Ulcerative colitis (UC) is a disease that is difficult to treat and has been associated with high rates of recurrence. Moreover, the current medications for UC induce serious side effects following prolonged use. Ganjiang Huangqin Huanglian Renshen Decoction (GJHQHLRSD), has been traditionally used to treat UC. However, its protective mechanisms have not been fully studied. In this study the mechanisms by which GJHQHLRSD treats UC was investigated. The GJHQHLRSD and GJHQHLRSD drug-containing serum (GJHQHLRSD-DS) were characterized using LC-MS/MS. The therapeutic effect of GJHQHLRSD on dextran sodium sulfate (DSS)-induced UC was explored by assessing various parameters including intestinal flora 16S rRNA, intestinal barrier function, oxidative stress (OS) response, inflammatory cytokines, colonic histopathological injury, colon length, disease activity index (DAI) and body weight. Treatment with GJHQHLRSD increased body weight, ameliorated colon length shortening and edema, reduced the DAI score, improved the pathological injury, down-regulated the levels of IL-1β, IL-6, IL-8, TNF-α, LPS, LDH, TLR4, and NLRP3, and up-regulated the ZO-1 and Occludin levels in UC mice. It also decreased intestinal oxidative stress in UC mice and improved mitogenic activity by modulating mitochondrial ultrastructure as well as the expression level of PINK1, LC3-II/Ⅰ, Beclin-1, p62, and Parkin proteins. In addition, we found that the effects of GJHQHLRSD on UC mice were inhibited by 3-MA.GJHQHLRSD treatment reduced the imbalance of intestinal flora in UC mice, by regulating the inflammation and oxidative stress. These findings suggested that GJHQHLRSD effectively attenuated inflammatory responses, inhibited the TLR4/NF-κB/NLRP3 signalling, oxidative stress, and modulated the gut microbiota, and alleviated the DSS-induced UC symptoms, making it a promising and innovative therapeutic option for the treatment of UC.

This study analyzes the distribution characteristics of traditional Chinese medicine (TCM) syndrome types in patients with insomnia and investigate the association between different factors and the distribution of the TCM syndrome types as well as the possible factors affecting this distribution. A retrospective analysis of the data from 468 insomnia patients was conducted. The association between different factors, such as gender, age, occupation, and the distribution of the TCM syndrome types, was evaluated using the Kruskal–Wallis H test, Chi-square test, and Fisher’s exact probability method. The potential factors affecting yin-yang syndrome insomnia were analyzed using binary logistic regression. The results of the TCM syndrome type distribution indicated that yin syndrome (69.9%) was significantly more common than yang syndrome (30.1%), among which the heart-spleen deficiency type (31.6%) was the most common. Age, occupation, hypertension, the presence or absence of children, and history of diabetes were significantly different among the different TCM syndrome types. The logistic regression analysis revealed that occupation (odds ratio [OR] = 2.099, 95% confidence interval [CI]: 1.356–3.251), offspring status (OR = 9.034, 95% CI: 1.181–69.085), diabetes status (OR = 2.202, 95% CI: 1.236–3.922), and gender (OR = 1.564, 95% CI: 1.009–2.423) were influencing factors of yang syndrome insomnia. This study revealed the correlation between the distribution of the TCM syndrome types of insomnia patients and age, occupation, hypertension, having offspring, a history of diabetes, especially other occupations, having children, a history of diabetes, and male gender were risk factors for yang syndrome insomnia.

Background/Objectives: Isocitrate dehydrogenase (IDH) status is important for the classification and prognosis of adult gliomas. Whole-tumor MRI summary measures may obscure intratumoral spatial heterogeneity, whereas data-driven habitat analysis identifies imaging-defined tumor subregions and may better capture this heterogeneity. This study aimed to evaluate the diagnostic performance of MRI habitat analysis for preoperative prediction of IDH status. Methods: We searched PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure (CNKI), and Wanfang Data from database inception through 22 August 2026. Eligible studies used data-driven MRI habitat analysis to predict IDH status in adult gliomas. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Sensitivity and specificity were pooled using a bivariate random-effects model. We also performed sensitivity analyses, univariable meta-regression, subgroup analyses, and Radiomics Quality Score 2.0 (RQS 2.0) assessment. The protocol was registered in PROSPERO (CRD420261489645). Results: Eighteen reports were included in the systematic review, and 13 independent studies involving 1236 patients contributed to the meta-analysis. Pooled sensitivity and specificity were 0.78 (95% CI, 0.70–0.84) and 0.85 (95% CI, 0.79–0.89), respectively, with an SROC AUC of 0.89 (95% CI, 0.86–0.91). I² was 82.1% for sensitivity and 71.3% for specificity. Excluding two studies with approximately reconstructed 2 × 2 tables did not materially change the pooled estimates. Radiomics studies and studies using ≥4 habitats showed higher specificity and lower sensitivity, but their overlap limited separate interpretation of feature type and habitat number. Conclusions: MRI habitat analysis showed promising diagnostic performance for preoperative prediction of IDH status in adult gliomas. However, limited external validation and incomplete assessment of reproducibility and clinical utility remain barriers to clinical translation. Future prospective multicenter studies should further evaluate habitat stability, model calibration, and clinical net benefit.