Chronic hepatitis B (CHB) remains a major global public health challenge. Current therapies based on nucleos(t)ide analogues and interferon mainly achieve long-term viral suppression, whereas only a small proportion of patients attain a functional cure, defined as sustained hepatitis B surface antigen loss with hepatitis B virus (HBV) DNA below the limit of quantification for at least 24 weeks after treatment discontinuation, with or without anti-HBs seroconversion. Emerging evidence from the gut–liver axis indicates that gut microbiota–derived metabolites, particularly short-chain fatty acids (SCFAs) and bile acids (BAs), modulate the HBV life cycle and immune regulation in CHB, thereby offering therapeutic targets to overcome immune tolerance. This review summarizes the biological characteristics of SCFAs and BAs and their mechanistic roles across different stages of HBV infection, with emphasis on translational relevance. In vitro and animal studies suggest that butyrate and related SCFAs suppress HBV gene expression by inhibiting histone deacetylases and remodeling covalently closed circular DNA minichromatin. SCFAs may also enhance antiviral immunity, although they may reinforce immune tolerance in certain contexts. For BAs, the farnesoid X receptor, Takeda G protein–coupled receptor 5, and the HBV entry receptor sodium taurocholate cotransporting polypeptide form a key signaling hub with dual effects on viral replication and host responses. Early-phase studies suggest that farnesoid X receptor agonists, pegylated interferon-α, or nucleos(t)ide analogues are associated with hepatitis B surface antigen reductions, though larger trials are needed. This review proposes biomarker-guided stratification and multi-target combination strategies to improve functional cure rates in CHB.

Vulvovaginal candidiasis, an infection caused by an abnormal proliferation of Candida species in the vagina and vulva, is particularly relevant, affecting up to 75% of women of reproductive age. Because of antifungal drug resistance, a significant number of plants are used to treat vaginal candidoses in Cameroon. Thus, the scientific validation of the use of these plants in treating candidiasis is valuable. This study sought to identify medicinal plants used to treat vaginal infections in the Dschang district and evaluate the antifungal activity of the most promising plants on five Candida species.

The ethnobotanical survey was conducted in Dschang (Menoua Division, West Cameroon) through individual interviews using a semi-structured questionnaire. Extracts from seventeen plants were obtained by maceration using water or a water–ethanol solution (3:7; v/v). Antifungal activity was evaluated using the microdilution method.

Forty-eight plants belonging to 33 families were identified as treating vaginal infections. Decoction and formulation of ovules were the prevalent modes of plant preparation, with leaves and bark being the predominant plant organs used. Out of thirty-four extracts tested, two (CSEHAlc and MIEHAlc) showed antifungal activity, with minimum inhibitory concentrations ranging from 0.315 to 2.5 mg/mL. The determination of the minimum fungicidal concentrations revealed the fungicidal orientation of these bioactive extracts.

This study identifies medicinal plants used to treat vaginal infections in Dschang and their modes of preparation. The in vitro antifungal screening of selected plants indicated Mangifera indica and Canarium schweinfurthii as the anti-Candida plants that can be further exploited for antifungal drug discovery.

Normalization can standardize and improve machine learning (ML) performance on omics data. However, it is unclear whether normalization is associated with overfitting (i.e., worse cross-dataset performance than intra-dataset performance). Therefore, we aimed to examine associations of normalization and regularization with overfitting of ML on omics data.

Using three paired transcriptomic and clinical datasets (lung adenocarcinoma: the Cancer Genome Atlas (TCGA)/Oncology Singapore; melanoma: TCGA/Dana-Farber Cancer Institute; glioblastoma: TCGA/Clinical Proteomic Tumor Analysis Consortium), we applied ANOVA-based gene selection methods, six normalization methods, and six ML models to classify cancer patients’ deaths. Balanced accuracy (BA) and area under the curve (AUC) in intra- and cross-dataset settings were compared using inferential analyses.

Normalization consistently improved intra-dataset performance (median BA/AUC changes: 0.035–0.214/0.115–0.279) on all data, particularly with Z_Raw, but decreased or slightly increased cross-dataset performance (median BA/AUC changes: −0.029–0.079/0.029–0.064). Least Absolute Shrinkage and Selection Operator (LASSO) model without normalization consistently outperformed most of the ML models in cross-dataset testing across cancer types. ML models on all and molecular-alone data showed similar best performances.

Normalization increases ML’s intra-dataset performance and overfitting in three paired cancer transcriptomic and clinical datasets. Regularized models such as LASSO appear to mitigate overfitting and achieve robust cross-dataset performance. Therefore, cross-dataset evaluation and regularized models are recommended to assess and reduce overfitting, while normalization should be used cautiously. Adding clinical data seems to have little impact on ML models’ performance. However, future work on other diseases and datasets is warranted.

