Background Metabolic dysfunction–associated steatohepatitis (MASH) is a liver disease that progresses and may be connected to neuroinflammation, though the specific molecular mechanisms are not yet understood. The objective of this research was to explore candidate diagnostic biomarkers related to neuroinflammation‐associated gene programs for MASH through integrated bioinformatics and machine learning, as a hypothesis‐generating study. Methods Genes with differential expression (DEGs) were pinpointed from the GSE89632 dataset, which includes 39 MASH samples compared with 24 controls. Candidate genes were identified using weighted gene coexpression network analysis (WGCNA) and gene sets related to neuroinflammation. A diagnostic model was constructed using 81 machine learning algorithm combinations (filtered from an initial set of 113 by excluding models with fewer than 2 features) within the training set, and its performance was subsequently evaluated in GSE126848 (31 MASH vs. 26 controls) as an evaluation set. Because the evaluation set contributed to model selection, it does not represent a fully independent validation cohort. Regulatory network construction, drug prediction, and molecular docking were used for further analysis of key genes. Results A total of 90 disease‐associated neuroinflammation‐related candidate genes were identified. Five candidate key genes (IRS1, HBEGF, MYC, CD274, and HMOX1) were screened, and a diagnostic model was constructed. The model achieved an AUC of 0.978 in the training set and 0.823 in the evaluation set; however, because the evaluation set contributed to model selection in the original analysis, the 0.823 estimate should be interpreted with caution. These findings are exploratory and require experimental validation. Conclusions This exploratory study identified five neuroinflammation‐related candidate genes that may serve as candidate biomarkers for MASH. These findings provide candidate molecular links and potential therapeutic hypotheses, but require experimental validation and should be regarded as hypothesis‐generating rather than clinically actionable.
Background Statins are widely used for cardiovascular disease prevention and exhibit multiple pleiotropic effects, including anti‐inflammatory properties. However, conclusions from observational studies regarding the causal relationship between statin use and upper gastrointestinal diseases (such as gastric cancer, gastric ulcer, and functional dyspepsia) remain controversial. This study is aimed at systematically evaluating the causal association between statin‐targeted gene (HMGCR)–mediated reductions in low‐density lipoprotein cholesterol (LDL‐C) levels and common upper gastrointestinal diseases using drug‐targeted Mendelian randomization (MR). This approach seeks to uncover potential unintended effects. Methods We extracted genetic variants associated with the HMGCR gene region from genome‐wide association studies (GWAS) as instrumental variables to simulate the lipid‐lowering effects of statins. Outcome data were derived from large‐scale GWAS meta‐analyses covering gastric cancer ( n = 202,308), gastroenteritis ( n = 7651), gastric ulcer ( n = 361,194), gastroesophageal reflux disease ( n = 462,933), and functional dyspepsia ( n = 84,572). The primary analysis employed inverse variance weighting (IVW), with sensitivity assessments for heterogeneity and pleiotropy conducted via MR‐Egger, weighted median, and MR‐PRESSO methods. Results Genetically predicted HMGCR‐mediated LDL‐C reduction was associated with reduced risk of gastric cancer (OR = 0.588, 95% CI: 0.423–0.816, p = 0.002), gastroenteritis (OR = 0.257, 95% CI: 0.086–0.766, p = 0.015), and gastric ulcer (OR = 0.996, 95% CI: 0.993–0.998, p = 0.003). However, analysis indicated a potential increased risk of functional dyspepsia (OR = 1.437, 95% CI: 1.014–2.036, p = 0.042). No significant causal association was found between statin use and gastroesophageal reflux disease (OR = 0.999, 95% CI: 0.992–1.006, p = 0.773). Sensitivity analyses confirmed the robustness of the results, with no evidence of significant level‐specific multiplicity. Conclusion This study provides genetic evidence supporting the potential protective effects of statins against gastric cancer, gastritis, and gastric ulcers, which may be associated with their anti‐inflammatory properties. However, the potential increased risk of functional dyspepsia suggests the complexity of the drug′s effects. These findings provide scientific basis for the repositioning of statins in gastrointestinal diseases and their safety assessment.
