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 evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Cataract is the world's leading cause of blindness, and surgery is the most effective treatment for cataract. With the development of femtosecond laser technology and ophthalmic surgical equipment, the application of femtosecond laser systems in cataract surgery is becoming increasingly widespread. It can be used in cataract surgery for corneal incisions, anterior capsulotomy, lens fragmentation, arcuate incisions and other key operations. Compared to traditional surgery, femtosecond laser assisted cataract surgery(FLACS)offers significant advantages in precision, safety and postoperative visual outcomes. Its clinical benefits have garnered growing recognition among ophthalmologists. However, the key technologies and high-precision equipment for FLACS remain predominantly controlled by Western countries. In China, the research in this field began later. This article reviews the technological advancements in FLACS, with a focus on femtosecond laser technology, optical coherence tomography(OCT), artificial intelligence, and clinical application progress. The objective is to provide theoretical foundations and practical insights for the development of ophthalmic medical technology in China.

Objective: To investigate the clinical characteristics, diagnostic approach, and multidisciplinary treatment strategy for a rare case of congenital defect presenting as a complex of hemifacial microsomia with cardiac and spinal deformities, in order to provide a reference for the clinical management of such cases Methods : The clinical data of a 9-year-old patient with hemifacial microsomia (HFM) complicated by post-operative Tetralogy of Fallot and scoliosis were retrospectively analyzed. A definitive diagnosis was established through specialized examinations, imaging studies, bone age assessment, and intellectual evaluation. The patient presented with right-sided HFM (with 3 accessory auricles, a transverse facial cleft, a microform median cleft of the upper lip, hypoplasia of the mandible and facial soft tissues, and agenesis of the right parotid gland and coronoid process), increased orbital distance, dental malalignment, congenital absence of one lateral incisor, and rampant caries in both primary and permanent dentition. The patient had undergone open-heart surgery for Tetralogy of Fallot with a patent foramen ovale four years prior and also presented with scoliosis and systemic developmental delay (bone age approximately 7 years). A retrospective analysis of the diagnosis and treatment of this type of case was conducted in conjunction with a literature review. Results: A multi-disciplinary treatment (MDT) model was adopted. The patient first received treatment for dental caries, followed by excision of the right accessory auricles, repair of the transverse facial cleft, and correction of the microform upper lip cleft under general anesthesia. A 6-month follow-up showed significant improvement in facial appearance and good recovery of oral function. The literature review indicated that hemifacial microsomia is a congenital disease characterized by the hypoplasia of multiple tissue structures on one side of the face. Its etiology may be related to impaired blood supply to the first and second branchial arches during early pregnancy. It often affects the craniofacial bones, ears, and soft tissues, leading to functional impairments in respiration, feeding, speech, and hearing, as well as psychological issues, severely impacting the quality of life in serious cases. The combination with cardiac and spinal deformities is relatively rare and requires individualized sequential treatment plans based on clinical evaluation and surgical indications. This typically includes cardiac surgical correction, spinal orthopedics, early soft and hard tissue reconstruction (e.g., distraction osteogenesis, facial cleft repair, and accessory auricle excision), orthodontic and dental management during the growth period, and final facial contouring in adulthood. Conclusion HFM can be associated with cardiac and spinal deformities, presenting with complex clinical manifestations. Early diagnosis, MDT collaboration, and sequential treatment plans are key to improving patients’ prognosis and quality of life.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

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Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

