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.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

Glioblastoma (GBM) is a highly aggressive primary brain tumor characterized by poor prognosis. Conventional chemo-radiotherapy demonstrates limited therapeutic efficacy and is often accompanied by significant side effects, largely due to factors such as drug resistance, radiation resistance, the presence of the blood-brain barrier (BBB), and the activation of DNA damage repair mechanisms. There is a pressing need to enhance treatment efficacy, with BRD4 identified as a promising target for increasing GBM sensitivity to therapy. Lacking small molecule inhibitors, BRD4 can be degraded using PROteolysis Targeting Chimera (PROTAC), thereby inhibiting DNA damage repair. To deliver PROTAC, SIAIS171142 (SIS) effectively, we designed a responsive nanocapsule, MPL_(SS)P@SIS, featuring GBM-targeting and GSH-responsive drug release. Modified with 1-methyl-l-tryptophan (MLT), nanocapsules facilitate targeted delivery of SIS, downregulating BRD4 and sensitizing GBM cells to radiotherapy and chemotherapy. After intravenous administration, MPL_(SS)P@SIS selectively accumulates in tumor tissue, enhancing the effects of radiotherapy and temozolomide (TMZ) by increasing DNA damage and oxidative stress. GSH activates the nanocapsules, triggering BRD4 degradation and hindering DNA repair. In mouse models, the nanosensitizer, combined with TMZ and X-ray irradiation, efficiently inhibited the growth of GBM. These findings demonstrate a novel PROTAC-based sensitization strategy targeting BRD4, offering a promising approach for effective GBM therapy.

OBJECTIVE: To determine risk factors for cutout failure in geriatric intertrochanteric fracture patients after cephalomedullary nail fixation. METHODS: A retrospective review of 518 elderly patients who underwent cephalomedullary nail fixation for intertrochanteric fractures between January 2008 and August 2018 was conducted, including 167 males and 351 females, age from 65 to 97 years old. All patients were followed up for at least one year after surgery and divided into a healed group and a cutout group based on whether the hip screw cutout occurred. Among all patients, 10 cases experienced hip screw cutout. The general information, surgical data, and radiological data of the two groups were compared, and risk factors influencing hip screw cutout were analyzed. Propensity score matching was then performed on the cutout group based on gender, age, body mass index(BMI), and American Society of Anesthesiologists(ASA), and 40 patients from the healed group were matched at a ratio of 1∶4. Key risk factors affecting hip screw cutout were further analyzed. Multivariable logistic regression analysis was conducted to evaluate associations between variables and cutout failure. RESULTS: There were no statistically significant differences between the healed group and the cutout group in terms of age, gender, BMI, ASA, and AO classification. However, statistically significant differences were observed between the two groups in terms of reduction quality(P=0.003) and tip-apex distance(TAD), P<0.001. Multivariate analysis identified poor reduction quality OR=23.138, 95%CI(2.163, 247.551), P=0.009 and TAD≥25 mm OR=30.538, 95%CI(2.935, 317.770), P=0.004 as independent risk factors for cutout failure. CONCLUSION The present study identified poor reduction quality and TAD≥25 mm as factors for cutout failure in geriatric intertrochanteric fractures treated with cephalomedullary nails. Further studies are needed to calculate the optimal TAD for cephalomedullary nails.
Humans ; Male ; Female ; Hip Fractures/surgery* ; Aged, 80 and over ; Aged ; Risk Factors ; Retrospective Studies ; Fracture Fixation, Intramedullary/adverse effects* ; Bone Nails ; Bone Screws

Objective To develop an artificial intelligence(AI)diagnostic system for computed tomography angiography(CTA)images related to acute aortic syndrome(AAS)and to evaluate its efficacy in diagnosing and differentiating between AAS subtypes.Methods We collected the CTA images of patients diagnosed with aortic dissection(AD),intramural hematoma(IMH),or penetrating atherosclerotic ulcer(PAU)who were treated in the Department of Peripheral Vascular Diseases,The First Affiliated Hospital of Xi'an Jiaotong University,from June 2016 to June 2022.Based on the strict inclusion and exclusion criteria,2 057 CTA images were selected and extracted.Normal human aorta CTA images served as the control group.The YOLO v7 neural network was used to diagnose and differentiate subgroups of AAS patients in the CTA images,and its diagnostic performance was evaluated.Results The sensitivity,specificity,positive predictive value,negative predictive value,and total accuracy of the AAS diagnostic system based on the YOLO v7 were 98.72％,83.10％,97.82％,89.40％,and 96.92％,respectively.The total accuracy for differential diagnosis of the subgroups was 85.58％.The total accuracy of diagnosis results was significantly higher than that of differential diagnosis results(P＜0.05).Conclusion The AI-based AAS diagnostic system utilizing YOLO v7 meets the established standards for disease diagnosis.However,further research is warranted involving larger image databases and more advanced deep learning networks to improve the differentiation among AAS subtypes.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

