Objective:To explore the developmental trajectory and influencing factors of self-management behavior among stroke patients.Methods:A total of 478 ischemic stroke patients admitted to the department of neurology of a grade-Ⅲ hospital in Henan Province from July 2023 to June 2024 were selected as the investigation objects. Baseline data of patients were collected using the general situation questionnaire, stroke knowledge questionnaire, stroke health belief scale, stroke self-management behavior scale and self-rating depression scale. The self-management behavior level of patients was assessed at discharge, 1 month, 3 months and 6 months after discharge. Mplus 7.0 software was used to conduct trajectory analysis of stroke patients' self-management behaviors, and multiple Logistic regression analysis was used to analyze the influencing factors associated with the development trajectory types of different stroke self-management behaviors.Results:The self-management behavior scores of stroke patients at discharge, 1 month, 3 months and 6 months after discharge were 206.59(167.59, 230.57), 169.59(129.73, 196.73), 149.82(120.89, 171.48), and 147.14(123.02, 181.64), respectively. Four trajectory categories were described. Category 1 was low-level pattern of initial decrease followed by stabilization, accounting for 16.95%(81/478)( P<0.001, intercept=2.701). Category 2 was low-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept =2.696). Category 3 was medium-level pattern of initial decrease followed by stabilization, accounting for 57.11%(273/478)( P<0.001, intercept =3.829). Category 4 was high-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept=4.366). The self-management behavior of stroke patients with low level of stroke knowledge, low level of health belief, aged 60 to 70 years old, residence in rural areas and middle school and below education level were more likely to belong to the low level group(all P<0.05). Patients with low depression in the low level group were more likely to be classified as low-level pattern of initial decrease followed by increase( P<0.05). Conclusion:The trajectory category of self-management behavior could be predicted by stroke knowledge level, health belief level, age, place of residence, educational background and depression. Their self-management behavior level may be improved through targeted interventions according to the characteristics of different trajectory categories.

Objective:To explore the dual mediating effects of health belief and depression among health knowledge, social support, and health behaviors based on the capacity, opportunity, motivation-behavior (COM-B) model, and analyze the influencing factors of health behaviors in patients with ischemic stroke.Methods:This multi-center cluster sampling research recruited ischemic stroke patients ( n=1 696) who were hospitalized in neurology departments of five tertiary hospitals in Henan Province from October 2023 to October 2024. A cross-sectional investigation was conducted using the general information questionnaire, social support rating scale (SSRS), stroke prevention knowledge questionnaire(SPKQ), short form health belief model scale(SF-HBMS), health promoting lifestyle profile-Ⅱ (HPLP-Ⅱ), and patient health questionnaire-9(PHQ-9) to ultimately reveal the pathways and effect sizes among variables. Partial correlation analysis and multiple linear stepwise regression analysis were conducted to examine the relationships among social support, health knowledge, health belief, health behaviors, and depression in stroke patients by SPSS 26.0 software. Structural equation modeling was constructed using AMOS 28.0 software, and the mediating effect was tested using the Bootstrap method. Results:The scores of social support, health knowledge, health belief, and health behaviors among ischemic stroke patients were (37.46±9.94), (26.56±6.84), (75.62±12.62) and (130.79±26.27), respectively. The score of depression was 5.00 (2.00, 8.00). Health behaviors were positively correlated with health knowledge, social support, and health belief( r=0.333, 0.246, 0.267, all P<0.05), while negatively correlated with depression ( r=-0.146, P<0.05). Multiple linear stepwise regression analysis showed that health knowledge, social support, health belief, and depression were all influencing factors of health behaviors in ischemic stroke patients (all P<0.05). Health belief (effect value=0.068, 95% CI=0.048-0.093) and depression (effect value=0.009, 95% CI=0.003-0.018) both played partial mediating roles between health knowledge and health behaviors, accounting for 17.3%(0.077/0.446) of the total effect. Meanwhile, health belief (effect value=0.045, 95% CI=0.029-0.063) and depression (effect value=0.016, 95% CI=0.008-0.027) both played partial mediating roles between social support and health behaviors, accounting for 26.5%(0.061/0.230) of the total effect. Conclusion:Health knowledge and social support can not only directly influence health behaviors but also indirectly affect them through health belief and depression in patients with ischemic stroke.

