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.

Liver transplant rejection significantly affects patient prognosis. Myeloid-derived suppressor cells (MDSCs), known for their potent immunoregulatory functions, represent a promising target for managing liver transplant rejection. This study aimed to systematically characterize the diversity of MDSC subsets and their context-dependent functions, particularly within the context of transplant tolerance.

We analyzed clinical and murine liver transplants using single-cell RNA sequencing, bulk RNA sequencing, flow cytometry, multiplex immunohistochemistry, and co-culture assays to phenotype MDSC subsets.

Single-cell RNA sequencing analysis of human and murine samples revealed MDSC involvement in transplant rejection. In mice, MDSC scores followed a normal distribution during the first week post-transplant and correlated with clinical flow cytometry data at one month. A distinct LDLR+ monocytic MDSC (M-MDSC) subset was identified and confirmed through spatial mapping by multiplex immunohistochemistry. Flow cytometry demonstrated dynamic changes in LDLR+ M-MDSCs across tissues (liver, spleen, peripheral blood, bone marrow, and lymph nodes), with a peak during acute rejection. Co-culture experiments showed that LDLR−/− M-MDSCs exhibited reduced Arg-1/iNOS expression and an impaired capacity to induce inhibitory receptors (TIGIT, PD1, CTLA-4) or suppress effector molecules (GZMB, IFN-γ, IL-2) in CD8+ T cells.

These findings highlight the critical role of MDSCs in liver transplant rejection. LDLR+ M-MDSCs exhibited enhanced immunosuppressive properties, underscoring their potential clinical relevance in mitigating rejection and promoting immune tolerance.

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.

The huge burden of type 1 diabetes mellitus (T1DM) has been a source of concern globally since the Industrial Revolution in the 18th–19th centuries. To this end, studies have shown that certain environmental changes that accompanied the Revolution may have increased the risk and burden of the disease in genetically predisposed individuals. However, documented studies that synthesize these environmental triggers are scarce. As a result, the current study was conceived to synthesize the environmental triggers of T1DM to boost public awareness. Relevant information was retrieved from reputable academic databases; namely, Scopus, PubMed, SpringerLink, and Embase. The results showed that chemical exposure, viral infection, gut microbiome disruption, vitamin and mineral deficiencies, inadequate or exclusive breastfeeding, as well as early exposure to infant feeding formulas could increase the risk and burden of T1DM in genetically predisposed individuals. As a consequence, these triggers could compromise the expression of certain genes involved in insulin synthesis and immune function, such as the human leukocyte antigen (HLA), insulin (INS), cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), and protein tyrosine phosphatase non-receptor type 22 (PTPN22) genes. This would result in a dysfunctional immune system in which immune cells, such as T-cells and B-cells and molecules, such as cytokines would attack self-tissues, thus causing autoimmunity of the pancreatic beta cells. Environmental triggers could also induce the T1DM pathophysiology by modifying the epigenome of the mentioned genes. Furthermore, some epigenetic changes could be reversed, which would infer that treatment procedures that would include the pathophysiology of the environmental triggers could be more effective.

Emerging evidence suggests that RNA-binding motif (RBM) proteins are involved in hepatocarcinogenesis and act either as oncogenes or tumor suppressors. The objective of this study was to investigate the role of RBM34, an RBM protein, in hepatocellular carcinoma (HCC).

We first examined the expression of RBM34 across cancers. The correlation of RBM34 with clinicopathological features and the prognostic value of RBM34 for HCC was then investigated. Functional enrichment analysis of RBM34-related differentially expressed genes (DEGs) was performed to explore its biological function. RNA sequencing (RNA-seq) was applied to identify downstream genes and pathways affected upon RBM34 knockout. The correlation of RBM34 with immune characteristics was also analyzed. The oncogenic function of RBM34 was examined in in vitro and in vivo experiments.

RBM34 was highly expressed in hepatocellular carcinoma and correlated with poor clinicopathological features and prognosis. RBM34 was positively associated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression. A positive correlation was also observed between RBM34, T cell exhaustion, and regulatory T cell marker genes. Knockout of RBM34 significantly inhibited cell proliferation, migration, and xenograft tumor growth, and sensitized HCC cells to sorafenib treatment. RBM34 inhibition reduced FGFR2 expression and affected PI3K-AKT pathway activation in HCC cells.

Our study suggests that RBM34 may serve as a new prognostic marker and therapeutic target of HCC.

Naringenin is an anti-inflammatory flavonoid that has been studied in chronic liver disease. The mechanism specific to its antifibrosis activity needs further investigation This study was to focused on the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS) pathway in hepatic stellate cells and clarified the antifibrosis mechanism of naringenin.

The relationship between the cGAS-stimulator of interferon genes (STING) pathway and liver fibrosis was analyzed using the Gene Expression Omnibus database. Histopathology, immunohistochemistry, fluorescence staining, Western blotting and polymerase chain reaction were performed to assess gene and protein expression levels associated with the cGAS pathway in clinical liver tissue samples and mouse livers. Molecular docking was performed to evaluate the relationship between naringenin and cGAS, and western blotting was performed to study the expression of inflammatory factors downstream of cGAS in vitro.

Clinical database analyses showed that the cGAS-STING pathway is involved in the occurrence of chronic liver disease. Naringenin ameliorated liver injury and liver fibrosis, decreased collagen deposition and cGAS expression, and inhibited inflammation in carbon tetrachloride (CCl4)-treated mice. Molecular docking found that cGAS may be a direct target of naringenin. Consistent with the in vivo results, we verified the inhibitory effect of naringenin on activated hepatic stellate cells (HSCs). By using the cGAS-specific agonist double-stranded (ds)DNA, we showed that naringenin attenuated the activation of cGAS and its inflammatory factors affected by dsDNA. We verified that naringenin inhibited the cGAS-STING pathway, thereby reducing the secretion of inflammatory factors by HSCs to ameliorate liver fibrosis.

Interrupting the cGAS-STING pathway helped reverse the fibrosis process. Naringenin has potential as an antihepatic fibrosis drug.