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.

OBJECTIVE To explore the expression level of miR-196a in cervical cells infected with high-risk human papillomavirus(HPV)16 and 18.METHODS The Gene Expression Omnibus(GEO)was used to screen for dif-ferentially expressed miRNAs between HPV 16 or 18-positive cervical cancer cells and normal cervical cells.On-line biological software https://kmplot.com/analysis/was utilized to analyze the relationship between the most differentially expressed miRNA and the overall survival of cervical cancer patients.Cervical swab samples positive for HPV 16 or HPV 18,detected by real-time fluorescent quantitative polymerase chain reaction(qPCR)genoty-ping,were collected as the study subjects.Cervical swab samples from the same period of physical examination population that were negative for HPV 16 or HPV 18 by qPCR genotyping served as negative controls.The qRT-PCR method was employed to detect the level of miR-196a in cervical cells,with data processed via the 2-△△Ctmethod.RESULTS Differential analysis of the GSE86100 data revealed that miR-196a expression de-creased in HPV 16 or HPV 18-positive cervical cells(log2FC=-6.60,P＜0.001),while miR-3188 expression significantly increased(log2FC=6.22,P＜0.001).Using online analysis tools https://kmplot.com/analysis,it was found that cervical cancer patients with high miR-196a expression had a shorter overall survival compared to those with low m iR-196a expression(HR=1.87,95％CI:1.17-3.00,P=0.008).H owever,there was no cor-relation between miR-3188 and the overall survival of cervical cancer patients(HR=1.47,95％CI:0.92-2.37,P=0.110).The results of specific qRT-PCR testing showed that the expression levels of miR-196a in cervical cells positive for HPV 16 and HPV 18 were 0.93±0.09 and 0.51±0.07,respectively,which were lower than those in the normal control group(1.89±0.13)(P＜0.05),consistent with the sequencing analysis results CONCLUSIONS Infection of cervical cells with HPV 16 or HPV 18 can lead to decreased expression of miR-196a,and the expres-sion level of miR-196a is negatively correlated with the overall survival of cervical cancer patients.

Objective To construct mice hepatocellular carcinoma models with different tumor immune microenvironments(TIME)and explore the differences.Methods H22 and hepa1-6 were used to construct subcutaneous transplantation tumor model of C57 mice as homologous hepatocellular carcinoma cell lines(denoted as H22 group and hepal-6 group,each n=8),and the differences of TIME were evaluated.Immunohistochemistry was used to detect and quantify the infiltration of T cells,CD4+T cells,CD8+T cells,regulatory T cells and B cells in TIME.Flow cytometry was performed to detect the differences of composition of immune cell subpopulations in peripheral blood and tumor parenchyma.Gene expression profile characteristics of tumor tissue were analyzed based on high-throughput transcriptome sequencing technology,and enrichment analyses of immune-related signaling pathways were evaluated combined with gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG).Results H22 group showed cold and hepa1-6 group showed hot TIME characteristics.The number of T cells,CD4+T cells and CD8+T cells in tumor tissue of H22 group were all lower,while the proportion of T cells,CD4+T cells and CD8+T cells in peripheral blood were all higher than those of hepa1-6 group(all P＜0.05).Compared with H22 group,up-regulated genes of tumor tissue in hepa1-6 group expressed significantly enriched in tumor immune activation-related signaling pathways.Conclusion H22 and hepa1-6 hepatocellular carcinoma models showed distinct TIME characteristics of cold and hot tumors,respectively,and the amount of immune cells in tumor tissue of the former were significantly lower than those in the latter.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Objective To design an intelligent monitoring platform for adverse drug reactions(ADRs)to solve the problems of the traditional ADR monitoring mode.Methods The ADR intelligent monitoring platform was designed based on artificial intelligence and big data technologies,which was developed with Browser/Server(B/S)architecture,C#programming language and.NET development tool.There were five functional modules involved in the platform for ADR knowledge base,monitoring rule setting,intelligent monitoring,report management and statistical analysis.Results The platform realized the full-process management of ADR intelligent monitoring,reporting,review and statistical analysis,which enhanced the ADR report in quantity,quality and timeliness.Conclusion The platform contributes to improving the monitoring of ADR and patient medication safety.[Chinese Medical Equipment Journal,2025,46(9):33-38]

