Jianpi Qinghua Formula Alleviates Diabetic Myocardial Injury Through Inhibiting JunB/c-Fos Expression.

OBJECTIVE: Diabetic cardiomyopathy (DCM) represents a substantial risk factor for heart failure and increased mortality in individuals afflicted with diabetes mellitus (DM). DCM typically manifests as myocardial fibrosis, myocardial hypertrophy, and impaired left ventricular diastolic function. While the clinical utility of the Jianpi Qinghua (JPQH) formula has been established in treating diabetes and insulin resistance, its potential efficacy in alleviating diabetic cardiomyopathy remains uncertain. This study aims to investigate the impact and underlying molecular mechanisms of the JPQH formula (JPQHF) in ameliorating myocardial injury in nonobese diabetic rats, specifically focusing on apoptosis and inflammation. METHODS: Wistar rats were assigned as the normal control group (CON), while Goto-Kakizaki (GK) rats were randomly divided into three groups: DM, DM treated with the JPQHF, and DM treated with metformin (MET). Following a 4-week treatment regimen, various biochemical markers related to glucose metabolism, cardiac function, cardiac morphology, and myocardial ultrastructure in GK rats were assessed. RNA sequencing was utilized to analyze differential gene expression and identify potential therapeutic targets. In vitro experiments involved high glucose to induce apoptosis and inflammation in H9c2 cells. Cell viability was evaluated using CCK-8 assay, apoptosis was monitored via flow cytometry, and the production of inflammatory cytokines was measured using quantitative real-time PCR (qPCR) and ELISA. Protein expression levels were determined by Western blotting analysis. The investigation also incorporated the use of MAPK inhibitors to further elucidate the mechanism at both the transcriptional and protein levels. RESULTS: The JPQHF group exhibited significant reductions in interventricular septal thickness at end-systole (IVSs) and left ventricular internal diameter at end-systole and end-diastole (LVIDs and LVIDd). JPQHF effectively suppressed high glucose-induced activation of IL-1ß and caspase 3 in cardiomyocytes. Furthermore, JPQHF downregulated the expression of myocardial JunB/c-Fos, which was upregulated in both diabetic rats and high glucose-treated H9c2 cells. CONCLUSION: The JPQH formula holds promise in mitigating diabetic myocardial apoptosis and inflammation in cardiomyocytes by inhibiting JunB/c-Fos expression through suppressing the MAPK (p38 and ERK1/2) pathway.

Candidate metabolite markers of peripheral neuropathy in Chinese patients with type 2 diabetes.

OBJECTIVES: To analyze the serum and urine metabolites present in type 2 diabetes mellitus (T2DM) patients and T2DM patients with diabetic peripheral neuropathy (DPN) and to select differentially expressed biomarkers for early diagnosis of DPN. METHODS: Serum and urine metabolites from 74 T2DM patients with peripheral neuropathy and 41 without peripheral neuropathy were analyzed using gas chromatograph system with time-of-flight mass spectrometer metabolomics to detect biomarkers of peripheral neuropathy in T2DM. RESULTS: There were increased serum triglycerides, alanine aminotransferase, and decreased C-peptide, and total cholesterol levels in T2DM patients with DPN compared to those without peripheral neuropathy. Metabolomic analysis revealed visible differences in metabolic characteristics between two groups, and overall 53 serum differential metabolites and 56 urine differential metabolites were identified with variable influence on projection (VIP) >1 and P<0.05. To further analyze the correlation between the identified metabolites and DPN, four serum metabolites and six urine metabolites were selected with VIP>2, and fold change (FC) >1, including serum ß-alanine, caproic acid, ß-alanine/L-aspartic acid, and L-arabinose/L-arabitol, and urine gluconic acid, erythritol, galactonic acid, guanidoacetic acid, cytidine, and aminoadipic acid. Furthermore, five serum biomarkers and six urine biomarkers were found to show significant changes (P<0.05, VIP>1, and FC>1) respectively in patients with mild, moderate, and severe DPN. In addition, we found that glyoxylate and dicarboxylate metabolism was a differential metabolic pathway not only between T2DM and DPN, but also among different degrees of DPN. The differential metabolites such as ß-alanine and caproic acid are expected to be biomarkers for DPN patients, and the significant changes in glyoxylate and dicarboxylate metabolism may be related to the pathogenesis of DPN. CONCLUSION: There were serum and urine spectrum metabolomic differences in patients with DPN, which could serve as biomarkers for T2DM and DPN patients.

[Analysis on pulse diagram characteristics of subjects with subhealth state].

OBJECTIVE: To study the pulse diagram parameters of subjects with subhealth state and to find the pulse parameters for subhealth state evaluation. METHODS: A total of 1 275 subjects without diagnosed diseases were recruited and their health conditions were assessed with Health Evaluating Questionnaire H20 V2009. The subjects were assigned to health group or subhealth group according to the scale score. Subjects' syndrome in the subhealth group was differentiated using score of "subhealth state of syndrome differentiation V2010". Another 121 patients with cardiovascular diseases were enrolled as a control. The pulse information was collected with YJJ-101 subhealth pulse monitoring system and the parameters include amplitude of main wave (h1), amplitude of repeat wave (h5) and its front wave (h3), 1/3 or 1/5 width of main wave (w1) or (w2), time of rapid ejection phase (t2), period of pulse (t), pulse pressure (Pp), square (S), area in systole (As) and area in diastole (Ad) of pulse diagram and ratios of h3/h1, h5/h1, w1/t, w2/t and h1/t1. RESULTS: Pulse diagram analysis showed significant differences among health, subhealth and disease group in Pp, h1, S and As and ratios of h5/h1 and w2/t. Compared with the health group, the values of w1/t and w2/t of the subhealth group increased (P<0.05), and Pp, h1, h5, h5/h1, S, As and Ad decreased (P<0.05). Compared with health group, the parameters of pulse of the subhealth group were increased in Pp and h5/h1 (P<0.05) and decreased in h1, w2/t, S and As (P<0.05). Compared with health group, pulse parameters h3/h1, w1, w1/t, w2/t of excess and deficiency syndrome group increased, and h1, h5, h1/t 1and h5/h1 decreased. Among different syndromes of subhealth state, pulse diagram parameters h1, h5, h3/h1, h5/h1 and w1/t of yin deficiency, qi deficiency, liver stagnation and excess heat group were significantly different (P<0.05) from the health group, for example, pulse parameters h1 and h5 of stagnation, yin deficiency, qi deficiency and excess heat group declined in order, and pulse parameters h3/h1 and w1/t of liver stagnation, excess heat, yin deficiency and qi deficiency group increased in order. Pulse index h1 in the kidney deficiency group was higher than that in the health group and the other syndrome groups. CONCLUSION: Results of analyzing sphygmogram parameters showed different characteristics among different health status and the subhealth state due to different syndromes. Sphygmogram parameters may be used for objective evaluation of health status or subhealth syndrome differentiation.