Objective To explore the application value of serum cystatin C(CysC)and cluster of differentiation 147(CD147)in predicting restenosis after intracranial artery stenosis stenting(ICASS)in patients with acute ischemic stroke(AIS).Methods A total of 151 AIS patients who received ICASS were selected as the study group,and 112 healthy individuals who underwent physical examinations during the same period were chosen as the control group.The study group was further divided into the restenosis group(30 cases)and the non-stenosis group(121 cases)based on the restenosis status within 6 months after ICASS.The serum CysC levels of the subjects were detected by immunoturbidimetry,and the serum CD147 levels were measured by enzyme-linked immunosorbent assay.Multivariate Logistic regression analysis was conducted to identify factors influencing restenosis after ICASS in AIS patients.The receiver operating characteristic(ROC)curve was used to evaluate the application efficacy of serum CysC and CD147 levels in predicting restenosis after ICASS in AIS patients.Results Serum levels of CysC and CD147 were higher in the study group than those in the control group(P＜0.01).The proportion of patients with stenosis degree>75%and serum levels of CysC and CD147 were higher in the restenosis group than those in the non-stenosis group(P＜0.01).The degree of stenosis>75%and the increased serum levels of CysC and CD147 were risk factors for restenosis after ICASS in AIS patients(P＜0.01).ROC curve analysis showed that serum CysC and CD147 levels independently predicted the AUC of AIS patients with restenosis after ICASS were 0.845 and 0.850,respectively,and the combined predicted AUC was 0.942.The combined prediction efficiency was significantly better than that of single indicator prediction(P＜0.05).Conclusion The increased levels of serum CysC and CD147 in AIS patients are risk factors for restenosis after ICASS,and the combination of the two is more effective in predicting intracranial artery restenosis after ICASS in AIS patients.

Objective:Exploring the role and mechanism of CHMP4C in regulating necroptosis during gastric can-cer development and progression.Method:The expression of CHMP4C in pan-cancer was analyzed by bioinformatics methods,and the expression of CHMP4C was detected in human normal gastric epithelial cells and GC cell lines by RT-qPCR and Western blot.Overexpression or knockdown of CHMP4C was performed in GC cell lines,and the effects of CHMP4C on the growth and proliferation of GC cells were detected using CCK-8 and clone formation assays.The CCK-8 experiment and Hoechst/PI double staining experiment were used to detect the changes in GC cell mortality and PI positive cell ratio after treatment with the necroptsis inducer TSZ or inhibitor necrostatin-1(Nec-1).Western blot assay was used to detect the protein and phosphorylation levels of RIPK1,RIPK3,and MLKL in GC cells.Result:CHMP4C was upregulated in GC tissues and cells.The CCK-8 and clone formation experiments showed that overex-pression of CHMP4C significantly improved the proliferation ability and colony formation efficiency of GC cells,while knockdown of CHMP4C significantly weakened GC cells.Moreover,the results of CCK-8 and Hoechst 33342/PI double staining experiments showed that upregulated CHMP4C could inhibit TSZ induced GC cell death;Nec-1 can reverse the decrease in GC cell viability caused by CHMP4C knockdown.Western blot experiment showed that the levels of p-RIPK1,p-RIPK3,and p-MLKL were significantly decreased in overexpressing cells,while they were increased in knockdown cells.After treatment with Nec-1,the expression levels of these three proteins decreased in knockdown cells.Conclusion:CHMP4C may promote GC progression by negatively regulating necroptosis through inhibiting the phosphorylation of the RIPK1/RIPK3/MLKL signaling pathway,suggesting that it is expected to be a potential target for GC therapy.

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.

Objective To construct a hierarchical dynamic management intelligent system for nurses and to validate its application effectiveness,providing a reference for the development of intelligent nursing human resource management.Methods The nurse hierarchical classification and dynamic promotion management mechanism were clarified,and a hierarchical dynamic management system for nurses was established,comprising 2 modules:personal growth,and tier management and review.The system was officially implemented in a tertiary A hospital in Henan Province in March 2024.A comparison was conducted between pre-implementation(2023)and post-implementation(2024),including nurse tier applications and promotions,efficiency in tier promotion evaluations,Psychological Capital Questionnaire scores of nurses,and user satisfaction with the system.Results Following the implementation of the hierarchical dynamic management intelligent system for nurses,the application rate for tier promotion increased by 11.33％.After system implementation,the promotion pass rate and Psychological Capital Questionnaire scores of nurses were significantly higher than those before implementation,while the time required for tier review was significantly shorter.These differences were statistically significant(P＜0.05).The satisfaction survey scores for nurses applying for tier promotion and for reviewers using the system were(62.28±4.56)and(64.09±3.17)scores,respectively.Conclusion The application of the hierarchical dynamic management intelligent system for nurses helps enhance nurses'promotion pass rates and psychological capital,streamlines the nurse tier review process,and demonstrates high user satisfaction with the system.

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.

