Diseases

Background/Objectives: Mycobacterial infections and autoimmune diseases affect many worldwide, and growing evidence suggests that there is a bidirectional relationship. This review examines mechanisms by which various autoimmune diseases predispose patients to mycobacterial infections, and vice versa. Methods: We conducted a PubMed/MEDLINE search using the keywords “mycobacterium” and the names of the autoimmune conditions to identify relevant papers. Results: Rheumatoid arthritis therapies, especially TNF-α inhibitors, raise tuberculosis (TB) and non-tuberculous mycobacteria (NTM) risk. Type 1 diabetes features impaired cell-mediated immunity and macrophage dysfunction, with evidence for Mycobacterium avium subspecies paratuberculosis (MAP) mimicry involving HSP65–GAD65. In systemic lupus erythematosus, immune dysregulation plus corticosteroids and cytotoxins elevates TB and NTM risk, amplified in endemic settings. In multiple sclerosis, heightened TLR2/4/9 signaling agents that inhibit pyrimidine synthesis may increase IL-10 and reduce antimycobacterial immunity. Crohn’s disease shows genetic susceptibility (e.g., NOD2 variants) and MAP detection, supporting impaired clearance of intracellular mycobacteria. Conclusions: Overall, evidence supports a bidirectional relationship: mycobacterial antigens can initiate or amplify autoimmunity via molecular mimicry and chronic stimulation, while autoimmune biology and iatrogenic immunosuppression increase susceptibility to infection. Implications include latent TB screening before immunosuppression, attention to local epidemiology, and vigilance for NTM. Research priorities include prospective cohorts, mechanistic studies of mimicry and NOD2–TLR pathways, safety registries, and trials of screening and prophylaxis.

Objectives: The TNM staging system for distal cholangiocarcinoma (dCCA) has limited accuracy due to its anatomical basis. This study developed a prognostic model integrating inflammatory-nutritional markers and tumor biomarkers to improve risk stratification. Methods: We analyzed 208 dCCA patients undergoing pancreaticoduodenectomy (2017–2024). Independent prognostic factors for overall survival (OS) were identified via Cox regression, including tumor marker (corrected CA19-9) and host status markers (PLR, CAR, and PNI). A nomogram was constructed and evaluated using calibration, ROC, and DCA. Patients were risk-stratified using the model’s score. Results: Four independent factors were identified: corrected CA19-9 (HR = 2.438), PLR (HR = 2.041), CAR (HR = 2.477), and PNI (HR = 0.415). The nomogram showed excellent discrimination for 1-, 3-, and 5-year OS (AUC: 0.847, 0.824, 0.858), good calibration, and clinical utility per DCA. Risk stratification significantly distinguished high-risk (n = 110) from low-risk (n = 98) groups (log-rank p < 0.0001). Discussion: This multidimensional model (tumor burden, inflammation, nutrition) outperforms TNM staging, highlighting host systemic status. Despite its single-center retrospective design, it shows promise for personalized risk assessment. Conclusion: The CINS (Cholangiocarcinoma Inflammation–Nutrition Score) accurately predicts prognosis and effectively risk-stratifies dCCA patients, aiding personalized treatment planning.

A compelling body of evidence links pesticide exposure to human diseases. The liver plays a central role in the detoxification of pesticides, suggesting intense pesticide–liver cell interactions. A growing body of studies highlighted in this review supports the contribution of pesticides of various chemical classes to the development of non-alcoholic fatty liver disease (NAFLD), alcohol-associated liver disease (ALD), liver cirrhosis, viral hepatitis, hepatocellular carcinoma, etc., via disrupting lipid and carbohydrate metabolism and redox homeostasis, promoting endoplasmic reticulum stress and mitochondrial dysfunction, as well as stimulating apoptosis, fibrosis, and inflammation. In this review, we systematically illustrated an underappreciated mechanism of pesticide-induced overall and hepatic toxicity, i.e., the ability to induce non-apoptotic regulated cell death (RCD) pathways such as ferroptosis, necroptosis, and pyroptosis. Our analysis indicates that pesticides are implicated in driving liver diseases by inducing ferroptosis, necroptosis, and pyroptosis. Non-apoptotic RCDs mediate pesticide-induced liver steatosis and fibrosis. Furthermore, these cell death modalities fuel inflammation through the promotion of pro-inflammatory cytokine production and the generation of damage-associated molecular patterns. Understanding of deeper mechanisms of pesticide-induced effects on the non-apoptotic cell death machinery and subsequent immunogenic effects in liver pathology might help develop novel preventive strategies to reduce liver damage.