Objective To develop an artificial intelligence(AI)diagnostic system for computed tomography angiography(CTA)images related to acute aortic syndrome(AAS)and to evaluate its efficacy in diagnosing and differentiating between AAS subtypes.Methods We collected the CTA images of patients diagnosed with aortic dissection(AD),intramural hematoma(IMH),or penetrating atherosclerotic ulcer(PAU)who were treated in the Department of Peripheral Vascular Diseases,The First Affiliated Hospital of Xi'an Jiaotong University,from June 2016 to June 2022.Based on the strict inclusion and exclusion criteria,2 057 CTA images were selected and extracted.Normal human aorta CTA images served as the control group.The YOLO v7 neural network was used to diagnose and differentiate subgroups of AAS patients in the CTA images,and its diagnostic performance was evaluated.Results The sensitivity,specificity,positive predictive value,negative predictive value,and total accuracy of the AAS diagnostic system based on the YOLO v7 were 98.72％,83.10％,97.82％,89.40％,and 96.92％,respectively.The total accuracy for differential diagnosis of the subgroups was 85.58％.The total accuracy of diagnosis results was significantly higher than that of differential diagnosis results(P＜0.05).Conclusion The AI-based AAS diagnostic system utilizing YOLO v7 meets the established standards for disease diagnosis.However,further research is warranted involving larger image databases and more advanced deep learning networks to improve the differentiation among AAS subtypes.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

OBJECTIVE To analyze the characteristics of pediatric medicines with priority review and approval for marketing in China,providing a reference for promoting enterprise R&D and production,as well as improving the supply guarantee mechanism for pediatric medicines.METHODS Based on publicly available data sources such as List of Approved Information for Pediatric Medications Subject to Priority Review and Approval,Pharnexcloud biomedical database,and National Medical Insurance Drug Directory,this study conducted a comprehensive analysis of the main characteristics of pediatric medicines with priority review and approval for marketing.RESULTS As of June 30,2024,a total of 68 pediatric medicines had been approved through the priority review and approval process,covering 12 therapeutic areas,with oral dosage forms accounting for 64.71％.The median time from application to inclusion in priority review was 35.50 days,with an average of 41.69 days.The median time from inclusion in priority review to market approval was 1.24 years,with an average of 1.42 years.This included 12 domestic new medicines,21 domestic generic medicines,35 imported medicines,as well as 29 pediatric-specific medicines and 21 orphan medicines.Additionally,31 of these medicines had been included in the medical insurance catalog,representing a proportion of 45.59％.CONCLUSIONS Currently,a trend of differentiated competition is emerging between domestic and imported pediatric medicines.The therapeutic areas for pediatric medicines are continuously expanding,and the dosage forms are becoming more tailored to children's needs.However,there are still issues such as slow progress in new medicine development,insufficient stability in the medicine review and approval process,and a need to increase the proportion of medicines included in medical insurance.

Talents are the main force for the development of traditional Chinese medicine（TCM）， and the construction of TCM talents and the reformation of talent evaluation system are essential to promote the inheritance and innovation of TCM. At present， we are still exploring and developing in the fields of the formulation， implementation and evaluation indicators of TCM talent evaluation system. However， there are shortcomings and difficulties. For instance， insufficient stratification in the evaluation， excessive emphasis on the quantity of achievements， neglecting the quality of the achievements and the actual contribution， imperfect assessment indicators， and the weak characteristics of TCM. Therefore， national ministries and commissions have jointly issued a document requesting to break the four only and set a new standard， in order to promote the construction of a scientific and technological talent evaluation system oriented by innovation value， ability and contribution. For the evaluation of TCM clinical talents， China Association for Science and Technology commissioned China Association of Chinese Medicine to build the China Clinical Cases Library of TCM（CCCL-TCM）， which aims at collecting the most authoritative and representative TCM clinical cases and exploring the advantages of applying clinical cases as masterpiece of achievement in TCM clinical talents evaluation. CCCL-TCM can promote the construction of a talent evaluation system that is more in line with the development characteristics of TCM industry， and to carry out relevant pilot in TCM colleges and institutions across the country in order to promote the reformation of TCM talent evaluation system.