Objective:To explore the application of nursing intervention based on the capability, opportunity, motivation-behavior model (COM-B) in stroke patients during the rehabilitation period.Methods:Using the convenience sampling method, 146 stroke patients admitted to the First Affiliated Hospital of Zhengzhou University from February 2021 to February 2024 were selected as the research objects. According to the admission time sequence, they were divided into the COM-B group and the routine group, with 73 cases in each group. The routine group received routine nursing measures, and the COM-B group was intervened with the COM-B intervention, both for 3 months. The scores of the Health Education Self-Management Scale for Stroke Patients (HES-SP), the Exercise of Self-Care Agency Scale (ESCA), the Fugl-Meyer Assessment (FMA), and the Barthel Index of the two groups before and after the intervention were compared.Results:Finally, 72 patients in the COM-B group and 71 patients in the routine group completed the study. After 3 months of intervention, the scores of ESCA, HES-SP, FMA, and the Barthel Index of the two groups were all higher than those before the intervention, and the scores of COM-B group were all higher than those of the routine group, and the differences were statistically significant ( P<0.05) . Conclusions:The application of the COM-B intervention in stroke patients can improve patients' healthy behaviors and self-care abilities, and enhance their limb motor function and activities of daily living abilities, with a good application effect.

Objective The effects of stachydrine(STA)on the proliferation,apoptosis and radiosensitivity of acute myeloid leukemia(AML)cells by regulating the transcription factor forkhead box protein O3(FOXO3)-forkhead box protein M1(FOXM1)signaling axis.Methods Human AML cells(HL-60)were treated with STA at a concentration of 50～1 600 μmol/L,and the activity of HL-60 cells was detected using the cell counting kit-8(CCK-8)method to screen for the optimal drug concentration;HL-60 cells were separated into Control group,low,medium,and high concentration STA groups(STA-L group,STA-M group,STA-H group),STA+lentivirus transfection control group(STA-H+LV-NC group),and high-concentration STA+FOXO3 overexpression lentiviral group(STA-H+LV-FOXO3 group).5-ethyny1-2'-deoxyuridine(Edu)was applied to detect HL-60 cell proliferation;flow cytometry(FCM)was applied to detect cell apoptosis;cell cloning experiments were applied to detect the radiotherapy sensitivity of cells;Western blot was applied to detect the expression of cell proliferation antigen markers(Ki67),Cyclin D1,Caspase-3,B-cell lymphoma2 assaciated X protein(Bax),FOXO3,and FOXM1 proteins.Results STA concentrations of 100,200 and 400 μmol/L were selected for subsequent experiments.Compared with the control group,the positive rate of Ki67,Cyclin D1,Edu,FOXO3 and FOXM1 expression levels in the STA-L,STA-M,and STA-H groups decreased sequentially(tSTA-L=2.169～5.879,tSTA-M=3.089～11.284,tSTA-H=4.572～11.502),Caspase-3 and Bax expression levels,the apoptosis rate,increased sequentially(tSTA-L=9.171,10.082,20.144;tSTA-M=5.435,7.530,7.450;tSTA-H=4.138,4.159,5.956)and the differences were statistically significant(all P<0.05),respectively.Compared with the STA-H+LV-NC group,the positive rate of Edu and the expression levels of Ki67,Cyclin D1,FOXO3 and FOXM1 were obviously increased in the STA-H+LV-FOXO3 group(t=10.055～16.267),Caspase-3 and Bax expression levels,the apoptosis rate were obviously reduced(t=5.736,5.433,8.933),and the differences were statistically significant(all P<0.05),respectively.The colony formation rate of HL-60 cells in the radiotherapy group and STA+radiotherapy group decreased with the increase of radiotherapy dose,and the differences were statistically significant(F=78.630,137.843,all P<0.05),and the colony formation rate of HL-60 cells in the STA+radiotherapy group was lower than that in the radiotherapy group at the same dose(t=1.480～11.301,all P<0.05).Conclusion Stachydrine inhibits AML cell proliferation,induces apoptosis,and enhances radiotherapy sensitivity by inhibiting the FOXO3-FOXM1 signaling axis.

Objective:To explore the effects of nursing interventions based on the self-mutual-group (SMG) health management model on self-efficacy, medication adherence, and lower limb functional recovery in patients with hemiplegia after ischemic stroke.Methods:Convenience sampling was used to select 200 patients with hemiplegia after ischemic stroke admitted to the First Affiliated Hospital of Zhengzhou University from February 2022 to January 2024 as study subjects. Patients were randomly assigned to a control group and an SMG group, with 100 patients in each group. Control group received conventional rehabilitation nursing, while SMG group received nursing interventions based on the SMG health management model, with both groups receiving interventions for 12 weeks. Self-efficacy, medication adherence, and lower limb functional recovery between two groups were compared.Results:After 12 weeks of intervention, the Stroke Self-Efficacy Questionnaire score, Various Medication Adherence scores, Fugl-Meyer Assessment Lower Extremity score, step frequency, step speed, stride length ratio, and surface electromyography integral values of the tibialis anterior and gastrocnemius muscles of the affected limb were all higher than those before intervention, and those of SMG group were higher than those of control group. All of the above differences were statistically significant ( P<0.05) . Conclusions:Nursing interventions based on the SMG health management model can improve the self-efficacy and medication compliance of patients with hemiplegia after ischemic stroke, enhance lower limb motor function and walking ability, and promote changes in surface electromyographic signals of the tibialis anterior and gastrocnemius muscles.

