ObjectiveTo investigate the therapeutic effect of wall-broken ganoderma lucidum spore powder （GLS） on a mouse model of hepatocellular carcinoma and to explore its underlying mechanism. MethodsFifty 2-week-old C57BL/6J mice were divided into a control group， a model group and low， medium and high-dose GLS groups（0.25， 0.5， 1.0 g/kg ）， with 10 mice in each group. A DEN/CCL₄ mouse hepatocellular carcinoma model was established， and GLS was administered by gavage starting from the 8th week， once a day for 14 weeks. At the end of the final administration， the number of liver nodules was observed ， and the serum alpha-fetoprotein （AFP） was detected using enzyme-linked immunosorbent assay. The content of catalase （CAT） in serum and liver tissue was determined by ammonium molybdate method. The content of reduced glutathione （GSH） in serum and liver tissue was measured by microplate assay. The content of glutathione peroxidase （GSH-PX） in serum and liver tissue was detected by colorimetric method. Immunohistochemistry （IHC-P） was employed to detect the protein expression of proliferating cell nuclear antigen （PCNA）. R eal-time fluorescence quantitative polymerase chain reaction was utilized to detect the relative expression of nuclear factor E2-related factor 2 （Nrf2）， Kelch-like epichlorohydrin-associated protein 1 （Keap1）， NAD（P）H quinone oxidoreductase 1 （Nqo1）， heme oxygenase-1 （Ho-1） and glutamate cysteine ligase catalytic subunit （Gclc） mRNA. ResultsCompared with the control group， the content of serum AFP were significantly higher in the model group （P<0.01）， while the contents of CAT， GSH and GSH-PX in liver and serum were significantly lower in the model group （P<0.01）. The relative expression of Keap1 and Nqo1 mRNA was significantly higher （P<0.01）， the relative expression of Nrf2， Ho-1， Gclc mRNA relative expression was significantly lower （P<0.01）， and the positive expression rate of PCNA was significantly higher （P<0.01）. Compared with the model group， the total number of liver nodules and content of serum AFP in the administered group were significantly lower （P<0.01）， and the contents of CAT， GSH， and GSH-PX in the liver and serum of mice significantly increased （P<0.05 or P<0.01）. The expression of Keap1 and Nqo1 mRNA significantly decreased （P<0.05）. The expression of Nrf2， Ho-1 and Gclc mRNA significantly increased （P<0.05）， and positive expression rate of PCNA significantly decreased （P<0.01）. ConclusionGLS has a significant protective effect on DEN/CCL4 -induced mouse hepatocellular carcinoma model， and the mechanism of action is related to the regulation of oxidative stress in mouse liver.

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.

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.

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.

Objective:Analyze the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and evaluate the application value of nomogram predic-tion models.Methods:Collected clinical data of 587 patients with gallstones and multiple common bile duct stones who underwent surgical treatment at Beijing Fengtai Hospital from January 2022 to January 2024.They were divided into a training cohort(n=410)and a validation cohort(n=177)according to a 7∶3 ratio.Analyzed the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and constructed a nomogram prediction model based on this.Results:The recurrence rate of postoperative common bile duct stones in the training queue was 38.05％(156/410).Age,BMI,intrahepatic bile duct stones,initial course of dis-ease,duodenal diverticulum,biliary tract infection,history of biliary surgery,thickness of the common bile duct wall,num-ber of multiple stones in the common bile duct,diameter of the common bile duct,and dysfunction of the Oddis sphincter in the duodenal papilla during ERCP examination are independent risk factors for postoperative recurrence in patients with gallbladder stones combined with multiple stones in the common bile duct(P＜0.05).The AUC of the constructed nomo-gram prediction model in the training queue and validation queue were 0.854 and 0.889,respectively.The Hosmer Lem-eshow fitting test results showed that there was no statistically significant difference between the predicted probability and the actual probability of the prediction model(x2=3.952,P=0.865),indicating that this model has good predictive abil-ity.Conclusion:The nomogram prediction model based on various risk factors can effectively predict the risk of post-operative common bile duct stone recurrence in patients with gallstones and multiple common bile duct stones.

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.

Myocardial fibrosis(MF)is the leading cause of car-diac insufficiency.Its complex pathogenesis and lack of effective treatment are key issues to be addressed in the cardiovascular field.Mitochondrial quality control system(MQC)is an impor-tant mechanism for eukaryotic cells to maintain the stability of mitochondrial form,quantity and quality.MQC disorders,which are characterized by low level of mitochondrial biogenesis,exces-sive mitochondrial oxidative stress,mitochondrial autophagy de-fect and mitochondrial dynamics disorder,play a crucial role in mediating the pathophysiological process of MF.Consequently,this article reviews the role of MQC in MF pathogenesis and the latest research,in order to better understand the molecular mech-anism of MF and provide reference for the development of more natural drugs in the future.

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]

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.