Inhibition of ACOX1 enhances the therapeutic efficacy of obeticholic acid in treating non-alcoholic fatty liver disease and mitigates its lipotoxicity.

Background and aims: High-dose Obeticholic acid exhibits promise for non-alcoholic fatty liver disease (NAFLD) treatment but can induce lipotoxicity. Our study sought to understand this mechanism and propose a solution. Approach and Results: In a non-alcoholic fatty liver disease (NAFLD) model induced by a high-fat diet in FXR-/- mice, we pinpointed that FXR regulated the expression of ACOX1 through RNA-Seq analysis. In the livers of FXR-/- mice, both ACOX1 mRNA and protein expression notably decreased. In both HL-7702 and HEP-G2 cells, the silencing of FXR through shRNA plasmids decreased ACOX1 expression, while FXR activation with GW4064 increased it. These effects were reversible with the ACOX1-specific inhibitor, 10,12-Tricosadiynoic acid. In the NAFLD model of FXR-/- mice, The activation of ACOX1 is correlated with elevated serum LDL, triglycerides, and aggravated hepatic steatosis. However, the combination of 10,12-Tricosadiynoic acid with low-dose obeticholic acid effectively treated hepatic steatosis, reducing LDL levels in the NAFLD model of wild-type mice. This combination therapy demonstrated efficacy comparable to high-dose obeticholic acid alone. Notably, the combined drug regimen treats hepatic steatosis by inhibiting the IL-1ß and α-SMA pathways in NAFLD. Conclusion: Combining ACOX1-specific inhibitors with low-dose obeticholic acid effectively treats high-fat diet-induced hepatic steatosis and reduces serum LDL. This approach enhances the therapeutic effects of obeticholic acid and mitigates its lipotoxicity by inhibiting the IL-1ß and α-SMA pathways.

Construction of an Immune-Related Prognostic Signature and lncRNA‒miRNA-mRNA ceRNA Network in Acute Myeloid Leukaemia.

The progression of acute myeloid leukaemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, Cancer Genome Atlas Program, Gene Expression Omnibus, Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic mRNA was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, GEPIA, and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential lncRNA/miRNA/mRNA regulatory axis. Our findings pinpointed nine immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 differentially expressed prognostic lncRNAs (DE-lncRNAs), six prognostic DE-miRNAs, and three prognostic immune-related IR-DEmRNAs. Correlation analyses linked these mRNA's expression to 22 immune cell types, six immune checkpoints, and potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including two mRNAs (CKLF, PNOC), one miRNA (hsa-miR-323a-3p), and ten lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

Risk factors for the development of sepsis in patients with cirrhosis in intensive care units.

Sepsis is a serious complication of liver cirrhosis. This study aimed to develop a risk prediction model for sepsis among patients with liver cirrhosis. A total of 3130 patients with liver cirrhosis were enrolled from the Medical Information Mart for Intensive Care IV database, and randomly assigned into training and validation cohorts in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression was used to filter variables and select predictor variables. Multivariate logistic regression was used to establish the prediction model. Based on LASSO and multivariate logistic regression, gender, base excess, bicarbonate, white blood cells, potassium, fibrinogen, systolic blood pressure, mechanical ventilation, and vasopressor use were identified as independent risk variables, and then a nomogram was constructed and validated. The consistency index (C-index), receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram. As a result of the nomogram, good discrimination was achieved, with C-indexes of 0.814 and 0.828 for the training and validation cohorts, respectively, and an area under the curve of 0.849 in the training cohort and 0.821 in the validation cohort. The calibration curves demonstrated good agreement between the predictions and observations. The DCA curves showed the nomogram had significant clinical value. We developed and validated a risk-prediction model for sepsis in patients with liver cirrhosis. This model can assist clinicians in the early detection and prevention of sepsis in patients with liver cirrhosis.

Prognostic-Related Biomarkers in Pancreatic Ductal Adenocarcinoma Correlating with Immune Infiltrates Based on Proteomics.

BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) accounts for 85% of pancreatic carcinoma cases. Patients with PDAC have a poor prognosis. The lack of reliable prognostic biomarkers makes treatment challenging for patients with PDAC. Using a bioinformatics database, we sought to identify prognostic biomarkers for PDAC. MATERIAL AND METHODS Using proteomic analysis of the Clinical Proteomics Tumor Analysis Consortium (CPTAC) database, we were able to identify core differential proteins between early and advanced pancreatic ductal adenocarcinoma tissue, and then we used survival analysis, Cox regression analysis, and area under the ROC curves to screen for more significant differential proteins. Additionally, the Kaplan-Meier plotter database was utilized to determine the relationship between prognosis and immune infiltration in PDAC. RESULTS We identified 378 differential proteins in early (n=78) and advanced stages (n=47) of PDAC (P<0.05). PLG, COPS5, FYN, ITGB3, IRF3, and SPTA1 served as independent prognostic factors of patients with PDAC. Patients with higher COPS5 expression had shorter overall survival (OS) and recurrence-free survival, and those with higher PLG, ITGB3, and SPTA1, and lower FYN and IRF3 expression had shorter OS. More importantly, COPS5, IRF3 were negatively associated with macrophages and NK cells, but PLG, FYN, ITGB3, and SPTA1 were positively related to the expression of CD8+ T cells and B cells. COPS5 affected the prognosis of PDAC patients by acting on B cells, CD8+ T cells, macrophages, and NK cells immune infiltration, while PLG, FYN, ITGB3, IRF3, and SPTA1 affected PDAC patient prognosis through some immune cells. CONCLUSIONS PLG, COPS5, FYN, IRF3, ITGB3 and SPTA1 could be potential immunotherapeutic targets and valuable prognostic biomarkers of PDAC.

Perivascular epithelioid cell tumors of the liver misdiagnosed as hepatocellular carcinoma: Three case reports.

BACKGROUND: Hepatic perivascular epithelioid cell neoplasms (PEComas) are rare. Diagnostic and treatment experience with hepatic PEComa remains insufficient. CASE SUMMARY: Three hepatic PEComa cases are reported in this paper: One case of primary malignant hepatic PEComa, one case of benign hepatic PEComa, and one case of hepatic PEComa with an ovarian mature cystic teratoma. During preoperative imaging and pathological assessment of intraoperative frozen samples, patients were diagnosed with hepatocellular carcinoma (HCC), while postoperative pathology and immunohistochemistry subsequently revealed hepatic PEComa. Patients with hepatic PEComa which is misdiagnosed as HCC often require a wider surgical resection. It is easy to mistake them for distant metastases of hepatic PEComa and misdiagnosed as HCC, especially when it's combined with tumors in other organs. Three patients eventually underwent partial hepatectomy. After 1-4 years of follow-up, none of the patients experienced recurrence or metastases. CONCLUSION: A clear preoperative diagnosis of hepatic PEComa can reduce the scope of resection and prevent unnecessary injuries during surgery.

Prolonged activated partial thromboplastin time predicts poor short-term prognosis in patients with acute pancreatitis: A retrospective cohort study.

It is unclear whether activated partial thromboplastin time (APTT) is predictive of survival in patients with acute pancreatitis (AP). Our study aimed to investigate the relationship between APTT and short-term prognosis in AP. From the Medical Information Mart for Intensive Care (MIMIC)-IV database, a total of 844 patients with AP were randomly divided into the training cohort (n = 591) and the validation cohort (n = 253) at a ratio of 7:3. Based on their APTT values, the patients were divided into the normal and high groups. The primary outcome of this study was 30- and 60-day survival. Kaplan-Meier survival analysis and Cox regression models were used to analyze associations between groups and outcomes. The training and validation cohort matched well on all parameters (p > 0.05). In terms of 30- and 60-day survival, Kaplan-Meier survival curves from both training and validation cohorts demonstrated a lower survival probability for patients in the high APTT group than the normal group (log-rank p < 0.05). In the training cohort, patients in the high APTT group had a statistically significantly higher risk of death than those in the normal group after controlling for possible confounders in Cox regression (p < 0.05). For the high APTT group, the hazard ratios (95% confidence interval [CI]) were 1.63 (95% CI 1.10, 2.61, p = 0.035) and 1.49 (95% CI 1.01, 2.38, p = 0.041), respectively. APTT performed as well as BISAP, Ranson, and APACHE II models in predicting 30- and 60-day survival in patients with AP. The results above have been verified in the validation cohort. Prolonged APTT in patients with AP may increase the risk of short-term death.