Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

AIM: To explore the factors influencing heart rate(HR)changes during small incision lenticule extraction(SMILE)surgery by monitoring HR trends at different time points of the procedure.METHODS: Prospective cohort study. A total of 69 patients who underwent SMILE surgery at the Laser Vision Correction Center of Xi'an No.1 Hospital from April to May 2024 were enrolled. Before the surgery, patients completed the State Anxiety Inventory(S-AI, questions 1-20)to assess their preoperative anxiety scores related to the next day's surgery. Baseline HR was recorded using medical pulse oximeter, and real-time HR was recorded during patient positioning, lenticule scanning, lenticule separation and extraction, and the application of postoperative eye drops.RESULTS: The HR during patient positioning was 83.61±13.87 bpm, which was significantly different from the baseline HR(77.52±10.88 bpm), HR during lenticule separation and extraction(75.54±12.52 bpm), and HR during postoperative eye drop application(76.65±10.54 bpm; all P<0.001). When stratified by median age, older patients(>26 years)had the HR during lenticule separation and extraction 76.27±9.93 bpm, which differed from the HR at positioning(84.82±14.10 bpm)and at lens scanning(82.76±13.72 bpm; all P<0.005). Stratified by gender, the HR of male patients at positioning was the highest(85.31±16.61 bpm), which differed significantly from the baseline HR(78.26±12.63 bpm), HR during lenticule separation and extraction(77.14±14.59 bpm), and HR during postoperative eye drop application(77.11±12.49 bpm; all P<0.005). There was no correlation between HR during positioning and preoperative anxiety scores(r=0.124, P=0.418).CONCLUSION: HR changes during SMILE surgery vary with different procedural stages, peaking during patient positioning and reaching the lowest point during lenticule separation and extraction. Older patients showed higher HR during positioning, and male patients exhibited higher HR during positioning.

As a neglected tropical disease, schistosomiasis remains a major public health challenge in underdeveloped areas, notably Africa. Currently, the national schistosomiasis control programmes in Africa mainly depend on foreign aids; however, conventional international aid models have multiple limitations. To enhance the effectiveness and sustainability of global schistosomiasis control programmes, this article proposes a trinity collaboration model based on international rules, China’s experiences and local needs, which is explained with China aid project of schistosomiasis control in Zanzibar as an example. Based on the successful experiences from the national schistosomiasis control programme in China, this model emphasizes the compliance with World Health Organization guidelines and fully considers local actual needs to promote the effectiveness and sustainability of the schistosomiasis control programme through integrating international resources and promoting China’s experience to meet local needs. The successful practice of the China aid project of schistosomiasis control in Zanzibar provides strong evidence that the model is of great theoretical significance and practical value to improve the efficiency of multilateral collaboration and promote global health governance.

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.

Objective: To investigate the awareness of knowledge about hepatitis C prevention and control among outpatients in Ningbo City, Zhejiang Province, and its influencing factors, so as to provide the evidence for strengthening health education on hepatitis C prevention and control. Methods: Based on sentinel surveillance of hepatitis C, the outpatients aged 15 to 65 years at seven hospitals in Yinzhou District, Cixi City and Xiangshan County of Ningbo City were selected using the convenient sampling method from April to June during 2020 and 2022. Demographic information, knowledge and behaviors related to hepatitis C prevention and control were collected through questionnaire surveys. The influencing factors for knowledge about hepatitis C prevention and control were analyzed using a multivariable logistic regression model. Results: A total of 2 792 participants were surveyed, including 1 157 males (41.44%) and 1 635 females (58.56%). The awareness rate of knowledge about hepatitis C prevention and control was 56.23%, and was lower in knowledge about hepatitis C vaccine and treatment. The awareness rates of knowledge about hepatitis C prevention and control among outpatients from 2020 to 2022 were 47.11%, 53.22% and 70.65%, respectively, showing an upward trend (P<0.05). Multivariable logistic regression analysis showed that participants aged 25 to <50 years (OR=1.358, 95%CI: 1.073-1.719), with an educational level of high school or junior college (OR=1.431, 95%CI: 1.134-1.806) or above junior college (OR=3.728, 95%CI: 2.958-4.699), with household monthly income per capita of 3 000 to <5 000 yuan (OR=1.828, 95%CI: 1.344-2.486) or ≥5 000 yuan (OR=1.858, 95%CI: 1.366-2.526), without a history of invasive treatments such as pedicure in public places (OR=1.287, 95%CI: 1.024-1.618), without a history of contact with family members' blood-contaminated items (OR=2.050, 95%CI: 1.552-2.707), and always using condoms during sexual contacts (OR=1.740, 95%CI: 1.273-2.378) had higher awareness of knowledge about hepatitis C prevention and control. Conclusions The awareness of knowledge about hepatitis C vaccine and treatment among outpatients in Ningbo City needs to be improved. Age, educational level, household monthly income per capita, history of invasive treatments such as pedicure in public places, history of contact with family members' blood-contaminated items and frequency of condom use during sexual contacts are associated with outpatients' awareness of knowledge about hepatitis C prevention and control.

