Objective To analyze the case data of farmers' foodborne disease surveillance reports in Guizhou Province from 2022 to 2024, and to provide reference for the precise prevention and control of foodborne diseases among farmers in Guizhou Province. Methods Case data of foodborne disease surveillance reports of farmers were systematically collected from 2022 to 2024 in Guizhou Province. Descriptive epidemiological methods were used to analyze the temporal, geographical, and demographic distribution of foodborne diseases among farmers, along with their primary clinical symptoms and pathogen detection results. Results From 2022 to 2024, a total of 22,882 cases of foodborne diseases were reported among farmers in Guizhou Province. The majority of clinical symptoms (97.81%) were related to the digestive system, with summer being the peak season. While females outnumbered males, the gender difference was statistically insignificant (P >0.05). The 36-55 age group accounted for the highest proportion (38.83%), with Zunyi City (34.89%) and Qiandongnan Prefecture (23.21%) reporting the most cases. Fungal products were the most frequently reported suspected food items (26.96%), and home-made preparation was the primary processing method (58.63%). A total of 1 210 fecal samples were collected through active monitoring with an overall detection rate of 13.22%. Norovirus showed the highest detection rate (9.92%, 120/1 210). Statistically significant differences were observed among different seasons, age groups, regions, types and processing methods of suspected food exposure, and pathogen detection rates (P <0.001). Conclusion Foodborne disease prevention and control among farmers in Guizhou Province should focus on the risks of wild mushroom poisoning in summer and homemade foods, and continuously improve farmers' awareness of the dangers of foodborne diseases and food safety.

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 construct and validate a prognostic prediction model for first-line immune checkpoint inhibitors （ICIs） therapy for advanced non-small cell lung cancer （NSCLC）.METHODS The clinicopathological data and peripheral blood parameters from 211 patients with advanced NSCLC who received first-line ICIs therapy at our hospital from January 2020 to December 2023 were retrospective collected. The patients were randomly divided into a training set （151 cases） and a validation set（60 cases） at a ratio of 7∶3. Using progression-free survival （PFS） as the outcome measure， LASSO regression was used to preliminarily screen predictive variables in the training set，and the preliminarily screened predictive variables were entered into a multivariable Cox regression model to construct Model 1. Meanwhile，restricted cubic splinec analysis was performed on the continuous variables preliminarily screened by LASSO regression. The variables with nonlinear relationships （ P ＜0.1） were analyzed by multivariable Cox regression in RCS form to construct Model 2. The concordance index，receiver operating characteristic curves，calibration curves，and decision curve analysis were used to compare the predictive performance of the two models； the optimal model was selected to construct a nomogram.Sensitivity analysis was performed by reconstructing the multivariable Cox regression model after excluding cases with unknown programmed death-ligand 1（PD-L1）status. Kaplan-Meier method was used to plot survival curves to analyze the survival differences among patients with different risk strata.RESULTS The variables used to construct Model 1 were sex， smoking history， PD-L1 expression status， bone metastasis， and carcinoembryonic antigen （CEA）；the variables used to construct Model 2 were sex， smoking history， PD-L1 expression status， bone metastasis， CEA， neutrophil（Neu）， and albumin（ALB）. The concordance indices of Model 2 were 0.710 in the training set and 0.672 in the validation set，both superior to those of Model 1 （0.649，0.634）. The areas under the curve （AUC） of Model 2 for 12， 18， and 24 months PFS were 0.737，0.782 and 0.788 in the training set，and 0.709，0.630 and 0.663 in the validation set，respectively，all outperforming Model 1 （0.653， 0.704， 0.697 in the training set；0.688， 0.605， 0.651 in the validation set）.The calibration curves of both models showed good consistency between the predicted probability and actual probability，and the clinical net benefit of Model 2 was higher than that of Model 1. Sensitivity analysis indicated that the prediction model was robust. The median PFS of patients in the low-risk group was significantly longer than that in the high-risk group（ P ＜0.05）.CONCLUSIONS Sex， smoking history， PD-L1 expression status， bone metastasis， Neu， ALB， and CEA were independent influencing factors for PFS in advanced NSCLC patients receiving first-line ICIs. The prediction model constructed based on the above factors has good predictive performance and can be used to predict the prognosis of advanced NSCLC patients.

