    ISSN 0925-4927 ; 0165-1781
    DOI 10.1016/j.psychres.2020.112895
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: Study of prognostic splicing factors in cancer using machine learning approaches.

    Yang, Mengyuan / Liu, Jiajia / Kim, Pora / Zhou, Xiaobo

    Human molecular genetics

    2024  

    Abstract: Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the ... ...

    Abstract Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the generation of oncogenic proteins involved in cancer hallmarks. In this study, we investigated the genes that encode RNA-binding proteins and identified potential splicing factors that contribute to the aberrant splicing applying a random forest classification model. The result suggested 56 splicing factors were related to the prognosis of 13 cancers, two SF complexes in liver hepatocellular carcinoma, and one SF complex in esophageal carcinoma. Further systematic bioinformatics studies on these cancer prognostic splicing factors and their related alternative splicing events revealed the potential regulations in a cancer-specific manner. Our analysis found high ILF2-ILF3 expression correlates with poor prognosis in LIHC through alternative splicing. These findings emphasize the importance of SFs as potential indicators for prognosis or targets for therapeutic interventions. Their roles in cancer exhibit complexity and are contingent upon the specific context in which they operate. This recognition further underscores the need for a comprehensive understanding and exploration of the role of SFs in different types of cancer, paving the way for their potential utilization in prognostic assessments and the development of targeted therapies.
    Sprache Englisch
    Erscheinungsdatum 2024-03-27
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 1108742-0
    ISSN 1460-2083 ; 0964-6906
    ISSN (online) 1460-2083
    ISSN 0964-6906
    DOI 10.1093/hmg/ddae047
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Advances in Non-Type 2 Asthma in the Severe Cases: from molecular insights to novel treatment strategies.

    Liu, Tao / Prescott, Woodruff G / Zhou, Xiaobo

    The European respiratory journal

    2024  

    Abstract: Asthma is a prevalent pulmonary disease that affects nearly 300 million people worldwide and imposes a substantial economic burden. While medication can effectively control symptoms in some patients, severe asthma attacks, driven by airway-inflammation ... ...

    Abstract Asthma is a prevalent pulmonary disease that affects nearly 300 million people worldwide and imposes a substantial economic burden. While medication can effectively control symptoms in some patients, severe asthma attacks, driven by airway-inflammation induced by environmental and infectious exposures, continue to be a major cause of asthma-related mortality. Heterogenous phenotypes of asthma include type 2 (T2) and non-T2 asthma. Non-T2 asthma is often observed in patients with severe and/or steroid-resistant asthma. This review will cover the molecular mechanisms, clinical phenotypes, causes and promising treatment of non-T2 severe asthma. Specifically, we will discuss the signaling pathways for non-T2 asthma including the activation of inflammasomes, interferon responses, and IL-17 pathways, and their contributions to the subtypes, progression, and severity of non-T2 asthma. Understanding the molecular mechanisms and genetic determinants underlying non-T2 asthma could form the basis for precision medicine in severe asthma treatment.
    Sprache Englisch
    Erscheinungsdatum 2024-05-02
    Erscheinungsland England
    Dokumenttyp Journal Article ; Review
    ZDB-ID 639359-7
    ISSN 1399-3003 ; 0903-1936
    ISSN (online) 1399-3003
    ISSN 0903-1936
    DOI 10.1183/13993003.00826-2023
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel: A Cell Cycle-aware Network for Data Integration and Label Transferring of Single-cell RNA-seq and ATAC-seq.

    Liu, Jiajia / Ma, Jian / Wen, Jianguo / Zhou, Xiaobo

    bioRxiv : the preprint server for biology

    2024  

    Abstract: In recent years, the integration of single-cell multi-omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non-single omics perspective, but it still suffers many challenges, such as omics- ...

