Acute liver failure (ALF) is a severe hepatic injury associated with high short-term mortality. Our previous study found that 1,5-anhydroglucitol (1,5AG) levels correlate with clinical outcomes in patients with liver failure. This study aimed to explore the potential effects and mechanisms of 1,5AG in ALF.

An experimental model of ALF was established using LPS and D-GalN. 1,5AG was administered to mice by gavage before modeling. Empagliflozin was then administered to reduce 1,5AG levels in mice. Peroxisome proliferator-activated receptor alpha (PPARα) agonists were also used to explore the role of 1,5AG in mice with liver failure.

1,5AG pretreatment significantly increased ALT and AST levels, aggravated histological damage and hepatocyte apoptosis, and increased mortality in ALF mice. Transcriptomic analysis and western blot validation revealed that 1,5AG significantly inhibited the PPARα signaling pathway and its downstream target, fibroblast growth factor 21. Empagliflozin treatment reduced 1,5AG levels, alleviated liver injury and hepatocyte apoptosis, and promoted the PPARα signaling pathway in ALF. PPARα agonists effectively reversed the effects of 1,5AG on ALF, thereby alleviating liver damage, pathological injury, and hepatocyte apoptosis.

1,5AG exacerbated liver injury in ALF mice by inhibiting the hepatic PPARα pathway, thereby promoting hepatocyte apoptosis.

The optimal management strategy for adults with immune-tolerant (IT) chronic hepatitis B infection remains undefined. This study aimed to investigate the efficacy and predictive factors of a pegylated interferon (Peg-IFN)-based treatment strategy in IT patients with chronic HBV infection.

In this pilot, open-label, prospective study, 286 patients aged 18 to 60 years with IT characteristics were enrolled and allocated to one of three groups. The combination group received Peg-IFN for 48–96 weeks, with tenofovir disoproxil fumarate (TDF) initiated at week 12 and continued through week 96 (n = 103). The monotherapy group received TDF monotherapy alone (n = 125), and the control group was monitored without therapeutic intervention (n = 58).

No patients in the control group met any predefined efficacy endpoints. Intention-to-treat analysis showed that patients in the combination group achieved significantly higher virological response rates (71.8% vs. 53.6%, p = 0.005), hepatitis B e antigen seroconversion rates (15.5% vs. 1.6%, p < 0.001), and hepatitis B surface antigen (HBsAg) loss rates (10.7% vs. 0%, p < 0.001) compared with those in the monotherapy group at week 96. In the combination group, the cumulative rate of HBsAg loss was 5.4% at week 48 and increased to 11.8% by week 96. Independent predictors of achieving either hepatitis B e antigen seroconversion or HBsAg loss were baseline age under 30 years (odds ratio = 0.217, 95% confidence interval: 0.048–0.976, p = 0.046) and a decline in HBsAg level greater than 1 log10 IU/mL by week 24 (odds ratio = 13.976, 95% confidence interval: 2.506–77.932, p = 0.003).

A Peg-IFN-based treatment strategy significantly increases response rates compared with TDF monotherapy or observation in patients with IT characteristics.

Extrahepatic cancers have been recognized as a significant outcome of metabolic dysfunction–associated steatotic liver disease (MASLD), which involves five cardiometabolic risk factors, including hypertension, and is associated with the tumorigenesis of several cancers or with anti-cancer treatment. We aimed to investigate the association between hypertension, liver fibrosis, and extrahepatic cancers in the MASLD population.

This multicenter cross-sectional study was based on a MASLD population from hospital-based databases across 11 centers nationwide in China, according to MASLD diagnostic criteria identified using keywords and ICD-10 codes. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between risk factors and extrahepatic cancers.

A total of 103,652 individuals with MASLD were identified, among whom 6,605 were diagnosed with extrahepatic cancers. The primary outcome revealed that hypertension was significantly associated with extrahepatic cancers (OR 1.14, 95% CI: 1.08–1.21), and its combination with hyperglycemia further increased this association (OR 1.36, 95% CI: 1.22–1.51). Risk factors for extrahepatic cancers included being over 40 years of age and female sex. Conversely, certain metabolism-based treatments were found to have potentially protective effects, including angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, fibrates, GLP-1 receptor agonists, and thiazolidinediones. After adjusting for confounding factors, the fibrosis-4 (FIB-4) score was associated with extrahepatic cancers. In the hypertension subgroup, FIB-4 scores of 1.30–2.66, 2.67–3.47, and ≥ 3.48 were associated with extrahepatic cancers in individuals aged 35–64 years, consistent with findings in those aged ≥ 65 years of age with FIB-4 ≥ 2.

Hypertension combined with liver fibrosis is associated with extrahepatic cancers in patients with MASLD.

