Antimicrobial Resistance Associated with Mass Gatherings: A Systematic Review.

Mass gatherings are associated with the spread of communicable diseases. Some studies have suggested that acquisition of antimicrobial resistance (AMR) may be associated with attendance at specific mass gatherings. This systematic review aimed to synthesise evidence on the association between attendance at mass gatherings and antimicrobial resistance (AMR) and assess the prevalence of AMR at mass gatherings.

Potentially probiotic NPL 1334 strain of Enterococcus durans benefits rats with diet-induced hypercholesterolemia.

Purpose: To study the potential of a candidate probiotic strain belonging to the Enterococcus durans species in alleviating hypercholesterolemia and improving the microbial milieu of rat gut.

Methods: A previously isolated and characterized E. durans strain NPL 1334 was further screened in vitro for its bile salt hydrolyzation and cholesterol assimilation ability.

Association of TCF7L2 genetic variants rs12255372 and rs7903146 with the polycystic ovary syndrome risk: systemic review and meta-analysis.

Background: A significant overlap in the pathophysiological features of polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus (T2DM) has been reported; and insulin resistance is considered a central driver in both. The expression and hepatic clearance of insulin and subsequent glucose homeostasis are mediated by TCF7L2 via Wnt signaling. Studies have persistently associated TCF7L2 genetic variations with T2DM, however, its results on PCOS are sparse and inconsistent.

Left Atrial Enlargement in Primary Cryptogenic Strokes Without Atrial Fibrillation.

The relationship between left atrial enlargement (LAE) and primary cryptogenic stroke (PCS) remains a mystery. LAE has been proposed to be an independent risk factor of PCS, recurrent ischemic strokes, paroxysmal atrial fibrillation, and thromboembolism. Our study evaluates the prevalence of LAE among patients with PCS in the absence of atrial fibrillation, unlike previous studies that included atrial fibrillation, in order to isolate LAE as a risk factor.

Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

Purpose: Meningiomas are the most common primary brain tumour and account for over one-third of cases. Traditionally, estimations of morbidity and mortality following surgical resection have depended on subjective assessments of various factors, including tumour volume, location, WHO grade, extent of resection (Simpson grade) and pre-existing co-morbidities, an approach fraught with subjective variability. This systematic review and meta-analysis seeks to evaluate the efficacy with which machine learning (ML) algorithms predict post-operative outcomes in meningioma patients.