Integrating Multi-Organ Imaging-Derived Phenotypes and Genomic Information for Predicting the Occurrence of Common Diseases.

As medical imaging technologies advance, these tools are playing a more and more important role in assisting clinical disease diagnosis. The fusion of biomedical imaging and multi-modal information is profound, as it significantly enhances diagnostic precision and comprehensiveness. Integrating multi-organ imaging with genomic information can significantly enhance the accuracy of disease prediction because many diseases involve both environmental and genetic determinants. In the present study, we focused on the fusion of imaging-derived phenotypes (IDPs) and polygenic risk score (PRS) of diseases from different organs including the brain, heart, lung, liver, spleen, pancreas, and kidney for the prediction of the occurrence of nine common diseases, namely atrial fibrillation, heart failure (HF), hypertension, myocardial infarction, asthma, type 2 diabetes, chronic kidney disease, coronary artery disease (CAD), and chronic obstructive pulmonary disease, in the UK Biobank (UKBB) dataset. For each disease, three prediction models were developed utilizing imaging features, genomic data, and a fusion of both, respectively, and their performances were compared. The results indicated that for seven diseases, the model integrating both imaging and genomic data achieved superior predictive performance compared to models that used only imaging features or only genomic data. For instance, the Area Under Curve (AUC) of HF risk prediction was increased from 0.68 ± 0.15 to 0.79 ± 0.12, and the AUC of CAD diagnosis was increased from 0.76 ± 0.05 to 0.81 ± 0.06.

Atractylodes macrocephala Koidz. and Cuscuta chinensis Lam. extract relieves insulin resistance via PI3K/Akt signalling in diabetic Drosophila.

Background and aim: Type-2 diabetes mellitus (T2DM) is mainly characterized by insulin resistance (IR) induced by hyperglycaemia and insufficient insulin secretion. We employed a diabetic fly model to examine the effect and molecular mechanism of Atractylodes macrocephala Koidz. and Cuscuta chinensis Lam. (AMK-CCL) extract as traditional Chinese medicine in treating IR and T2DM. Experimental procedure: The contents of the active ingredients (rhamnose, xylose, mannose, and hyperoside) in AMK-CCL extract were determined by high-performance liquid chromatography. Wild-type (Cg-GAL4/+) or diabetic (Cg > InRK1409A) Drosophila flies were divided into the control group or metformin group and AMK-CCL (0.0125, 0.025, 0.05, 0.1 g/ml) groups. Food intake, haemolymph glucose and trehalose, protein, weight, triglycerides (TAG), and glycogen were measured to assess glycolipid metabolism. Phosphatidylinositol-3-kinase (PI3K)/Akt signalling was detected using fluorescent reporters [tGPH, Drosophila forkhead box O (dFoxO)-green fluorescent protein (GFP), Glut1-GFP, 2-NBDG] in vivo. Glut1/3 mRNA levels and Akt phosphorylation levels were detected by quantitative polymerase chain reaction and western blotting, respectively, in vitro. Results: AMK-CCL extract contained 0.038 % rhamnose, 0.017 % xylose, 0.69 % mannose, and 0.039 % hyperoside. AMK-CCL at 0.0125 g/mL significantly suppressed the increase in circulating glucose, and the decrease in body weight, TAG, and glycogen contents of diabetic flies. AMK-CCL improved PI3K activity, Akt phosphorylation, Glut1/3 expression, and glucose uptake in diabetic flies, and also rescued diabetes-induced dFoxO nuclear localisation. Conclusions: These findings indicate that AMK-CCL extract ameliorates IR-induced diabetes via the PI3K/Akt signalling pathway, providing an experimental basis for clinical treatment.

The health status, social support, and subjective well-being of older individuals: evidence from the Chinese General Social Survey.

Objectives: This study aims to investigate the impact of health status and social support on the subjective well-being of older individuals. Methods: Using data from the China General Social Survey 2017, this research analyzed 5,187 Chinese citizens aged 60 years and older. The predicted effect of each variable on subjective well-being was evaluated through hierarchical regression analysis. The direct and indirect effects of social support and health status on subjective well-being are examined based on a structural equation model. Results: The mental health and social support positively impact subjective well-being. Mental health mediates the effect of physical health on subjective well-being, and social support mediates the relationship between physical and mental health and subjective well-being. Conclusion: The findings provide strong evidence for the interrelationship mechanisms among the factors influencing subjective well-being. Consequently, improving mental health services and social support systems is advantageous for enhancing the well-being of Chinese seniors.

Two new 2,5-diketopiperazine derivatives from mangrove-derived endophytic fungus Nigrospora camelliae-sinensis S30.

Two new 2,5-diketopiperazines derivatives (1-2), together with eight known analogs (3-10), were isolated from a culture broth of an endophytic fungus Nigrospora camelliae-sinensis S30, derived from mangrove Lumnitzera littorea. Their complete structures were determined by a detailed analysis of spectroscopic data and ECD calculations. The antimicrobial activity and neuroprotective activity of these isolated compounds were also evaluated.