Background and aim: Previous studies have reported an association between gut microbiota and cirrhosis. However, the causality between intestinal flora and liver cirrhosis still remains unclear. In this study, bi-directional Mendelian randomization (MR) analysis was used to ascertain the potential causal effect between gut microbes and cirrhosis.Methods: Large-scale Genome Wide Association Study (GWAS) data of cirrhosis and gut microbes were obtained from FinnGen, Mibiogen consortium, and a GWAS meta-analysis of Alcoholic cirrhosis (ALC). Two-sample MR was performed to determine the causal relationship between gut microbiota and cirrhosis. Furthermore, a bi-directional MR analysis was employed to examine the direction of the causal relations.Result: In MR analysis, we found that 21 gut microbiotas were potentially associated with cirrhosis. In reverse MR analysis, 11 gut microbiotas displayed potentially associations between genetic liability in the gut microbiome and cirrhosis. We found that the family Lachnospiraceae (OR: 1.59, 95% CI:1.10–2.29) might be harmful in cirrhotic conditions (ICD-10: K74). Furthermore, the genus Erysipelatoclostridium might be a protective factor for cirrhosis (OR:0.55, 95% CI:0.34–0.88) and PBC (OR:0.68, 95% CI:0.52–0.89). Combining the results from the MR analysis and reverse MR analysis, we firstly identified the Genus Butyricicoccus had a bi-directional causal effect on PBC (Forward: OR: 0.37, 95% CI:0.15–0.93; Reverse: OR: 1.03, 95% CI:1.00–1.05).Conclusion: We found a new potential causal effect between cirrhosis and intestinal flora and provided new insights into the role of gut microbiota in the pathological progression of liver cirrhosis.

Ulcerative colitis (UC) is a chronic, recurrent inflammatory bowel disease. UC confronts with severe challenges including the unclear pathogenesis and lack of specific diagnostic markers, demanding for identifying predictive biomarkers for UC diagnosis and treatment. We perform immune infiltration and weighted gene co-expression network analysis on gene expression profiles of active UC, inactive UC, and normal controls to identify UC related immune cell and hub genes. Neutrophils, M1 macrophages, activated dendritic cells, and activated mast cells are significantly enriched in active UC. MMP-9, CHI3L1, CXCL9, CXCL10, CXCR2 and S100A9 are identified as hub genes in active UC. Specifically, S100A9 is significantly overexpressed in mice with colitis. The receiver operating characteristic curve demonstrates the excellent performance of S100A9 expression in diagnosing active UC. Inhibition of S100A9 expression reduces DSS-induced colonic inflammation. These identified biomarkers associated with activity in UC patients enlighten the new insights of UC diagnosis and treatment.

Background: Necroptosis plays a critical role in the onset and progression of numerous malignancies, with colorectal cancer (CRC) ranking among the leading causes of cancer-related mortality worldwide. However, the relationship between necroptosis-related genes (NRGs) and CRC remains contentious. Hence, this study aims to develop a novel NRG-based signature to predict the prognosis of CRC patients and explore its potential role.Methods: Transcriptome data from the Gene Expression Omnibus (GEO) databases and the Cancer Genome Atlas (TCGA) were employed to identify cancer hallmarks associated with outcomes in CRC. A novel NRG signature was formulated and validated using least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression analysis. Subsequently, univariate and multivariate Cox regression analyses, Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curves, and nomograms were utilized to assess the predictive capability of our signature. Furthermore, a variety of bioinformatics analysis algorithms were leveraged to uncover potential mechanisms, tumor immune status, and differences in drug sensitivity between the two-risk groups. The expression of signature NRGs in CRC was evaluated through quantitative reverse transcription polymerase chain reaction (qRT-PCR).Results: A novel signature consisting of eighteen NRGs (CTSB, PAEP, ARL4C, TAP2, WFS1, BATF2, DUSP27, CXCL9, EPHB2, IRF8, CXCL13, GZMB, APOL6, NLRC5, CXCL10, IRF1, HES6, and PTGDR) was successfully established. This signature displayed consistent predictive performance and general applicability for CRC, as validated across three independent cohorts. Moreover, stromal and immune cells within the tumor microenvironment (TME) were found to be correlated with necroptosis. Additionally, notable differences in the sensitivity to anti-tumor agents were observed between the two groups. The qRT-PCR results indicated aberrant expression of these signature NRGs in CRC.Conclusion: NRG was proved to be an accurate predictor of CRC prognosis. Furthermore, the novel signature exhibited consistent value and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in CRC.

Purpose: The systemic immune-inflammation index (SII) comprehensively reflects the balance between immune status and host inflammation. We aimed to investigate the potential predictive value of the SII in the prognosis of granulomatous mastitis (GM). Patients and Methods: We enrolled 245 patients with GM who underwent surgery between 2015 and 2020 in this study. Using the receiver operating characteristic (ROC) curve, we divided the patients into low SII groups (SII≤ 836× 10⁹/L) and high SII groups (SII> 836× 10⁹/L). The associations between SII and clinical parameters were assessed using chi-squared or Fisher’s exact tests. Kaplan-Meier plots and Log rank tests were performed to investigate the clinical outcomes of cumulative no-recurrence rates. Risk factors were analyzed by using logistic regression analysis. Results: We found a correlation between the recurrence of GM and the preoperative level of SII, and the high SII group exhibited a higher recurrence rate than the low SII group. To further explore the factors affecting the risk of recurrence, we found that young age at disease onset, skin rupture, and the postoperative use of corticosteroids could increase the risk of GM recurrence. Multivariate logistic regression analysis suggested that young age and postoperative corticosteroid use were the risk factors for disease recurrence. Conclusion: As a noninvasive and readily available clinical parameter, the preoperative SII level has great significance in evaluating the efficacy and prognosis of surgical treatment for GM combined with age and postoperative corticosteroid use, which provides valuable insights for making treatment decisions.