ObjectiveTo observe the protective effect of Erchentang （ECT） on SiO₂-induced lung injury in rats and to explore its underlying mechanism. MethodsA rat model of lung injury was established by a single intratracheal instillation of 50 mg·mL^-1 SiO₂ suspension. Thirty male Sprague-Dawley （SD） rats were randomly assigned to five groups： control， model， low and high-dose （4.5 g·kg^-1·d^-1 and 9 g·kg^-1·d^-1， respectively） ECT， and dexamethasone （0.2 mg·kg^-1·d^-1）. All the groups were treated for 4 consecutive weeks. Histopathological alterations in the lung tissue were examined by hematoxylin and eosin （HE） staining. The levels of malondialdehyde （MDA）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px） in the lung tissue were measured through biochemical assays. The expression of key molecules in the nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1） pathway was determined by Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， Western blot， and immunofluorescence assay. The primary active components of ECT were identified by ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）， and their binding affinity to Nrf2/HO-1 was assessed by molecular docking. Untargeted metabolomics of the lung tissue was performed based on UPLC-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS）， and correlation analysis was performed to identify differential metabolites and parameters closely associated with the Nrf2/HO-1 pathway. ResultsCompared with the control group， the model group exhibited a reduction in body weight gain， an increase in lung index， increased MDA content， weakened SOD and GSH-Px activities in the lung tissue， down-regulated mRNA and protein levels of Nrf2 and protein levels of HO-1 and GPX4， and an up-regulated protein level of Keap1 （P<0.05， P<0.01）. Treatment with ECT attenuated the SiO₂-induced decline in body weight （P<0.05）， alleviated inflammatory cell infiltration and silicotic nodule formation in alveoli， and reduced the MDA content and enhanced the SOD and GSH-Px activities in the lung tissue （P<0.05， P<0.01）. UPLC-MS/MS and molecular docking revealed that core components of ECT， such as hesperidin and glycyrrhizic acid， displayed strong binding affinity to Nrf2/HO-1. Molecular biological experiments demonstrated that ECT promoted nuclear translocation of Nrf2， up-regulated the mRNA and protein levels of HO-1 and GPX4， and down-regulated Keap1 expression （P<0.05， P<0.01）. Metabolomic analysis indicated that ECT reversed the SiO₂-induced aberrant expression of metabolites， including linoleic acid and glutamine （P<0.05， P<0.01）. Correlation analysis showed that Nrf2 and HO-1 were positively correlated with SOD and GSH-Px （P<0.05， P<0.01）， but negatively correlated with glutamine and serine （P<0.05， P<0.01）. ConclusionECT may activate the Nrf2/HO-1 pathway through its core active components， thereby regulating oxidative stress and metabolic disorders to ameliorate SiO₂-induced lung injury in rats. This study provides experimental evidence for ECT in the prevention and treatment of occupational lung injury.

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.

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.

Objective:To analyze the screening results of the Urban Cancer Early Diagnosis and Treatment Project in Qinghai Province from 2019 to 2024.Methods:A summary and statistical analysis were conducted on six years of screening data from the Urban Cancer Early Dia-gnosis and Treatment Program in Qinghai Province,with the high-risk rate,screening rate,and detection rate calculated separately for each type of cancer.Results:From 2019 to 2024,56,882 high-risk individuals were identified.The high-risk rates for lung,colorectal,breast,up-per gastrointestinal,and liver cancer were 22.02%,21.57%,14.23%,13.52%,and 6.10%,respectively.Overall,13,592 individuals com-pleted clinical screening,with detection rates of 0.32%for lung cancer,0.41%for liver cancer,0.08%for precancerous gastric lesions,3.63%for precancerous colorectal lesions,0.08%for esophageal cancer,0.16%for gastric cancer,and 0.14%for colorectal cancer.Conclusions:The implementation of the Urban Cancer Early Diagnosis and Treatment Program in Qinghai Province aids in the early detection of cancer,improves early diagnosis and survival rates,and reduces mortality.Nevertheless,due to low public awareness and limited participation,en-hancements in program management and public outreach are required.

Objective:To analyze the screening results of the Urban Cancer Early Diagnosis and Treatment Project in Qinghai Province from 2019 to 2024.Methods:A summary and statistical analysis were conducted on six years of screening data from the Urban Cancer Early Dia-gnosis and Treatment Program in Qinghai Province,with the high-risk rate,screening rate,and detection rate calculated separately for each type of cancer.Results:From 2019 to 2024,56,882 high-risk individuals were identified.The high-risk rates for lung,colorectal,breast,up-per gastrointestinal,and liver cancer were 22.02%,21.57%,14.23%,13.52%,and 6.10%,respectively.Overall,13,592 individuals com-pleted clinical screening,with detection rates of 0.32%for lung cancer,0.41%for liver cancer,0.08%for precancerous gastric lesions,3.63%for precancerous colorectal lesions,0.08%for esophageal cancer,0.16%for gastric cancer,and 0.14%for colorectal cancer.Conclusions:The implementation of the Urban Cancer Early Diagnosis and Treatment Program in Qinghai Province aids in the early detection of cancer,improves early diagnosis and survival rates,and reduces mortality.Nevertheless,due to low public awareness and limited participation,en-hancements in program management and public outreach are required.

