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.

ObjectiveTo identify the rate， population characteristics， and vaccination history of repeat infections among previously infected people in the current epidemic based on the rate of repeat infection and population characteristics of different mutant strains at different times in Pudong New Area of Shanghai， and to provide reference for the prevention and control strategies of novel coronavirus repeat infections. MethodsA total of 9 250 investigated subjects were randomly selected from the new cases of asymptomatic infection and confirmed cases reported by Pudong New Area from March to May 2022. The investigation mainly focused on demographic characteristics， nucleic acid or antigen test results， and symptoms after infection. The repeat infection rates among different populations were compared， and logistic regression was used to analyze the impact of gender， age， and vaccination status on repeat infections. ResultsThe survey sample of 9 250 people had a response rate of 81.85%. There were 4 043 males （53.40%） and 3 528 females （46.60%）， with a median age of 34 years old （P₂₅， P₇₅： 7， 61）. The overall vaccine uptake rate was 59.44% （4 500/7 571）. In December of 2022， there were 563 cases of repeat infection， with an infection rate of 7.44%. The lowest rate of repeat infection was seen in the 3‒ year-old group （2.86%） and the highest rate in the 30‒ year-old group （12.42%）， with significant differences between different age groups. The repeated infection rate for those who had completed their vaccinations was significantly lower （6.57%） compared to those who had not （7.11%）. The age groups of 3‒ years， 70‒79 years， as well as individuals who completed full vaccination and received booster shots were protective factors against repeat infections. ConclusionThe overall rate of reinfection among the infected in Shanghai during the spring of 2022 was low in the outbreak of the Omicron variant， and the rate of reinfection in the 3‒ year-old group was significantly lower than in other age groups. Completing the full course of vaccination significantly reduces the risk of reinfection. Although the reinfection rate is high in individuals who received booster shots， it remains a mitigating factor compared to those who do not receive the vaccine. It is recommended to continue monitoring reinfections in key populations and further strengthen immunization efforts.

Objective To construct a visual intelligent recognition model for Oncomelania hupensis robertsoni in Yunnan Province based on the EfficientNet-B4 model, and to evaluate the impact of data augmentation methods and model hyperparameters on the recognition of O. hupensis robertsoni. Methods A total of 400 O. hupensis robertsoni and 400 Tricula snails were collected from Yongsheng County, Yunnan Province in June 2024, and snail images were captured following identification and classification of 300 O. hupensis robertsoni and 300 Tricula snails. A total of 925 O. hupensis robertsoni images and 1 062 Tricula snail images were collected as a dataset and divided into a training set and a validation set at a ratio of 8:2, while 352 images captured from the remaining 100 O. hupensis robertsoni and 354 images from the remaining 100 Tricula snails served as an external test set. All acquired images were subjected to preprocessing, including cropping and resizing. Three data augmentation approaches were employed, including baseline, Mixup and Gaussian blurring, and model hyperparameters included two optimization algorithms of adaptive moment estimation (Adam) and stochastic gradient descent (SGD), two loss functions of focal loss and cross entropy loss, and two learning rate decay strategies of cosine annealing and multi-step. The intelligent recognition models of O. hupensis robertsoni and Tricula snails were constructed based on the EfficientNet-B4 model, and 7 training strategy groups were generated by combinations of different data augmentation approaches and hyperparameters. The performance of intelligent recognition models was tested with external test sets, and evaluated with accuracy, precision, recall, F1 score, loss, Youden’s index, and the area under the receiver operating characteristic curve (AUC) under different training strategies. Results The variation of loss values was comparable among intelligent recognition models with different data augmentation approaches. The Group 4 model constructed with Mixup and Gaussian blurring data augmentation approaches showed the optimal performance, with an accuracy of 90.38%, precision of 90.07%, F1 score of 89.44%, Youden’s index of 0.81 and AUC of 0.961 in the external test set. The accuracy of models using the SGD optimizer reduced by 29.16% as compared to those using the Adam optimizer (χ² = 81.325, P < 0.001), and the accuracy of models using the cross entropy loss function reduced by 0.80% as compared to the Group 4 model (χ² = 3.147, P > 0.05), while the accuracy of models using the multi-step learning rate decay strategy increased by 0.65% as compared to the Group 4 model (χ² = 0.208, P > 0.05). In addition, the model with the baseline + Mixup + Gaussianblurring data augmentation approach and hyperparameters of Adam optimizer, focal loss function and multi-step learning rate decay strategy showed the highest performance, with an accuracy of 91.03%, precision of 91.97%, recall of 88.11%, F1 score of 90.00%, Youden’s index of 0.82 and AUC values of 0.969 in external test set, respectively. Conclusions The intelligent recognition model of O. hupensis robertsoni based on EfficientNet-B4 model is accurate for identification of O. hupensis robertsoni and Tricula snails in Yunnan Province.