Objective:To explore the developmental trajectory and influencing factors of self-management behavior among stroke patients.Methods:A total of 478 ischemic stroke patients admitted to the department of neurology of a grade-Ⅲ hospital in Henan Province from July 2023 to June 2024 were selected as the investigation objects. Baseline data of patients were collected using the general situation questionnaire, stroke knowledge questionnaire, stroke health belief scale, stroke self-management behavior scale and self-rating depression scale. The self-management behavior level of patients was assessed at discharge, 1 month, 3 months and 6 months after discharge. Mplus 7.0 software was used to conduct trajectory analysis of stroke patients' self-management behaviors, and multiple Logistic regression analysis was used to analyze the influencing factors associated with the development trajectory types of different stroke self-management behaviors.Results:The self-management behavior scores of stroke patients at discharge, 1 month, 3 months and 6 months after discharge were 206.59(167.59, 230.57), 169.59(129.73, 196.73), 149.82(120.89, 171.48), and 147.14(123.02, 181.64), respectively. Four trajectory categories were described. Category 1 was low-level pattern of initial decrease followed by stabilization, accounting for 16.95%(81/478)( P<0.001, intercept=2.701). Category 2 was low-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept =2.696). Category 3 was medium-level pattern of initial decrease followed by stabilization, accounting for 57.11%(273/478)( P<0.001, intercept =3.829). Category 4 was high-level pattern of initial decrease followed by increase, accounting for 12.97%(62/478)( P<0.001, intercept=4.366). The self-management behavior of stroke patients with low level of stroke knowledge, low level of health belief, aged 60 to 70 years old, residence in rural areas and middle school and below education level were more likely to belong to the low level group(all P<0.05). Patients with low depression in the low level group were more likely to be classified as low-level pattern of initial decrease followed by increase( P<0.05). Conclusion:The trajectory category of self-management behavior could be predicted by stroke knowledge level, health belief level, age, place of residence, educational background and depression. Their self-management behavior level may be improved through targeted interventions according to the characteristics of different trajectory categories.

Objective:To explore the dual mediating effects of health belief and depression among health knowledge, social support, and health behaviors based on the capacity, opportunity, motivation-behavior (COM-B) model, and analyze the influencing factors of health behaviors in patients with ischemic stroke.Methods:This multi-center cluster sampling research recruited ischemic stroke patients ( n=1 696) who were hospitalized in neurology departments of five tertiary hospitals in Henan Province from October 2023 to October 2024. A cross-sectional investigation was conducted using the general information questionnaire, social support rating scale (SSRS), stroke prevention knowledge questionnaire(SPKQ), short form health belief model scale(SF-HBMS), health promoting lifestyle profile-Ⅱ (HPLP-Ⅱ), and patient health questionnaire-9(PHQ-9) to ultimately reveal the pathways and effect sizes among variables. Partial correlation analysis and multiple linear stepwise regression analysis were conducted to examine the relationships among social support, health knowledge, health belief, health behaviors, and depression in stroke patients by SPSS 26.0 software. Structural equation modeling was constructed using AMOS 28.0 software, and the mediating effect was tested using the Bootstrap method. Results:The scores of social support, health knowledge, health belief, and health behaviors among ischemic stroke patients were (37.46±9.94), (26.56±6.84), (75.62±12.62) and (130.79±26.27), respectively. The score of depression was 5.00 (2.00, 8.00). Health behaviors were positively correlated with health knowledge, social support, and health belief( r=0.333, 0.246, 0.267, all P<0.05), while negatively correlated with depression ( r=-0.146, P<0.05). Multiple linear stepwise regression analysis showed that health knowledge, social support, health belief, and depression were all influencing factors of health behaviors in ischemic stroke patients (all P<0.05). Health belief (effect value=0.068, 95% CI=0.048-0.093) and depression (effect value=0.009, 95% CI=0.003-0.018) both played partial mediating roles between health knowledge and health behaviors, accounting for 17.3%(0.077/0.446) of the total effect. Meanwhile, health belief (effect value=0.045, 95% CI=0.029-0.063) and depression (effect value=0.016, 95% CI=0.008-0.027) both played partial mediating roles between social support and health behaviors, accounting for 26.5%(0.061/0.230) of the total effect. Conclusion:Health knowledge and social support can not only directly influence health behaviors but also indirectly affect them through health belief and depression in patients with ischemic stroke.

