Bmc Med
-
The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. ⋯ Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.
-
Considering the heterogeneity of tumors, it is a key issue in precision medicine to predict the drug response of each individual. The accumulation of various types of drug informatics and multi-omics data facilitates the development of efficient models for drug response prediction. However, the selection of high-quality data sources and the design of suitable methods remain a challenge. ⋯ NeRD's feature fusion provides a new idea for drug response prediction, which is of great significance for precise cancer treatment.
-
Extraintestinal symptoms are common in inflammatory bowel diseases (IBD) and include depression and fatigue. These are highly prevalent especially in active disease, potentially due to inflammation-mediated changes in the microbiota-gut-brain axis. The aim of this study was to investigate the associations between structural and functional microbiota characteristics and severity of fatigue and depressive symptoms in patients with active IBD. ⋯ This study provides the first evidence of association triplets between microbiota composition, function and extraintestinal symptoms in active IBD. Depression and fatigue were associated with lower abundances of short-chain fatty acid producers and distinct pathways implicating glycan, carbohydrate and amino acid metabolism. Our results suggest that microbiota-directed therapeutic approaches may reduce fatigue and depression in IBD and should be investigated in future research.
-
Heart failure (HF) with preserved ejection fraction (HFpEF) prevalence is increasing, and large clinical trials have failed to reduce mortality. A major reason for this outcome is the failure to translate results from basic research to the clinics. Evaluation of HFpEF in mouse models requires assessing three major key features defining this complex syndrome: the presence of a preserved left ventricular ejection fraction (LVEF), diastolic dysfunction, and the development of HF. In addition, HFpEF is associated with multiple comorbidities such as systemic arterial hypertension, chronic obstructive pulmonary disease, sleep apnea, diabetes, and obesity; thus, non-cardiac disorders assessment is crucial for a complete phenotype characterization. Non-invasive procedures present unquestionable advantages to maintain animal welfare and enable longitudinal analyses. However, unequivocally determining the presence of HFpEF using these methods remains challenging. ⋯ Identification of reliable models of HFpEF in mice by using proper diagnosis tools is necessary to translate basic research results to the clinics. Determining the presence of several HFpEF indicators and a higher number of abnormal parameters will lead to more reliable evidence of HFpEF.
-
In view of accumulating case reports of thyroid dysfunction following COVID-19 vaccination, we evaluated the risks of incident thyroid dysfunction following inactivated (CoronaVac) and mRNA (BNT162b2) COVID-19 vaccines using a population-based dataset. ⋯ Our population-based study showed no evidence of vaccine-related increase in incident hyperthyroidism or hypothyroidism with both BNT162b2 and CoronaVac.