In multi-ethnic Asian adults, lower eGFR and higher albuminuria were independently associated with incident CVD and all-cause mortality. These findings extend previously reported similar associations in Western populations to Asians and emphasize the need for early detection of CKD and intervention to prevent adverse outcomes.

Objective Ovarian cancer (OC) affects nearly 22,000 women annually in the United States and ranks fifth in cancer deaths, largely because of being diagnosed at an advanced stage. Autophagy is the cellular process of self-degrading damaged or degenerate proteins and organelles. Long non-coding RNAs (lncRNAs) are a group of RNA molecules whose transcripts are greater than 200 nt but are not translated into proteins. However, just a small number of autophagy-related lncRNAs have been explored in depth. Methods We used RNA sequencing data from The Cancer Genome Atlas (TCGA) and autophagy datasets to identify dysfunctional autophagy-related lncRNAs and provide potential useful biomarkers for OC diagnosis and prognosis. Results Seventeen differentially expressed lncRNAs (AC010186.3, AC006001.2, LBX2-AS1, SNHG17, AC011445.1, AC083880.1, MIR193BHG, AC025259.3, HCG14, AC007114.1, AC108673.2, USP30-AS1, AC010336.5, LINC01132, AC006333.2, LINC00665 and AC027348.1) were selected as independent prognostic factors for OC patients. Functional annotation of the data was performed through gene set enrichment analysis (GSEA). The results suggested that the high-risk group was mainly enriched in specific tumor-related and metabolism pathways. Conclusion Based on the online databases, we identified novel autophagy-related lncRNAs for the prognosis of ovarian cancer.

Although majority of elderly dialysis patients were comfortable with their decision to start dialysis, a proportion was ambivalent or regretted this choice. Regret was more likely among those who experienced decisional conflict and/or expressed poorer information satisfaction. Healthcare professionals should recognize these risk factors and take steps to minimize chances of regret among this population subset.

Single-cell sequencing technology refers to the sequencing of the genome, transcriptome and epigenome in one single cell. Comparing to traditional histology, single-cell sequencing can reveal the genetic heterogeneity among different cells. Due to the complex pathogenesis and various pathological types of hepatocellular carcinoma (HCC), studies on the heterogeneity of tumor cells confer improvement for its clinical diagnosis, treatment and prognosis. This article summarizes the principal basis and development of single-cell sequencing technology, as well as its increasing application in the field of HCC.