Acute-on-chronic liver failure (ACLF) lacks a universally accepted definition, and recent efforts have proposed consensus organ failure criteria. In this study, we aimed to compare the clinical validity of a recently proposed consensus ACLF framework with the outcome-calibrated A-TANGO classification.

We performed a multinational cohort study including 2,398 patients from the TIH cohort (India) and 2,568 from the CATCH-LIFE cohort (China) who were hospitalized with acute decompensation of cirrhosis. ACLF was defined using A-TANGO and an operationalized version of the 2025 consensus framework. Outcomes were 28- and 90-day mortality. Analyses assessed case capture, overlap, mortality risk, sensitivity, specificity, and net reclassification improvement (NRI).

ACLF prevalence differed substantially by definition. In TIH, A-TANGO classified 79.2% as ACLF versus 42.3% by the consensus definition; in CATCH-LIFE, the corresponding values were 31.4% versus 5.8%, respectively. Most consensus ACLF cases were captured by A-TANGO, which additionally classified 26%–37% of patients as having ACLF. These patients had substantial mortality (28-day: 18.1%–26.9%; 90-day: 33.2%–37.9%), significantly higher than those negative by both frameworks and comparable to established ACLF risk thresholds. A-TANGO showed higher sensitivity for 28-day mortality (TIH: 94.1% vs. 67.8%; CATCH-LIFE: 76.1% vs. 25.6%), whereas consensus criteria were more specific. Reclassification analyses showed improved discrimination with A-TANGO (NRI: 17.1% in TIH; 27.4% in CATCH-LIFE). Within the consensus non-ACLF group, A-TANGO further stratified patients into distinct risk groups with stepwise increase in mortality.

In conclusion, the two frameworks identify fundamentally different populations. The consensus definition significantly reduces sensitivity and under-recognizes high-risk patients. Compared with consensus definitions, the outcome-calibrated framework better supports diagnosis, clinical decision-making, risk stratification, and trial design in ACLF.

Alpha-1 antitrypsin deficiency (AATD) is an autosomal codominant genetic disorder caused by mutations in the SERPINA1 gene. It results in reduced circulating levels of alpha-1 antitrypsin (AAT), a serine proteinase inhibitor (PI) primarily produced by hepatocytes. The most common deficient alleles are PI*S and PI*Z, with PI*ZZ homozygotes having the most severe deficiency and highest risk for lung and liver disease. While AATD is well established as a cause of early-onset emphysema and liver cirrhosis, emerging evidence suggests a potential association with the formation of arterial aneurysms. The pathophysiological rationale for this association centers on protease-antiprotease imbalance and potential extracellular matrix degradation of elastin in arterial vessel walls. Several studies have reported increased frequencies of AATD alleles in patients with abdominal aortic aneurysms and intracranial aneurysms compared to the general population, with some demonstrating statistically significant associations. Additionally, patients with the PI*ZZ genotype have been shown to have larger aortic diameters, greater aortic stiffness, and reduced distensibility compared to controls. However, the evidence is inconsistent, as several large studies have failed to demonstrate significant associations between AATD and aneurysm formation. Overall, current evidence suggests an association of AATD with the development of arterial aneurysms. However, it is also clear that the presence of AATD alone is not sufficient to increase the risk of developing new-onset arterial aneurysms.

Immunothrombosis, the interplay between immune activation and coagulation, contributes to disease progression in inflammatory disorders. Its role in hepatitis B virus–related acute-on-chronic liver failure (HBV-ACLF) and the involvement of neutrophil extracellular traps (NETs) remain unclear. This study aimed to elucidate NETs-mediated immunothrombosis in HBV-ACLF.

Liver single-cell RNA sequencing data from HBV-ACLF patients and healthy controls were analyzed to define immune and endothelial transcriptional profiles. A cohort of 46 HBV-ACLF patients, 20 chronic hepatitis B patients, and 20 healthy controls was assessed for circulating NETs, endothelial injury markers, and coagulation parameters. Histopathology and in vitro assays examined NETs distribution and endothelial interactions.

NETs were markedly elevated in HBV-ACLF and correlated with endothelial injury markers (syndecan-1, von Willebrand factor, soluble thrombomodulin), coagulopathy, and prognostic scores. Histology revealed NETs colocalization with endothelial cells and platelets within hepatic microthrombi. NETs from patient neutrophils impaired endothelial integrity and enhanced procoagulant activity in vitro. Mechanistically, toll-like receptor 2 (TLR2) and complement component 5a receptor 1 (C5aR1) signaling were involved in NETs formation, and their pharmacological inhibition reduced NETs generation.

NETs are associated with endothelial injury and immunothrombosis in HBV-ACLF. Mechanistic analyses suggest a role for TLR2 and C5aR1 pathways in NETs formation, indicating potential targets for future therapeutic investigation.

Synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies, and multiple system atrophy (MSA), are a group of neurodegenerative diseases characterized by the oligomerization of α-synuclein protein in neurons or glial cells. Various splicing isoforms of α-synuclein have been described, each with different aggregation properties. The α-synuclein gene (SNCA) has been identified as a highly significant genetic risk locus associated with various synucleinopathies across populations. This study aimed to assess the association of SNCA genetic variants with MSA and the levels of SNCA transcripts in peripheral blood mononuclear cells (PBMCs) from MSA and PD patients.

In this retrospective case–control study, 96 MSA patients, 1086 PD patients, and 485 healthy volunteers were included. PCR followed by restriction endonuclease analysis was used to detect four SNCA single-nucleotide polymorphisms (rs356219, rs3756063, rs11931074, and rs356168) in these individuals. In addition, RT-qPCR was performed to detect the levels of α-synuclein transcripts (SNCA mRNA isoforms -140, -126, and -112) in PBMCs of 24 MSA patients (including parkinsonian (MSA-P) and cerebellar (MSA-C) variants), 31 PD patients, and 32 healthy volunteers.

The frequency of the ‘T’ allele (of rs11931074) was significantly higher in MSA patients than in the healthy controls. The level of SNCA-140 mRNA was significantly decreased in MSA and PD patients compared with the controls, while the level of SNCA-112 mRNA was significantly increased in MSA-P patients than in PD patients and the controls. SNCA-112 mRNA/SNCA-140 mRNA and SNCA-112 mRNA/SNCA-126 mRNA ratios were significantly increased in MSA patients than in the controls.

The SNCA rs11931074 polymorphism is associated with MSA. There is a pronounced alteration in the expression of SNCA transcripts in PBMCs of MSA and PD patients.

Amatoxin-containing mushroom poisoning causes fatal acute liver failure with >50% mortality despite maximal medical therapy. Interrupting the enterohepatic recirculation of amatoxins is a mechanistically rational but unproven therapeutic strategy. This study aimed to evaluate the efficacy and safety of biliary drainage (BD) in patients with pre-acute liver failure caused by amatoxin-containing mushroom poisoning.

In this prospective cohort study (ChiCTR2300073442), consecutive adults with amatoxin-induced pre-acute liver failure received standardized care (silibinin, N-acetylcysteine, dehydration). Patients undergoing percutaneous or endoscopic BD were compared to non-BD controls. The primary outcome was survival to hospital discharge.

Nine patients were enrolled (mean age: 63.3 ± 15.6 years; 44.4% female). All five patients who underwent BD (performed at a median of three days after ingestion) survived (100%), whereas only one of the four non-BD patients survived (25%; P = 0.048). BD initiated a rapid biochemical recovery: within 48 h, mean alanine and aspartate transaminase levels decreased by 67.6% and 91.6%, respectively, from their peak levels (P < 0.001), and the international normalized ratio decreased from 1.99 to 1.27 (P = 0.008). Non-survivors in the non-BD group progressed to multiorgan failure. Procedure-related complications (transient pancreatitis/amylasemia) occurred in three of the five BD patients but resolved with conservative management.

Timely BD was associated with 100% survival after amatoxin-induced pre-acute liver failure, contrasting sharply with 75% mortality in non-BD controls. The dramatic biochemical improvement after BD supports enterohepatic recirculation interruption as a mechanistic intervention. BD represents a potentially definitive, life-saving intervention for this lethal poisoning as a preliminary finding; larger, multicenter studies are required to confirm the observed association between BD and survival.

Hepatocellular carcinoma (HCC) remains one of the most fatal cancers, primarily due to late diagnosis and the lack of effective early biomarkers. Recent advances in multi-omics and liquid biopsy technologies hold promise for improving early detection, prognostication, and monitoring of HCC. Understanding the immune landscape of HCC through genetic and epigenetic signatures is essential for identifying therapeutic targets and improving immunotherapy outcomes. This review aims to present current findings on immune-related biomarkers, multi-omics strategies, and biomarker validation in HCC. It also aims to evaluate the role of liquid biopsy and gene signatures in predicting treatment responses, with a specific focus on their applications in immunotherapy. The goal is to provide a comprehensive framework for integrating these emerging tools into clinical practice. The integration of multi-omics approaches has led to the identification of robust gene signatures that predict HCC prognosis and response to immune checkpoint inhibitors. Liquid biopsy technologies, including circulating tumor DNA, provide non-invasive alternatives for monitoring tumor evolution and therapeutic responses. Despite promising results, challenges remain in clinical validation, particularly in cross-platform reproducibility and the interpretation of complex multi-omics data. While genetic biomarkers are rapidly advancing, their clinical application in personalized medicine remains hindered by technical and ethical challenges, such as data privacy, informed consent, and method standardization. The integration of multi-omics data and liquid biopsies offers a promising path toward real-time, personalized treatment and the development of universal prognostic signatures for HCC. However, successful clinical adoption depends on cross-disciplinary collaboration to standardize data protocols and overcome challenges regarding accuracy, reproducibility, and patient privacy.