Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

In order to investigate the teaching effectiveness of artificial intelligence(AI)in molecular bi-ology,this study selected students from the Animal Medicine major of the College of Animal Science and Technology at Hebei North University in 2022 and 2023 as research subjects.There was no significant difference in professional foundation,admission scores,and other aspects between the two grades,and they were taught by the same lecturer to ensure the reliability of research results.The 2022 students will adopt the traditional teaching mode,while the 2023 students will implement the AI-enabled teaching mode,which includes four stages:pre class exploration,in class assistance,post class learning support,and teaching reflection and improvement.Before class,the teaching team pushes teaching videos of vari-ous knowledge points in the course and relevant preview materials organized by the AI system to students to complete self-learning,and use AI systems to track students' learning difficulties.In class,the teacher uses various teaching methods such as case teaching,group discussions,AI animation demonstrations and virtual experiments,etc..Thus,they provide in-depth explanations of key contents based on the feed-back data from the intelligent learning companion AI system,promoting students' understanding of the knowledge.After class,the AI system generates personalized learning plans for students and provides dif-ferent levels of learning resources to broaden their horizons.At the same time,the AI system provides teachers with students'learning data analysis reports,and teachers can adjust and optimize their teaching plans accordingly.Research has found that students in the 2023 AI-empowered teaching class have signif-icantly higher satisfaction in multiple dimensions such as learning interest,understanding and mastery of knowledge points,and cultivation of scientific research thinking than those in the 2022 traditional teach-ing class.In terms of student participation in comprehensive activities,the proportion of 2023 students participating in subject competitions and innovation and entrepreneurship activities has significantly in-creased.In terms of academic performance,the mid-term,laboratory,and final grades of 2023 students are higher than those of 2022 students,with a significant increase in the excellence rate and a significant decrease in the failure rate.The results indicate that the application of AI technology in molecular biology teaching has stimulated students' interest in learning,helped them better understand and master knowl-edge,significantly improved their academic performance.In sum,it has a positive impact on improving teaching quality.

In recent years,the incidence and mortality of heatstroke have been increasing annually alongside global warming,with a marked rise in cases exhibiting atypical symptoms.To address the increasingly complex challenges in heatstroke prevention and treatment,Heatstroke Prevention and Treatment Research Center of Chinese PLA,Expert Group of Heatstroke Prevention and Treatment of Chinese PLA,and Chinese PLA Professional Committee of Critical Care Medicine have jointly developed this guideline(2025 edition).Utilizing the Grading of Recommendations Assessment,Development and Evaluation(GRADE)system,Appraisal of Guidelines for Research and Evaluation(AGREE)criteria,and Reporting Items for Practice Guidelines in Healthcare(RIGHT)standards,and based on the 2015 draft"Expert Consensus on the Standardized Diagnosis and Treatment of Heatstroke"and the 2019"Chinese Expert Consensus on the Diagnosis and Treatment of Heatstroke",this guideline has been crafted.This guideline provides 25 evidence-based recommendations to guide the prevention,treatment and research of heatstroke,which thoroughly covers 8 critical domains:clinical classification,pathophysiological mechanisms,clinical manifestations,diagnostic criteria,differential diagnosis,treatment protocols,rehabilitation and return to work,and prevention.

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]

Relevant China's literature on the application of brain-computer interface technology in the field of rehabilita-tion of stroke patients was retrieved in the China Knowledge Network database from its establishment to December 31,2024,and CiteSpace visual analysis software was used to analyze the selected literature in terms of trend of annual publica-tion number,author collaboration network,keyword co-occurrences and emergences and to generate a corresponding knowledge map.It's pointed out brain-computer interface technology showed significant application potential for motor function recovery and neurorehabilitation,which had the research hotspots of the cross technologies covering motor imagina-tion,rehabilitation training and virtual reality and the research frontiers of the fusion application of intelligent algorithms of deep learning and pattern recognition.The challenges and future development directions of the field were investigated,and references were provided for promoting the application of brain-computer interface technology to rehabilitation of sroke patients in China.[Chinese Medical Equipment Journal,2025,46(9):65-69]

