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 construct a non-drug intervention program for acute chemotherapy-related nausea and vomiting in children with cancer and to evaluate its efficacy.Methods Through literature review and Delphi expert correspondence,a non-drug intervention program for acute chemotherapy-related nausea and vomiting in children with cancer was constructed.By the convenience sampling method,200 consecutive children who received chemotherapy in the neurosurgery department of a tertiary children's hospital in Zhejiang province from February 1 to October 31,2023 were included as the application subjects,with 100 cases in an experimental group and 100 cases in a control group.The experimental group applied the non-drug intervention program of acute chemotherapy-related nausea and vomiting in children with cancer,and the routine measures were applied in the control group.The incidence of nausea and vomiting,severity of vomiting,compliance rate of normal sleep duration and incidence of negative emotions were compared between the 2 groups.Results The recovery rate of the valid questionnaire in 2 rounds of expert letter inquiry was 100％,and the expert authority coefficient was 0.836.The Kendall harmony coefficients were 0.471 and 0.820(P＜0.001),and the final non-drug intervention program for pediatric acute chemotherapy-related nausea and vomiting included 5 primary,14 secondary and 18 tertiary items.The results showed that the incidence of nausea,vomiting and negative emotions in the experimental group were lower than that in the control group,with statistically significant differences(P＜0.05).The severity of vomiting was less than it in the control group,with statistically significant difference(P＜0.05).The standard rate of normal sleep time was higher than that of the control group,and the difference was statistically significant(all P＜0.05).Conclusion The non-drug intervention program of chemotherapy-related nausea and vomiting in children is scientific and feasible,and the implementation of the program can reduce the incidence of nausea,vomiting and negative emotions,reduce the severity of vomiting,and improve the standard rate of normal bedtime in children.

Objective:To construct polydopamine-coated silicified collagen(SC@PDA)by polymerization of dopamine,and to ex-plore its biological safety and photothermal antibacterial properties.Methods:Dopamine was coated on the surface of silicified colla-gen by polymerization reaction to construct SC@PDA.The surface morphology of SC@PDA was observed by SEM and TEM,the silic-ic acid release was detected by silicic acid release experiment,and the photothermal properties of SC@PDA were detected by 808 nm laser irradiation and infrared thermography.The biocompatibility of SC@PDA was evaluated by CCK-8 assay with rat bone marrow mesenchymal stem cells and acute systemic toxicity test in SD rats.The materials were co-cultured with Staphylococcus aureus(S.au-reus)and Escherichia coli(E.coli)respectively for 6 h followed by 808 nm laser irradiation and culture for 6 h,and then the antibac-terial rate of the materials was calculated by absorbance detection.Finally,the anti-infection effect was observed 7 days after implan-tation in the rat femoral defect infection model of SD rats.Results:SC@PDA maintained the silicic acid release characteristics of si-licified collagen and had good biocompatibility and good photothermal property.In vitro and in vivo antibacterial experiments showed that SC@PDA had good antibacterial activity without cytotoxicity and acut system toxicity.Conclusion:SC@PDA has biocompatibili-ty and the dopamine coating endows the silicified collagen scaffold with excellent photothermal antibacterial properties.

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 develop a highly sensitive and rapid nucleic acid detection method for the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Methods We designed,developed,and manufactured an integrated disposable device for SARS-CoV-2 nucleic acid extraction and detection.The precision of the liquid transfer and temperature control was tested.A comparison between our device and a commercial kit for SARS-Cov-2 nucleic acid extraction was performed using real-time fluorescence reverse transcription polymerase chain reaction(RT-PCR).The entire process,from SARS-CoV-2 nucleic acid extraction to amplification,was evaluated. Results The precision of the syringe transfer volume was 19.2±1.9 μL(set value was 20),32.2±1.6(set value was 30),and 57.2±3.5(set value was 60).Temperature control in the amplification tube was measured at 60.0±0.0 ℃(set value was 60)and 95.1±0.2 ℃(set value was 95)respectively.SARS-Cov-2 nucleic acid extraction yield through the device was 7.10×106 copies/mL,while a commercial kit yielded 2.98×106 copies/mL.The mean time to complete the entire assay,from SARS-CoV-2 nucleic acid extraction to amplification detection,was 36 min and 45 s.The detection limit for SARS-CoV-2 nucleic acid was 250 copies/mL. Conclusion The integrated disposable devices may be used for SARS-CoV-2 Point-of-Care test(POCT).