ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

Background Lung cancer, one of the most common malignant tumors worldwide, has long ranked first in cancer incidence and mortality, posing a severe challenge to public health systems. Objective To analyze the trends in incidence, mortality, and disability-adjusted life years (DALYs) of lung cancer among residents in Jing'an District, Shanghai, from 2002 to 2021, explore the impacts of population aging, population growth, and age-specific prevalence on disease burden, and provide a scientific basis for optimizing regional lung cancer prevention and control strategies. Methods Based on the cancer registration and cause-of-death surveillance data of registered residents in Jing'an District, Shanghai, from 2002 to 2021, Joinpoint regression models were used to analyze the annual change trends (APC) and average annual change trends (AAPC) of lung cancer incidence, mortality, DALY rate, and their age-standardized rates. Decomposition analysis was applied to quantify the contribution of population aging, population growth, and age-specific prevalence to changes in the number of new cases, deaths, and DALYs. Results From 2002 to 2021, the crude incidence rate of lung cancer in Jing'an District increased from 68.00 per 100000 to 144.36 per 100000 (AAPC=4.86%, P<0.001), and the age-standardized incidence rate rose from 43.09 per 100000 to 61.46 per 100000 (AAPC=2.89%, P<0.001). The growth rate of incidence was significantly higher in females (AAPC=6.73%) than in males (AAPC=3.62%). The crude mortality rate increased from 58.08 per 100000 to 66.11 per 100000 (AAPC=1.10%, P<0.001), while the age-standardized mortality rate decreased (AAPC=−1.54%, P<0.001). The crude DALY rate showed an upward trend (AAPC=0.94%, P=0.002), whereas the age-standardized DALY rate declined (AAPC=−1.63%, P<0.001). Significant differences were observed across genders and age groups: the mortality and DALY rates increased in males aged 60-64 years, while the fastest incidence growth occurred in females aged 45-64 years. The results of decomposition analysis indicated that the increase in new cases was primarily attributed to age-specific incidence (38.15%) and aging (37.31%); the growth in deaths and DALYs was driven by aging, while age-specific mortality and population growth showed offsetting effects. From 2002 to 2021, the probability of premature death from lung cancer among males (2.04%-2.52%) in Jing'an District showed no statistically significant trend (AAPC=−0.28%, P=0.440), while it presented a decreasing trend in the total population (1.37%-1.89%) and females (0.72%-1.26%) (AAPC=−0.80% and −2.23%, respectively; P=0.029 and <0.001, respectively). Conclusion From 2002 to 2021, the risk of lung cancer incidence in Jing’an District, Shanghai, continue to increase, with a disease burden exhibiting significant heterogeneity by gender and age: key features include a rapid increase in new cases and a trend toward younger onset among females, alongside rising mortality risk among males aged 60–64 years. Population aging and increasing age-specific incidence rates are primary drivers of the growing number of cases, while declining age-specific mortality rates mitigate the rise in mortality burden.

ObjectiveTo explore the possible mechanisms by which ligustilide （LIG） exerts neuroprotective effects on ischemic stroke （IS） by inhibiting the release of neutrophil extracellular traps （NETs）， promoting blood-brain barrier repair， and alleviating post-ischemic neuroinflammation， thereby providing a new direction for IS treatment. MethodsA middle cerebral artery occlusion （MCAO） model was established in rats. The rats were divided into the sham operation （Sham） group， model （Model） group， low- and high-dose LIG groups （20， 40 mg·kg^-1）， and the NET inhibitor CI-amidine group （CI-amidine， 10 mg·kg^-1）. Drug treatments were administered for 3 days. Neurological injury after ischemia was evaluated by 2，3，5-triphenyltetrazolium chloride （TTC） staining， neurological deficit scoring， and brain index measurement. Flow cytometry and Western blot were used to analyze changes in neutrophil expression. Immunofluorescence was used to observe the fluorescence intensity of the NET marker citrullinated histone H3 （H3Cit）. Western blot was performed to detect the expression of blood-brain barrier tight junction-related proteins and inflammatory factors， including interleukin-18 （IL-18） and interleukin-1β （IL-1β）. ResultsCompared with the Sham group， the Model group exhibited significant brain tissue injury （P<0.05）， significantly increased neutrophil numbers and NET expression （P<0.05）， significantly impaired blood-brain barrier permeability （P<0.05）， and significantly increased expression of inflammatory factors （P<0.05）. Compared with the Model group， both low- and high-dose LIG significantly alleviated brain tissue injury in rats （P<0.01）， inhibited neutrophil numbers and NET expression （P<0.01）， reduced blood-brain barrier damage （P<0.01）， and suppressed the expression of inflammatory factors IL-18 and IL-1β （P<0.01）， thereby ultimately exerting a neuroprotective effect. ConclusionThe neuroprotective effect of LIG in rats with cerebral ischemia-reperfusion injury may be related to inhibition of neutrophils and the NETs induced by them.

