ObjectiveTo elucidate the underlying mechanism through which Zhuluan decoction suppresses excessive autophagy in human ovarian granulosa cells （KGN） and ameliorates premature ovarian insufficiency （POI） via the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. MethodsThe optimal concentration of cyclophosphamide for inducing a POI model in KGN cells was identified via the cell counting kit-8 （CCK-8） assay. Subsequently， the impacts of varying concentrations of Zhuluan decoction-containing serum on the viability of the KGN cell model were assessed. After the optimal drug concentration was determined， KGN cells were categorized into the following groups： blank control （20% blank serum）， model （20% blank serum + 5 μmol·L^-1 cyclophosphamide）， Zhuluan decoction-containing serum （20% Zhuluan decoction-containing serum + 5 μmol·L^-1 cyclophosphamide）， autophagy inhibitor （20% blank serum + 5 μmol·L^-1 cyclophosphamide + 20 μmol·L^-1 chloroquine phosphate）， autophagy inhibitor + Zhuluan decoction-containing serum （20% Zhuluan decoction-containing serum + 5 μmol·L^-1 cyclophosphamide + 20 μmol·L^-1 chloroquine phosphate）， and estradiol valerate （20% estradiol valerate-containing serum + 5 μmol·L^-1 cyclophosphamide）. Following 48 hours of incubation， flow cytometry was utilized to measure the apoptosis rate of KGN cells in each group. Western blotting was employed to quantify the protein levels of PI3K， phosphorylated （p）-Akt， Akt， p-mTOR， and mTOR， along with the expression levels of autophagy-related proteins such as Beclin1， autophagy-related 5 homolog （ATG5）， and microtubule-associated protein 1 light chain 3 （LC3）， in each group. Additionally， monodansylcadaverine （MDC） staining was performed to evaluate the extent of autophagy in each group. ResultsIncubation of KGN cells with 5 μmol·L^-1 cyclophosphamide for 48 h successfully established a POI model， marked by a significant inhibition of KGN cell proliferation. Notably， the inhibitory effect of cyclophosphamide on KGN cell proliferation exhibited a positive correlation with its concentration. Zhuluan decoction-containing serum at 20% and 30% promoted cell proliferation and mitigated the inhibitory effect of cyclophosphamide on KGN cell proliferation， with comparable therapeutic efficacy observed at both concentrations. Compared with the blank control group， the model group displayed an elevated apoptosis rate （P<0.01）， reduced protein levels of PI3K， p-Akt， and p-mTOR （P<0.01）， increased protein levels of Beclin1， LC3， and ATG5 （P<0.01）， no significant alterations in the protein levels of Akt and mTOR， and an enhanced MDC autophagy fluorescence intensity （P<0.01）. In comparison to that the model group， the apoptosis rates in the blank control group， model group， Zhuluan decoction-containing serum group， autophagy inhibitor group， autophagy inhibitor + Zhuluan decoction-containing serum group， and estradiol valerate group all reduced （P<0.05， P<0.01）， with the most pronounced reduction observed in the autophagy inhibitor + Zhuluan decoction-containing serum group. The protein levels of PI3K， p-Akt， and p-mTOR were higher in other groups than in the model group （P<0.05， P<0.01）， being the highest in the autophagy inhibitor + Zhuluan decoctio-containing serum group （P<0.01）. The protein levels of Beclin1 and ATG5 were lower in other groups than in the model group （P<0.05， P<0.01）. The expression level of LC3 declined in the Zhuluan decoction-containing serum group and the estradiol valerate group （P<0.05， P<0.01）， while it decreased without statistical significance in the autophagy inhibitor group and the autophagy inhibitor + Zhuluan decoction-containing serum group. ConclusionZhuluan decoction may activate the PI3K/Akt/mTOR pathway to inhibit excessive autophagy and counteract the detrimental effects of cyclophosphamide on the KGN cell model， thus managing POI.