    Abstract In recent years, the integration of single-cell multi-omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non-single omics perspective, but it still suffers many challenges, such as omics-variance, sparsity, cell heterogeneity and confounding factors. As we know, cell cycle is regarded as a confounder when analyzing other factors in single-cell RNA-seq data, but it's not clear how it will work on the integrated single-cell multi-omics data. Here, we developed a Cell Cycle-Aware Network (CCAN) to remove cell cycle effects from the integrated single-cell multi-omics data while keeping the cell type-specific variations. This is the first computational model to study the cell-cycle effects in the integration of single-cell multi-omics data. Validations on several benchmark datasets show the out-standing performance of CCAN in a variety of downstream analyses and applications, including removing cell cycle effects and batch effects of scRNA-seq datasets from different protocols, integrating paired and unpaired scRNA-seq and scATAC-seq data, accurately transferring cell type labels from scRNA-seq to scATAC-seq data, and characterizing the differentiation process from hematopoietic stem cells to different lineages in the integration of differentiation data.
    Sprache Englisch
    Erscheinungsdatum 2024-02-02
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2024.01.31.578213
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel: Single-cell Landscape of Malignant Transition: Unraveling Cancer Cell-of-Origin and Heterogeneous Tissue Microenvironment.

    Luo, Ruihan / Liu, Jiajia / Wen, Jianguo / Zhou, Xiaobo

    Research square

    2024  

    Abstract: Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by ... ...

    Abstract Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.
    Sprache Englisch
    Erscheinungsdatum 2024-04-05
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.21203/rs.3.rs-4085185/v1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; Online: CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.

    Hosseini, Sayed-Rzgar / Zhou, Xiaobo

    Briefings in bioinformatics

    2022  Band 24, Heft 1

    Abstract: Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug ... ...

    Abstract Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, context aware and integrative deep-learning framework that we have established to unleash the potential of the Chemical Checker extended drug bioactivity profiles for the purpose of drug synergy prediction. We have shown that CCSynergy enables predictions of superior accuracy, remarkable robustness and improved context generalizability as compared to the state-of-the-art methods in the field. Having established the potential of CCSynergy for generating experimentally validated predictions, we next exhaustively explored the untested drug combination space. This resulted in a compendium of potentially synergistic drug combinations on hundreds of cancer cell lines, which can guide future experimental screens.
    Mesh-Begriff(e) Drug Synergism ; Deep Learning ; Computational Biology/methods ; Cell Line, Tumor ; Antineoplastic Agents/pharmacology ; Antineoplastic Agents/therapeutic use ; Drug Combinations
    Chemische Substanzen Antineoplastic Agents ; Drug Combinations
    Sprache Englisch
    Erscheinungsdatum 2022-12-23
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2068142-2
    ISSN 1477-4054 ; 1467-5463
    ISSN (online) 1477-4054
    ISSN 1467-5463
    DOI 10.1093/bib/bbac588
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Buch ; Dissertation / Habilitation: Characterization and regulation of calcium activated potassium channels

    Zhou, Xiaobo

    1997  

    Verfasserangabe Xiao-Bo Zhou
    Sprache Englisch
    Umfang 59 S. : graph. Darst.
    Dokumenttyp Buch ; Dissertation / Habilitation
    Dissertation / Habilitation München, Techn. Univ., Diss., 1997
    HBZ-ID HT008601171
    Datenquelle Katalog ZB MED Medizin, Gesundheit

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  8. Artikel ; Online: LVPT: Lazy Velocity Pseudotime Inference Method.

    Mao, Shuainan / Liu, Jiajia / Zhao, Weiling / Zhou, Xiaobo

    Biomolecules

    2023  Band 13, Heft 8

    Abstract: The emergence of RNA velocity has enriched our understanding of the dynamic transcriptional landscape within individual cells. In light of this breakthrough, we embarked on integrating RNA velocity with cellular pseudotime inference, aiming to improve ... ...

