BackgroundPatients with depressive episode and schizophrenia have a high risk of suicide. The sleep electroencephalogram power spectral density characteristics of patients with depressive episode accompanied by suicidal behavior and those with schizophrenia may be different， but there is currently a lack of direct comparative studies on these two groups of patients. ObjectiveTo compare the sleep electroencephalogram power spectral density between depressive episode and schizophrenic patients with suicidal behavior， in order to provide references for exploring predictive indicators of suicidal behavior. MethodsFrom June 2018 to December 2020， 20 patients with depressive episode and 20 patients with schizophrenia who had committed suicide within the past month and were treated at the outpatient department of Shenzhen Kangning Hospital were selected. All of them met the diagnostic criteria for depressive episode or schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）. Using a random sampling method， 20 volunteers with matching gender and age to the patient groups were selected from the Cuiping community in Shenzhen as the control group. The subjective sleep of the patients was evaluated using the Insomnia Severity Index （ISI）， the Dysfunctional Belief and Attitude about Sleep （DBAS）， the Disturbing Dreams and Nightmare Severity Index （DDNSI）， and the Epworth Somnolence Scale （ESS）. The objective sleep of the patients was assessed using polysomnography. The sleep electroencephalogram was filtered and the power spectral density of the brain wave was analyzed and processed for all the subjects. The subjective and objective sleep conditions of the two patient groups were compared， and the sleep electroencephalogram power spectral density of the patient groups and the control group were also compared. ResultsA comparison of subjective and objective sleep conditions between patients with depressive episode accompanied by suicidal behavior and patients with schizophrenia accompanied by suicidal behavior showed no statistically significant differences （P>0.05）. Comparisons of sleep electroencephalogram power spectral density in the W stage （average power of α wave， total power of δ wave， average power of δ wave， average power of θ wave）， N1 stage （average power of β wave， total power of α wave， total power of δ wave）， N2 stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave）， N3 stage （average power of α wave， average power of δ wave）， and R stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave） between patients with depressive episode accompanied by suicidal behavior， patients with schizophrenia accompanied by suicidal behavior， and the control group showed statistically significant differences （P<0.05 or 0.01）. The total power of δ wave in the W stage and the average power of β wave and δ wave in the N1 stage were higher in two patient groups were higher than those of the control group. The total power of α wave and the average power of α wave in the N2 stage were lower than those of the control group， while the average power of δ wave was higher than that of the control group. The average power of α wave in the N3 stage of both patient groups were lower than that of the control group， while the average power of δ wave was higher than that of the control group. The total power and average power of α wave in the R stage were lower than those of the control group， while the total power and average power of δ wave were higher than those of the control group. All the differences were statistically significant. Patients with depressive episode accompanied by suicidal behavior had higher average powers of α wave， δ wave， and θ wave in the W stage compared with the control group， while the total power of α wave in the N1 stage was lower in the former group. All these differences were statistically significant （P<0.05）. ConclusionThe depressive episode patients accompanied by suicidal behavior have highly overlapping sleep electroencephalogram abnormal patterns with those of schizophrenia patients， mainly manifested as a general decrease in α wave power （N2， N3， R stage） and a general increase in δ wave power （W， N1， N2， N3， R stage） as well as β wave power in N1 stage. At the same time， patients with depressive episode accompanied by suicidal behavior also show specific changes， including an increase in the average power of α and θ waves during the wakefulness period （W stage）， and a decrease in the total power of α wave in N1 stage. ［Funded by Guangdong Province High-level Clinical Key Specialty （with supporting funds from Shenzhen City） （number， SZGSP013）； Shenzhen Key Medical Discipline （number， SZXK041）； Shenzhen Clinical Medicine Research Center Project （number， 20210617155253001）］

ObjectiveTo analyze the research hotspots and development trends in the field of spinal cord stimulation (SCS) for spinal cord injury (SCI). MethodsLiterature about SCS for SCI was retrieve from the Web of Science (WOS) Core Collection database, with a time range from January, 1999 to July, 2025. VOSviewer 1.6.20 and CiteSpace 6.4.R2 were used to analyze the annual publication volume, countries, authors, institutions, journals and keywords. ResultsA total of 636 literatures were included. From 1999 to 2025, the overall publication trend in this field showed an upward trajectory, with recent years fluctuating but tending to stabilize. The country with the most publications was the United States (429 papers), followed by Russia (98 papers) and China (70 papers). The institution with the highest number of publications was the University of California, Los Angeles (76 papers), the author with the most publications was V. Reggie Edgerton (70 papers), and the journal with the most publications was Journal of Clinical Medicine (31 papers). The most frequently cited study focused on exploring the combination of epidural spinal cord stimulation with task-specific training to restore motor function in patients with complete SCI. Keyword analysis showed that the research hotspots in this field were mainly focused on neuroregulation mechanisms, recovery of motor and autonomic nervous dysfunction, artificial intelligence, closed-loop stimulation and brain-computer interface technology innovations. In recent years, the research focus gradually shifted from basic mechanisms to personalized and precise multifunctional rehabilitation strategies. ConclusionThe field of SCS for SCI has undergone phases of basic mechanism exploration and clinical application expansion. Current research hotspots and future trends focus primarily on the development of new stimulation paradigms and combined innovative technologies.