Objective To predict the potential geographic distribution of Oncomelania hupensis in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province. Methods The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population). Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross-validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.950 and TSS values of > 0.850 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.900 and all mean TSS values and Kappa values of > 0.800, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24%(24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.950 and TSS values of > 0.850 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models. Conclusions Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control.

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.

Objective To investigate the knowledge, attitudes and practices (KAP) towards scrub typhus control and analyse the influencing factors among residents in Longling County, Yunnan Province in 2023, so as to provide insights into management of scrub typhus in the county. Methods Two townships were randomly sampled from Longling County, Baoshan City, Yunnan Province in July 2023, and 2 to 3 administrative villages were randomly selected from each township. Then, 20 to 40 households were randomly selected from each village, and 1 to 2 villagers were surveyed in each household. Residents’ KAP towards scrub typhus control was investigated, and factor affecting residents’ KAP towards scrub typhus control were identified with independent samples t test or analysis of variance (ANOVA) and multiple linear regression analysis. Results A total of 417 questionnaires were allocated, and 410 valid questionnaires were recovered, with an effective recovery rate of 98.32%. Of all respondents, 65.85% (270/410) heard of scrub typhus but were not familiar with it, and 12.68% (52/410) and 1.95% (8/410) were familiar and very familiar with it, respectively. Residents mainly acquired scrub typhus control knowledge via their relatives and friends. The knowledge, attitude, and behavior scores of the respondents with regard to scrub typhus were (34.14 ± 13.07), (55.04 ± 6.69), and (21.40 ± 5.61), respectively, and the total score for knowledge, belief, and behavior in relation to scrub typhus prevention and control was (110.57 ± 18.80). Univariate analysis revealed that age (F = 3.12, P < 0.05), education (F = 10.77, P < 0.05), occupation (F = 4.89, P < 0.05), frequency of outdoor activities (F = 3.61, P < 0.05), and type of place of residence (t = 1.33, P < 0.05) were the factors that influenced the participants’ scores for knowledge of the prevention and control of scrub typhus. Multiple linear regression analysis revealed that literacy level (β = 10.20 to 16.71, P < 0.05) and category of residence (β = −7.23, P < 0.05) were the factors that influenced residents’ current knowledge and trust behavior in relation to scrub typhus. Conclusions Place of residence and educational level are critical factors affecting scrub typhus control among residents in Longling County, Yunnan Province. Intensified health education pertaining to scrub typhus control and appropriate behavioral interventions are required among residents living in urban areas, with a low educational level and frequent outdoor activities.

