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 compare the external morphological characteristics and movement patterns between Schistosoma japonicum and S. sinensis cercariae. Methods S. japonicum and S. sinensis cercariae were heat-fixed, and well-extended cercariae, of 50 each species, were randomly selected for measurement of body length, body width, tail stem length, and tail fork length. The external morphological characteristics of S. japonicum and S. sinensis cercariae were compared. In addition, S. japonicum-infected Oncomelania snails and S. sinensis-infected Tricula snails were observed under a microscope and the movement patterns of S. japonicum and S. sinensis cercariae were compared. Results The mean body length, body width, tail stem length, and tail fork length were (0.16 ± 0.01), (0.05 ± 0.01), (0.14 ± 0.01) mm and (0.06 ± 0.01) mm for S. japonicum cercariae, and (0.13 ± 0.01), (0.05 ± 0.01), (0.13 ± 0.01) mm and (0.06 ± 0.01) mm for S. sinensis cercariae, respectively, and there were significant differences in terms of cercaria body length (t = 14.583, P < 0.05) and tail stem length (t = 3.861, P < 0.05), while no significant differences were seen in terms of body width (t = 0.896, P > 0.05) or tail fork length (t = −0.454, P > 0.05). Microscopy revealed that the tails of both S. japonicum and S. sinensis cercariae swung from side to side and there was no significant difference in their movement pattern. Conclusion S. sinensis and S. japonicum cercariae share highly similar external external morphological characteristics and movement patterns.

Schistosomiasis was once hyper-endemic in Yunnan Province. Following concerted efforts for over 70 years, remarkable achievements have been made for schistosomiasis control in the province. In 2004, the Mid- and Long-term Plan for Schistosomiasis Prevention and Control in Yunnan Province was initiated in Yunnan Province, and the target for transmission control of schistosomiasis was achieved in the province in 2009. Following the subsequent implementation of the Outline for Key Projects in Integrated Schistosomiasis Control Program (2009—2015) and the 13th Five - year Plan for Schistosomiasis Control in Yunnan Province, no acute schistosomiasis had been identified in Yunnan Province for successive 12 years, and no local Schistosoma japonicum infections had been detected in humans, animals or Oncomelania hupensis snails for successive 6 years in the province by the end of 2020. The transmission of schistosomiasis was interrupted in Yunnan Province in 2020. This review summarizes the history of schistosomiasis, changes in schistosomiasis prevalence and progress of schistosomiasis control in Yunnan Province, and proposes the future priorities for schistosomiasis control in the province.

Background Excessive radon exposure is considered the second risk factor for lung cancer. Since the opening of the subway in a city of Zhejiang Province, the exposure level of radioactive gas radon in subway stations and its impact on occupational health have become one of the important issues of public concern. Objective To monitor the radon concentration of subways in a city in Zhejiang Province and explore the effect of radon exposure on chromosome aberration and micronuclei in the working population. Methods A total of 55 vehicle control rooms of 55 stations affiliated to two different subway lines in a city were measured for one year; the 110 ticket offices and 55 security checkpoints from the same 55 stations were measured from 16 March to 14 June. The radon concentrations were compared by job types, subway lines, and seasons referring to Measurement methods for determination of radon in environmental air (HJ 1212-2021). Peripheral blood lymphocyte chromosome aberration and micronucleus analyses were conducted in 165 subway workers from monitoring sites for three different job types, then the influencing factors were analyzed. The detection methods were adopted from the standards of Test and assessment of chromosomal aberrations on occupational health examinations for radiation workers (GBZ/T 248-2014) and Standard for the method of micronucleus detection in lymphocytes on occupational health examination for radiation workers and exposure dose estimation (GBZ/T 328-2023). Results The radon concentration range of the target subways in Zhejiang Province was 10-320 Bq·m⁻³, all lower than the national limit (≤400 Bq·m⁻³). The differences in radon radioactivity levels among different lines, job types, and time segments were statistically significant (P<0.05). The rates of chromosomal aberration and micronucleus formation among the 165 subjects were 0.224% and 0.024%, respectively. There were significant differences in the rates of chromosome aberration and micronuclei among different jobs (vehicle control room, ticket office, security checkpoint) (P<0.05), but the abnormal rates were lower than the limits of the corresponding national standard. No significant correlation was found between jobs and chromosomal aberrations or micronuclei (P>0.05). Chromosome aberration and micronuclei varied by age, subway station seniority, and smoking (P<0.05). No effect of the above factors on chromosome aberration and micronuclei was observed by logistic regression (P>0.05). Conclusion The radon concentration in the target subway system is at a normal level. The rates of chromosomal aberration and micronucleus formation vary by jobs, but both are lower than the corresponding national limits. Therefore, radon exposure has not yet caused outstanding health impact on the subway workers.

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).