Objective:To investigate the predictive value of color Doppler ultrasound combined with electrocardio-gram for right heart dys function in patients with pulmonary heart disease(PHD).Methods:A total of 100 PHD patients admitted in Dongcheng Branch of First Affiliated Hospital of Anhui Medical University between January 2020 and December 2023 were retrospectively analyzed.According to results of 6min walking test(6MWT),pa-tients were divided into good right heart function group(n=64,≥350m)and right heart dysfunction group(n=36,＜350m).The indexes of cardiac color ultrasound[isovolumic relaxation time(IVRT),isovolumetric contraction time(IVCT)and right ventricular Tei index],ECG[24h mean R-R interval standard deviation(SDNN),normal R-R interval standard deviation per 5min(SDANN)and the ratio of low frequency components to high frequency components(LF/HF)]were compared between two groups.Receiver operating characteristic(ROC)curve was drawn to analyze the diagnostic value of color Doppler ultrasound,ECG and their combination for right heart dys-function in PHD patients.Spearman correlation coefficient was used to analyze the association of color Doppler ul-trasound,ECG and their combination with right heart dysfunction in PHD patients.Results:Compared with those in good right heart function group,patients in right heart dysfunction group had significant higher IVRT[(120.64±14.08)ms vs.(97.87±10.93)ms],IVCT[(84.28±12.33)ms vs.(71.92±10.61)ms]and Tei index[(0.85±0.11)vs.(0.63±0.07)](P＜0.001 all),and significant lower SDNN[(75.52±12.58)ms vs.(85.58±11.75)ms],SDANN[(63.86±10.92)ms vs.(76.75±11.71)ms]and LF/HF[(1.33±0.19)vs.(1.84±0.27)](P＜0.001 all).ROC curve indicated that the AUC of color Doppler ultrasound combined ECG in diagnosing right heart dysfunction in PHD patients was 0.911(95％CI 0.838～0.959),which was significantly higher than those of color Doppler ultrasound[0.775(95％CI 0.681～0.853),Z=2.404,P=0.016]and ECG[0.688(95％CI 0.588～0.777),Z=3.968,P=0.001]alone.Spearman correlation analysis indicated that there was a significant positive correlation of color Doppler ultrasound(r=0.547),ECG(r=0.375)and their combination(r=0.810)with right heart dysfunction in PHD patients(P＜0.001 all),and the correlation between combined detection and right heart dysfunction in PHD patients was significantly higher.Conclusion:Color Doppler ultrasound combined with ECG possesses high diagnostic performance for right heart dysfunction in PHD patients.

In order to investigate the teaching effectiveness of artificial intelligence(AI)in molecular bi-ology,this study selected students from the Animal Medicine major of the College of Animal Science and Technology at Hebei North University in 2022 and 2023 as research subjects.There was no significant difference in professional foundation,admission scores,and other aspects between the two grades,and they were taught by the same lecturer to ensure the reliability of research results.The 2022 students will adopt the traditional teaching mode,while the 2023 students will implement the AI-enabled teaching mode,which includes four stages:pre class exploration,in class assistance,post class learning support,and teaching reflection and improvement.Before class,the teaching team pushes teaching videos of vari-ous knowledge points in the course and relevant preview materials organized by the AI system to students to complete self-learning,and use AI systems to track students' learning difficulties.In class,the teacher uses various teaching methods such as case teaching,group discussions,AI animation demonstrations and virtual experiments,etc..Thus,they provide in-depth explanations of key contents based on the feed-back data from the intelligent learning companion AI system,promoting students' understanding of the knowledge.After class,the AI system generates personalized learning plans for students and provides dif-ferent levels of learning resources to broaden their horizons.At the same time,the AI system provides teachers with students'learning data analysis reports,and teachers can adjust and optimize their teaching plans accordingly.Research has found that students in the 2023 AI-empowered teaching class have signif-icantly higher satisfaction in multiple dimensions such as learning interest,understanding and mastery of knowledge points,and cultivation of scientific research thinking than those in the 2022 traditional teach-ing class.In terms of student participation in comprehensive activities,the proportion of 2023 students participating in subject competitions and innovation and entrepreneurship activities has significantly in-creased.In terms of academic performance,the mid-term,laboratory,and final grades of 2023 students are higher than those of 2022 students,with a significant increase in the excellence rate and a significant decrease in the failure rate.The results indicate that the application of AI technology in molecular biology teaching has stimulated students' interest in learning,helped them better understand and master knowl-edge,significantly improved their academic performance.In sum,it has a positive impact on improving teaching quality.

