OBJECTIVE: To investigate the predictive role of the modified Endothelial Activation and Stress Index (mEASIX) in the efficacy of chimeric antigen receptor T-cell (CAR-T) therapy and cytokine release syndrome (CRS). METHODS: The clinical data of 70 relapsed and refractory (R/R) B-cell tumor patients who were treated with CAR-T therapy from September 1, 2018 to February 28, 2023 in the Department of Hematology, Affiliated Hospital of Xuzhou Medical University, were retrospectively analyzed. The value of log-2 mEASIX before conditioning (-7 d) was calculated, and the patients were divided into a low-mEASIX group (42 patients) and a high-mEASIX group (28 patients) based on the cut-off value of 5.443 determined by the receiver operating characteristic (ROC) curve. Eventually, the predictive role of mEASIX before conditioning on the efficacy of CAR-T cell therapy and CRS was analyzed. RESULTS: The high-mEASIX group exhibited significantly worse median overall survival (OS) and median progression-free survival (PFS) in comparison to the low mEASIX group (OS: 3.2 months vs not reached, P < 0.01; PFS: 1.3 months vs 6.0 months, P =0.009). The incidence of grade ≥2 CRS in the high-mEASIX group was substantially higher than that in the low-mEASIX group (57.1% vs 19.0%, P =0.007). The degree of remission after CAR-T therapy (P =0.001), whether CRS occurs or not (P =0.041), the lactate dehydrogenase (LDH) level before conditioning (P =0.046), and the mEASIX score before conditioning (P =0.047) were independent influencing factors for the OS of patients receiving CAR-T cell therapy. CONCLUSION The mEASIX score before conditioning can predict OS and the incidence of grade ≥2 CRS in patients with relapsed and refractory B-cell tumors who receive CAR-T cell therapy.
Cytokine Release Syndrome/therapy* ; Immunotherapy, Adoptive/methods* ; Humans ; Lymphoma, B-Cell/therapy* ; Retrospective Studies ; Hematology ; China ; Receptors, Chimeric Antigen/blood* ; Predictive Value of Tests

BACKGROUND: Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients. METHODS: In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients. RESULTS: A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer. CONCLUSIONS Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.

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]

Copy number variation encompassing SNP plays an important role in IVD and precision medi-cine.As the most commonly used method,FISH could not overcome the probe cross-reactivity which is common when to detect SNP.Here we developed a quantitative and qualitative method on copy number variation encompassing SNP.In this study,the rs76711854 was used as an example to establish a quanti-tative method by advantage of probe cross-reactivity.The fragment encompassing rs76711854 and its downstream to 9 514 bp were amplified by PCR.The allelic genotypes were verified by Sanger sequen-cing.Different probes with or without cross-reactivity to be used via quantitative real-time PCR and digit-al PCR.The different clusters(2D)and fluorescence intensity layers(1D)exist by adding probe with cross-reactivity.The A/G ratio measured by digital PCR is 2︰1,which is verified by probe targeting to the SNP.The copy-number variant exists in the 9kb-long fragment upstream to the SNP of prostate cancer cell line but not in human endometrial adenocarcinoma cell line Ishikawa.The data suggest that there is a multi-copy variation at this locus in DU145 cells.The method applied here is based on one single cross-reactivity probe via digital PCR.

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 investigate the predictive value of endothelial activation and stress index(EASIX)for the prognosis of patients with mantle cell lymphoma(MCL).Methods:A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023,had therapeutic indications and received standard treatment.Results:A total of 66 patients were included and divided into high EASIX group and low EASIX group,according to a cutoff value of 0.97 determined by the receiver operating characteristic(ROC)curve.Multivariate Cox regression analysis showed that prealbumin＜0.2 g/L,high EASIX,and ECOG PS score ≥2 were independent risk factors influencing overall survival(OS)in MCL patients.The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months,and the median progression-free survival was 8.8 and 26.0 months,respectively.The proportions of patients with ECOG PS score ≥2 and prealbumin＜0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group.Conclusion:At the time of initial diagnosis,EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL.Furthermore,patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.

Copy number variation encompassing SNP plays an important role in IVD and precision medi-cine.As the most commonly used method,FISH could not overcome the probe cross-reactivity which is common when to detect SNP.Here we developed a quantitative and qualitative method on copy number variation encompassing SNP.In this study,the rs76711854 was used as an example to establish a quanti-tative method by advantage of probe cross-reactivity.The fragment encompassing rs76711854 and its downstream to 9 514 bp were amplified by PCR.The allelic genotypes were verified by Sanger sequen-cing.Different probes with or without cross-reactivity to be used via quantitative real-time PCR and digit-al PCR.The different clusters(2D)and fluorescence intensity layers(1D)exist by adding probe with cross-reactivity.The A/G ratio measured by digital PCR is 2︰1,which is verified by probe targeting to the SNP.The copy-number variant exists in the 9kb-long fragment upstream to the SNP of prostate cancer cell line but not in human endometrial adenocarcinoma cell line Ishikawa.The data suggest that there is a multi-copy variation at this locus in DU145 cells.The method applied here is based on one single cross-reactivity probe via digital PCR.

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 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]

Helicobacter pylori(HP)infection is a Class Ⅰ carcinogen in gastric cancer,closely related to the occurrence of gastric cancer.Many studies have shown that HP eradication has a preventive effect on gastric cancer.However,2.7%-6.1%of patients with early gastric cancer who have been eradicated after endoscopic submucosal dissection(ESD)can still develop metachronous gastric cancer(MGC),and the mechanism of its occurrence is still unclear.In this review,the atrophy of gastric mucosa and intestinal metaplasia cannot be completely reversed after HP eradication,the excessive proliferation of gastric mucosa epithelial cells,the accumulation of genetic abnormalities,the homeostasis imbalance of the epigenetic group,changes in immune microenvironment,the abnormality of stem cells in gastric mucosa,chromatin accessibility,and changes in chromosome remodeling were discussed in the mechanism of carcinogenesis caused by the above molecular changes after ESD and HP eradication in early gastric cancer.