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  1. Article ; Online: FOXO1 reduces STAT3 activation and causes impaired mitochondrial quality control in diabetic cardiomyopathy.

    Zhou, Lu / Su, Wating / Wang, Yafeng / Zhang, Yuefu / Xia, Zhongyuan / Lei, Shaoqing

    Diabetes, obesity & metabolism

    2023  Volume 26, Issue 2, Page(s) 732–744

    Abstract: Aims: To investigate the role of FOXO1 in STAT3 activation and mitochondrial quality control in the diabetic heart.: Methods: Type 1 diabetes mellitus (T1DM) was induced in rats by a single intraperitoneal injection of 60 mg · kg: Results: Rats ... ...

    Abstract Aims: To investigate the role of FOXO1 in STAT3 activation and mitochondrial quality control in the diabetic heart.
    Methods: Type 1 diabetes mellitus (T1DM) was induced in rats by a single intraperitoneal injection of 60 mg · kg
    Results: Rats with T1DM or T2DM had excessive cardiac FOXO1 activation, accompanied by decreased STAT3 activation. Immunofluorescence and immunoprecipitation analysis showed colocalization and association of FOXO1 and STAT3 under basal conditions in isolated cardiomyocytes. Selective inhibition of FOXO1 activation by AS1842856 or FOXO1 siRNA transfection improved STAT3 activation, mitophagy and mitochondrial fusion, and decreased mitochondrial fission in isolated cardiomyocytes exposed to HG. Transfection with STAT3 siRNA further reduced mitophagy, mitochondrial fusion and increased mitochondrial fission in HG-treated cardiomyocytes. AS1842856 alleviated cardiac dysfunction, pathological damage and improved STAT3 activation, mitophagy and mitochondrial dynamics in diabetic db/db mice. Additionally, AS1842856 improved mitochondrial function indicated by increased mitochondrial membrane potential and adenosine triphosphate production and decreased mitochondrial reactive oxygen species production in isolated cardiomyocytes exposed to HG.
    Conclusions: Excessive FOXO1 activation during diabetes reduces STAT3 activation, with subsequent impairment of mitochondrial quality, ultimately promoting the development of diabetic cardiomyopathy.
    MeSH term(s) Animals ; Mice ; Rats ; Diabetes Mellitus, Type 1/complications ; Diabetes Mellitus, Type 1/metabolism ; Diabetes Mellitus, Type 2/complications ; Diabetes Mellitus, Type 2/metabolism ; Diabetic Cardiomyopathies ; Glucose/metabolism ; Mitochondria ; Myocytes, Cardiac/metabolism ; RNA, Small Interfering/therapeutic use
    Chemical Substances Glucose (IY9XDZ35W2) ; RNA, Small Interfering ; Foxo1 protein, rat ; Foxo1 protein, mouse ; Stat3 protein, rat ; Stat3 protein, mouse
    Language English
    Publishing date 2023-11-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 1454944-x
    ISSN 1463-1326 ; 1462-8902
    ISSN (online) 1463-1326
    ISSN 1462-8902
    DOI 10.1111/dom.15369
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The role of circadian clock-controlled mitochondrial dynamics in diabetic cardiomyopathy.

    Jin, Zhenshuai / Ji, Yanwei / Su, Wating / Zhou, Lu / Wu, Xiaojing / Gao, Lei / Guo, Junfan / Liu, Yutong / Zhang, Yuefu / Wen, Xinyu / Xia, Zhong-Yuan / Xia, Zhengyuan / Lei, Shaoqing

    Frontiers in immunology

    2023  Volume 14, Page(s) 1142512

    Abstract: Diabetes mellitus is a metabolic disease with a high prevalence worldwide, and cardiovascular complications are the leading cause of mortality in patients with diabetes. Diabetic cardiomyopathy (DCM), which is prone to heart failure with preserved ... ...

    Abstract Diabetes mellitus is a metabolic disease with a high prevalence worldwide, and cardiovascular complications are the leading cause of mortality in patients with diabetes. Diabetic cardiomyopathy (DCM), which is prone to heart failure with preserved ejection fraction, is defined as a cardiac dysfunction without conventional cardiac risk factors such as coronary heart disease and hypertension. Mitochondria are the centers of energy metabolism that are very important for maintaining the function of the heart. They are highly dynamic in response to environmental changes through mitochondrial dynamics. The disruption of mitochondrial dynamics is closely related to the occurrence and development of DCM. Mitochondrial dynamics are controlled by circadian clock and show oscillation rhythm. This rhythm enables mitochondria to respond to changing energy demands in different environments, but it is disordered in diabetes. In this review, we summarize the significant role of circadian clock-controlled mitochondrial dynamics in the etiology of DCM and hope to play a certain enlightening role in the treatment of DCM.
    MeSH term(s) Humans ; Circadian Clocks ; Mitochondria/pathology ; Diabetes Mellitus ; Diabetic Cardiomyopathies/pathology ; Mitochondrial Dynamics ; Animals
    Language English
    Publishing date 2023-05-05
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2606827-8
    ISSN 1664-3224 ; 1664-3224
    ISSN (online) 1664-3224
    ISSN 1664-3224
    DOI 10.3389/fimmu.2023.1142512
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations.