Biochemistry,as a fundamental course for science and engineering majors related to biology and chemistry,holds a significant position in the curriculum.The course team at Dalian Minzu University is committed to teaching innovation,adopting the outcome-based education(OBE)concept for teaching de-sign and incorporating ideological and political elements,in order to achieve the dual goals of knowledge transmission and value guidance.The team has established a three-dimensional teaching goal of"knowl-edge,morality,and ability",covering"consolidating core knowledge,cultivating moral sentiment,and enhancing innovation ability".Through a multi-dimensional integrated teaching method of"three integra-tions and five combinations",multiple rounds of teaching practice have been carried out in the applied chemistry major using"classification and specificity of enzyme"as an example.The output of teaching re-sults and survey questionnaires show that students highly recognize the teaching design and its"process-based learning"evaluation method,fully reflecting the student-centered teaching idea.Research has shown that OBE design combined with ideological and political elements can effectively promote students' knowl-edge acquisition,moral growth,and innovation ability improvement in the course of Biochemistry.This teaching design not only helps students construct correct worldviews,outlooks on life,and values,but also significantly enhances their innovative thinking and practical abilities.This teaching design can not only ef-fectively improve the teaching quality of the course,but also provide new perspectives and ideas for the teaching design of Biochemistry,realizing the organic integration of professional knowledge imparting and i-deological and political education,and has certain innovation and practical significance.

Objective To design a new type of elastic gloves for burn scar rehabilitation to solve the problems of conventional elastic gloves in pressure distribution,elasticity maintenance and absorption of sweat stains.Methods The new elastic gloves was made of non-woven fabric by spandex material,which was composed of external and internal parts.The main body of the external part was used as the primary structure of the gloves,which was provided with a sealing strip,a storage bag,a drawstring,etc.The internal part consisted of a bonding sheet,an elastic band,a fiber sheet,an absorbent sponge,some breathable holes,etc.Results The new elastic gloves designed could be used for the pressure therapy for the scars on the opisthenar,palm side,finger web and purlicue with scar proliferation inhibitted effectively,and the breathable hole and absorbent sponge contributed to the absorption of the sweat of the patient.Conclusion The new type of elastic gloves gains advantages in elasticity,wearing comfort and effectiveness of the pressure therapy for purlicue and finger web,and can be used for the pressure therapy to inhibit proliferative scarring after burns.[Chinese Medical Equipment Journal,2025,46(8):118-120]

To compare and analyze the clinical manifestations,laboratory characteristics,imaging findings,and treatment outcomes of patients with acute and chronic brucellosis,a retrospective analysis was conducted on 258 patients with brucellosis(202 in the acute group and 56 in the chronic group)hospitalized in Xinkang Hospital in Dalad Banner,Ordos City,Inner Mongolia Autonomous Region,from November 2023 to November 2024.General data,epidemiological characteristics,clinical presentations,laboratory test results,imaging findings,treatment outcomes,and prognosis were collected.The incidences of fever(51.5%vs 7.1%),fatigue(30.2%vs 12.5%),joint pain(42.9%vs 16.1%),and muscle pain(9.9%vs.1.8%)were significantly higher in the acute phase group(all P<0.05).The incidence of osteoarthritis complications was higher in the chronic brucellosis group(51.8%vs 8.9%,χ2=75.697,P<0.01).Univariate ANOVA analysisshowed that the Serum Agglutination Tests(SAT),alanine aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TBIL),creatinine(CRE),C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),and bone destructionexhibited statistically significant differences between the acute and chronic phases of brucellosis(all P<0.05).Multivariate logistic regression analysis indicated that abnormal ALT(OR=14.18,95%CI:1.11-181.72;P=0.041)and bone destruction(OR=0.16,95%CI:0.04-0.63;P=0.009)were associated with chronic brucellosis.After treatment,all patients experienced have symptom relief in varying degrees,with 157 patients(60.9%)cured and 101 patients(39.1%)symptomatic improved(P<0.01).In conclusion,the incidences of fever,fatigue,and joint pain in patients during the acute phase is significantly higher than that those in patients during the chronic phase,while the incidence of osteoarthritis complications is higher in chronic phase patients.The incidences of abnormal SAT,ALT,AST,TBIL,CRE,CRP,and ESR,and bone destruction varies at different stages of brucellosis.Of those,abnormal ALT and bone destruction show a stronger association with,which can assist the clinical staging of brucellosis.