ObjectiveFor prepubertal and urgently treated malignant tumor patients, ovarian tissue cryopreservation and transplantation represent more appropriate fertility preservation methods. Current clinical practices often involve freezing ovarian tissue with high concentrations of cryoprotectants (CPAs) and thawing with water baths. These processes lead to varying degrees of toxicity and devitrification damage to ovarian tissue. Therefore, this paper proposes optimized methods for vitrification of ovarian tissues based on sodium alginate hydrogel encapsulation and magnetic induction nanowarming technology. MethodsFirstly, the study investigated the effects of sodium alginate concentration, the sequence of hydrogel encapsulation and CPAs loading on vitrification efficiency of encapsulated ovarian tissue. Additionally, the capability of sodium alginate hydrogel encapsulation to reduce the required concentration of CPAs was validated. Secondly, a platform combining water bath and magnetic induction nanowarming was established to rewarm ovarian tissue under various concentrations of magnetic nanoparticles and magnetic field strengths. The post-warming follicle survival rate, antioxidant capacity, and ovarian tissue integrity were evaluated to assess the efficacy of the method. ResultsThe study found that ovarian tissue encapsulated with 2% sodium alginate hydrogel exhibited the highest follicle survival rate after vitrification. The method of loading CPAs prior to encapsulation proved more suitable for ovarian tissue cryopreservation, effectively reducing the required concentration of CPAs by 50%. A combination of 8 g/L Fe₃O₄ nanoparticles and an alternating magnetic field of 300 Gs showed optimal warming effectiveness for ovarian tissue. Combining water bath rewarming with magnetic induction nanowarming yielded the highest follicle survival rate, enhanced antioxidant capacity, and preserved tissue morphology. ConclusionSodium alginate hydrogel encapsulation of ovarian tissue reduces the concentration of CPAs required during the freezing process. The combination of magnetic induction nanowarming with water bath provides an efficient method ovarian tissue rewarming. This study offers novel approaches to optimize ovarian tissues vitrification.

