Modulation of glycolipid metabolism in T2DM rats by Rubus irritans Focke extract: Insights from metabolic profiling and ERK/IRS-1 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: The extracellular regulated protein kinase (ERK) plays a crucial role in the mitogen-activated protein kinase (MAPK) family, influencing apoptosis, proliferation, and differentiation. It connection to the insulin (INS) signaling cascade and the development of type 2 diabetes mellitus (T2DM) has been established. Rubus irritans Focke, an indispensable herb in Chinese Tibetan medicine for diabetes mellitus treatment, lacks a comprehensive understanding of its effects and pharmacological mechanisms in T2DM. AIM OF THE STUDY: This study aimed to elucidate the effects of Rubus irritans Focke extract (Rife) on a T2DM rat model, exploring its impact on glycemic and lipid metabolism, histopathological changes, and its potential targeting of the extracellular regulated protein kinase/insulin receptor substrate-1 (ERK/IRS-1) signaling pathway. MATERIALS AND METHODS: A T2DM rat model was induced by streptozotocin (STZ) injection (40 mg/kg) in high-fat diet-fed (HFD) male Wistar rats. Rife and metformin (Met) were administered for 4 weeks, and glycemic, lipid metabolism indices, and histopathological changes were assessed. Protein expression of ERK, IRS-1 in rat liver tissues was examined to evaluate the impact on the ERK/IRS-1 pathway. RESULTS: Rife reducing hepatic ERK and IRS-1 protein expression in T2DM rats. Untargeted metabolomics identified 13 potential biomarkers and 4 differential metabolic pathways related to glycolipid metabolism disorders. CONCLUSIONS: Rife demonstrated improved glycolipid metabolism in T2DM rats by inhibiting the ERK/IRS-1 related signaling pathway and influencing multiple metabolic pathways. This study provides valuable insights into the potential therapeutic mechanisms of Rife in the context of T2DM.

The complete chloroplast genome sequence of Rubus irritans Focke 1910 (Rosaceae).

Rubus irritans Focke is a type of tonifying kidney-essence herb used in China. We present the complete chloroplast (cp) genome of R. irritans, a member of the genus Rubus. The complete cp genome of R. irritans was 155,286 bp long and consisted of an 84,613 bp long large single-copy (LSC) region, an 18,697 bp long SSC region, and a pair of 25,988 bp long inverted repeats (IR). Furthermore, the plastid genome contained 130 genes, including 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The overall GC content of the genome was 37.29%. Based on the complete cp genome, phylogenetic analysis revealed that R. irritans is closely related to R. amabilis.

Electronic Health Record-Based Prediction of 1-Year Risk of Incident Cardiac Dysrhythmia: Prospective Case-Finding Algorithm Development and Validation Study.

BACKGROUND: Cardiac dysrhythmia is currently an extremely common disease. Severe arrhythmias often cause a series of complications, including congestive heart failure, fainting or syncope, stroke, and sudden death. OBJECTIVE: The aim of this study was to predict incident arrhythmia prospectively within a 1-year period to provide early warning of impending arrhythmia. METHODS: Retrospective (1,033,856 individuals enrolled between October 1, 2016, and October 1, 2017) and prospective (1,040,767 individuals enrolled between October 1, 2017, and October 1, 2018) cohorts were constructed from integrated electronic health records in Maine, United States. An ensemble learning workflow was built through multiple machine learning algorithms. Differentiating features, including acute and chronic diseases, procedures, health status, laboratory tests, prescriptions, clinical utilization indicators, and socioeconomic determinants, were compiled for incident arrhythmia assessment. The predictive model was retrospectively trained and calibrated using an isotonic regression method and was prospectively validated. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). RESULTS: The cardiac dysrhythmia case-finding algorithm (retrospective: AUROC 0.854; prospective: AUROC 0.827) stratified the population into 5 risk groups: 53.35% (555,233/1,040,767), 44.83% (466,594/1,040,767), 1.76% (18,290/1,040,767), 0.06% (623/1,040,767), and 0.003% (27/1,040,767) were in the very low-risk, low-risk, medium-risk, high-risk, and very high-risk groups, respectively; 51.85% (14/27) patients in the very high-risk subgroup were confirmed to have incident cardiac dysrhythmia within the subsequent 1 year. CONCLUSIONS: Our case-finding algorithm is promising for prospectively predicting 1-year incident cardiac dysrhythmias in a general population, and we believe that our case-finding algorithm can serve as an early warning system to allow statewide population-level screening and surveillance to improve cardiac dysrhythmia care.