Aberrant expression of Colgalt1 is closely associated with tumorigenesis and tumor progres-sion;however,the mechanism by which it regulates macrophages to influence tumor development remains poorly understood.This study aimed to establish a macrophage-specific Colgalt1 gene knockout mouse model to delve into the mechanisms through which Colgalt1 modulates macrophage function and subse-quently affects the occurrence and progression of tumor-related diseases.Initially,Colgalt1flox+mice were generated using gene editing techniques,followed by crossing with Lyz2-Cre+mice,which exhibit tissue-specific expression in the myeloid lineage(including monocytes and mature macrophages).Through this strategy,mice with the genotype Colgalt1-/-Lyz2-Cre+were successfully obtained,achieving conditional knockout of the Colgalt1 gene in macrophages.Colgalt1flox/flox Lyz2-Cre-mice were used as control.PCR and agarose gel electrophoresis were employed to identify the Flox and Cre genotypes of the knockout mice.RT-qPCR and Western Blot techniques were utilized to detect the expression levels of Colgalt1 in BMDMs from knockout mice at both the mRNA and protein levels,respectively.Western Blot results re-vealed a significant downregulation of Colgaltl expression in BMDMs from knockout mice compared to controls(P＜0.01).RT-qPCR results demonstrated a significant reduction in Colgalt1 mRNA levels in BMDMs from knockout mice compared to contro1s(P＜0.001),while no significant differences in Col-galt1 mRNA expression were observed in liver,lung,or spleen tissues between the two groups.Addition-ally,immunohistochemistry was employed to detect Colgalt1 expression in liver-specific macrophages,re-vealing an absence of Colgalt l-positive staining in liver macrophages from knockout mice.HE staining was used to observe cellular morphology in liver tissues from both groups of mice,showing no significant differences in cellular morphology or obvious pathological changes in tissues and organs.Moreover,the o-verall survival of the mice was not affected.Finally,RT-qPCR was used to assess the expression of mac-rophage-related inflammatory factors in BMDMs from both groups of mice.The results indicated that com-pared to controls,knockout mice exhibited downregulated expression of TNF-α(P＜0.05)and signifi-cantly upregulated expression of IL-10(P＜0.01),Arginase1(P＜0.001),and CD206(P＜0.001)in BMDMs,suggesting an anti-inflammatory trend and M2 polarization of macrophages following Colgalt 1 knockout.In summary,this study successfully established a macrophage-specific Colgalt1 gene knockout mouse model,providing a more reliable experimental animal model for in-depth exploration of the specific roles of Colgalt1 in macrophage functional regulation and the pathogenesis of tumor-related diseases.This model holds promise for identifying novel therapeutic targets and strategies for tumors and other diseases.

Objective To explore the application value of serum cystatin C(CysC)and cluster of differentiation 147(CD147)in predicting restenosis after intracranial artery stenosis stenting(ICASS)in patients with acute ischemic stroke(AIS).Methods A total of 151 AIS patients who received ICASS were selected as the study group,and 112 healthy individuals who underwent physical examinations during the same period were chosen as the control group.The study group was further divided into the restenosis group(30 cases)and the non-stenosis group(121 cases)based on the restenosis status within 6 months after ICASS.The serum CysC levels of the subjects were detected by immunoturbidimetry,and the serum CD147 levels were measured by enzyme-linked immunosorbent assay.Multivariate Logistic regression analysis was conducted to identify factors influencing restenosis after ICASS in AIS patients.The receiver operating characteristic(ROC)curve was used to evaluate the application efficacy of serum CysC and CD147 levels in predicting restenosis after ICASS in AIS patients.Results Serum levels of CysC and CD147 were higher in the study group than those in the control group(P＜0.01).The proportion of patients with stenosis degree>75%and serum levels of CysC and CD147 were higher in the restenosis group than those in the non-stenosis group(P＜0.01).The degree of stenosis>75%and the increased serum levels of CysC and CD147 were risk factors for restenosis after ICASS in AIS patients(P＜0.01).ROC curve analysis showed that serum CysC and CD147 levels independently predicted the AUC of AIS patients with restenosis after ICASS were 0.845 and 0.850,respectively,and the combined predicted AUC was 0.942.The combined prediction efficiency was significantly better than that of single indicator prediction(P＜0.05).Conclusion The increased levels of serum CysC and CD147 in AIS patients are risk factors for restenosis after ICASS,and the combination of the two is more effective in predicting intracranial artery restenosis after ICASS in AIS patients.