Objective:To investigate the value of nomogram based on radiomics features of CT enterography (CTE) combined with clinical characteristics to predict secondary loss of response (SLOR) after infliximab (IFX) treatment in patients with Crohn′s disease (CD).Methods:This study was a case-control study. Clinical and imaging data of 155 patients with CD diagnosed at the First Affiliated Hospital of Anhui Medical University from March 2015 to July 2022 were retrospectively collected. The patients were divided into a training set ( n=108) and a testing set ( n=47) in the ratio of 7∶3 by stratified sampling method. All patients were treated according to the standardized protocol and were classified as SLOR (43 in the training set and 18 in the testing set) and non-SLOR (65 in the training set and 29 in the testing set) according to treatment outcome. Based on the data from the training group, independent clinical predictors of SLOR after IFX treatment were screened in the clinical data using univariate and multivariate logistic regression analysis to establish a clinical model. Intestinal phase images were selected to be outlined layer by layer along the margin of the lesion to obtain the volume of the region of interest to extract the radiomics features. The radiomics features were screened using univariate analysis and the minimum absolute shrinkage and selection operator to establish the radiomics model. Multivariate logistic regression analysis was used to build a combined clinical-radiomics model based on the screened clinical independent predictors and radiomics characters, then a nomogram was drawn. The predictive efficacy of the 3 models for SLOR after IFX treatment was assessed by receiver operating characteristic curves, and the area under the curve (AUC) was calculated. The decision curve analysis was applied to evaluate the clinical utility of the models. Results:Disease duration ( OR=1.983, 95% CI 1.966-2.000, P=0.046) and intestinal stenosis ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as the independent predictors of SLOR in the clinical data, and a clinical model was established. Totally 9 radiomics features were included in the radiomics model. The AUCs of clinical, radiomics, and combined models for predicting SLOR after IFX treatment in CD patients were 0.691 (95% CI 0.591-0.792), 0.896 (95% CI 0.836-0.955), and 0.910 (95% CI 0.855-0.965) in the training set, and 0.722 (95% CI 0.574-0.871), 0.866 (95% CI 0.764-0.968), and 0.889 (95% CI 0.796-0.982) in the testing set. Decision curve analysis in the testing set showed higher net clinical benefits for both the radiomics model and combined model than the clinical model, and combined model had higher net clinical benefits than the radiomics model over most threshold probability intervals. Conclusions:CTE-based radiomics model can effectively predict SLOR after IFX treatment in patients with CD, and a combined model by incorporating clinical characteristics of disease duration and intestinal stenosis can further improve the predictive efficacy.

Objective To observe the clinical efficacy of Chang'an Juntai Granules(mainly composed of Pseudostellariae Radix,Atractylodis Macrocephalae Rhizoma,Poria,Glycyrrhizae Radix et Rhizoma Praeparata cum Melle,Paeoniae Radix Alba,Saposhnikoviae Radix,Citri Reticulatae Pericarpium,Coptidis Rhizoma,and Aucklandiae Radix)in the treatment of diarrhea-predominant irritable bowel syndrome(IBS-D)with liver depression and spleen deficiency syndrome,and to evaluate its safety.Methods A single-center,randomized,double-blind,placebo-controlled clinical trial was designed.A total of 130 patients with IBS-D of liver depression and spleen deficiency were included.The patients were randomly divided into a treatment group and a control group by random number table method,with 65 cases in each group.The treatment group was treated with Chang'an Juntai Granules,and the control group was treated with Chang'an Juntai Placebo Granules.The course of treatment covered 12 weeks.The changes in the scores of IBS Symptom Severity Scale(IBS-SSS),Bristol Stool Form Scale(BSFS),IBS Quality of Life Questionnaire(IBS-QOL)and Hospital Anxiety and Depression Scale(HADS)in the two groups were observed before and after treatment.After treatment,the clinical efficacy and medication safety in the two groups were evaluated.Results(1)During the trial,six cases in the treatment group and eight cases in the control group fell off.Eventually,a total of 116 patients completed the clinical trial,including 59 cases in the treatment group and 57 cases in the control group.(2)After 12 weeks of treatment,the total effective rate of the treatment group was 88.14％(52/59),and that of the control group was 45.61％(26/57).The intergroup comparison(tested by chi-square test)showed that the clinical efficacy of the treatment group was significantly superior to that of the control group,and the difference was statistically significant(P＜0.01).(3)After treatment,the IBS-SSS scores of the two groups and the BSFS and IBS-QOL scores of the treatment group were significantly lower than those before treatment(P＜0.01),while the scores of Hospital Anxiety and Depression Scale-Anxiety subscale(HADA)and Hospital Anxiety and Depression Scale-Depression subscale(HADD)in the two groups and the BSFS and IBS-QOL scores in the control group showed no obvious changes(P＞0.05).Compared with the control group,the decrease of IBS-SSS,BSFS and IBS-QOL scores in the treatment group was significantly superior to that in the control group(P＜0.05 or P＜0.01).(4)During the trial,no serious adverse reactions or adverse events occurred in the two groups,no drug-related abnormalities of liver and kidney function,blood,and heart function were found,either.Conclusion Chang'an Juntai Granules are effective on improving the clinical symptoms and fecal characteristics of IBS-D patients with liver depression and spleen deficiency syndrome,and on enhancing the quality of life of patients.The granules excert definite curative effect and high safety,and has certain value of clinical application.

