Drug-induced liver injury (DILI) is rare but clinically important due to a high rate of mortality. However, specific biomarkers for diagnosing and predicting the severity and prognosis of DILI are lacking. Here, we used targeted metabolomics to identify and quantify specific types of bile acids that can predict the severity of DILI. A total of 161 DILI patients were enrolled in this prospective cohort study, as well as 31 health controls. A targeted metabolomics method was used to identify 24 types of bile acids. DILI patients were divided into mild, moderate, and severe groups according to disease severity. A multivariate analysis was performed to identify characteristic bile acids. Then the patients were divided into severe and non-severe groups, and logistic regression was used to identify bile acids that could predict DILI severity. Among the enrolled DILI patients, 32 were in the mild group, 90 were in the moderate group, and 39 were in the severe group. Orthogonal partial least squares-discriminant analysis (OPLS-DA) modeling clearly discriminated among the different groups. Among the four groups, glycochenodeoxycholate (GCDCA), taurochenodeoxycholate (TCDCA), deoxycholic acid (DCA), Nor Cholic acid (NorCA), glycocholic acid (GCA), and taurocholic acid (TCA) showed significant differences in concentration between at least two groups. NorCA, GCDCA, and TCDCA were all independent risk factors that differentiated severe DILI patients from the other groups. The area under the receiver operating characteristic curve (AUROC) of GCDCA, TCDCA, and NorCA was 0.856, 0.792, and 0.753, respectively. Together, these three bile acids had an AUROC of 0.895 for predicting severe DILI patients. DILI patients with different disease severities have specific bile acid metabolomics. NorCA, GCDTA, and TCDCA were independent risk factors for differentiating severe DILI patients from less-severe patients and have the potential to predict DILI severity.

Non-alcoholic fatty liver disease (NAFLD) is currently the most prevalent chronic liver disease worldwide. At the same time, the relationship between air pollution and the likelihood of developing NAFLD has been a subject of debate due to conflicting findings in previous observational research. Our objective was to examine the potential correlation between air pollutant levels and the risk of NAFLD in the European population by employing a two-sample Mendelian randomization (MR) analysis. The UK Biobank Consortium provided the summary statistics for various air pollution indicators (PM_2.5, PM_2.5 absorbance, PM_2.5–10, PM₁₀, NO₂, and NO_x). Additionally, information on NAFLD was obtained from three studies, including one derivation set and two validation sets. Heterogeneity, pleiotropy, and sensitivity analyses were performed under different MR frameworks, and instrumental variables associated with confounders (such as education, smoking, alcohol, and BMI) were detected by tools. In the derivation set, causal relationships between PM_2.5, NO₂, and NAFLD were observed in univariable Mendelian randomization (UVMR) (Odds Ratio (OR) = 1.99, 95% confidence interval (95% CI) = [1.22–3.22], p = 0.005; OR = 2.08, 95% CI = [1.27–3.40], p = 0.004, respectively). After adjustment for air pollutants or alcohol intake frequency in multivariable Mendelian randomization (MVMR), the above genetic correlations disappeared. In validation sets, the null associations remained in UVMR. Our findings from MR analysis using genetic data did not provide evidence for a causal association between air pollution and NAFLD in the European population. The associations observed in epidemiological studies could be partly attributed to confounders.

Cancer is a heavy burden worldwide, with high morbidity and mortality rates. Cancer treatments currently involve surgical and nonsurgical approaches. Molecular targeted therapy is the latest breakthrough. miRNAs are small noncoding RNAs found in plants and animals that play a role in cancer and various diseases through influencing numerous biological processes, such as cell proliferation, apoptosis, the immune response, and drug resistance. One miRNA, miR-622, has been shown to regulate various pathways to influence disease processes. Abnormal miR-622 expression can promote or inhibit liver, colorectal, and breast cancers and other tumors, such as glioma. Herein, we reviewed the expression levels and clinical effects of miR-622 in various tumors and summarized its mechanisms and related molecules.

