As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

AIM To study the effects of total flavonoids of Dracocephalum Moldavica L.(TFDM)on reducing the inflammatory response of RAW264.7 macrophages induced by ox-LDL via the nuclear factor κB(NF-κB)/NOD-like receptor 3(NLRP3)signaling pathway.METHODS The RAW264.7 macrophages cultured in vitro were divided into the normal group,the model group(50 μg/mL ox-LDL),the TFDM group(100 μg/mL TFDM+50 μg/mL ox-LDL),the NF-κB inhibitor group(10 μmol/L Bay11-7821+50 μg/mL ox-LDL)and the TFDM+NF-κB inhibitor group(100 μg/mL TFDM+10 μmol/L Bay11-7821+50 μg/mL ox-LDL).The cells had their viability assessed by CCK-8 method;their ROS expression detected by the ROS kit;their mRNA expressions of NF-κB p65,NLRP3,Caspase-1,IL-18 and IL-1β detected by RT-qPCR;their protein expressions of NF-κB p65,IκBα,NLRP3,pro-Caspase-1,Caspase-1,IL-18 and IL-1β by Western blot;their protein expressions of NF-κB p65 and NLRP3 detected using immunofluorescence method.RESULTS Compared with the normal group,the model group showed increased ROS expression(P＜0.01);increased mRNA expressions of NF-κB p65,NLRP3,Caspase-1,IL-18 and IL-1β(P＜0.05,P＜0.01);decreased protein expressions of IκBα and cytoplasmic NF-κB p65(P＜0.01);increased protein expressions of nuclear NF-κB p65,NLRP3,Caspase-1,IL-1 β and IL-18(P＜0.01);and increased fluorescence intensity of NF-κB p65 and NLRP3(P＜0.01).Compared with the model group,the groups intervened with either TFDM or TFDM+inhibitor displayed decreased ROS expression(P＜0.01);the groups administrated with TFDM or NF-κB inhibitor,or TFDM+inhibitor showed decreased mRNA expressions of NF-κB p65,NLRP3,Caspase-1,IL-18 and IL-1β(P＜0.05,P＜0.01),increased protein expressions of IκBα and cytoplasmic NF-κB p65(P＜0.05,P＜0.01),decreased protein expressions of nuclear NF-κB p65,NLRP3,Caspase-1,IL-1β and IL-18(P＜0.05,P＜0.01),and decreased fluorescence intensity of NF-κB p65 and NLRP3(P＜0.01).There existed no significant group difference between the TFDM group and the NF-κB inhibitor group(P＞0.05).The TFDM+inhibitor group demonstrated decreased mRNA expressions of IL-1βand IL-18(P＜0.05),increased IκBα protein expression(P＜0.05),decreased protein expressions of nuclear NF-κB p65,NLRP3,Caspase-1,IL-1 β and IL-18(P＜0.05),and decreased fluorescence intensity of NLRP3 protein(P＜0.05).CONCLUSION TFDM can inhibit the ox-LDL-induced inflammatory response of RAW264.7 macrophages,and the mechansism may be associated with the reduced ROS expression and inflammatory factors due to the inhibited activation of the NF-κB/NLRP3 signaling pathway.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To compare the therapeutic effect of ureteroscopy(RIRS)combined with fine needle ultra fine channel percutaneous nephrolithotomy(SMP)and microchannel percutaneous nephrolithotomy(MPCNL)in the treatment of complex kidney stones.Methods:100 patients with complex kidney stones who were admitted to our hospital from March 2022 to May 2024 were divided into control group of 50 cases and study group of 50 cases by using random number table method.The control group patients received MPCNL treatment,while the study group patients received fine needle SMP combined with RIRS treatment.The clinical indicators,pain status,inflammatory stress indicators,renal function indicators,and incidence of complications between the two groups were compared.Results:Surgical time in the study group was longer than that in the control group,the intraoperative blood loss was less than that of the control group,the postoperative hospitalization time and time to get out of bed after surgery were shorter than those in the control group(P＜0.05).There was no statistically significant difference in the success rate of stone removal between the two groups(P＞0.05).The visual analog pain scale(VAS)scores in the study group were lower than those in the control group at 6 h,24 h,and 48 h after surgery(P＜0.05).Serum procalcitonin(PCT),high-sensitivity C-reactive protein(hs-CRP),cortisol(Cor),norepinephrine(NE),urea nitrogen(BUN),serum creatinine(Scr),and cystatin C(Cys C)in the study group were lower than those in the control group at 3 d after surgery(P＜0.05).There was no statistically significant difference in the incidence of complications between the two groups(P＞0.05).Conclusion:Compared with MPCNL treatment for complex kidney stones,fine needle SMP combined with RIRS can reduce intraoperative bleeding,shorten time to get out of bed and hospitalization time,alleviate inflammatory stress response,and reduce damage to kidney function and postoperative pain without increasing the incidence of complications.