Liver fibrosis is a pivotal and reversible stage in the progression of chronic liver disease. However, the mechanisms underlying fibrosis reversal remain unclear, and effective diagnostic biomarkers are lacking in clinical practice. In this study, we aimed to elucidate the role and molecular mechanisms of glutathione S-transferase Mu 3 (GSTM3) in liver fibrosis reversal, and preliminarily determine whether GSTM3 can serve as a novel biomarker for liver fibrosis reversal.

Carbon tetrachloride-induced mouse models of liver fibrosis and spontaneous reversal were established. Proteomic analysis was used to identify proteins shared between liver tissue and serum that were continuously downregulated during fibrosis reversal. The expression of GSTM3 was evaluated in the livers of mice undergoing fibrosis reversal and in clinical samples from patients with liver fibrosis. Hepatic stellate cells (HSCs) were transfected with Gstm3-silencing RNA or an overexpression plasmid to assess the effects on fibrosis markers. RNA sequencing analyses were performed, and the underlying molecular mechanisms were investigated.

Proteomic analysis revealed significantly decreased GSTM3 levels in both hepatic tissue and serum in mice undergoing fibrosis reversal, and its expression was negatively correlated with the extent of reversal. GSTM3 levels were markedly increased in the hepatic tissue and serum of patients with liver fibrosis. GSTM3 expression was upregulated in transforming growth factor-β-stimulated HSCs. GSTM3 knockdown inhibited the expression of fibrosis markers, such as collagen type I α1 and tissue inhibitor of metalloproteinase 1, whereas its overexpression promoted their expression. Mechanistic studies indicated that GSTM3 knockdown activated peroxisome proliferator-activated receptor γ (PPARγ) signaling and downregulated its downstream targets, cluster of differentiation 36 and fatty acid-binding protein 4, thereby suppressing HSC activation.

GSTM3 knockdown promotes liver fibrosis reversal via PPARγ signaling-mediated inhibition of HSC activation. Therefore, GSTM3 is a promising therapeutic target and diagnostic biomarker for liver fibrosis.

Irinotecan is a camptothecin derivative that exerts its antitumor effects by metabolizing into the active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38). It is widely used clinically for treating various advanced solid tumors. However, irinotecan frequently induces neutropenia, predisposing patients to infection and even death. This review aims to provide a theoretical basis for the clinical management of irinotecan-induced neutropenia (IIN). Irinotecan and SN-38 mainly induce hematopoietic stem cell damage and dysfunction by inhibiting topoisomerase I and triggering mitochondrial injury, which ultimately results in neutropenia. Notably, the risk factors of IIN include irinotecan dosage, gene polymorphism, individual baseline characteristics, and drug combination. And several strategies effectively prevent IIN, such as adjustment of drug dosage, genotype testing, oral alkalinizing drugs, supplement of granulocyte colony-stimulating factor, and regulation of intestinal microorganisms. In summary, this review systematically elaborates on the classification, epidemiology, pathogenesis, risk factors, and management strategies of IIN, with the goal of providing references for the clinical prevention and management of irinotecan-related adverse reactions.

Artificial intelligence (AI) is increasingly reshaping diagnostic pathology, with breast pathology representing one of the most advanced and clinically impactful areas of adoption. Despite rapid progress, many practicing pathologists remain unfamiliar with core AI concepts and their practical implications. This review provides a concise and accessible overview of AI in breast pathology, focusing on foundational principles, current clinical applications, and future directions.

Pertinent literature was reviewed. Personal experiences were also summarized and incorporated.

Key AI concepts, including algorithms, models, architectures, machine learning, deep learning, neural networks, and multimodal and foundational models, are introduced to establish a common framework. Important distinctions among generative, black-box, and explainable AI are highlighted, emphasizing the need for transparency and interpretability in clinical settings. The evolution of AI in breast pathology is reviewed, from early rule-based computer-assisted diagnostic systems to modern deep learning approaches leveraging large-scale whole-slide imaging datasets. Current applications span multiple domains, including detection of lymph node metastases, Nottingham grading, classification of benign and malignant lesions, and automated quantification of critical biomarkers. AI-based approaches to prognosis, risk stratification, prediction of treatment response, and analysis of the tumor microenvironment are also discussed. Finally, the review addresses challenges associated with real-world implementation, including data quality, bias, regulatory considerations, cost, infrastructure, and workflow integration.

As AI continues to evolve toward large-scale, multimodal, and explainable models, it is expected to function as an augmentative tool rather than a replacement for pathologists, supporting diagnostic accuracy, standardization, and personalized management in breast cancer care.

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.