ObjectiveTo observe the clinical efficacy of Anshen Buxin Gao in patients with coronary artery disease （CAD） complicated with somatization disorder after percutaneous coronary intervention （PCI）， as well as its effect on heart rate variability （HRV）. MethodsA total of 96 patients with somatization disorder after PCI were selected and randomized into control and treatment groups （48 cases）. On the basis of standardized Western medical treatment for CAD， the control group received Dailixin， while the treatment group received Dailixin combined with Anshen Buxin Gao. The somatic symptom scale （SSS）， generalized anxiety disorder 7-item scale （GAD-7）， patient health questionnaire-9 （PHQ-9）， and self-rating scale of sleep （SRSS） scores in both groups were recorded before and after treatment. The traditional Chinese medicine symptom efficacy， HRV， and incidence of adverse drug reactions were observed. ResultsA total of 90 patients completed the trial， encompassing 45 patients in the control group and 45 patients in the treatment group. Baseline characteristics between the two groups showed no statistically significant differences， indicating comparability. After treatment， both groups exhibited reductions in SSS， GAD-7， and PHQ-9 scores （P<0.05）， and the treatment group outperformed the control group in alleviating somatic symptoms and anxiety-depression symptoms （P<0.05）. The control group did not achieve a significant reduction in SRSS score， whereas the treatment group effectively lowered the SRSS score （P<0.05）. Regarding traditional Chinese medicine symptom efficacy， the total response rate in the treatment group was 91.1% （41/45）， which was higher than that （71.1%， 32/45） in the control group （Z=-2.663， P<0.05）. Both groups improved HRV in patients with somatization disorder， and the treatment group showed greater improvement （P<0.05）. There were no serious clinical adverse events during the study period. The incidence of adverse reactions in the treatment group was 6.7% （3/45）， which was lower than that （14/45， 31.10%） in the control group （χ²=7.252， P<0.05）. ConclusionThe addition of Anshen Buxin Gao to Dailixin therapy significantly alleviates the clinical symptoms and improves the sleep quality， treatment efficacy， and HRV in patients with CAD complicated with somatization disorder after PCI， while reducing the adverse effects associated with Dailixin alone. This approach demonstrates considerable clinical value and warrants further promotion.

This paper systematically analyzes schistosomiasis transmission risks during the elimination stage and reviews the evolution of the schistosomiasis surveillance system in China from a One Health perspective, with a special emphasis on schistosomiasis surveillance and response practices during the elimination stage from a One Health perspective. These practices include precise screening of human schistosomiasis under low-endemicity conditions, systematic monitoring of schistosomiasis in domestic and wild animals, ecological management of Oncomelania snails, and information-coordinated responses. Nevertheless, the current surveillance and response system for schistosomiasis suffers from challenges of insufficient cross-sectoral coordination and complex external environments, which constrain precise schistosomiasis surveillance and response in China. Therefore, it is urgently necessary to integrate coordination mechanisms, empower the surveillance system with technological innovation, improve capacity building, and actively promote diverse social participation in the One Health framework, so as to consolidate current schistosomiasis control achievements and achieve the target for schistosomiasis elimination across China, which may provide a replicable technical model for global zoonoses control.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective:To explore the intervention effects of the "four-steps tendon resetting and collaterals dredging manipulation" on the symptoms and muscle status of calf muscle group of patients with chronic ankle sprains.Methods:This study was a prospective self-controlled clinical trial. A total of 39 patients with chronic ankle sprains who sought treatment at the basic units from April to September 2023 and Rehabilitation Medicine Center of Characteristic Medical Center of PLA Rocket Force from February to October 2023 were recruited. The "four-steps tendon resetting and collaterals dredging manipulation" was employed for treatment, with two sessions conducted per patient and one session per week. Pain levels were assessed using the Visual Analog Scale (VAS), ankle joint function was evaluated using the Ankle Osteoarthritis Scale and Function Assessment (AOFAS) score, and MyotonPRO digital palpation instrument was used to measure bilateral triceps and peroneal longus muscles and evaluate muscle status.Results:Compared with before treatment, VAS scores decreased ( t values were 5.85, 5.97, respecively, P<0.001) and AOFAS scores increased ( Z values were -4.59, -4.68, respecively, P<0.001). Before the first treatment and after the second treatment, the damping vibration frequency (Freq) of the affected and healthy triceps and peroneal muscles increased ( t values were -3.09,-2.92,-2.97,-2.28, respecively, P<0.05), the muscle stiffness (Stiff) increased ( t values were -3.12, -2.99, -2.88, -2.15, respecively, P<0.05), and the logarithmic attenuation value (Decr) of the damping vibration of the healthy calf triceps muscle decreased ( t=-2.31, P<0.05); Compared before and after the first treatment, the Decr value ( t=-2.51, P<0.05) and Stiff value ( t=-2.05, P<0.05) of the affected fibular longus muscle increased, while the Ferq, Decr, and Stiff values of the healthy calf triceps muscle increased before and after treatment ( t values were -2.92, -2.13, -2.64, respecively, P<0.05); before and after the second treatment, the Freq values of the triceps and peroneal longus muscles on the affected and healthy sides increased ( t values were -4.28, -2.67, -2.69, -2.38, respecively, P<0.05) and Stiff values increased ( t values were -4.24, -3.43, -3.87, -2.33, respecively, P<0.05); there was no statistical significance in Ferq, Decr, and Stiff values between the affected and healthy sides before and after the first and second treatments ( P>0.05). Conclusion:The "four-steps tendon resetting and collaterals dredging manipulation" can improve the symptoms of chronic ankle sprains and significantly change the muscle condition of the affected and healthy sides of the calf. The mechanism may be related to the neuromuscular control mechanism.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.