As China has become the second largest market for medical devices in the world,the domestic medical device industry has been growing.As an important part of preclinical evaluation of medical devices,large animal research directly affects the research and application of medical devices.Large animals are widely used in the evaluation of safety and feasibility of medical devices because they are closer to humans in terms of body size,anatomical structure and physiological functions.In large animal experimental research,the selection of suitable experimental animals and the establishment of suitable animal disease models are the basis for ensuring the smooth progress of experiments.In this paper,the selection of experimental animals and the establishment of disease models in medical device large animal experimental research are systematically sorted out,and the existing problems and deficiencies are pointed out.

Fetal ultrasound standard plane detection was introduced in terms of its importance and problems encountered.The deep learning techniques applied in fetal standard plane detection were reviewed,including transfer learning,modified basic network,hybrid network and multi-task network.The problems encountered by the deep learning techniques during the application were analyzed,and the future research directions were envisioned.[Chinese Medical Equipment Journal,2025,46(5):91-101]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

This study investigated the association between a proximal promoter polymorphism of IFNGR1 (interferon-γ receptor α chain, IFNGR-α) and breast cancer susceptibility, as well as the prognostic value of its expression variation in breast cancer patients. A case-control study was conducted at the Sixth Medical Center of PLA General Hospital from June 2020 to June 2022. The study included 182 pathologically confirmed breast cancer patients as the breast cancer group, 177 non-tumor patients with benign breast lesions as the benign breast lesions group, and 229 healthy individuals as the normal control group. 2-3 ml EDTA anticoagulant whole blood samples were collected from all participants, and genomic DNA was extracted and stored for further analysis. Basic patient information was retrieved from the hospital′s electronic medical records by patients′ ID number. The proximal promoter sequence of IFNGR1 was obtained from NCBI, and sequencing primers were designed using Primer Premier 6.0. Sanger sequencing was employed to analyze the IFNGR1 promoter sequence in the three groups, and the results were compared with the Eukaryotic Promoter Database (EPD) sequence using Bioedit software. Statistical analysis was performed on single nucleotide polymorphisms (SNPs) in the IFNGR1 promoter. The TCGA database was utilized to assess the relationship between IFNGR1 expression levels and breast cancer patient survival. The findings revealed that the -56 TG genotype of the IFNGR1 promoter was significantly associated with increased breast cancer risk ( Z=2.73, P<0.05). Notably, IFNGR1 expression was lower in breast cancer group compared to normal control group ( P<0.05). Analysis of the TCGA database indicated that patients with high IFNGR1 expression had longer survival times than those with low expression ( HR=0.87, 95% CI:0.77-0.98, P<0.05). In summary, the IFNGR1 -56 TG genotype is associated with an increased risk of breast cancer, and there is a positive correlation between IFNGR1 expression levels and the survival of breast cancer patients.

Objective To develop a predictive model integrating clinical features,deep learning(DL),and radiomics based on T2-weighted imaging for prenatal assessment of postpartum hemorrhage(PPH)risk in high-risk pregnant women.Methods A total of 538 pregnant women with ultrasound-reported high-risk placenta accrete were retrospectively enrolled and divided into training,internal test,and external test cohorts.A nnUNet model was trained for automatic placental segmentation.Univariate and multivariate analyses were conducted on clinical features to identify those associated with PPH.Quantitative radiomic features were extracted from the placental region,and a random forest model was developed to predict estimated blood loss(EBL)and PPH risk.A DenseNet-based multi-task DL model was trained to predict PPH risk,EBL,and placenta previa status.Finally,a DL-radiomics ensemble(DRE)model was constructed by integrating clinical features,DL outputs,and radiomics scores.Diagnostic performance was evaluated using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results The DRE model achieved AUC values of 0.874(95%CI:0.792-0.951)and 0.836(95%CI:0.648-0.974)in the internal and external test cohorts,respectively,significantly outperforming the standalone clinical,DL,and radiomics models.Incorporation of EBL regression improved the performance of the PPH classification model,with the external test AUC increasing from 0.261-0.788 to 0.836.Conclusion The DRE model integrating DL and radiomics can efficiently predict PPH risk and assist in the clinical management of high-risk pregnancies.