Objective To prepare an advanced irrigation device equipped with a specialized nozzle designed to access the pericoronal blind sac of impacted wisdom teeth,and evaluate its efficacy in plaque removal.Methods 3D-printer was utilized to develop pericoronal models simulating mandibular wisdom teeth with high vertical impaction and varying soft tissue coverage(0%,25%,50%,and 75%,respectively)and personalized pericoronal irrigator.The obtained pericoronal models were randomly divided into 3 groups,treated with personalized precision pericoronal flushing,routine flushing and brushing,respectively,and,under a pressures of 45 psi or 75 psi(1 psi=6 894.76 Pa),were performed to clean the test surfaces of plaque-biofilm-obstructed wisdom teeth,respectively.Images of the tooth surfaces were analyzed before and after cleaning,and the cleaning rate was calculated using Python software.Results For wisdom teeth with 50%and 75%pericoronal soft tissue coverage,at a pressure of 45 psi,the precision pericoronal flushing group demonstrated significantly higher cleaning rate when compared to the brushing and routine flushing groups(P<0.05).At 0%and 25%pericoronal soft tissue coverage,the precision pericoronal flushing and brushing groups exhibited significantly higher cleaning rates than the routine flushing group(P<0.05).Furthermore,at 75 psi,the precision pericoronal flushing group achieved a significantly higher cleaning rate across all 4 levels of pericoronal soft tissue coverage than both the routine flushing and brushing groups(P<0.05).Notably,the precision pericoronal flushing group at 75 psi obtained significantly higher cleaning rate than at 45 psi across 0%,25%,and 50%pericoronal soft tissue coverage(P<0.05).Conclusion The precision pericoronal irrigation device demonstrates significantly superior cleaning efficacy for vertically impacted mandibular third molars compared to conventional irrigation devices and manual tooth brushing.It is an effective device for preventing and treating pericoronitis.

Objective To investigate whether microRNA-21-5p(miR-21)plays a protective role in hyperoxia-induced acute lung injury(HALI)by regulating ferroptosis through the STAT3/P53/SLC7A11 axis.Methods The interaction between STAT3 and P53 was analyzed by co-immunoprecipitation(Co-IP).Fifty 9-week-old male C57BL/6J mice were randomly divided into normoxia(Control)group,HALI group,miR-21 overexpression(miR-21)group,STAT3 inhibitor(HY-13818)group,and ferrostatin-1(Fer-1)group.After the mice from the miR-21 group received miR-21-5p AAV6 or empty vector via tracheal catheter instillation,the animals were then monitored for 3 weeks.The HY-13818 group was intraperitoneally injected with HY-13818(10 mg/kg)3 times weekly for 2 weeks.The Fer-1 group received 0.8 mg/kg ferrostatin-1 via tail vein injection once daily for 2 consecutive days during modeling.The HALI model was established by exposure to>90%oxygen.After 48 h of hyperoxia,blood samples were collected via orbital sampling for RT-PCR analysis of miR-21 expression.Lung tissues were harvested for wet/dry weight ratio and assessment of histopathological changes via HE staining for lung injury score.Activity of superoxide dismutase(SOD)and contents of malondialdehyde(MDA),Fe2?,glutathione(GSH),and reactive oxygen species(ROS)were measured using photocolorimetry,spectrophotometry and fluorometry.Western blotting was used to evaluate the protein expression of STAT3,P53,SLC7A11,and GPX4.Results The results of Co-IP showed that STAT3 could bind to P53.The HALI group exhibited obviously destroyed alveolar structure,disordered arrangement,thickened interval,with a large number of infiltrated neutrophils and collapsed alveoli,and had significantly increased pathological score of lung injury and ratio of lung Wwet/Ddry weight when compared with the Control group(P<0.05).In the miR-21 group,HY-13818 group and Fer-1 group,the severity of lung injury was significantly reduced,and the pathological score of lung injury and the ratio of Wwet/Ddry weight were decreased(P<0.05)when compared with the HALI group.Compared with the control group,the contents of MDA,Fe2+and ROS were increased(P<0.05),the activity of SOD and content of GSH were declined(P<0.05),the protein levels of STAT3 and P53 were increased(P<0.05),and those of SLC7A11 and GPX4 were decreased(P<0.05)in the HALI group.Compared with the HALI group,decreased MDA and ROS levels(P<0.05),enhanced SOD activity,Fe2+and GSH levels(P<0.05),down-regulation of STAT3 and P53(P<0.05)and up-regulation of SLC7A11 and GPX4(P<0.05)were observed in the miR-21 group and HY-13818 group.Conclusion MiR-21 alleviates HALI,which may be related to its inhibition of ferroptosis through the STAT3/P53/SLC7A11 axis.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.