The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

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.

Aim To investigate the effect of neogam-bogic acid(NGA)on inducing ferroptosis in osteosar-coma K7M2 cells and subcutaneous transplanted tumor mice and explore the underlying mechanism.Methods MTT assay was employed to detect the effect of NGA(1,2,4,8,16,32,64,128 μmol·L-1)on cell prolif-eration,and the IC50 value was calculated.Calcein AM assay was used to detect cell viability.Transwell was applied to detect cell invasion.TEM was utilized to ob-serve the mitochondria morphology.K7M2 cells were subjected to treat with ferroptosis inducers erastin(Era)and inhibitors ferrostatin-1(Fer-1)to assess the levels of MDA,GSH,Fe2+,and LDH.RT-qPCR and Western blot were used to detect the mRNA and protein expression of STAT3,GPX4,and SLC7A11.A transplanted tumor model was established and treated with NGA to assess the impact of it on tumor growth and ferroptosis in vivo.HE staining was applied to ana-lyze the pathological status of tumor tissues.Nile red fluorescence staining was applied to detect the level of lipid components in tumor tissues.Results The pro-liferation,viability and invasion ability of K7M2 cells were significantly reduced after treatment with NGA at different concentrations(P＜0.05),and typical fea-tures of ferroptosis such as decreased mitochondrial vol-ume and reduced mitochondrial spine were observed.Compared to the control,the expression of MDA,Fe2+and LDH significantly increased(P＜0.01),while the content of GSH significantly decreased(P＜0.01).The ferroptosis in osteosarcoma was enhanced by the erastin,while inhibited by ferrostatin-1.In terms of mechanism,NGA inhibited the mRNA and protein ex-pression levels of STAT3,GPX4 and SLC7A11(P＜0.05).In vivo experiments confirmed that NGA signif-icantly improved the pathological state of tumor tissues,inhibited tumor growth,and induced ferroptosis in os-teosarcoma tissue cells.Conclusion NGA induces ferroptosis in osteosarcoma cells both in vitro and in vi-vo by inhibiting the STAT3/GPX4/SLC7A11 signaling axis,thereby exerting an anti-osteosarcoma effect.

This paper summarized the current status of infection and quality control of medical flexible endoscope (abbreviation:endoscope),which can identify that defect of the quality control of endoscopic forceps channels was a major cause of nosocomial infections of endoscopy. Based on this,a multifunctional quality control workstation with forceps channel of detecting flexible endoscope,and precision components included top ends for medical endoscopes has been developed,which can clearly display residual contaminants and damages in the forceps channels and precision components after the endoscope was reprocessed. It is contribute to enhance the quality control of reprocessing endoscope,and reduce cross-infection of endoscope.

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]

Objective To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

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.

The development of artificial intelligence(AI)technology has provided new avenues for the public to access health information.While both domestic and international research and practical applications of health conversational AI have emerged,there remains a lack of consensus on the key issues surrounding their development.Based on a comprehensive review of domestic and international literature and multiple rounds of expert consultations,the study focuses on six issues:the definition,characteristics,application scenarios,evaluation elements,evaluation methods,as well as prospects and challenges of AI-driven health consultation systems,and develops the practice guideline for health conversational artificial intelligence.The findings aim to provide scientific reference for promoting the innovative application of AI technology in the healthcare field.

Aim To investigate the effect of neogam-bogic acid(NGA)on inducing ferroptosis in osteosar-coma K7M2 cells and subcutaneous transplanted tumor mice and explore the underlying mechanism.Methods MTT assay was employed to detect the effect of NGA(1,2,4,8,16,32,64,128 μmol·L-1)on cell prolif-eration,and the IC50 value was calculated.Calcein AM assay was used to detect cell viability.Transwell was applied to detect cell invasion.TEM was utilized to ob-serve the mitochondria morphology.K7M2 cells were subjected to treat with ferroptosis inducers erastin(Era)and inhibitors ferrostatin-1(Fer-1)to assess the levels of MDA,GSH,Fe2+,and LDH.RT-qPCR and Western blot were used to detect the mRNA and protein expression of STAT3,GPX4,and SLC7A11.A transplanted tumor model was established and treated with NGA to assess the impact of it on tumor growth and ferroptosis in vivo.HE staining was applied to ana-lyze the pathological status of tumor tissues.Nile red fluorescence staining was applied to detect the level of lipid components in tumor tissues.Results The pro-liferation,viability and invasion ability of K7M2 cells were significantly reduced after treatment with NGA at different concentrations(P＜0.05),and typical fea-tures of ferroptosis such as decreased mitochondrial vol-ume and reduced mitochondrial spine were observed.Compared to the control,the expression of MDA,Fe2+and LDH significantly increased(P＜0.01),while the content of GSH significantly decreased(P＜0.01).The ferroptosis in osteosarcoma was enhanced by the erastin,while inhibited by ferrostatin-1.In terms of mechanism,NGA inhibited the mRNA and protein ex-pression levels of STAT3,GPX4 and SLC7A11(P＜0.05).In vivo experiments confirmed that NGA signif-icantly improved the pathological state of tumor tissues,inhibited tumor growth,and induced ferroptosis in os-teosarcoma tissue cells.Conclusion NGA induces ferroptosis in osteosarcoma cells both in vitro and in vi-vo by inhibiting the STAT3/GPX4/SLC7A11 signaling axis,thereby exerting an anti-osteosarcoma effect.