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  1. Article: Developmental timing in C. elegans is regulated by kin-20 and tim-1, homologs of core circadian clock genes.

    Banerjee, Diya / Kwok, Alvin / Lin, Shin-Yi / Slack, Frank J

    Developmental cell

    2005  Volume 8, Issue 2, Page(s) 287–295

    Abstract: ... a 24 hr day/night cycle. We show a role for two other circadian gene homologs, tim-1 and kin-20 ... in the developmental timer. Along with lin-42, tim-1 and kin-20, the C. elegans homologs of the Drosophila ...

    Abstract In Caenorhabditis elegans, heterochronic genes constitute a developmental timer that specifies temporal cell fate selection. The heterochronic gene lin-42 is the C. elegans homolog of Drosophila and mammalian period, key regulators of circadian rhythms, which specify changes in behavior and physiology over a 24 hr day/night cycle. We show a role for two other circadian gene homologs, tim-1 and kin-20, in the developmental timer. Along with lin-42, tim-1 and kin-20, the C. elegans homologs of the Drosophila circadian clock genes timeless and doubletime, respectively, are required to maintain late-larval identity and prevent premature expression of adult cell fates. The molecular parallels between circadian and developmental timing pathways suggest the existence of a conserved molecular mechanism that may be used for different types of biological timing.
    MeSH term(s) Animals ; Animals, Genetically Modified ; Caenorhabditis elegans/genetics ; Caenorhabditis elegans/growth & development ; Caenorhabditis elegans/metabolism ; Caenorhabditis elegans Proteins/genetics ; Caenorhabditis elegans Proteins/metabolism ; Casein Kinase Idelta/genetics ; Casein Kinase Idelta/metabolism ; Circadian Rhythm/genetics ; Gene Expression Regulation, Developmental ; Genes, Helminth ; Isoenzymes/genetics ; Isoenzymes/metabolism ; MicroRNAs ; Models, Biological ; Molecular Sequence Data ; Mutation ; Phenotype ; Phylogeny ; RNA Interference
    Chemical Substances Caenorhabditis elegans Proteins ; Isoenzymes ; MicroRNAs ; TIM-1 protein, C elegans ; let-7 microRNA, C elegans ; Casein Kinase Idelta (EC 2.7.11.1)
    Language English
    Publishing date 2005-02
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
    ZDB-ID 2054967-2
    ISSN 1878-1551 ; 1534-5807
    ISSN (online) 1878-1551
    ISSN 1534-5807
    DOI 10.1016/j.devcel.2004.12.006
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  2. Article ; Online: Learning from and optimising divergent pandemic responses.

    Tang, Julian W / Kwok, Kin On

    Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

    2022  Volume 28, Issue 8, Page(s) 1168–1169

    MeSH term(s) Humans ; Pandemics/prevention & control
    Language English
    Publishing date 2022-04-07
    Publishing country England
    Document type Letter
    ZDB-ID 1328418-6
    ISSN 1469-0691 ; 1470-9465 ; 1198-743X
    ISSN (online) 1469-0691
    ISSN 1470-9465 ; 1198-743X
    DOI 10.1016/j.cmi.2022.03.038
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    Zs.MO 284: Show issues

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  3. Article ; Online: Actionable targets to reduce COVID-19 severity.

    Au Yeung, Shiu Lun / Luo, Shan / Kwok, Kin On

    Nature metabolism

    2023  Volume 5, Issue 2, Page(s) 195–196

    MeSH term(s) Humans ; COVID-19/therapy ; Patient Acuity
    Language English
    Publishing date 2023-03-01
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Comment
    ISSN 2522-5812
    ISSN (online) 2522-5812
    DOI 10.1038/s42255-023-00743-9
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  4. Article ; Online: Correction: A hybrid machine learning framework to improve prediction of all-cause rehospitalization among eldely patients in Hong Kong.

    Guan, Jingjing / Leung, Eman / Kwok, Kin-On / Chen, Frank Youhua

    BMC medical research methodology

    2023  Volume 23, Issue 1, Page(s) 38

    Language English
    Publishing date 2023-02-13
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-023-01851-6
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  5. Article ; Online: Paradoxical findings on smoking in reduced risk of severe COVID-19.

    Au Yeung, Shiu Lun / Kwok, Kin On

    International journal of epidemiology

    2022  Volume 51, Issue 4, Page(s) 1351–1352

    MeSH term(s) COVID-19 ; Humans ; SARS-CoV-2 ; Smoking/epidemiology ; Tobacco Smoking
    Language English
    Publishing date 2022-05-14
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 187909-1
    ISSN 1464-3685 ; 0300-5771
    ISSN (online) 1464-3685
    ISSN 0300-5771
    DOI 10.1093/ije/dyac099
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    Zs.A 893: Show issues Location:
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  6. Article ; Online: The importance of transparency: Declaring the use of generative artificial intelligence (AI) in academic writing.

