Association between gout and atrial fibrillation: A meta-analysis of observational studies

Background: Gout is a systemic inflammatory arthritis characterized by the deposition of monosodium urate crystals due to hyperuricemia. Previous studies have explored the link between gout and atrial fibrillation (AF). Given the increasing prevalence and incidence of gout, there is a need to quantify the relationship between gout and the risk of AF. Therefore, we conducted a systematic review and meta-analysis on this topic. Methods: PubMed and Embase were searched for studies that reported the association between gout and AF using the following search term: (‘Gout’ and ‘Arrhythmia’). The search period was from the start of the database to 3rd August 2018 with no language restrictions. Results: A total of 75 and 22 articles were retrieved from PubMed and Embase, respectively. Of these, four observational studies (three cohort studies, one case-control study) including 659,094 patients were included. Our meta-analysis demonstrated that gout was significantly associated with increased risk of AF (adjusted hazard ratio: 1.31; 95% confidence interval: 1.00-1.70; P = 0.05; I2 = 99%) after adjusting for significant comorbidities and confounders. Conclusions: Our meta-analysis confirms the significant relationship between gout and AF. More data are needed to determine whether this risk can be adequately reduced by urate-lowering therapy

Predicting stroke and mortality in mitral regurgitation: A machine learning approach

We hypothesized that an interpretable gradient boosting machine (GBM) model considering comorbidities, P-wave and echocardiographic measurements, can better predict mortality and cerebrovascular events in mitral regurgitation (MR). Patients from a tertiary center were analyzed. The GBM model was used as an interpretable statistical approach to identify the leading indicators of high-risk patients with either outcome of CVAs and all-cause mortality. A total of 706 patients were included. GBM analysis showed that age, systolic blood pressure, diastolic blood pressure, plasma albumin levels, mean P-wave duration (PWD), MR regurgitant volume, left ventricular ejection fraction (LVEF), left atrial dimension at end-systole (LADs), velocity-time integral (VTI) and effective regurgitant orifice were significant predictors of TIA/stroke. Age, sodium, urea and albumin levels, platelet count, mean PWD, LVEF, LADs, left ventricular dimension at end systole (LVDs) and VTI were significant predictors of all-cause mortality. The GBM demonstrates the best predictive performance in terms of precision, sensitivity c-statistic and F1-score compared to logistic regression, decision tree, random forest, support vector machine, and artificial neural networks. Gradient boosting model incorporating clinical data from different investigative modalities significantly improves risk prediction performance and identify key indicators for outcome prediction in MR

Predicting stroke and mortality in mitral regurgitation: A machine learning approach

We hypothesized that an interpretable gradient boosting machine (GBM) model considering comorbidities, P-wave and echocardiographic measurements, can better predict mortality and cerebrovascular events in mitral regurgitation (MR). Patients from a tertiary center were analyzed. The GBM model was used as an interpretable statistical approach to identify the leading indicators of high-risk patients with either outcome of CVAs and all-cause mortality. A total of 706 patients were included. GBM analysis showed that age, systolic blood pressure, diastolic blood pressure, plasma albumin levels, mean P-wave duration (PWD), MR regurgitant volume, left ventricular ejection fraction (LVEF), left atrial dimension at end-systole (LADs), velocity-time integral (VTI) and effective regurgitant orifice were significant predictors of TIA/stroke. Age, sodium, urea and albumin levels, platelet count, mean PWD, LVEF, LADs, left ventricular dimension at end systole (LVDs) and VTI were significant predictors of all-cause mortality. The GBM demonstrates the best predictive performance in terms of precision, sensitivity c-statistic and F1-score compared to logistic regression, decision tree, random forest, support vector machine, and artificial neural networks. Gradient boosting model incorporating clinical data from different investigative modalities significantly improves risk prediction performance and identify key indicators for outcome prediction in MR. [Abstract copyright: Copyright © 2022. Published by Elsevier Inc.

Vitamin D3 and carbamazepine protect against Clostridioides difficile infection in mice by restoring macrophage lysosome acidification

Clostridioides difficile infection (CDI) is a common cause of nosocomial diarrhea. TcdB is a major C. difficile exotoxin that activates macrophages to promote inflammation and epithelial damage. Lysosome impairment is a known trigger for inflammation. Herein, we hypothesize that TcdB could impair macrophage lysosomal function to mediate inflammation during CDI. Effects of TcdB on lysosomal function and the downstream pro-inflammatory SQSTM1/p62-NFKB (nuclear factor kappa B) signaling were assessed in cultured macrophages and in a murine CDI model. Protective effects of two lysosome activators (i.e., vitamin D3 and carbamazepine) were assessed. Results showed that TcdB inhibited CTNNB1/β-catenin activity to downregulate MITF (melanocyte inducing transcription factor) and its direct target genes encoding components of lysosomal membrane vacuolar-type ATPase, thereby suppressing lysosome acidification in macrophages. The resulting lysosomal dysfunction then impaired autophagic flux and activated SQSTM1-NFKB signaling to drive the expression of IL1B/IL-1β (interleukin 1 beta), IL8 and CXCL2 (chemokine (C-X-C motif) ligand 2). Restoring MITF function by enforced MITF expression or restoring lysosome acidification with 1α,25-dihydroxyvitamin D3 or carbamazepine suppressed pro-inflammatory cytokine expression in vitro. In mice, gavage with TcdB-hyperproducing C. difficile or injection of TcdB into ligated colon segments caused prominent MITF downregulation in macrophages. Vitamin D3 and carbamazepine lessened TcdB-induced lysosomal dysfunction, inflammation and histological damage. In conclusion, TcdB inhibits the CTNNB1-MITF axis to suppress lysosome acidification and activates the downstream SQSTM1-NFKB signaling in macrophages during CDI. Vitamin D3 and carbamazepine protect against CDI by restoring MITF expression and lysosomal function in mice. Abbreviations: ATP6V0B: ATPase H+ transporting V0 subunit b; ATP6V0C: ATPase H+ transporting V0 subunit c; ATP6V0E1: ATPase H+ transporting V0 subunit e1; ATP6V1H: ATPase H+ transporting V1 subunit H; CBZ: carbamazepine; CDI: C. difficile infection; CXCL: chemokine C-X-X motif ligand; IL: interleukin; LAMP1: lysosomal-associated membrane protein 1; LC3: microtubule-associated protein 1 light chain 3; LEF: lymphoid enhancer binding factor 1; MITF: melanocyte inducing transcription factor; NFKB: nuclear factor kappa B; PMA: phorbol 12-myristate 13-acetate; TcdA: Clostridial toxin A; TcdB: Clostridial toxin B; TFE3: transcription factor E3; TFEB: transcription factor EB.Published versionThis work was supported by the National Natural Science Foundation of China [82070576] and the Hong Kong Food and Health Bureau (FHB) Commissioned Health and Medical Research Fund [CID-CUHK-C]