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.

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.

To explore the variation laws of volatile oil during the extraction process of Artemisiae Argyi Folium and its impact on the quality of the medicinal solution, as well as to achieve precise control of the extraction process, this study employed headspace solid phase microextraction gas chromatography-mass spectrometry(HS-SPME-GC-MS) in combination with multiple light scattering techniques to conduct a comprehensive analysis, identification, and characterization of the changes in volatile components and the physical properties of the medicinal solution during the extraction process. A total of 82 volatile compounds were identified using the HS-SPME-GC-MS technique, including 21 alcohols, 15 alkenes, 14 ketones, 9 acids, 6 aldehydes, 5 phenols, 3 esters, and 9 other types of compounds. At different extraction time points(15, 30, 45, and 60 min), 71, 72, 64, and 44 compounds were identified in the medicinal solution, respectively. It was observed that the content of volatile components gradually decreased with the extension of extraction time. Through multivariate statistical analysis, four compounds with significant differences during different extraction time intervals were identified, namely 1,8-cineole, terpinen-4-ol, 3-octanone, and camphor. RESULTS:: from multiple light scattering techniques indicated that at 15 minutes of extraction, the transmittance of the medicinal solution was the lowest(25%), the particle size was the largest(0.325-0.350 nm), and the stability index(turbiscan stability index, TSI) was the highest(0-2.5). With the extension of extraction time, the light transmittance of the medicinal solution improved, stability was enhanced, and the particle size decreased. These laws of physicochemical property changes provide important basis for the control of Artemisiae Argyi Folium extraction process. In addition, the changes in the bioactivity of Artemisiae Argyi Folium extracts during the extraction process were investigated through mouse writhing tests and antimicrobial assays. The results indicated that the analgesic and antimicrobial effects of the medicinal solution were strongest at the 15-minute extracting point. In summary, the findings of this study demonstrate that the content of volatile oil in Artemisiae Argyi Folium extracts gradually decreases with the extension of extraction time, and the variation in volatile oil content directly influences the physicochemical properties and pharmacological efficacy of the medicinal solution. This discovery provides important scientific reference for the optimization of Artemisiae Argyi Folium extraction processes and the development and application of process analytical technologies.
Oils, Volatile/pharmacology* ; Artemisia/chemistry* ; Gas Chromatography-Mass Spectrometry ; Drugs, Chinese Herbal/pharmacology* ; Chlorogenic Acid/pharmacology* ; Solid Phase Microextraction ; Quality Control

Simultaneous management of intestinal mucosal barrier dysfunction and gut microbiota dysregulation represents a significant challenge in the treatment of inflammatory bowel disease (IBD). Herein, we report a novel system that integrates multi-enzyme mimicking cerium single-atom nanocatalysts (CeSACs) with Lactobacillus reuteri probiotics (LR@CeSACs) for multipronged management of IBD. In this system, CeSACs demonstrate robust multi-enzyme activities across a broad pH range, effectively scavenging elevated reactive oxygen species, downregulating pro-inflammatory cytokines, and suppressing the expression of fibrosis-related genes. Moreover, probiotics promote the targeting and retention of the CeSACs for sustained catalytic antioxidant therapy. In turn, the inflammation relief enabled by CeSACs promotes bacterial viability, allowing for the rapid reshaping of intestinal barrier function and the restoration of gut microbiota. Therefore, LR@CeSACs exhibit excellent catalytic anti-inflammatory and anti-fibrotic therapeutic effects, as well as a certain prophylactic effect, as demonstrated in several murine models.

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Tauopathies, including Alzheimer's disease (AD), are a series of neurodegenerative diseases characterized by pathological accumulation of the microtubule-associated protein tau. Since the abnormal modification and deposition of tau in nerve cells are crucial for tauopathy etiology, methods for reducing tau levels, such as promoting tau degradation, may become effective strategies for disease treatment. Herein, we identified that sorafenib significantly reduced total tau and phosphorylated tau levels through screening FDA-approved drugs. We showed that sorafenib treatment attenuated cognitive deficits and tau pathologies in PS19 tauopathy model mice. Mechanistically, we found that sorafenib inhibited multiple kinases involved in tau phosphorylation and promoted autophagy. Importantly, we further demonstrated that sorafenib also promoted the expression of the E3 ubiquitin ligase FBXW7, which could bind tau and mediate tau degradation through the ubiquitin-proteasome pathway. Finally, we showed that FBXW7 expression decreased in the brains of AD patients and tauopathy model mice, and that overexpression of FBXW7 in the hippocampus attenuated cognitive deficits and tau pathologies in PS19 mice. These results suggest that sorafenib may be a promising treatment option for tauopathies by promoting tau degradation and reducing tau phosphorylation, and that targeting FBXW7 could also serve as an alternative therapeutic strategy for tauopathies.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.