    Abstract The emergence of RNA velocity has enriched our understanding of the dynamic transcriptional landscape within individual cells. In light of this breakthrough, we embarked on integrating RNA velocity with cellular pseudotime inference, aiming to improve the prediction of cell orders along biological trajectories beyond existing methods. Here, we developed LVPT, a novel method for pseudotime and trajectory inference. LVPT introduces a lazy probability to indicate the probability that the cell stays in the original state and calculates the transition matrix based on RNA velocity to provide the probability and direction of cell differentiation. LVPT shows better and comparable performance of pseudotime inference compared with other existing methods on both simulated datasets with different structures and real datasets. The validation results were consistent with prior knowledge, indicating that LVPT is an accurate and efficient method for pseudotime inference.
    Mesh-Begriff(e) Cell Differentiation ; Probability ; RNA
    Chemische Substanzen RNA (63231-63-0)
    Sprache Englisch
    Erscheinungsdatum 2023-08-12
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
    ZDB-ID 2701262-1
    ISSN 2218-273X ; 2218-273X
    ISSN (online) 2218-273X
    ISSN 2218-273X
    DOI 10.3390/biom13081242
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel ; Online: Prevalence and factors associated with smartphone addiction among nursing postgraduates during the COVID-19 pandemic: a multilevel study from China's mainland.

    Liu, Jie / Yu, Xingfeng / Kong, Lingna / Zhou, Xiaobo

    BMC psychiatry

    2023  Band 23, Heft 1, Seite(n) 915

    Abstract: Background: Smartphone addiction is prevalent among college students, and there is a concern that the COVID-19 pandemic may bring an increased prevalence of smartphone addiction due to constant online classes and repeat quarantine policies. This study ... ...

    Abstract Background: Smartphone addiction is prevalent among college students, and there is a concern that the COVID-19 pandemic may bring an increased prevalence of smartphone addiction due to constant online classes and repeat quarantine policies. This study aims to assess the prevalence and influencing factors of smartphone addiction among Chinese nursing postgraduates during the pandemic by examining variables, including loneliness, perceived stress, resilience, and sense of security.
    Methods: This online cross-sectional survey recruited 224 nursing postgraduates in four cities in 2022, using Smartphone Addiction Scale for College Students, the Chinese version of Perceived Stress Scale, UCLA Loneliness Scale Version 3, Chinese version of the 10-item Connor-Davidson Resilience Scale, and the Security Questionnaire. Hierarchical regression analysis and logistic regression analysis were performed to explore the associated factors and predictors of smartphone addiction.
    Results: During the COVID-19 pandemic, the prevalence of smartphone addiction was 10.41%. There was a positive correlation between smartphone addiction and loneliness, perceived stress (P < 0.001), and a negative relationship with resilience and sense of security (P < 0.001). The logistic regression analysis identified five risk factors that contribute to smartphone addiction, including daily duration of using a smartphone (3-5 h) (OR = 11.085, 95%CI = 1.21-101.79), numbers of smartphone (OR = 3.704, 95%CI = 1.33-10.30), perceived stress (OR = 1.163, 95%CI = 1.06-1.28), loneliness (OR = 1.071, 95%CI = 1.01-1.13), age of using a smartphone first time (OR = 0.754, 95%CI = 0.60-0.95). Two protective factors, resilience (OR = 1.098, 95%CI = 1.01-1.20) and sense of security (OR = 0.950, 95%CI = 0.90-1.00), were identified.
    Conclusions: Collectively, our study found that during the COVID-19 pandemic, smartphone addiction was prevalent among nursing postgraduates, and loneliness and perceived stress are important risk factors for smartphone addiction. Therefore, administrators should adopt targeted interventions to reduce smartphone addiction and the negative impacts on the psychological well-being of nursing postgraduates during a sudden outbreak of a national epidemic crisis.
    Mesh-Begriff(e) Humans ; COVID-19/epidemiology ; Pandemics ; Prevalence ; Cross-Sectional Studies ; Internet Addiction Disorder ; Smartphone ; China/epidemiology
    Sprache Englisch
    Erscheinungsdatum 2023-12-06
    Erscheinungsland England
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2050438-X
    ISSN 1471-244X ; 1471-244X
    ISSN (online) 1471-244X
    ISSN 1471-244X
    DOI 10.1186/s12888-023-05369-5
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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