N6-methyladenosine (m6A), the most prevalent internal RNA modification in eukaryotic cells, is a dynamic regulator of RNA metabolism and cancer biology. In colorectal cancer (CRC), dysregulated m6A reshapes transcriptomic programs that control tumor growth, metastasis, immune evasion, and therapeutic resistance. However, the context-dependent functions of individual m6A regulators remain incompletely defined, the integration of m6A with canonical oncogenic signaling remains incomplete, and its role in metabolic reprogramming lacks a systematic overview. This review aims to integrate current evidence on m6A regulatory machinery in CRC, clarify its coordination with oncogenic signaling and metabolic pathways, and highlight emerging translational implications. The key players regulating m6A in CRC progression are m6A “writers”, including methyltransferase-like 3 and methyltransferase-like 14; m6A “erasers”, including fat mass and obesity-associated protein and AlkB homolog 5; and m6A “readers”, including the YTH m6A RNA-binding protein family and the insulin-like growth factor 2 mRNA-binding protein family. m6A modification coordinates key oncogenic pathways, including Wnt/β-catenin, PI3K/Akt, MAPK, and p53 signaling. Moreover, m6A-dependent regulation of metabolic enzymes such as hexokinase 2, pyruvate kinase M2, and fatty acid synthase promotes the reprogramming of glucose, amino acid, and lipid metabolism, linking epitranscriptomic control to bioenergetic adaptation. We also discuss context-dependent and paradoxical functions of m6A regulators and advances in m6A-targeted therapies. In conclusion, m6A modification functions as a central regulatory hub in CRC by integrating signaling networks and metabolic pathways. Deeper mechanistic insights into spatiotemporal m6A regulation may accelerate the development of biomarkers and targeted therapies for precision CRC management.

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.

Hepatic ischemia–reperfusion (HIR) injury impairs outcomes post–liver transplantation. Therefore, we aimed to investigate the role and mechanism of miR-381-3p in HIR.

The study enrolled 150 healthy controls, 82 non-HIR-injured patients, and 68 patients with HIR injury following liver transplantation. Clinical data were analyzed. Multivariate analysis identified HIR risk factors; the predictive value of miR-381-3p was assessed via receiver operating characteristic analysis. An in vitro hypoxia/reoxygenation (H/R) model was established and employed. The cellular effects of miR-381-3p and JAK2 were evaluated using CCK-8, flow cytometry, ELISA, luciferase, RIP, and bioinformatics.

Serum miR-381-3p was significantly elevated in HIR compared with the other groups. miR-381-3p was the strongest independent HIR risk factor, which was confirmed by receiver operating characteristic analysis. H/R upregulated miR-381-3p. Inhibiting miR-381-3p counteracted H/R-induced decreased viability and increased apoptosis, inflammation, and oxidative stress. miR-381-3p directly bound to and suppressed JAK2 via its 3′ untranslated region (validated by luciferase and RIP). Transfection of si-JAK2 abolished the protective effects of miR-381-3p inhibition.

miR-381-3p exacerbates post-transplant HIR by directly targeting JAK2, amplifying inflammation and oxidative stress. Thus, our findings nominate serum miR-381-3p as a promising non-invasive biomarker and suggest its potential as a therapeutic target for mitigating HIR injury.

Predicting the malignant transformation of rectal precancerous lesions remains challenging because conventional Whole Slide Images (WSIs) capture morphological information but lack molecular insight. Multiomics data provide complementary biological signals that often precede visible morphological changes. This study aimed to develop an artificial intelligence (AI)-based multimodal framework integrating WSI and multiomics data for accurate early prediction of malignant transformation.

WSI patches (512×512 px at 20× magnification) and matched multiomics profiles were used for 450 rectal tissue samples from the publicly available The Cancer Genome Atlas dataset. A multimodal architecture was designed, employing a Vision Transformer (ViT-B/16) for WSI feature extraction and a Variational Autoencoder for multiomics representation learning. Features were fused via a cross-attention mechanism to capture inter-modality dependencies. Baseline models, including a convolutional neural network-only image model and an omics-only multilayer perceptron, were trained for comparison. Five-fold cross-validation was applied, with binary cross-entropy loss, the AdamW optimizer, early stopping, and hyperparameter tuning to ensure reproducibility.

The multimodal Vision Transformer–Variational Autoencoder fusion model outperformed unimodal baselines, achieving an accuracy of 0.892 ± 0.012 and an area under the receiver operating characteristic curve of 0.927 ± 0.009, corresponding to a 7–10% improvement over WSI-only and omics-only models. Cross-attention–based fusion improved prediction stability and classification performance, while interpretability analyses (Grad-CAM and SHAP) highlighted biologically meaningful histopathological regions and molecular feature contributions.

This study presents a robust and scalable AI-based framework for integrating WSI and multiomics data in rectal precancerous lesions. The model improves predictive precision compared with unimodal baselines and offers preliminary interpretability insights through attention mechanisms. These findings support the potential of multimodal AI for early cancer risk assessment and precision pathology.