Background Pegylated interferon alpha has been shown to enhance the likelihood of achieving a functional cure in patients with hepatitis B. However, it was associated with a greater number of contraindications and adverse reactions compared with nucleotide analogs. Current research has placed comparatively less emphasis on the potential for this treatment to induce decision regret among patients. Aim: The aim of this study was to investigate the current status of decision regret in hepatitis B patients undergoing interferon therapy and to explore its influencing factors. Method A cross‐sectional study was conducted in a comprehensive hospital in Xiamen, Fujian Province, China, from February 20 to June 13, 2024. The study recruited hepatitis B patients undergoing treatment with pegylated interferon alpha. The survey encompassed general information, the All Aspects of Health Literacy Scale, the Perceived Social Support Scale, the Control Preferences Scale, the Decisional Conflict Scale, and the Decision Regret Scale. Results A total of 130 questionnaires were analyzed. Only 13.85% of patients had no regrets at all about the decision, 34.60% experienced mild regret, and the proportion of patients with moderate to severe regrets reached 51.50%. Mild impact on life, active decision‐making roles, passive decision‐making roles, and decision conflict were the influencing factors of decisional regret in hepatitis B patients on pegylated interferon alpha therapy, which together explained 29.6% of the total variation. Conclusion Hepatitis B patients undergoing pegylated interferon alpha therapy had a high percentage of decisional regret. Healthcare professionals should pay close attention to this phenomenon. In the future, they can investigate additional potential influencing factors and promptly develop intervention strategies to effectively reduce decision regret.
Helicobacter pylori ( H. pylori ), recognized as the primary pathogen responsible for chronic gastric infections, has exhibited an increasing prevalence of antibiotic resistance, which significantly impairs the efficacy of clinical treatments. In recent years, the extensive utilization of antibiotics alongside the rising prevalence of resistant strains has elevated the investigation of the resistance mechanisms of H. pylori to a prominent area of research. This article systematically examines the phenotypic characteristics associated with the antibiotic resistance of H. pylori , establishing a correspondence with resistance genotypes. Particular emphasis is placed on analyzing the resistance mechanisms linked to commonly prescribed antibiotics such as clarithromycin, metronidazole, and amoxicillin, in addition to the molecular characteristics of the relevant resistance genes (such as mutations in “gyrA,” “gyrB,” “23S rRNA,” “frxA,” “pbp1,” and “rdxA”). By merging advancements in molecular biology with findings from epidemiological studies, this review explores the potential application of resistance genotype detection in facilitating tailored clinical treatment approaches. The objective of this review is to enhance the understanding of the resistance mechanisms of H. pylori , fostering the development of precise diagnostic and therapeutic strategies and offering theoretical insights and future research pathways for the treatment of anti– H. pylori infections.
Background and Objective This study is aimed at evaluating the predictive value of the blood urea nitrogen‐to‐albumin ratio (BAR) for both mortality and delirium risk in patients with pancreatitis. Pancreatitis carries a substantial mortality risk and significant long‐term sequelae, with delirium being a severe neurological complication, underscoring the clinical need for effective prognostic markers. Methods A retrospective cohort study was performed using the MIMIC‐IV v3.0 database. A total of 1748 ICU patients meeting diagnostic criteria for pancreatitis (ICD‐9/10 codes: 577.0, 577.1, K85) with documented baseline blood urea nitrogen (BUN) and albumin levels were included. BAR was calculated (BUN[mg/dL]/Albumin[g/dL]) and patients were stratified into quartiles (Q1: BAR < 3.0; Q2: BAR 3.0–5.0; Q3: BAR 5.0–9.2; Q4: BAR ≥ 9.2). The primary endpoints were all‐cause mortality and delirium occurrence (identified using ICD‐9 codes 293.0, 293.1, and ICD‐10 codes F05, F05.9). Multivariable Cox proportional hazards regression (mortality) and logistic regression (delirium) were employed, adjusting for demographics, illness severity scores (GCS, SAPS II, OASIS, and Charlson Comorbidity Index), and comorbidities. Restricted cubic splines (RCS) were used to explore nonlinear associations. Results Higher BAR levels significantly correlated with greater disease severity: compared with Q1, Q4 exhibited a higher Charlson Comorbidity Index and mortality rate. BAR was an independent predictor of delirium; each 1‐unit increase in BAR was associated with a 2.7% increased risk of delirium (adjusted OR = 1.027, 95% CI: 1.009–1.044), and patients in Q4 had a significantly higher risk compared with those in Q1 (adjusted OR = 1.882, 95% CI: 1.157–3.108). After multivariable adjustment, BAR was not significantly independently associated with mortality (Q4 adjusted HR = 1.022, p = 0.8). RCS analysis revealed BAR > 9.0 as a high‐risk threshold, characterized by delirium OR > 1.78 and mortality HR > 1.97. The BAR quartile model yielded AUCs of 0.635 and 0.599 for predicting mortality and delirium, respectively, indicating modest predictive ability. Conclusion BAR independently predicts delirium risk and reflects disease severity in pancreatitis patients, but does not demonstrate significant independent predictive value for mortality after accounting for confounders. The identified threshold (BAR > 9.0) supports the utility of BAR as a supplementary biomarker for delirium risk stratification in this population.