    Tang, Arthur / Li, Kin-Kit / Kwok, Kin On / Cao, Liujiao / Luong, Stanley / Tam, Wilson

    Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing

    2023  Volume 56, Issue 2, Page(s) 314–318

    Abstract: The integration of generative artificial intelligence (AI) into academic research writing has revolutionized the field, offering powerful tools like ChatGPT and Bard to aid researchers in content generation and idea enhancement. We explore the current ... ...

    Abstract The integration of generative artificial intelligence (AI) into academic research writing has revolutionized the field, offering powerful tools like ChatGPT and Bard to aid researchers in content generation and idea enhancement. We explore the current state of transparency regarding generative AI use in nursing academic research journals, emphasizing the need for explicitly declaring the use of generative AI by authors in the manuscript. Out of 125 nursing studies journals, 37.6% required explicit statements about generative AI use in their authors' guidelines. No significant differences in impact factors or journal categories were found between journals with and without such requirement. A similar evaluation of medicine, general and internal journals showed a lower percentage (14.5%) including the information about generative AI usage. Declaring generative AI tool usage is crucial for maintaining the transparency and credibility in academic writing. Additionally, extending the requirement for AI usage declarations to journal reviewers can enhance the quality of peer review and combat predatory journals in the academic publishing landscape. Our study highlights the need for active participation from nursing researchers in discussions surrounding standardization of generative AI declaration in academic research writing.
    MeSH term(s) Humans ; Artificial Intelligence ; Publishing ; Peer Review ; Writing ; Nursing Research
    Language English
    Publishing date 2023-10-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2008214-9
    ISSN 1547-5069 ; 1527-6546
    ISSN (online) 1547-5069
    ISSN 1527-6546
    DOI 10.1111/jnu.12938
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  7. Article ; Online: A hybrid machine learning framework to improve prediction of all-cause rehospitalization among elderly patients in Hong Kong.

    Guan, Jingjing / Leung, Eman / Kwok, Kin-On / Chen, Frank Youhua

    BMC medical research methodology

    2023  Volume 23, Issue 1, Page(s) 14

    Abstract: Background: Accurately estimating elderly patients' rehospitalisation risk benefits clinical decisions and service planning. However, research in rehospitalisation and repeated hospitalisation yielded only models with modest performance, and the model ... ...

    Abstract Background: Accurately estimating elderly patients' rehospitalisation risk benefits clinical decisions and service planning. However, research in rehospitalisation and repeated hospitalisation yielded only models with modest performance, and the model performance deteriorates rapidly as the prediction timeframe expands beyond 28 days and for older participants.
    Methods: A temporal zero-inflated Poisson (tZIP) regression model was developed and validated retrospectively and prospectively. The data of the electronic health records (EHRs) contain cohorts (aged 60+) in a major public hospital in Hong Kong. Two temporal offset functions accounted for the associations between exposure time and parameters corresponding to the zero-inflated logistic component and the Poisson distribution's expected count. tZIP was externally validated with a retrospective cohort's rehospitalisation events up to 12 months after the discharge date. Subsequently, tZIP was validated prospectively after piloting its implementation at the study hospital. Patients discharged within the pilot period were tagged, and the proposed model's prediction of their rehospitalisation was verified monthly. Using a hybrid machine learning (ML) approach, the tZIP-based risk estimator's marginal effect on 28-day rehospitalisation was further validated, competing with other factors representing different post-acute and clinical statuses.
    Results: The tZIP prediction of rehospitalisation from 28 days to 365 days was achieved at above 80% discrimination accuracy retrospectively and prospectively in two out-of-sample cohorts. With a large margin, it outperformed the Cox proportional and linear models built with the same predictors. The hybrid ML revealed that the risk estimator's contribution to 28-day rehospitalisation outweighed other features relevant to service utilisation and clinical status.
    Conclusions: A novel rehospitalisation risk model was introduced, and its risk estimators, whose importance outweighed all other factors of diverse post-acute care and clinical conditions, were derived. The proposed approach relies on four easily accessible variables easily extracted from EHR. Thus, clinicians could visualise patients' rehospitalisation risk from 28 days to 365 days after discharge and screen high-risk older patients for follow-up care at the proper time.
    MeSH term(s) Aged ; Humans ; Patient Readmission ; Retrospective Studies ; Hong Kong ; Hospitalization ; Machine Learning
    Language English
    Publishing date 2023-01-13
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-022-01824-1
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  8. Article ; Online: Can Asia now learn from the experience of the West?

