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  1. Chu AH, Koh D, Moy FM, Müller-Riemenschneider F
    Occup Med (Lond), 2014 Jun;64(4):235-45.
    PMID: 24850815 DOI: 10.1093/occmed/kqu045
    Mental health is an important issue in the working population. Interventions to improve mental health have included physical activity.
  2. Huang J, Ma ZF, Zhang Y, Wan Z, Li Y, Zhou H, et al.
    Glob Health Res Policy, 2020 11 30;5(1):52.
    PMID: 33292806 DOI: 10.1186/s41256-020-00178-9
    BACKGROUND: Fructose plays an important role in the complex metabolism of uric acid in the human body. However, high blood uric acid concentration, known as hyperuricemia, is the main risk factor for development of gout. Therefore, we conducted an updated meta-analysis on the prevalence and geographical distribution of hyperuricemia among the general population in mainland China using systematic literature search.

    METHODS: Five electronic databases were used to search for relevant articles published until 2019. All calculations were conducted using the Comprehensive Meta-Analysis (CMA) software. We included 108 eligible articles (172 studies by sex, 95 studies by regions, and 107 studies by study type) and an overall sample size of > 808,505 participants.

    RESULTS: The pooled prevalence of hyperuricemia among the general population in mainland China was 17.4% (95% CI: 15.8-19.1%). Our subgroup analysis indicated that the pooled prevalence by regions ranged from 15.5 to 24.6%. Those living Northeast region and being males had the highest prevalence (P  20%), particularly in males. An increasing prevalence was reported since 2005-2009 until 2015-2019. No publication of bias was observed as indicated by a symmetrical funnel plot and Begg and Mazumdar rank correlation (P = 0.392).

    CONCLUSION: Prevalence of hyperuricemia is increasing in China, and future studies should investigate the association between the prevalence of hyperuricemia and its risk factors in order to tackle the issue, particularly among the vulnerable groups. Also, our study was the first comprehensive study to investigate the overall prevalence of hyperuricemia in mainland China covering the six different regions.

  3. Harris EM, Chamseddine S, Chu A, Senkpeil L, Nikiciuk M, Al-Musa A, et al.
    medRxiv, 2024 Mar 07.
    PMID: 38464255 DOI: 10.1101/2024.02.25.24303331
    INTRODUCTION: Autoimmune diseases are heterogeneous and often lack specific or sensitive diagnostic tests. Increased percentages of CD4+CXCR5+PD1+ circulating T follicular helper (cTfh) cells and skewed distributions of cTfh subtypes have been associated with autoimmunity. However, cTfh cell percentages can normalize with immunomodulatory treatment despite persistent disease activity, indicating the need for identifying additional cellular and/or serologic features correlating with autoimmunity.

    METHODS: The cohort included 50 controls and 56 patients with autoimmune cytopenias, gastrointestinal, pulmonary, and/or neurologic autoimmune disease. Flow cytometry was used to measure CD4+CXCR5+ T cell subsets expressing the chemokine receptors CXCR3 and/or CCR6: CXCR3+CCR6- Type 1, CXCR3-CCR6- Type 2, CXCR3+CCR6+ Type 1/17, and CXCR3- CCR6+ Type 17 T cells. IgG and IgA autoantibodies were quantified using a microarray featuring 1616 full-length, conformationally intact protein antigens. The 97.5th percentile in the control cohort defined normal limits for T cell subset percentages and total number (burden) of autoantibodies.

    RESULTS: This study focused on CD4+CXCR5+ T cells because CXCR5 upregulation occurs after cognate T-B cell interactions characteristic of autoimmune diseases. We refer to these cells as circulating T follicular memory (cTfm) cells to acknowledge the dynamic nature of antigen-experienced CXCR5+ T cells, which encompass progenitors of cTfh or Tfh cells as well as early effector memory T cells that have not yet lost CXCR5. Compared to controls, 57.1% of patients had increased CXCR5+CXCR3+CCR6+ cTfm1/17 and 25% had increased CXCR5+CXCR3-CCR6+ cTfm17 cell percentages. Patients had significantly more diverse IgG and IgA autoantibodies than controls and 44.6% had an increased burden of autoantibodies of either isotype. Unsupervised autoantibody clustering identified three clusters of patients with IgG autoantibody profiles distinct from those of controls, enriched for patients with active autoimmunity and monogenic diseases. An increased percentage of cTfm17 cells was most closely associated with an increased burden of high-titer IgG and IgA autoantibodies. A composite measure integrating increased cTfm1/17, cTfm17, and high-titer IgG and/or IgA autoantibodies had 91.1% sensitivity and 90.9% specificity for identifying patients with autoimmunity. Percentages of cTfm1/17 and cTfm17 percentages and numbers of high-titer autoantibodies in patients receiving immunomodulatory treatment did not differ from those in untreated patients, thus suggesting that measurements of cTfm can complement measurements of other cellular markers affected by treatment.

    CONCLUSIONS: This study highlights two new approaches for assessing autoimmunity: measuring CD4+CXCR5+ cTfm subsets as well as total burden of autoantibodies. Our findings suggest that these approaches are particularly relevant to patients with rare autoimmune disorders for whom target antigens and prognosis are often unknown.

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