In recent years,organoid technology has emerged as a pivotal tool in central nervous system(CNS)tumor research.By recapitulating the 3D architecture,molecular profiles,and dynamic interactions of tumors with their microenvironment,it provides an innovative platform for elucidating disease mechanisms and facilitating drug screening.Brain organoids are primarily utilized to model normal neurodevelopmental processes and investigate CNS disease pathogenesis,whereas CNS tumor organoids are chiefly employed to simulate tumor heterogeneity and therapeutic responses.This review delineates the methodologies for establishing brain organoids and CNS tumor organoid models,along with their applications in CNS oncology research,with parti-cular emphasis on the technical features and advantages of pluripotent stem cell-derived,patient-derived,and xenograft-derived organoid models.Furthermore,it examines current challenges in model standardization,mi-croenvironment recapitulation,and ethical considerations pertaining to human tissue sources.Future directions for advancing this technology are also discussed.

Objective:To evaluate the efficacy and safety of the Chi-BEAM regimen (chidamide combined with carmustine, etoposide, cytarabine, and melphalan) followed by autologous hematopoietic stem cell transplantation (ASCT) in patients with high-risk or relapsed/refractory lymphoma.Methods:This retrospective case series included 78 patients with newly treated high-risk or relapsed/refractory lymphoma who underwent ASCT with the Chi-BEAM conditioning regimen in the Department of Hematology, the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital), from June 2021 to May 2024. Descriptive statistics were employed to evaluate clinical characteristics, efficacy, and adverse events. The Kaplan-Meier method was applied to calculate cumulative progression-free survival (PFS) and overall survival (OS) rates.Results:The median age of the 78 evaluable patients was 47 years (range 16-68), with 8 patients (10.3%) aged ≥60 years. At the first post-transplant assessment (3 months), the objective response rate was 94.9% (74/78). The median follow-up was 20.1 months (range 2.9-44.9). The median PFS time was 20.1 months (range 1.6-45.1), with a 2-year cumulative PFS rate of 81.8%. The median OS time was 20.6 months (range 3.1-45.1), with a cumulative 2-year OS rate of 93.2%. The regimen was well-tolerated; mild-to-moderate hypocalcemia within 1 week post-infusion and transient mild erythrocyturia on the infusion day were the primary adverse reactions.Conclusion:The Chi-BEAM regimen combined with ASCT demonstrates both safety and clinical benefit in patients with high-risk or relapsed/refractory lymphoma.

Objective:To analyze the evolution of ceftazidime/avibactam (CZA) resistance phenotyes and clinical features of 11 ST11-KL64 carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates carrying bla KPC. Methods:Eleven CRKP isolates, designated K01 to K11, obtained from infected liver transplant patients from June to September 2024 were retrospectively studied. Broth microdilution method, whole genome sequencing (WGS) and plasmid conjugation assays were employed to investigate the antimicrobial susceptibility, resistance mechanisms, and genetic structural characteristics of these CRKP isolates. Clinical data were simultaneously collected and organized to analyze the correlation between bla KPC gene mutations and the clinical efficacy of antimicrobial therapy. Results:All eleven isolates of CRKP exhibited multidrug resistance phenotypes. Among them, K01-K09 and K11 were sensitive to CZA and resistant to carbapenems, while K10 was resistant to CZA and displayed sensitivity or intermediate resistance to carbapenems. WGS analysis showed that all 11 CRKP isolates belonged to the ST11-KL64 clonal type. Among these isolates, the K01-K09 and K11 isolates carry the bla KPC-2 gene, whereas the K10 isolate carries the bla KPC-33 gene. A single nucleotide mutation in bla KPC-2 (G532T) resulted in a substitution of tyrosine (Y) for aspartic acid (D) at Ambler position 179 (D179Y), causing resistance of CRKP to CZA and reduced sensitivity to Imipenem and Meropenem. The conjugative plasmid was successfully constructed, and compared to the parental strain, its minimum inhibitory concentration (MIC) to CZA increased 32 folds. Clinical data revealed that the patient developed the bla KPC-33 mutation after 51 days of CZA treatment. Conclusions:The bla KPC-33 mutation following CZA treatment for CRKP infection exhibits a considerable delay. It is essential to dynamically monitor the evolution of CRKP resistance to ensure timely adjustment of therapeutic strategies in case of the occurrence of mutations such as bla KPC-33.