Phage-microbe interactions are appealing systems to study coevolution,and have also been increasingly emphasized due to their roles in human health,disease,and the development of novel therapeutics.Phage-microbe interactions leave diverse signals in bacterial and phage geno-mic sequences,defined as phage-host interaction signals(PHISs),which include clustered regularly interspaced short palindromic repeats(CRISPR)targeting,prophage,and protein-protein interac-tion signals.In the present study,we developed a novel tool phage-host interaction signal detector(PHISDetector)to predict phage-host interactions by detecting and integrating diverse in silico PHISs,and scoring the probability of phage-host interactions using machine learning models based on PHIS features.We evaluated the performance of PHISDetector on multiple benchmark datasets and application cases.When tested on a dataset of 758 annotated phage-host pairs,PHISDetector yields the prediction accuracies of 0.51 and 0.73 at the species and genus levels,respectively,outper-forming other phage-host prediction tools.When applied to 125,842 metagenomic viral contigs(mVCs)derived from 3042 geographically diverse samples,a detection rate of 54.54％could be achieved.Furthermore,PHISDetector could predict infecting phages for 85.6％of 368 multidrug-resistant(MDR)bacteria and 30％of 454 human gut bacteria obtained from the National Institutes of Health(NIH)Human Microbiome Project(HMP).

Objective: To analyze the heritability of diabetes among the Chinese twin adults. Methods: A total of 10 253 same-sex twin pairs aged 25 years and older, were selected from the Chinese National Twin Registry (CNTR) program. Heritability of diabetes was calculated by using the structural equation model. Results: After adjusted for age and gender, the overall heritability rates of diabetes were 0.41 (0.15-0.75), 0.83 (0.72-0.91) and 0.34 (0.04-0.73) in the <45 and ≥45 years twin pairs, respectively. After adjusted for age, rates of heritability appeared as 0.37 (0.05-0.78) and 0.88 (0.79-0.94) in men and women, respectively. Conclusions Diabetes is affected by both genetic and environmental factors. The genetic effect of diabetes seemed stronger on female than that on male twins but was dying down along with ageing.