    Chen, Qingyu / Allot, Alexis / Leaman, Robert / Islamaj, Rezarta / Du, Jingcheng / Fang, Li / Wang, Kai / Xu, Shuo / Zhang, Yuefu / Bagherzadeh, Parsa / Bergler, Sabine / Bhatnagar, Aakash / Bhavsar, Nidhir / Chang, Yung-Chun / Lin, Sheng-Jie / Tang, Wentai / Zhang, Hongtong / Tavchioski, Ilija / Pollak, Senja /
    Tian, Shubo / Zhang, Jinfeng / Otmakhova, Yulia / Yepes, Antonio Jimeno / Dong, Hang / Wu, Honghan / Dufour, Richard / Labrak, Yanis / Chatterjee, Niladri / Tandon, Kushagri / Laleye, Fréjus A A / Rakotoson, Loïc / Chersoni, Emmanuele / Gu, Jinghang / Friedrich, Annemarie / Pujari, Subhash Chandra / Chizhikova, Mariia / Sivadasan, Naveen / Vg, Saipradeep / Lu, Zhiyong

    Database : the journal of biological databases and curation

    2022  Volume 2022

    Abstract: The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature-at a rate of about 10 000 articles on ... ...

    Abstract The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature-at a rate of about 10 000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation. For instance, LitCovid is a literature database of COVID-19-related articles in PubMed, which has accumulated more than 200 000 articles with millions of accesses each month by users worldwide. One primary curation task is to assign up to eight topics (e.g. Diagnosis and Treatment) to the articles in LitCovid. The annotated topics have been widely used for navigating the COVID literature, rapidly locating articles of interest and other downstream studies. However, annotating the topics has been the bottleneck of manual curation. Despite the continuing advances in biomedical text-mining methods, few have been dedicated to topic annotations in COVID-19 literature. To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature. The BioCreative LitCovid dataset-consisting of over 30 000 articles with manually reviewed topics-was created for training and testing. It is one of the largest multi-label classification datasets in biomedical scientific literature. Nineteen teams worldwide participated and made 80 submissions in total. Most teams used hybrid systems based on transformers. The highest performing submissions achieved 0.8875, 0.9181 and 0.9394 for macro-F1-score, micro-F1-score and instance-based F1-score, respectively. Notably, these scores are substantially higher (e.g. 12%, higher for macro F1-score) than the corresponding scores of the state-of-art multi-label classification method. The level of participation and results demonstrate a successful track and help close the gap between dataset curation and method development. The dataset is publicly available via https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/ for benchmarking and further development. Database URL https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/.
    MeSH term(s) COVID-19/epidemiology ; Data Mining/methods ; Databases, Factual ; Humans ; PubMed ; Publications
    Language English
    Publishing date 2022-08-26
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Intramural
    ZDB-ID 2496706-3
    ISSN 1758-0463 ; 1758-0463
    ISSN (online) 1758-0463
    ISSN 1758-0463
    DOI 10.1093/database/baac069
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Online: Multi-label classification for biomedical literature

    Chen, Qingyu / Allot, Alexis / Leaman, Robert / Doğan, Rezarta Islamaj / Du, Jingcheng / Fang, Li / Wang, Kai / Xu, Shuo / Zhang, Yuefu / Bagherzadeh, Parsa / Bergler, Sabine / Bhatnagar, Aakash / Bhavsar, Nidhir / Chang, Yung-Chun / Lin, Sheng-Jie / Tang, Wentai / Zhang, Hongtong / Tavchioski, Ilija / Pollak, Senja /
    Tian, Shubo / Zhang, Jinfeng / Otmakhova, Yulia / Yepes, Antonio Jimeno / Dong, Hang / Wu, Honghan / Dufour, Richard / Labrak, Yanis / Chatterjee, Niladri / Tandon, Kushagri / Laleye, Fréjus / Rakotoson, Loïc / Chersoni, Emmanuele / Gu, Jinghang / Friedrich, Annemarie / Pujari, Subhash Chandra / Chizhikova, Mariia / Sivadasan, Naveen / Lu, Zhiyong

    an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations

    2022  

    Abstract: The COVID-19 pandemic has been severely impacting global society since December 2019. Massive research has been undertaken to understand the characteristics of the virus and design vaccines and drugs. The related findings have been reported in biomedical ...

    Abstract The COVID-19 pandemic has been severely impacting global society since December 2019. Massive research has been undertaken to understand the characteristics of the virus and design vaccines and drugs. The related findings have been reported in biomedical literature at a rate of about 10,000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation. For instance, LitCovid is a literature database of COVID-19-related articles in PubMed, which has accumulated more than 200,000 articles with millions of accesses each month by users worldwide. One primary curation task is to assign up to eight topics (e.g., Diagnosis and Treatment) to the articles in LitCovid. Despite the continuing advances in biomedical text mining methods, few have been dedicated to topic annotations in COVID-19 literature. To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature. The BioCreative LitCovid dataset, consisting of over 30,000 articles with manually reviewed topics, was created for training and testing. It is one of the largest multilabel classification datasets in biomedical scientific literature. 19 teams worldwide participated and made 80 submissions in total. Most teams used hybrid systems based on transformers. The highest performing submissions achieved 0.8875, 0.9181, and 0.9394 for macro F1-score, micro F1-score, and instance-based F1-score, respectively. The level of participation and results demonstrate a successful track and help close the gap between dataset curation and method development. The dataset is publicly available via https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/ for benchmarking and further development.
    Keywords Computer Science - Digital Libraries ; Computer Science - Computation and Language ; Computer Science - Information Retrieval ; Computer Science - Machine Learning
    Subject code 028
    Publishing date 2022-04-20
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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