Objective: To explore the association role of anxiety and depressive symptoms with Internet gaming disorder (IGD) and emotional-behavioral problems among junior high school students, so as to provide references for preventing the occurrence and progression of emotional-behavioral problems in middle school students. Methods: From September to October 2024, a random cluster sampling method was adopted to select 38 069 students from 28 junior high schools in 14 counties (cities and districts) and functional areas of Jining City, Shandong Province. Surveys were conducted by Nine item Internet Gaming Disorder Scale-Short Form, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Strengths and Difficulties Questionnaire. The correlation of emotional and behavioral issues, online game addiction, anxiety and depressive symptoms among junior high school students was analyzed by Speaman correlation analysis. Mediation analysis was used to explore the role of anxiety and depressive symptoms between IGD and emotional-behavioral problems among junior high school students. Results: The detection rates of emotional-behavioral problems, anxiety symptoms, depressive symptoms, and IGD among junior high school students were 19.24 %, 9.48%, 16.69%, and 19.68%, respectively. The scores of emotional-behavioral problems, anxiety symptoms, depressive symptoms and IGD were 10.00 (6.00, 15.00), 3.00 (0.00, 7.00), and 4.00 (1.00, 8.00), 13.00 (10.00, 19.00), respectively. There were positive correlations between each pair of emotional-behavioral problem, IGD, anxiety symptoms, and depressive symptoms scores ( r =0.51-0.81, all P <0.01). Anxiety and depressive symptoms played mediating roles between IGD and emotional-behavioral problems among junior high school students, with mediating effect values of 0.16 (95% CI =0.15-0.17) and 0.12 (95% CI =0.11-0.14), respectively (both P <0.01). Conclusions Anxiety and depressive symptoms mediate the relationship between IGD and emotional-behavioral problems among junior high school students. It is necessary to identify early signs of IGD among junior high school students, strengthen intervention for anxiety and depressive symptoms, to prevent the occurrence and development of emotional and behavioral issues.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

The liver is a vital metabolic organ sustaining human life activities， and its dysfunction is closely associated with various liver diseases. In recent years， an increasing number of studies have shown that semaphorins （SEMA） play a significant role in pathological processes such as immune inflammatory response， tumor progression， and fibrosis in liver diseases by interacting with their receptors plexins and neuropilins. This article reviews the expression， functions， and molecular mechanisms of different SEMA in viral hepatitis， hepatocellular carcinoma， liver fibrosis， nonalcoholic fatty liver disease， and hepatic ischemia-reperfusion injury， and it also explores the potential application value of SEMA in the diagnosis and treatment of liver diseases， in order to provide new ideas for precise diagnosis and targeted treatment of liver diseases.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective:To evaluate the efficacy and safety of blinatumomab in adult patients with relapsed/refractory(R/R)or measurable residual disease(MRD)positive B-cell acute lymphoblastic leukemia(B-ALL)in the real world.Methods:The clinical data of 30 B-ALL patients received at least 1 course of blinatumomab therapy in the Chinese PLA General Hospital from January 1st,2021 to December 31st,2023 were retrospectively analyzed,including pre-treatment baseline clinical feature,post-treatment complete response(CR),CR with partial hematologic recovery(CRh),CR with incomplete hematologic recovery(CRi),complete MRD response rate,MRD response rate(MRD＜10-4),overall survival(OS),and disease-free survival(DFS),as well as drug-related adverse reactions.Results:Among 5 patients who were not assessed 4 were MRD negative and 1 did not receive bone marrow biopsy.In the R/R B-ALL group(13 cases),11 patients achieved CR/CRh/CRi and 10 patients achieved complete MRD response.In MRD+group(12 cases),9 patients achieved overall MRD response and 7 patients achieved complete MRD response.The median follow-up time was 8.4(95％CI:6.3-10.4)months.The median OS was 15.5(95％CI:0.7-30.3)months in the R/R group,while not reached in the MRD+group.The median DFS of the two groups were not reached.Drug-related adverse reactions occurred in 22 patients,and pyrexia was the most common(13 cases).Grade ≥3 adverse reactions occurred in 15 patients,and neutropenia was the most common(9 cases).Cytokine release syndrome occurred in 6 patients,including 5 cases with grade 1 and 1 case with grade 3.No patients interrupted therapy or died due to drug-related adverse reactions.Conclusion:Blinatumomab is effective in the treatment of R/R or continuous MRD+B-ALL with acceptable adverse reactions.

[Objective]To investigate and explore the characteristics and influencing factors of glucose metabolism in children with β-thalassemia major(β-TM)after allogeneic hematopoietic stem cell transplantation(allo-HSCT).[Methods]The follow-up data of 41 patients with β-TM who underwent HSCT at Hematopoietic Stem Cell Transplantation Department of Children's Medical Center of Sun Yat-sen Memorial Hospital,Sun Yat-sen University were retrospectively analyzed.Their glucose metabolism characteristics were evaluated through laboratory tests and the related influencing factors were analyzed.[Results]In the study,41.46％(17/41)of patients developed abnormal glucose homeostasis after HSCT.Among them,82.35％(14/17)characterized by insulin resistance,but no cases of diabetes mellitus were found.The results of insulin releasing test and oral glucose tolerance test(OGTT)showed that 45.00％(9/20)of patients had abnormal insulin releasing curve and 40.0％(8/20)had delayed serum glucose peak.The average age of HSCT in abnormal glucose homeostasis group was significantly older than that in the normal glucose homeostasis group[(8.8±3.9)years old vs(6.0±3.1)years old,P=0.015].[Conclusions]Patients with β-TM after HSCT may develop abnormal glucose homeostasis,consists largely of insulin resistance.The elder age of HSCT(≥7 years old)is a risk factor for abnormal glucose homeostasis in β-TM patients after HSCT.It is recommended to regularly monitor glucose metabolism indicators in β-TM children after HSCT,especially in elderly transplant recipients.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.