This work aims to explore the long‐term prognosis of hepatitis B virus‐related acute‐on‐chronic liver failure (HBV‐ACLF). In this prospective study, eligible inpatients with HBV‐ACLF are enrolled and followed up from December 2012 to February 2023, for clinical events, laboratory tests at least every 6 months. Overall, the survival rates at 28 days, 90 days, 1 year, 5 years, and 8 years are 64.7%, 48.8%, 46.1%, 43.8%, and 42.2%, respectively. Among the 8‐year mortality and liver transplant cases, ACLF survivors (who survived over 90 days) accounted for 7.8% (9/115). Among 101 patients who survived for more than 90 days, 97.9% of patients achieve virologic response at 1 year. For HBeAg‐positive patients, the HBeAg seroconversion are 25.5%, 63.6%, and 76.9% at 1, 5, and 8 years, respectively. Alanine aminotransferase, aspartate aminotransferase, total bilirubin, INR, white blood cell count, and albumin levels gradually improve within the first year. Fibrosis biomarkers APRI, FIB‐4 and Chitinase‐3‐like protein 1 (CHI3L1) levels decreases within the first 5 years. The Cox proportional hazards regression reveal that high total bilirubin (HR = 1.008, p = 0.021) is the independent risk factor for 8‐year survival of ALCF survivors. The 90‐day period following of HBV‐ACLF represented a critical juncture for long‐term prognosis, revealing favorable outcomes beyond this timeframe.

Background and Aims: Hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) remains a serious entity with high mortality. Growth hormone (GH) is related to the liver metabolism and regeneration. The present study aimed to explore the changes and prognostic efficacy of GH on the outcome of HBV-ACLF.Methods: A prospective cohort of 124 patients and a cross-sectional cohort of 142 subjects were enrolled. GH and insulin-like growth factor-1(IGF-1) were detected by ELISA. Thirty-day survival was collected and the association between GH and the 30-day mortality of HBV-ACLF was analyzed.Results: The mean age of the whole prospective cohort was 46.61 ± 12.71 years, and 19 (15.3%) patients were female. The median (IQR) of GH levels in non-survivors were 1106.55 (674.25, 1922.4) pg/ml, which were significantly lower than in survivors (p < 0.001). In the cross-sectional cohort, GH level was significantly higher in liver cirrhosis - acute decompensation (LC-AD) group than liver cirrhosis (LC) group (p < 0.001) while IGF-1 decreased significantly in LC, LC-AD, ACLF groups than health control (HC) and chronic Hepatitis B (CHB) groups (p < 0.001). The area under the receiver operating characteristic curve (AUROC) of GH for predicting 30-day mortality was 0.793. We built a new prognostic model, namely MELD-GH, which showed better predictive efficacy than Child-Pugh, MELD, CLIF-SOFA, and CLIF-C ACLF scores.Conclusions: Low GH predicted the poor outcome of HBV-ACLF patients. GH and IGF-1 levels were differently distributed among HC, CHB, LC, LC-AD, and ACLF patients. MELD-GH had better predictive accuracy when compared to Child-Pugh, MELD, CLIF-SOFA, and CLIF-C ACLF scores.

This study investigates the longitudinal dynamic changes in immune cells in COVID-19 patients over an extended period after recovery, as well as the interplay between immune cells and antibodies. Leveraging single-cell mass spectrometry, we selected six COVID-19 patients and four healthy controls, dissecting the evolving landscape within six months post-viral RNA clearance, alongside the levels of anti-spike protein antibodies. The T cell immunophenotype ascertained via single-cell mass spectrometry underwent validation through flow cytometry in 37 samples. Our findings illuminate that CD8 + T cells, gamma-delta (gd) T cells, and NK cells witnessed an increase, in contrast to the reduction observed in monocytes, B cells, and double-negative T (DNT) cells over time. The proportion of monocytes remained significantly elevated in COVID-19 patients compared to controls even after six-month. Subpopulation-wise, an upsurge manifested within various T effector memory subsets, CD45RA + T effector memory, gdT, and NK cells, whereas declines marked the populations of DNT, naive and memory B cells, and classical as well as non-classical monocytes. Noteworthy associations surfaced between DNT, gdT, CD4 + T, NK cells, and the anti-S antibody titer. This study reveals the changes in peripheral blood mononuclear cells of COVID-19 patients within 6 months after viral RNA clearance and sheds light on the interactions between immune cells and antibodies. The findings from this research contribute to a better understanding of immune transformations during the recovery from COVID-19 and offer guidance for protective measures against reinfection in the context of viral variants.