Hepatic stellate cell (HSC) activation has traditionally been described as a binary transition from vitamin A-rich quiescent cells to alpha-smooth muscle actin-positive, collagen-producing myofibroblast-like cells. Advances in single-cell RNA sequencing, single-nucleus RNA sequencing, spatial transcriptomics, and chromatin-accessibility profiling now reveal a more complex and dynamic landscape. During chronic liver injury, HSCs can adopt five overlapping activation-associated states characterized by injury sensing, inflammatory signaling, proliferation, extracellular matrix production and contractility, together with a senescent state that represents a possible fate of activated HSCs. These states differ in their molecular markers, spatial distribution, regulatory pathways, and interactions with hepatocytes, liver sinusoidal endothelial cells, macrophages, natural killer cells, and cholangiocytes. Importantly, they are not fixed lineages and may coexist or interconvert during fibrosis progression and regression. This review revisits the classical quiescent-activated framework and proposes a state-based approach for interpreting HSC heterogeneity. We summarize the defining features and translational relevance of six major HSC functional states, discuss their multicellular niches, and highlight the opportunities and limitations of function-selective therapeutic targeting. A reproducible classification that integrates molecular identity, spatial context, and causal function may help refine antifibrotic treatment strategies.

Rising resistance in Helicobacter pylori to metronidazole, clarithromycin, and fluoroquinolones has significantly reduced eradication efficacy. This narrative review explores evidence-based strategies that minimize the impact of antibiotic resistance. Current practical approaches include empirical therapy (EMT), in which regimens are selected without individual susceptibility testing based on local or regional resistance patterns, previous antibiotic exposure, guideline recommendations, and expected effectiveness, and susceptibility-guided therapy (SGT), which avoids antibiotics to which the infecting strain is resistant. EMT does not simply exclude every antibiotic with a high resistance prevalence because regimen-level efficacy may remain high despite resistance to one component. When susceptibility testing is unavailable, optimized 14-day bismuth quadruple therapy is a guideline-preferred empirical regimen and can remain effective despite metronidazole resistance with adequate dosing and treatment duration. Rifabutin-based triple therapy provides an additional empirical or rescue option for selected patients without penicillin allergy. SGT is not universally superior to well-selected EMT, but may improve eradication rates in selected populations, particularly in settings with high clarithromycin resistance or where rapid molecular testing is available. However, susceptibility testing may be time-consuming, costly, and limited to only a few antibiotics. Emerging approaches include potassium-competitive acid blockers (PCABs), antimicrobial stewardship, probiotics, N-acetylcysteine, nanomaterial-based drug delivery, and vaccination. Among these, vonoprazan-based regimens are the most clinically mature. Vonoprazan-amoxicillin dual therapy can reduce exposure to resistance-prone antibiotics, although its use should reflect regional effectiveness, availability, and cost. Other non-antibiotic approaches remain investigational. In conclusion, management should move from undifferentiated empirical regimen selection toward risk-stratified precision treatment. Locally validated EMT remains appropriate when susceptibility testing is unavailable, whereas SGT should be prioritized after treatment failure or in patients at high risk of resistance. Rifabutin-based and vonoprazan-amoxicillin therapies provide additional options according to treatment history, penicillin allergy, regional evidence, and accessibility.

Artificial intelligence (AI)-based computer-aided detection (CADe) has been associated with improved adenoma detection during colonoscopy. However, prior meta-analyses synthesized earlier trials, and whether the benefit remains consistent in recent contemporary trials is uncertain. This meta-analysis aimed to estimate the effects of current-generation AI-assisted colonoscopy on adenoma detection rate (ADR) as the primary outcome and polyp detection rate (PDR) as the secondary outcome in randomized and quasi-randomized trials published from August 1, 2024, to August 18, 2026, without re-pooling trials included in earlier comprehensive meta-analyses.

MEDLINE/PubMed, Embase, CENTRAL, Scopus, and Google Scholar were searched for peer-reviewed parallel-group randomized and quasi-randomized trials enrolling adults undergoing screening, surveillance, or diagnostic colonoscopy and comparing real-time AI-based CADe-assisted with conventional high-definition white-light colonoscopy. Tandem designs were excluded. The primary and secondary outcomes were ADR and PDR, respectively. Random-effects risk ratios with 95% confidence intervals (CIs) were calculated; heterogeneity and leave-one-out sensitivity were assessed.

Seventeen trials comprising 15,242 patients were included for ADR; 12 trials comprising 8,665 patients reported extractable PDR data. The pooled risk ratio was 1.14 (95% CI 1.09–1.20; I² = 53.8%) for ADR and 1.13 (95% CI 1.07–1.20; I² = 63.4%) for PDR.

This meta-analysis supports an average improvement in adenoma and polyp detection with AI-assisted colonoscopy; however, moderate-to-substantial heterogeneity and variability across settings and platforms warrant cautious interpretation rather than an unqualified recommendation for routine adoption.

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.