Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

Background/Aims: Cholangiocarcinoma (CCA) is a primary malignant neoplasm with an extremely poor prognosis. While combined chemoradiotherapy has been demonstrated to delay CCA progression to a certain extent, the absence of specific molecular biomarkers or targets significantly hinders the diagnosis and treatment of CCA. Methods: Through cross-analysis of proteomics and ADMA modificationomics, we identified DDX1 overexpressed in CCA with elevated R602-ADMA modifications. HPLC-MS/MS identified PRMT1 as the methyltransferase and USP10 as the deubiquitinating enzyme for DDX1. Immunofluorescence and nuclear-cytoplasmic partitioning experiments confirmed DDX1’s nuclear localization. GO and KEGG analyses clarify the biological functions of DDX1 in response to hypoxia. RNA-seq transcriptomics analyzed key pathways influenced by DDX1. A hydrodynamic in situ CCA mouse model was established to validate the chemopreventive effects of the PRMT1-specific inhibitor GSK715 on CCA development. Results: DDX1 promotes CCA progression both in vivo and in vitro and can be inhibited by GSK715. Mechanistically, PRMT1 mediates ADMA modification at position R602 of DDX1. This modification promotes DDX1 nuclear localization by recruiting USP10 to deubiquitinate DDX1, while simultaneously inhibiting PRMT1 degradation. DDX1 promotes the transcription of PRMT1 and USP10 by binding to the mRNA 3’UTR region, establishing a positive feedback regulatory pathway. This mechanism promotes the occurrence and development of CCA and can serve as a target for the inhibitor GSK715 to suppress CCA progression. Conclusions Our study identified DDX1-R602-ADMA modification as a novel ADMA modification in CCA. It further confirmed its pivotal role in CCA progression. Targeting the USP10-PRMT1-DDX1 axis may represent a significant therapeutic approach for CCA.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

The femoral vein is the primary venous trunk of the lower limbs and is commonly used for central venous catheterization in clinical practice.Traditional textbooks lack summarizes of the different types of anatomical variations of the femoral vein,making it more challenging for operators to perform punctures.Ultrasound-guided catheterization provides visualization,but there are still frequent instances of failed punctures and various complications.Operators usually use ultrasound equipment according to personal habits,but may not reach its full potential.This review summarizes recent researches on anatomical variations of the femoral vein and ultrasound-guided femoral vein catheterization,offering reference for medical professionals in clinical practice.

Objective:To explore the predictive potential of dual-energy CT (DECT) quantitative parameters in identifying breast cancer molecular subtypes and the expression of the epidermal growth factor receptor (EGFR) .Methods:A cohort of 97 breast cancer patients, treated between Jun. 2022 and Jun. 2024 were selected. The study compared DECT parameters-such as iodine concentration (IC) , normalized iodine concentration (NIC) , spectral curve slope (λ HU) , and effective atomic number (Z eff) in both arterial and venous phases across different molecular subtypes. A multiclass logistic regression model was employed to assess the parameters' value in predicting molecular subtypes, while a binary logistic regression model was used to evaluate their predictive value for EGFR expression. Results:Multiple Logistic regression analysis showed that after adjusting for confounder age and family history, IC ( OR=1.72, 2.78, 3.05) , NIC ( OR=2.52, 1.94, 2.93) , λ HU ( OR=2.08, 2.54, 3.17) and Z eff ( OR=2.03, 2.30, 2.37) at arterial stage were independently correlated with the molecular subtypes of breast cancer ( P<0.05) . Binary logistic regression analysis, adjusted for tumor size and lymph node metastasis, identified arterial phase IC ( OR=3.45) , NIC ( OR=2.73) , λ HU ( OR=2.59) , and Z eff ( OR=1.76) as independent risk factors for EGFR-positive breast cancer ( P<0.05) . Conclusion:DECT quantitative parameters, particularly arterial phase IC, NIC, λ HU, and Zeff, offer valuable insights into the molecular subtyping of breast cancer and EGFR expression, thereby assisting in the development of personalized treatment strategies.