ObjectiveTo elucidate the underlying mechanism through which Zhuluan decoction suppresses excessive autophagy in human ovarian granulosa cells （KGN） and ameliorates premature ovarian insufficiency （POI） via the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. MethodsThe optimal concentration of cyclophosphamide for inducing a POI model in KGN cells was identified via the cell counting kit-8 （CCK-8） assay. Subsequently， the impacts of varying concentrations of Zhuluan decoction-containing serum on the viability of the KGN cell model were assessed. After the optimal drug concentration was determined， KGN cells were categorized into the following groups： blank control （20% blank serum）， model （20% blank serum + 5 μmol·L^-1 cyclophosphamide）， Zhuluan decoction-containing serum （20% Zhuluan decoction-containing serum + 5 μmol·L^-1 cyclophosphamide）， autophagy inhibitor （20% blank serum + 5 μmol·L^-1 cyclophosphamide + 20 μmol·L^-1 chloroquine phosphate）， autophagy inhibitor + Zhuluan decoction-containing serum （20% Zhuluan decoction-containing serum + 5 μmol·L^-1 cyclophosphamide + 20 μmol·L^-1 chloroquine phosphate）， and estradiol valerate （20% estradiol valerate-containing serum + 5 μmol·L^-1 cyclophosphamide）. Following 48 hours of incubation， flow cytometry was utilized to measure the apoptosis rate of KGN cells in each group. Western blotting was employed to quantify the protein levels of PI3K， phosphorylated （p）-Akt， Akt， p-mTOR， and mTOR， along with the expression levels of autophagy-related proteins such as Beclin1， autophagy-related 5 homolog （ATG5）， and microtubule-associated protein 1 light chain 3 （LC3）， in each group. Additionally， monodansylcadaverine （MDC） staining was performed to evaluate the extent of autophagy in each group. ResultsIncubation of KGN cells with 5 μmol·L^-1 cyclophosphamide for 48 h successfully established a POI model， marked by a significant inhibition of KGN cell proliferation. Notably， the inhibitory effect of cyclophosphamide on KGN cell proliferation exhibited a positive correlation with its concentration. Zhuluan decoction-containing serum at 20% and 30% promoted cell proliferation and mitigated the inhibitory effect of cyclophosphamide on KGN cell proliferation， with comparable therapeutic efficacy observed at both concentrations. Compared with the blank control group， the model group displayed an elevated apoptosis rate （P<0.01）， reduced protein levels of PI3K， p-Akt， and p-mTOR （P<0.01）， increased protein levels of Beclin1， LC3， and ATG5 （P<0.01）， no significant alterations in the protein levels of Akt and mTOR， and an enhanced MDC autophagy fluorescence intensity （P<0.01）. In comparison to that the model group， the apoptosis rates in the blank control group， model group， Zhuluan decoction-containing serum group， autophagy inhibitor group， autophagy inhibitor + Zhuluan decoction-containing serum group， and estradiol valerate group all reduced （P<0.05， P<0.01）， with the most pronounced reduction observed in the autophagy inhibitor + Zhuluan decoction-containing serum group. The protein levels of PI3K， p-Akt， and p-mTOR were higher in other groups than in the model group （P<0.05， P<0.01）， being the highest in the autophagy inhibitor + Zhuluan decoctio-containing serum group （P<0.01）. The protein levels of Beclin1 and ATG5 were lower in other groups than in the model group （P<0.05， P<0.01）. The expression level of LC3 declined in the Zhuluan decoction-containing serum group and the estradiol valerate group （P<0.05， P<0.01）， while it decreased without statistical significance in the autophagy inhibitor group and the autophagy inhibitor + Zhuluan decoction-containing serum group. ConclusionZhuluan decoction may activate the PI3K/Akt/mTOR pathway to inhibit excessive autophagy and counteract the detrimental effects of cyclophosphamide on the KGN cell model， thus managing POI.