Objective:To automatically classify hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) based on mul-titask learning algorithm using native T1 mapping images.Methods:A total of 203 patients admitted to Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University from January 2017 to December 2021 were enrolled, including 53 patients with HHD, 121 patients with HCM, and 29 patients with normal control (NC). Native T1 mapping images of all enrolled patients were acquired using MRI and processed by a multi-task learning algorithm. The classification performance of each model was validated using ten-fold crossover, confusion matrix, and receiver operator characteristic (ROC) curves. The Resnet 50 model based on the original images was established as a control.Results:The ten-fold crossover validation results showed that the MTL-1 024, MTL-64, and MTL-all models showed better performance in terms of area under the curve (AUC), accuracy, sensitivity, and specificity compared to the Resnet 50 model. In the classification task, the MTL-64 model showed the best performance in terms of AUC (0.942 1), while the MTL-all model reached the highest value in terms of accuracy (0.852 2). In the segmentation task, the MTL-64 model achieved the best results with the Dice coefficient (0.879 7). The confusion matrix plot showed that the MTL model outperforms the Resnet 50 model based on the original image in terms of overall performance. The ROC graphs of all MTL models were significantly higher than the original image input Resnet 50 model.Conclusions:Multi-task learning-based native T1 mapping images are effective for automatic classification of HHD and HCM.

Rapid epidemiological screening for tuberculosis (TB) usually uses tuberculin pure protein derivative (PPD) skin test, which has limitations such as low specificity and high side effects. ESAT-6 and CFP-10 are secreted proteins of Mycobacterium tuberculosis, but the related genes are missing from Bacillus Calmette-Guerin (BCG). In this study, the fusion protein ESAT6-CFP10 (EC) was expressed and purified, and prepared into chitosan nanoparticles (EC-NPs), which were loaded into the microneedle patch and carried out the preliminary test of tuberculosis skin test. The drug loading capacity of MNP-EC-NPs (microneedle patch, MNP) can reach 0.03 μg per needle and 1.92 μg per patch. The shelf life of MNP-EC-NPs can reach 6 months at room temperature, and it can effectively penetrate the epidermis. Volunteer skin test results showed that MNP-EC-NPs can effectively distinguish between BCG vaccinators, and can effectively show positive reaction in the skin of tuberculosis patients without significant side effects. The experiment was approved by the Ethics Committee of Wuhan Pulmonary Hospital [2022 (2)]. In this study, a TB skin test method was established, using ESAT6-CFP10 fusion protein instead of PPD, and using soluble microneedle dosage form, which improved the specificity of TB skin test diagnosis and provided a new technical scheme for TB epidemic screening.

The detection principle of microfluidic microfluidic technology was introduced.The current research status of microfluidic platform-based SARS-CoV-2 nucleic acid detection technologies were reviewed such as reverse transcription quantitative real-time polymerase chain reaction(RT-qPCR),digital PCR,isothermal amplification and clustered regularly interspaced palindromic repeats/CRISPR-associated protein.The deficiencies of microfluidic platform-based SARS-CoV-2 nucleic acid detection were analyzed.It's pointed out microfluidic platform-based SARS-CoV-2 nucleic acid detection had to be optimized and validated clinically in specialty,sensitivity,detection limit,reproducibility,informatization,quality control and reagent cost.[Chinese Medical Equipment Journal,2024,45(1):101-107]