Objective To investigate the cIinicopathological features and immunohistochemical expression of gastric hyperplastic polyps(GHPs)with dysplasia/adenocarcinoma.Methods A retrospective analysis of 24 cases(44 polyps)that were diagnosed as GHPs with dysplasia/adenocarcinoma in our hospital from January 2020 to December 2024 was reviewed,and clinical,histomorphological,immunophenotypic and follow-up data were analyzed.Results There were 20 female and 4 male cases,with a mean age of(65.5±7.9)(range 56～76)years.Among 44 polyps,3 occurred in the antrum of the stomach,1 in the gastric horn,and 40 in the fundus/body.Among the polyps,32 cases were diagnosed as high-grade dysplasia,4 cases as low-grade dysplasia,4 cases as coexistence of low-grade+high-grade dysplasia,2 cases as mucinous adenocarcinoma,1 cases as poorly differentiated adenocarcinoma,and 1 cases as signet-ring cell carcinoma.The histological manifestations of 23 cases of background mucosa were autoimmune metaplastic atrophic gastritis(AMAG).the P53 of 8 polyps showed a mutant expression pattern.Through MUC5/MUC6/MUC2/CD10 joint examination,33 cases showed gastric type(25 cases of which were foveal epithelium type),4 cases were intestinal type,5 cases were mixed gastrointestinal type,and 2 cases were non-gastrointestinal type.Conclusion The neoplastic transformation of GHPs is closely related to AMAG.It is necessary for clinicians and pathologists to strengthen their evaluation of background mucosa,to achieve early detection,early diagnosis and early treatment.

Objective To explore the value of MRI subtraction technique(ST)for evaluating the efficacy of systemic therapy for advanced hepatocellular carcinoma(HCC)and predicting prognosis after combining with surgery.Methods Totally 35 patients with 39 HCC lesions who received systemic therapy+radical resection were retrospectively collected.Based on preoperative MRI,tumor activity ratio(recorded as tumor activityST)was obtained with ST,while tumor activity value(recorded as tumor activitypathology)was obtained through postoperative pathology,and their correlation was analyzed.The patients were regularly followed up after surgery,and the survival data were recorded.Receiver operating characteristic(ROC)curve was drawn to evaluate the efficacy of tumor activityST for predicting patients'survival status.Then the patients were divided into survival benefit group and no survival benefit group according to the cut-off value,and survival analysis was conducted.Results Tumor activityST was positively correlated with tumor activitypathology(r=0.900,P＜0.001).The median follow-up time was 32.93 months,during which 8 patients died,and the median survival time was 29.9 months.The area under the curve(AUC)of tumor activityST for predicting patients'survival status was 0.67,and the cut-off value was 0.36.Thirty patients with tumor activityST＜0.36 were enrolled in survival benefit group,while 5 patients≥0.36 were collected in no survival benefit group.The overall survival in survival benefit group was longer than that in no survival benefit group(P＜0.001).Conclusion MRI ST could be used to non-invasively evaluate the efficacy of systemic therapy for advanced HCC and predict prognosis after combining with surgery.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Aim To infer novel therapeutic and phar-macological targets related to lung cancer treatment through multiomics approaches,so as to provide new directions for developing more personalized and effec-tive treatment strategies.Methods Genome-wide as-sociation study(GWAS)data analysis,pan-cancer,single-cell,transcriptomics,and protein-protein interac-tion analysis were employed in this study.Results We analyzed biomarkers and therapeutic targets associ-ated with lung cancer.The study identified key bio-markers closely related to lung cancer progression and explored the interrelationships between these biomark-ers and viral infections.According to KEGG pathway annotation,the number of genes related to metabolic processes increased significantly.In particular,metab-olites such as alanine and isoleucine emerged as pivotal factors in therapeutic interventions.The IgD+CD24+and IgD+CD24-B cell subsets were identified as cen-tral elements in immune evasion and treatment re-sponse.Concurrently,the Lachnospiraceae and Prevo-tella were shown to modulate host immune responses and the tumor microenvironment by regulating short-chain fatty acid levels,thereby opening novel avenues for cancer research.Conclusions Through mul-tiomics analysis combined with transcriptomics and pro-teomics analysis,we identify several potential therapeu-tic targets for lung cancer,providing key insights for developing novel treatment strategies.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]