Background As common public facilities essential to daily life, hair and beauty salons frequently contain various airborne toxic and hazardous pollutants potentially leading to adverse health effects for salon practitioners. Objective To characterize the indoor air pollution profiles of common contaminants in hair and beauty salons in Shanghai and to evaluate the associated health risks for practitioners, in order to provide a scientific basis for strengthening the public health management in Shanghai and protecting the health of practitioners. Methods The air quality monitoring data of hair and beauty salons in Shanghai from 2016 to 2024 were obtained from the “Health Hazard Factors Monitoring Program for Public Places” of the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention. Monitoring indicators included particulate matter ≤10 μm in aerodynamic diameter (PM₁₀), particulate matter ≤2.5 μm in aerodynamic diameter (PM_2.5), formaldehyde, ammonia, benzene, toluene, and xylene. Indicator compliance rates were calculated across various years in accordance with GB 9666-1996 Hygienic standard for barber shop and beauty shop and GB 37488-2019 Hygiene indicators and limit for public places; specifically, PM_2.5 was assessed against the limits stipulated in GB/T 18883-2022 Standards for indoor air quality. A questionnaire survey was conducted among salon practitioners to collect weekly working days and daily working hours. The non-carcinogenic risks associated with inhalation exposure to formaldehyde, ammonia, benzene, toluene, and xylene as well as the carcinogenic risks posed by formaldehyde and benzene were evaluated following WS/T 777-2021 Technical guide for environmental health risk assessment of chemical exposure and the U.S. Environmental Protection Agency inhalation risk model. Results The overall compliance rates of PM₁₀, formaldehyde, ammonia, benzene, and toluene in the air of hair and beauty salons in Shanghai from 2016 to 2024 were 92.13%, 96.59%, 96.15%, 94.93%, and 94.97%, respectively; the overall compliance rate of xylene was a little lower (85.92%), and the overall compliance rate of PM_2.5 was 57.18%. The P₅₀ concentrations of PM₁₀, PM_2.5, formaldehyde, ammonia, benzene, toluene, and xylene did not exceed the corresponding limits. The P₅₀ of non-carcinogenic risk indicator (hazard quotient, HQ) for formaldehyde, ammonia, benzene, toluene, and xylene were <1. The probabilities of non-carcinogenic risk HQ >1 for formaldehyde and xylene were 41.4% and 10.9%, respectively, which were higher than that of other pollutants. The P₅₀ of carcinogenic risk (CR) for formaldehyde and benzene were between 1.0×10⁻⁶ and 1.0×10⁻⁴, while the probabilities of CR >1.0×10⁻⁴ were 16.9% and 14.0%, respectively. Conclusion The overall compliance rate of common pollutant concentrations in the air of hair and beauty salons in Shanghai is high, and the hygienic condition meets the requirements of national standards. The non-carcinogenic health risks posed by formaldehyde and xylene to employees (with formaldehyde being more prominent), as well as the carcinogenic risks associated with formaldehyde and benzene, deserve heightened attention in future health supervision.

Objective To investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective: To investigate the characteristics of the breakthrough cases of mumps in Ningbo City, Zhejiang Province from 2018 to 2023, so as to provide insights into improving prevention and control measures for mumps. Methods: Data of mumps cases and mumps containing vaccine (MuCV) vaccination in Ningbo City from 2018 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System and Zhejiang Immunization Planning Information System. The population distribution characteristics and MuCV immunization history of mumps breakthrough cases were described. The impacts of the final immunization age and immunization interval on the age of onset were analyzed. Results: A total of 6 643 mumps cases were reported in Ningbo City from 2018 to 2023, with an average incidence rate of 11.72/105. There were 5 142 breakthrough cases (77.40%), including 3 173 males (61.71%) and 1 969 females (38.29%). The median age of onset was 6.00 (interquartile range, 4.00) years. There were 2 487 cases in preschool children (48.37%) and 2 232 cases in students (43.41%). There were 4 736 one-dose breakthrough cases (92.10%) and 406 two-dose breakthrough cases (7.90%). The proportion of two-dose breakthrough cases among all mumps cases increased from 1.00% in 2018 to 25.32% in 2023. Among individuals born after December 2018, the median age of onset of two-dose breakthrough cases was 3.00 (interquartile range, 1.00) years, which was older than that of one-dose breakthrough cases at 1.00 (interquartile range, 2.00) year (P<0.05). The ages of onset of mumps breakthrough cases differed significantly with varying final immunization ages and immunization intervals (both P<0.05). Conclusions The breakthrough cases of mumps in Ningbo City from 2018 to 2023 were mainly males, preschool children and students. The proportion of two-dose breakthrough cases increased, and the age of onset delayed.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.