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Background There is growing recognition of natural history, complications, and outcomes of patients who develop non-acetaminophen (APAP) drug-induced acute liver failure (ALF). To clarify high-risk factors and develop a nomogram model to predict transplant-free survival (TFS) in patients with non-APAP drug-induced ALF. Methods Patients with non-APAP drug-induced ALF from 5 participating centers were retrospectively analyzed. The primary endpoint was 21-day TFS. Total sample size was 482 patients. Results Regarding causative agents, the most common implicated drugs were herbal and dietary supplements (HDS) (57.0%). The hepatocellular type (R ≥ 5) was the main liver injury pattern (69.0%). International normalized ratio, hepatic encephalopathy grades, the use of vasopressor, N-acetylcysteine, or artificial liver support system were associated with TFS and incorporated to construct a nomogram model (drug-induced acute liver failure-5, DIALF-5). The AUROC of DIALF-5 for 7-day, 21-day, 60-day, and 90-day TFS in the internal cohort were 0.886, 0.915, 0.920, and 0.912, respectively. Moreover, the AUROC of DIALF-5 for 21-day TFS had the highest AUROC, which was significantly higher than 0.725 of MELD and 0.519 of KCC (p p > 0.05). These results were successfully validated in the external cohort (147 patients). Conclusions Based on easily identifiable clinical data, the novel DIALF-5 model was developed to predict transplant-free survival in non-APAP drug-induced ALF, which was superior to KCC, MELD and had a similar prediction performance to ALFSG-PI but is more convenient, which can directly calculate TFS at multiple time points.

We aimed to develop a prediction model based on the PIRO concept (Predisposition, Injury, Response and Organ failure) for patients with Hepatitis B Virus (HBV) related acute-on-chronic liver failure (ACLF). 774 patients with HBV related ACLF defined in the CANONIC study were analyzed according to PIRO components. Variables associated with mortality were selected into the prediction model. Based on the regression coefficients, a score for each PIRO component was developed, and a classification and regression tree was used to stratify patients into different nodes. The prediction model was then validated using an independent cohort (n = 155). Factors significantly associated with 90-day mortality were: P: age, gender and ACLF type; I: drug, infection, surgery, and variceal bleeding; R: systemic inflammatory response syndrome (SIRS), spontaneous bacteria peritonitis (SBP), and pneumonia; and O: the CLIF consortium organ failure score (CLIF-C OFs). The areas under the receiver operating characteristics curve (95% confidence interval) for the combined PIRO model for 90-day mortality were 0.77 (0.73–0.80). Based on the scores for each of the PIRO components and the cut-offs estimated from the classification and regression tree, patients were stratified into different nodes with different estimated death probability. Based on the PIRO concept, a new prediction model was developed for patients with HBV related ACLF, allowing stratification into different clusters using the different scores obtained in each PIRO component. The proposed model will likely help to stratify patients at different risk, defining individual management plans, assessing criteria for specific therapies, and predicting outcomes.

Organ-specific and systemic autoimmune diseases share numerous features and often coexist in the same patient. Autoimmune cholangitis/primary biliary cirrhosis and Sjogren syndrome represent paradigmatic examples of the common grounds of different autoimmunity phenotypes based on similarities in clinical manifestations and immunopathogenesis. In fact, primary biliary cirrhosis and Sjogren's syndrome have both been coined as an autoimmune epithelitis in which apoptosis may be in both cases the key element to explain the organ-specific immune-mediated injury against the biliary and exocrine gland epithelia, respectively. Further, growing evidence supports in both diseases the view that B cells, T cytotoxic cells, and T helper cells are involved in chronic inflammation, likely via the altered expression of pro-inflammatory cytokines. The presence of estrogen receptors on the biliary and exocrine gland epithelia has been advocated as a key to the female predominance encountered in primary biliary cirrhosis and Sjogren's syndrome. Sadly, despite available data, therapeutic approaches remain largely unsatisfactory and recent studies with mechanistic approaches (as in the case of B cell depletion with rituximab) have been of partial benefit only. Future studies should focus on new molecular tools (single-cell transcriptomics, microRNA, epigenetics) to provide unique insights into common mechanisms.

Rock burst prediction method for coal mining is one of the worldwide challenging problems. Based on a high precision microseismic monitoring system consisting of nine geophones installed in Qixing Coal Mine in China, abundant microseismic events were detected through the continuous monitoring for 80 days. The potential high risk areas of rock burst were determined by analyzing the spatial and temporal distribution characteristics of microseismic events, which provides the basis for the early risk warning during the mining process. After a comprehensive analysis of the spatial and temporal evolution characteristics of the microseismic events, a prediction model for rock burst prediction was built based on the principles of seismology and rock mechanics by setting four indicators as prediction parameters, such as the average number of microseismic events N, the average released energy E, the decrease Δb of the seismological parameter b, and the potential maximum seismic magnitude M m. It was found that all the four prediction indicators are useful for predicting rock burst but they could vary greatly in efficiency in the practical engineering applications.