    Tang, Julian W / Wu, Samantha / Kwok, Kin On

    Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

    2021  Volume 27, Issue 12, Page(s) 1864–1866

    MeSH term(s) Asia/epidemiology ; Humans ; Risk Factors
    Language English
    Publishing date 2021-07-28
    Publishing country England
    Document type Letter
    ZDB-ID 1328418-6
    ISSN 1469-0691 ; 1470-9465 ; 1198-743X
    ISSN (online) 1469-0691
    ISSN 1470-9465 ; 1198-743X
    DOI 10.1016/j.cmi.2021.07.026
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  9. Article: Revisiting Vaccine Hesitancy in Residential Care Homes for the Elderly for Pandemic Preparedness: A Lesson from COVID-19.

    Leung, Cyrus Lap Kwan / Wei, Wan In / Li, Kin-Kit / McNeil, Edward B / Tang, Arthur / Wong, Samuel Yeung Shan / Kwok, Kin On

    Vaccines

    2023  Volume 11, Issue 11

    Abstract: Residents in residential care homes for the elderly (RCHEs) are at high risk of severe illnesses and mortality, while staff have high exposure to intimate care activities. Addressing vaccine hesitancy is crucial to safeguard vaccine uptake in this ... ...

    Abstract Residents in residential care homes for the elderly (RCHEs) are at high risk of severe illnesses and mortality, while staff have high exposure to intimate care activities. Addressing vaccine hesitancy is crucial to safeguard vaccine uptake in this vulnerable setting, especially amid a pandemic. In response to this, we conducted a cross-sectional survey to measure the level of vaccine hesitancy and to examine its associated factors among residents and staff in RCHEs in Hong Kong. We recruited residents and staff from 31 RCHEs in July-November 2022. Of 204 residents, 9.8% had a higher level of vaccine hesitancy (scored ≥ 4 out of 7, mean = 2.44). Around 7% of the staff (
    Language English
    Publishing date 2023-11-08
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2703319-3
    ISSN 2076-393X
    ISSN 2076-393X
    DOI 10.3390/vaccines11111700
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  10. Article ; Online: Amplifying research influence through the social network, open access publishing, and international collaboration: A mediation analysis on nursing studies literature.

    Tang, Arthur / Li, Kin-Kit / Han, SeungHee / Kwok, Kin On / Tung, Neo / Tam, Wilson

    Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing

    2022  Volume 55, Issue 2, Page(s) 477–483

    Abstract: Introduction: Research impact and influence are commonly measured quantitatively by citation count received by research articles. Many institutes also use citation count as one of the factors in faculty performance appraisal and candidate selection of ... ...

    Abstract Introduction: Research impact and influence are commonly measured quantitatively by citation count received by research articles. Many institutes also use citation count as one of the factors in faculty performance appraisal and candidate selection of academic positions. Various strategies were recommended to amplify and accelerate research influence, particularly citation counts, by bringing research articles to a wider reach for potential readers. However, no prior empirical study was conducted to examine and valid effects of those strategies on nursing studies. This study examines and verifies the direct effects and mediation effects of some strategies, namely, the use of Twitter, international collaboration, the use of ResearchGate, and open access publishing, for amplifying the citation of research and review articles in nursing studies.
    Design: Cross-sectional study design.
    Methods: Articles published in top nursing journals in 2016 were identified in PUBMED and the citation metrics for individual articles until 2021 were extracted from Scopus. The primary outcome was the citation count of the article, while the tweet count on Twitter of the article was considered a mediator. The predictors included paper type, the total number of authors, the proportion of authors with a ResearchGate account in the article, funding support, open-accessed article, and the number of different countries stated in the authors' affiliation. A mediation analysis was conducted to examine the predictors' direct and indirect effects (i.e., via tweet count) on the citation count of the article.
    Results: A total of 2210 articles were included in this study, of which 223 (10.1%) were review articles. The median (IQR) number of Scopus citations, tweets, countries, and percentage of authors with ResearchGate accounts were 12 (6-21), 2 (0-6), 1 (1-1), and 75% (50%-100%) respectively. In the mediation analysis, tweet count, article type, number of countries, percentage of authors with a ResearchGate account, and journal impact factors in 2014 were positively associated with the Scopus citation count. The effects of article type, open access, and journals' impact factors in 2014 on Scopus citation count were mediated by the tweet count.
    Conclusion: This study provides empirical support for some strategies researchers may employ to amplify the citation count of their research articles. The methodology of our study can be extended to compare research influence between entities (e.g., across countries or institutes).
    Clinical relevance: The citation refers to the research work cited by peers and is one of the indicators for research impact. Higher citations implied the research work is read and used by others, therefore, understanding the associated factors with higher citations is critical.
    MeSH term(s) Humans ; Open Access Publishing ; Publishing ; Mediation Analysis ; Cross-Sectional Studies ; Social Networking
    Language English
    Publishing date 2022-10-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2008214-9
    ISSN 1547-5069 ; 1527-6546
    ISSN (online) 1547-5069
    ISSN 1527-6546
    DOI 10.1111/jnu.12827
    Database MEDical Literature Analysis and Retrieval System OnLINE

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