ObjectiveTo investigate the therapeutic effect of proanthocyanidins （PC） on rats with type 2 diabetes mellitus （T2DM） complicated with cognitive impairment （CI） and to explore its potential mechanism by inhibiting the NOD-like receptor family pyrin domain-containing protein 3 （NLRP3）/cysteine-aspartic acid protease-1 （Caspase-1） pathway. MethodsA T2DM rat model was established by high-fat diet combined with intraperitoneal streptozotocin （STZ） injection. Thirty-six diabetic rats complicated with CI were screened by Morris water maze test and randomly divided into model group， PC low-dose （50 mg/kg） group， PC medium-dose （100 mg/kg） group， and PC high-dose （200 mg/kg） group. Another 9 normal rats served as the normal control group. Each group was administered with the corresponding doses of PC or an equal volume of distilled water by gavage for 8 weeks. After the intervention， spatial learning and memory abilities were evaluated using the Morris water maze test. Fasting blood glucose， body weight， and organ coefficients were measured. Pathological changes in the hippocampus were observed by hematoxylin-eosin （HE） staining. Reactive oxygen species （ROS） levels， as well as levels of inflammatory cytokines tumor necrosis factor-α （TNF-α） and interleukin-1β （IL-1β） in hippocampal tissue， were detected by enzyme-linked immunosorbent assay （ELISA）. The protein expression levels of NLRP3， Caspase-1， IL-1β， and IL-18 in the hippocampus were determined by Western blot. ResultsCompared with the normal control group， the model group exhibited significantly increased blood glucose and decreased body weight （P<0.05）. In the Morris water maze test， the model group showed prolonged escape latency， fewer platform crossings， and lower percentages of time and path length in the target quadrant （P<0.05）. Disordered arrangement and pyknotic nuclei were observed in hippocampal neurons. ROS and the levels of TNF-α and IL-1β were elevated， and the protein expression levels of NLRP3， Caspase-1， IL-1β and IL-18 were upregulated （P<0.05）. Compared with the model group， all PC-treated groups， especially the high-dose group， presented dose-dependent improvements in the above indicators， including reduced blood glucose （P<0.05）， improved spatial memory performance in the Morris water maze （P<0.01）， alleviated hippocampal pathological damage， decreased ROS and inflammatory cytokine levels （P<0.05）， and significantly downregulated expression of NLRP3/Caspase-1 pathway-related proteins （P<0.05）. ConclusionProanthocyanidins can ameliorate glycolipid metabolic disorder， visceral organ injury as well as cognitive dysfunction in T2DM rats. The underlying mechanism may be associated with reduced hippocampal ROS levels， inhibition of the NLRP3/Caspase-1 signaling pathway， and attenuated neuroinflammation in the hippocampus， with the optimal effect observed at a dose of 200 mg/kg.

BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

Objective:To develop and validate a clinical prediction model for assessing the risk of postoperative pulmonary complications (PPCs) in elderly patients undergoing surgery with general anesthesia.Methods:This prospective observational study enrolled patients aged ≥65 years who underwent general anesthesia with mechanical ventilation duration >3 hours across six tertiary hospitals between December 2022 and August 2023. Based on follow-up outcomes (until discharge or postoperative day 7), patients were categorized into a non-PPCs group and a PPCs group. Detailed records included baseline patient characteristics, preoperative comorbidities, surgical information (type, duration), and bedside lung ultrasound scores (LUS) assessed within 24 hours postoperatively using a standardized 12-zone protocol. Predictor selection was performed using LASSO regression. Significant predictors identified were incorporated into a multivariate logistic regression analysis to build the prediction model, visualized as a nomogram. Internal validation was conducted via bootstrap resampling (1 000 repetitions). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves for calibration accuracy, and decision curve analysis (DCA) for clinical utility.Results:A total of 130 eligible elderly surgical patients were included. PPCs occurred in 17 patients (incidence rate: 13.1%). Multivariate analysis identified LUS ( OR=1.248, 95% CI: 1.099-1.417, P=0.001) and elective surgery type ( OR=0.206, 95% CI: 0.043-0.988, P=0.048) as independent predictors of PPCs. The nomogram model demonstrated an AUC of 0.867 (95% CI: 0.775-0.959) upon initial testing. Internal validation confirmed good discrimination (AUC=0.863, 95% CI: 0.778-0.972). Calibration curves indicated excellent agreement between predicted probabilities and observed outcomes. Decision curve analysis demonstrated significant clinical net benefit across a wide range of threshold probabilities (0.03-0.89). Conclusions:The clinical prediction model, developed using early postoperative LUS scores and surgical type, effectively predicts the risk of postoperative pulmonary complications in elderly patients following surgery under general anesthesia. The model exhibits strong discrimination, calibration, and clinical utility, providing clinicians with a reliable tool for individualized risk assessment to support clinical decision-making and potentially reduce PPC incidence.

Objective To investigate the effect of triptolide on cerebral ischemia- reperfusion injury （CIRI） and explore its molecular mechanism. Methods One hundred and forty-four Wistar rats were randomly divided into sham operation group, model group, low, medium, high dose of triptolide group and butylphthalide group, with 24 rats in each group. The CIRI rat model was established by blocking the middle cerebral artery for 2 hours. 3 days before modeling, the rats in each group were ip administration once a day. 24 hours after reperfusion, the neurological deficit score was detected, the rate of cerebral infarction was measured by TTC staining, the blood brain barrier （BBB） permeability was detected by EB penetration test. The pathological changes neurons in the ischemic penumbra cortex were observed by HE and TUNEL staining. The content of inflammatory factors in ischemic cerebral cortex were detected by Elisa method. The expression of TLR4/NF-κB pathway related proteins were detected by Western blot. Results Compared with the model group, the neurological deficit score, cerebral infarction rate and EB content in the triptolide middle, high dose groups and the butylphthalide group were significantly decreased （P<0.05）. The pathological changes of cortical neurons in the ischemic penumbra were significantly improved, and the apoptosis rate of neurons was significantly decreased （P<0.05）. The content of TNF-α, IL-1β and the expression of TLR4, p-NF-κB, cleaved caspase-3, Bax were significantly decreased, the expression of Bcl-2 was significantly increased, the ratio of p-NF-κB/NF-κB and Bax/Bcl-2 were significantly decreased （P<0.05）. The regulatory effect of the high dose triptolide group on various detection indexes were better than that of the butylphthalide group （P<0.05）. Conclusion Triptolide could protect the permeability of BBB, improve the neurological deficit and neuropathy in CIRI rats, and reduce the rate of cerebral infarction, its mechanism may be related to the inhibition of TLR4/NF-κB pathway and which mediated inflammatory response and neuronal apoptosis.

Objective:To analyze the correlation of serum salt-induced kinase 2 (SIK2) and receptor activator of nuclear factor κB ligand (RANKL) expression levels with osteoporosis in perimenopausal women.Methods:A total of 500 perimenopausal women admitted to the Second Hospital of Tianjin Medical University from Jan. 2023 to Jun. 2023 were studied and separated into osteoporosis group and non-osteoporosis group according to with or without osteoporosis. The general data, serum SIK2 and RANKL expression levels and bone metabolism indexes [type I collagen carboxy peptide (CTX), procollagen I N-Terminal propeptide (PINP), and osteocalcin of N-MID-Osteocalcin (N-MID-OT) ] were compared between the two groups. The correlation of the expression levels of serum SIK2 and RANKL with bone metabolism indexes was analyzed by Pearson correlation; The risk factors of osteoporosis in perimenopausal women were analyzed by Logistic multi-factor model. Results:Of the 500 patients, 88 had osteoporosis (17.6%) ; The serum levels of SIK2 and RANKL, CTX, PINP and N-MID-OT in osteoporosis group were significantly higher than those in non-osteoporosis group ( t=7.53, 13.11, 19.69, 28.79, 26.14, P<0.05). Pearson correlation analysis showed that serum SIK2 and RANKL levels were significantly positively correlated with all indexes of bone metabolism ( r=0.541, 0.480, 0.447; r=0.369, 0.516, 0.482, P<0.05). Logistic regression analysis showed that the number of births, diabetes, SIK2, RANKL and bone metabolism were the factors affecting the incidence of osteoporosis in perimenopausal women ( OR=2.123, 2.243, 3.083, 4.773, 3.789, 2.927, 2.633, P<0.05) . Conclusions:SIK2 and RANKL may be involved in the pathogenesis of osteoporosis by promoting bone turnover imbalance. Together with fertility times, diabetes mellitus and bone metabolism indexes, SIK2 and RANKL are all factors in the development of osteoporosis in perimenopausal women.