Objective:To investigate the role of heat shock transcription factor 1(HSF1)in hepatitis B virus X protein(HBx)-driven migration and invasion of hepatocellular carcinoma(HCC)cells,and to preliminarily explore the mechanism of HSF1 mediating HBx-driven HCC progression.Methods:4D label-free quantitative proteomics and Western blot were used to analyze the effect of HBx on HSF1 expression.HBx was overexpressed in the HCC cell lines Huh7 and MHCC97H,and its impact on the mRNA and protein levels and stability of HSF1 was assessed by RT-PCR and Western blot.The Cancer Genome Atlas database was used to analyze the expres-sion of HSF1 in hepatitis B virus(HBV)-associated HCC tissues and its relationship with tumor stage/grade and patient prognosis,and Western blot was used to measure the expression of HSF1 in HBV-associated HCC tissues.HBx was overexpressed in HCC cells,fol-lowed by HSF1 knockdown or cell treatment with the HSF1 inhibitor KRIBB11,and Transwell migration and invasion assay,scratch as-say,and F-actin staining experiment were performed to analyze the role of HSF1 in HBx-driven HCC cell migration and invasion.GEO and HCMDB datasets were used to identify the downstream target of HSF1,and the role of downstream target c-Myb in HSF1-me-diated HBx-driven HCC progression.Results:HBx upregulated HSF1 protein levels without significantly affecting its mRNA expres-sion,through enhancing HSF1 protein stability.HSF1 was highly ex-pressed in HBV-associated HCC tissues,and its elevated expres-sion correlated with tumor stage/grade and poor prognosis.HBx overexpression significantly promoted the migration,invasion,wound-healing capacity,and pseudopodia formation capacity of Huh7 and MHCC97H cells,while HSF1 knockdown or KRIBB11 treatment significantly attenuated the HBx-driven migration and in-vasion of HCC.HSF1 promoted the expression of the metastasis-associated protein c-Myb,and c-Myb overexpression in HSF1-knock-down HCC cells restored the promotive effect of HBx on HCC cell migration and invasion.Conclusion:HBx enhances HSF1 protein stability to promote its expression.Upregulation of c-Myb by HSF1 plays a pivotal role in HBx-driven HCC cell migration and inva-sion.Targeting HSF1 may help to delay the progression of HBV-associated HCC.

Fibromyalgia syndrome （FMS） is a refractory， chronic non-articular rheumatic disease characterized by widespread pain throughout the body， for which there are no satisfactory therapeutic drugs or options. There are rich Chinese medical therapies， and some non-drug therapies， such as acupuncture， Tai Chi， and Ba-Duan-Jin， have shown satisfactory efficacy and safety and definite advantages of simultaneously adjusting mind and body. FMS is taken as a disease responding specifically to traditional Chinese medicine （TCM） by the National Administration of Traditional Chinese Medicine in 2018. In order to clarify the research progress in FMS and the clinical advantages of TCM/integrated Chinese and Western medicine， the China Academy of Chinese Medicine organized a seminar for nearly 20 experts in Chinese and Western medicine， including rheumatology， psychology， acupuncture and moxibustion， and encephalopathy， with the topic of difficulties in clinical diagnosis and treatment of FMS and advantages of TCM and Western medicine. The recommendations were reached on the difficulties in early diagnosis and solutions of FMS， mitigation of common non-specific symptoms， preferential analgesic therapy， TCM pathogenesis and treatment advantages， and direction of treatment with integrated Chinese and Western medicine. FMS is currently facing the triple dilemma of low early correct diagnosis， poor patient participation， and unsatisfactory benefit from pure Western medicine treatment. To solve the above problems， this paper suggests that rheumatologists should serve as the main diagnostic force of this disease， and they should improve patient participation in treatment decision-making， implement exercise therapy， and fully utilize the holistic and multidimensional features of TCM， which is effective in alleviating pain， improving mood， and decreasing adverse events. In addition， it is suggested that FMS treatment should rely on both TCM and Western medicine and adopt multidisciplinary joint treatment， which is expected to improve the standard of diagnosis and treatment of FMS in China.

Objective To compare the clinical efficacy of abdominal ultrasound-guided endoscopic retrograde appendicitis therapy(ERAT)with laparoscopic appendectomy(LA)for acute uncomplicated appendicitis using propensity score matching.Methods The clinical data of 441 patients with acute uncomplicated appendicitis admitted to the Third People's Hospital of Yunnan Province from March 2020 to April 2023 were collected.The cases were classified based on the differences in surgical method and divided into the ERAT group(n = 30)and LA group(n = 411).The clinical efficacy of patients was compared between the two groups after reducing confounding bias by propensity score matching(PSM).Results After PSM,a total of 30 pairs of patients in the two groups were successfully matched,and the baseline data of the two groups met the requirements for comparability.At 24 hours after the operation,the ERAT group exhibited lower white blood cells,neutrophil counts,and C-reactive protein levels compared to the LA group,and these differences were statistically significant(P<0.05).There was no significant difference in the operation time and total effective rate between the ERAT group and the LA group(P>0.05).However,the ERAT group had lower intraoperative blood loss and shorter pain relief time compared to the LA group,and these differences were statistically significant(P<0.05).Conclusion Abdominal ultrasound-guided endoscopic retrograde appendicitis treatment is an effective,safe,and feasible technique with good prospects for the treatment of acute uncomplicated appendicitis.