Objective To explore the surgical techniques and experiences in the treatment of Peyronie's disease using electric rotary grinding of tunica albuginea plaques followed by graft repair with tunica vaginalis or bovine pericardium under a microscope.Methods A retrospective cohort study was performed on 21 patients with severe penile curvature due to Peyronie's disease admitted in our department from January 2021 and May 2023.All of them underwent microscopic electric rotary grinding of tunica albuginea plaques followed by graft repair surgery.Short-term and mid-term outcomes were observed.Results For the 21 enrolled patients,12(57.1％)underwent repair using unilateral tunica vaginalis,3(14.3％)underwent repair using bilateral tunica vaginalis,and 6(28.6％)underwent repair using bovine pericardium.The operation time was 170～385(average 272±69)min,and the average postoperative follow-up duration was3～24(average 12.1±7.2)months.Seventeen patients(81.0％)had their penis fully extended,while 4 patients(19.0％)had slight dorsal curvature,which was less than 10°.All patients were satisfied with the shape of their penis during erection.The change in penile length was+(1.1±0.5)cm,and 9 patients(42.9％)reported early postoperative penile head numbness,which spontaneously resolved after an average duration of 3.2±1.9 months.All patients were able to successfully engage in sexual activity,with an average penile erection hardness score of 3.8.The overall satisfaction rate was 90.5％post operatively.Conclusion Meticulous dissection of Buck's fascia under a microscope is advantageous in reliably preserving dorsal neurovascular structures.Application of an electric grinding drill for plaque ablation allows for more precise release of the tunica.Graft repair of tunica albuginea defects with testicular tunica vaginalis or bovine pericardium for Peyronie's disease yields overall favorable clinical outcomes and obtains high satisfaction.It is worthy of promotion in clinical practice.

OBJECTIVE: To review the research progress in biotherapy of rotator cuff injury in recent years, in order to provide help for clinical decision-making of rotator cuff injury treatment. METHODS: The literature related to biotherapy of rotator cuff injury at home and abroad in recent years was widely reviewed, and the mechanism and efficacy of biotherapy for rotator cuff injury were summarized from the aspects of platelet-rich plasma (PRP), growth factors, stem cells, and exosomes. RESULTS: In order to relieve patients' pain, improve upper limb function, and improve quality of life, the treatment of rotator cuff injury experienced an important change from conservative treatment to open surgery to arthroscopic rotator cuff repair. Arthroscopic rotator cuff repair plus a variety of biotherapy methods have become the mainstream of clinical treatment. All kinds of biotherapy methods have ideal mid- and long-term effectiveness in the repair of rotator cuff injury. The biotherapy method to promote the healing of rotator cuff injury is controversial and needs to be further studied. CONCLUSION All kinds of biotherapy methods show a good effect on the repair of rotator cuff injury. It will be an important research direction to further develop new biotherapy technology and verify its effectiveness.
Humans ; Rotator Cuff Injuries/therapy* ; Quality of Life ; Arthroplasty ; Exosomes ; Neurosurgical Procedures

Objective:To explore the relationship between knowledge of a friend's non-suicidal self-injury (NSSI) behavior and self injury and suicide behaviors of adolescents.Methods:From January 2020 to January 2021, totally 1 683 students from a middle school in Xiamen were randomly selected by cluster sampling.The suicide items of the self-injurious thoughts and behaviors interview(SITBT) were used to assess whether students were aware of their friends' self injurious history and their self injurious behaviors.The suicide items of the mini international neuropsychiatric interview for children and adolescents (MINI-KID) were used to assess students' suicide ideation and behavior.The data were statistically analyzed by SPSS 21.0 software.Logistic regression model was used to analyze the relationship between knowledge of a friend's NSSI and adolescents' own self-reported NSSI and suicidal behaviors.Results:A total of 1 683 junior and senior high school students completed the survey, including 412 (24.4%) who knew their friend's NSSI history and 1 271 (75.6%) who did not know their friend's NSSI history.There were statistically significant differences between the adolescents known and unknown friends' NSSI histories in terms of age, gender, whether they were left-behind children, mental disorders, their own NSSI, suicide attempts, and suicidal ideation (all P<0.05). Knowledge of a friend's NSSI behavior had positive predictive effect on adolescents' own NSSI behavior ( β=0.558, OR=2.01, 95% CI=1.58-3.88), suicidal ideation( β=0.238, OR=3.03, 95% CI=2.08-5.55), and suicide attempts ( β=0.233, OR=2.88, 95% CI=1.55-5.45) (all P<0.05). Conclusion:Knowledge of a friend's NSSI behavior may have an impact on adolescents' own self-injury and suicidal behavior.