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Background and purpose:According to the latest data from the National Cancer Center,the incidence rate and mortality of lung cancer in China rank first among all malignant tumors,and 85%are non-small cell lung cancer(NSCLC).In recent years,immunotherapy based on programmed cell death protein-1(PD-1)/programmed death ligand-1(PD-L1)immune checkpoint inhibitors(ICIs)has made breakthrough progress in lung cancer,bringing more survival benefits to lung cancer patients.This study aimed to evaluate the cost-effectiveness of three major PD-L1 testing assays in guiding immunotherapy for patients with NSCLC,and to provide empirical evidence to guide the selection of cost-effective diagnosis and ICIs monotherapy regimens for NSCLC patients in China.Methods:From a healthcare system perspective,a decision-tree model was constructed to simulate the cost and effectiveness(percentage of the patients who were successfully diagnosed and who were correctly prescribed and underwent correct treatment according to China treatment guidelines)of employing Ventana PD-L1 IHC(SP263)assay,PD-L1 IHC 22C3 pharmDx,and Dako 22C3 antibody concentrate in early to mid-stage and advanced NSCLC patients in China,respectively.The cost-effectiveness of SP263 assay compared to other testing methods was assessed through the incremental analysis.The robustness of the base case analysis results was validated by using one-way sensitivity analysis and probabilistic sensitivity analysis.Results:When considering atezolizumab monotherapy following chemotherapy for early to mid-stage(Ⅱ A-Ⅲ B)NSCLC patients,in comparison to the 22C3 assay or 22C3 antibody concentrate,the SP263 assay incurred an additional cost of 9 449 yuan per successfully diagnosed and treated patient.The SP263 assay,which can guide multiple ICIs monotherapies(e.g.,atezolizumab,pembrolizumab)for advanced(Ⅳ)NSCLC patients,was dominant by achieving a higher percentage of successfully diagnosed and treated patients at a lower cost compared to Dako 22C3 assay and Dako 22C3 antibody concentrate.One-way sensitivity analysis and probabilistic sensitivity analysis both confirmed the robustness of the results.Conclusion:The Ventana PD-L1 IHC SP263 assay was cost-effective,compared to Dako PD-L1 IHC 22C3 assay and Dako 22C3 antibody concentrate for the immunotherapy treatment for both stage Ⅱ A-Ⅲ B and stage Ⅳ NSCLC patients in China.

Objective:To evaluate the efficacy of remimazolam-based anesthesia in daytime laparoscopic cholecystectomy.Methods:In this multicenter, non-inferiority, randomized controlled trial, 300 American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ patients of either sex, aged 18-60 yr, with body mass index of 18-28 kg/m 2, who underwent daytime laparoscopic cholecystectomy under general anesthesia with tracheal intubation at Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine, the Fourth Affiliated Hospital of Zhejiang University School of Medicine, Jinhua Hospital Affiliated to Zhejiang University School of Medicine, Hangzhou First People′s Hospital Affiliated to Westlake University School of Medicine, Ningbo No. 2 Hospital, and the Second Affiliated Hospital of Nanchang University from August 2021 to August 2023, were selected and divided into 2 groups ( n=150 each) using a random number table method: remimazolam group (R group) and propofol group (P group). Anesthesia was induced as follows: Sufentanil was intravenously injected at a rate of 0.5 μg/kg, remimazolam was intravenously injected at a rate of 0.3 mg/kg in group R, propofol was intravenously injected at a rate of 2.0-2.5 mg/kg in group P, and cisatracurium besilate was intravenously injected at a rate of 0.2 mg/kg after loss of consciousness in two groups. The patients were mechanically ventilated after tracheal intubation. Anesthesia was maintained as follows: Remimazolam was intravenously injected at a rate of 0.5-1.0 mg·kg -1·h -1 in group R, propofol was intravenously injected at a rate of 4-10 mg·kg -1·h -1 in group P, and remifentanil was intravenously infused at a rate of 0.25-2.00 μg·kg -1·min -1, maintaining intraoperative bispectral index value of 40-60. The success rate of sedation was recorded, and non-inferiority tests were conducted. The time to loss of consciousness, emergence time, extubation time, recovery time of orientation, time of stay in post-anesthesia care unit and occurrence of delayed emergence were recorded. Liver function and renal function were measured before operation and within 24 h after operation. The occurrence of abnormal alanine transaminase, abnormal aspartate transaminase, abnormal creatinine and abnormal urea was recorded. The occurrence of adverse reactions during and after operation was recorded. Results:The success rates of sedation were 98.6% and 99.3% in group R and group P, respectively, there was no statistically significant difference in the success rate of sedation between the two groups ( P>0.05), and the difference in the success rates of sedation between the two groups was -0.007 (95% confidence interval-0.0301-0.0161), which met the pre-set non-inferiority criteria(95% confidence interval >-0.055). Compared with group P, the time to loss of consciousness and recovery time of orientation were significantly prolonged, and the incidence of delayed emergence was increased ( P<0.05), and no statistically significant changes were found in the emergence time, extubation time, time of stay in post-anesthesia care unit and severity of postoperative nausea and vomiting in group R ( P>0.05). There was no statistically significant difference in the abnormal rates of alanine transaminase, aspartate transaminase, creatinine and urea before and after operation between the two groups ( P>0.05). Conclusions:The efficacy of remimazolam-based anesthesia in daytime laparoscopic cholecystectomy is not inferior to that of propofol-based anesthesia.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.