Effects of mirabegron on brown adipose tissue and metabolism in humans: A systematic review and meta-analysis.

BACKGROUND: Brown adipose tissue (BAT) has emerged as a potential therapeutic target for metabolic disorders due to its thermogenic and anti-obesity properties. ß3-adrenergic receptor (ß3-AR) agonists have also gained attention as potential agents for BAT activation and metabolic regulation. Mirabegron, a selective ß3-AR-agonist used clinically for overactive bladder syndrome, has been explored for its utility in metabolic disorders. However, the controversy surrounding the ability of mirabegron to activate BAT to accelerate metabolism requires further investigation. The aim of this systematic review is to characterize comprehensively the impact of mirabegron on human BAT and its metabolism. METHODS: We searched PubMed Central, Web of Science, Embase, and Cochrane Library databases for relevant papers published from the date of database inception to March 2023 for systematic reviews and meta-analyses. We extracted data on primary outcome indicators such as BAT volume, BAT activity, body temperature, and resting energy expenditure (REE), as well as secondary outcome indicators such as heart rate (HR), diastolic blood pressure (DBP), systolic blood pressure (SBP), non-esterified fatty acids (NEFA), blood glucose, and blood insulin from relevant studies. For studies that did not provide suitable data for meta-analysis, we used narrative data synthesis. For studies that provided suitable data for meta-analysis, we conducted meta-analysis using RevMan 5.4 software. RESULTS: We reviewed 10 papers and included 6 in our meta-analysis. Our findings revealed no significant changes in BAT volume (p = 0.72) or blood glucose (p = 0.52) with mirabegron when compared to the placebo or pre-dose population. However, patients showed significant increases in BAT activity (p < 0.01), blood NEFA (p < 0.01), body temperature (p < 0.01), REE (p < 0.01), HR (p < 0.01), DBP (p < 0.01), SBP (p = 0.25), and blood insulin (p < 0.01). CONCLUSION: Through our meta-analysis of 6 papers, we found that mirabegron has the potential to increase human BAT activity, REE, NEFA content, body temperature, HR, blood pressure, and blood insulin content. These effects may lead to reductions in blood glucose levels in obese/overweight and diabetic patients. Additionally, the activation of BAT by mirabegron could represent a novel approach for treating obesity, diabetes, and cardiovascular disease. TRIAL REGISTRATION NUMBER AND DATE: CRD42023413446, 04/11/2023.

Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study.

PURPOSE: The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa. MATERIAL AND METHODS: A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic. RESULTS: The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively. CONCLUSIONS: MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.