ObjectiveTo find out whether there is any difference in the monitoring results of mosq-ovitraps placed in different orientations in multi-storey residential areas, so as to provide a scientific basis for routine and emergency monitoring of Aedes albopictus with mosq-ovitraps in residential areas. MethodsFrom July 6th to October 26th 2023, one mosquito ovitrap was set up in each of the 4 orientations of east, south, west and north around the buildings in a multi-storey residential area in Jinhui Town, Fengxian District, Shanghai. Data was collected and recorded 72 hours after placement. The chi-square test was used to compare the mosquito ovitrap indices (MOIs) of two independent samples, and the Kruskal⁃Wallis H test was used to compare the MOIs of multiple independent samples. ResultsAfter 16 weeks of surveillance, 997 mosquito ovitraps were recovered, of which 211 were positive, with the mosquito ovitrap index (MOI) of 21.16% and the Aedes albopictus density index of 1.03 mosquitoes·ovitrap^-1. The MOIs were higher in September (24.22%) and October (23.96%), and the MOIs in the west, south and north within the two months were all above 20.00%. From July to October, the MOIs in the east, west, south and north were 20.70%, 22.20%, 25.50% and 16.20%, respectively, and the difference in MOIs among the 4 orientations was not statistically significant (χ²=6.647, P=0.084). Stratified analysis by month showed that in August, the south side of the multi-storey residential areas had the highest MOI (31.30%), the north side had the lowest MOI (1.30%), and there was a statistically significant difference in MOI in the east, west, south and north (χ²=25.986, P<0.001). In October, the MOI in the west was the highest (33.30%) and the MOI in the east was the lowest (6.30%), the difference in MOIs of the 4 orientations was statistically significant (χ²=12.007, P=0.007). The MOIs in the south side of the building in the outskirts of the residential area from the 1st week in July to the 4th week in October was lower (19.20%) than that in the south side of the inner building (31.70%), and the difference in MOI was statistically significant (χ²=5.118, P=0.024). ConclusionThe study of MOI in different orientations in a multi-storey residential area is a preliminary exploration based on field work, and the results show that there is a difference in MOIs in different orientations during the peak breeding period of mosquitoes. Further indicators such as temperature, humidity and wind speed in different orientations can be collected to explore the influencing factors of MOIs.

With the rapid increase in the ownership of MRI equipment in China,quality control,particularly in clinical usage aspects,has become critically important.For clinical quality control of MRI systems,it is essential to establish comprehensive workflow principles encompassing multiple elements such as personnel,equipment,standards,tools and methodologies.To advance the standardization and widespread adoption of clinical quality control for MRI equipment,efforts must focus on strengthening regulatory frameworks,advancing phantom research,development and enhancing professional expertise.Concurrently,continuous improvements in training programs and supervision mechanisms are necessary to ensure the effective implementation of MRI clinical quality control practices.Furthermore,in the era of digital healthcare,clinical quality assurance for MRI equipment is evolving toward automation and intelligent solutions,providing higher-quality and more efficient assurance for clinical applications.