Objective:Exploring the role and mechanism of CHMP4C in regulating necroptosis during gastric can-cer development and progression.Method:The expression of CHMP4C in pan-cancer was analyzed by bioinformatics methods,and the expression of CHMP4C was detected in human normal gastric epithelial cells and GC cell lines by RT-qPCR and Western blot.Overexpression or knockdown of CHMP4C was performed in GC cell lines,and the effects of CHMP4C on the growth and proliferation of GC cells were detected using CCK-8 and clone formation assays.The CCK-8 experiment and Hoechst/PI double staining experiment were used to detect the changes in GC cell mortality and PI positive cell ratio after treatment with the necroptsis inducer TSZ or inhibitor necrostatin-1(Nec-1).Western blot assay was used to detect the protein and phosphorylation levels of RIPK1,RIPK3,and MLKL in GC cells.Result:CHMP4C was upregulated in GC tissues and cells.The CCK-8 and clone formation experiments showed that overex-pression of CHMP4C significantly improved the proliferation ability and colony formation efficiency of GC cells,while knockdown of CHMP4C significantly weakened GC cells.Moreover,the results of CCK-8 and Hoechst 33342/PI double staining experiments showed that upregulated CHMP4C could inhibit TSZ induced GC cell death;Nec-1 can reverse the decrease in GC cell viability caused by CHMP4C knockdown.Western blot experiment showed that the levels of p-RIPK1,p-RIPK3,and p-MLKL were significantly decreased in overexpressing cells,while they were increased in knockdown cells.After treatment with Nec-1,the expression levels of these three proteins decreased in knockdown cells.Conclusion:CHMP4C may promote GC progression by negatively regulating necroptosis through inhibiting the phosphorylation of the RIPK1/RIPK3/MLKL signaling pathway,suggesting that it is expected to be a potential target for GC therapy.

Aberrant expression of Colgalt1 is closely associated with tumorigenesis and tumor progres-sion;however,the mechanism by which it regulates macrophages to influence tumor development remains poorly understood.This study aimed to establish a macrophage-specific Colgalt1 gene knockout mouse model to delve into the mechanisms through which Colgalt1 modulates macrophage function and subse-quently affects the occurrence and progression of tumor-related diseases.Initially,Colgalt1flox+mice were generated using gene editing techniques,followed by crossing with Lyz2-Cre+mice,which exhibit tissue-specific expression in the myeloid lineage(including monocytes and mature macrophages).Through this strategy,mice with the genotype Colgalt1-/-Lyz2-Cre+were successfully obtained,achieving conditional knockout of the Colgalt1 gene in macrophages.Colgalt1flox/flox Lyz2-Cre-mice were used as control.PCR and agarose gel electrophoresis were employed to identify the Flox and Cre genotypes of the knockout mice.RT-qPCR and Western Blot techniques were utilized to detect the expression levels of Colgalt1 in BMDMs from knockout mice at both the mRNA and protein levels,respectively.Western Blot results re-vealed a significant downregulation of Colgaltl expression in BMDMs from knockout mice compared to controls(P＜0.01).RT-qPCR results demonstrated a significant reduction in Colgalt1 mRNA levels in BMDMs from knockout mice compared to contro1s(P＜0.001),while no significant differences in Col-galt1 mRNA expression were observed in liver,lung,or spleen tissues between the two groups.Addition-ally,immunohistochemistry was employed to detect Colgalt1 expression in liver-specific macrophages,re-vealing an absence of Colgalt l-positive staining in liver macrophages from knockout mice.HE staining was used to observe cellular morphology in liver tissues from both groups of mice,showing no significant differences in cellular morphology or obvious pathological changes in tissues and organs.Moreover,the o-verall survival of the mice was not affected.Finally,RT-qPCR was used to assess the expression of mac-rophage-related inflammatory factors in BMDMs from both groups of mice.The results indicated that com-pared to controls,knockout mice exhibited downregulated expression of TNF-α(P＜0.05)and signifi-cantly upregulated expression of IL-10(P＜0.01),Arginase1(P＜0.001),and CD206(P＜0.001)in BMDMs,suggesting an anti-inflammatory trend and M2 polarization of macrophages following Colgalt 1 knockout.In summary,this study successfully established a macrophage-specific Colgalt1 gene knockout mouse model,providing a more reliable experimental animal model for in-depth exploration of the specific roles of Colgalt1 in macrophage functional regulation and the pathogenesis of tumor-related diseases.This model holds promise for identifying novel therapeutic targets and strategies for tumors and other diseases.

Objective:To explore the status quo of fertility information need of breast cancer patients at childbearing age, and analyze its influencing factors.Methods:From April to October 2023, 400 cases of breast cancer patients of childbearing age in two Class Ⅲ Grade A hospitals in Zhengzhou City were selected by convenience sampling. Patents were investigated with the General Information Questionnaire and the Fertility Information Needs Assessment Questionnaire for Breast Cancer Patients of Childbearing Age. Multiple linear regression was used to analyze the influencing factors of fertility information need of breast cancer patients of childbearing age. A total of 400 questionnaires were distributed, and 385 valid questionnaires were collected, with an effective response rate of 96.25% (385/400) .Results:The 385 breast cancer patients of childbearing age had a high level of need for fertility information with an average score of items (3.17±0.73). The scores for each dimension in descending order of the mean score of items were disease impact information, treatment impact information, psychosocial information, fertility management information, sexual health information, and fertility protection information. Age, marital status, education level, per capita monthly family income and duration of illness were the factors influencing the fertility information need ( P<0.05) . Conclusions:Breast cancer patients of childbearing age have a high level of need for fertility information, and their need is influenced by a number of factors. Medical and nursing staff should improve the fertility information support program based on the real needs of breast cancer patients, and provide personalized fertility information support for breast cancer patients of childbearing age with different characteristics.