Objective: To analyze changes in tuberculosis infection among junior high school students before and after tuberculosis exposure, so as to provide a reference for improving school tuberculosis prevention and control measures and policy formulation. Methods: Retrospectively collect data on a tuberculosis outbreak that occurred in a grade of a junior high school in Chongqing in 2025, including tuberculosis screening records of students in this grade upon their enrollment in 2022 (1 156 students) and after two tuberculosis outbreaks in 2023 (206 students) and 2025 (171 students). The Wilcoxon signed rank test for paired design was used to compare the induration diameters of the subjects, and the Chi square test was adopted to analyze the rate of tuberculosis infection among students. Results: In the tuberculosis outbreak in 2023, the rate of tuberculosis infection among close contacts ( 11.84 %) and the rate of tuberculosis infection among freshrman at school enrollment (12.89%) showed no statistically significant difference ( χ 2=0.25, P >0.05). The rate of tuberculosis infection of close contacts in the 2025 tuberculosis outbreak (55.56%) was higher than that in the 2023 outbreak (11.84%) ( χ 2=30.42, P <0.01). Among the 106 students included in the cohort analysis, the median induration diameter was 3.50 (1.50, 7.50) mm in 2023 and 8.75 (4.25, 11.50) mm in 2025, with a statistically significant difference ( Z=-5.76, P <0.01). There was no statistically significant difference between the infection rate in 2022 (16.98%) and that in 2023 (10.38%) ( χ 2=1.96, P =0.16). The infection rate in 2025 (43.40%) was higher than those in 2022 and 2023 ( χ 2=17.55, 29.39, both P <0.017). The seroconversion rate of students in the same class in 2025 ( 58.00 %) was higher than that of students in different classes (16.07%), with a statistically significant difference ( χ 2=20.19, P <0.01). All 72 individuals with latent tuberculosis infections identified during the pandemic in 2023 and 2025 refused to undergo prophylactic treatment. Conclusions The lack of preventive treatment may be the underlying cause of the successive outbreaks during the epidemic. Early detection of infection sources and standardized outbreak management are crucial to controlling the spread of the epidemic.

A pyrene-phenol-based fluorescent probe PyP which showed typical intramolecular charge transfer(ICT)and monomer-excimer activities was synthesized by using pyrene carboxaldehyde hydrazone and 4-tert-butyl-2,6-diformylphenol as the raw materials.The effects of solvents on PyP were studied,and the results showed that the color of protic polar solvents(Ethanol,N,N-dimethylformamide,methanol and H2O)were successfully identified.Based on the solvent polarity-regulated PyP monomer-excimer switching,the rapid and highly sensitive ratiometric probe,"Turn-off"and"Turn-on"multimodal probes were established for detection of trace water content in organic solvents(Dimethyl sulfoxide,N,N-dimethylformamide,ethanol and methanol),with detection limits(3σ/k)of 0.0021％,0.046％,0.062％and 0.024％.The method was successfully used to detect water content in dimethyl sulfoxide,N,N-dimethy lformamide,ethanol and methanol commercial organic solvents,with recoveries ranging from 97.2％to 108.0％.The developed method showed good accuracy and stability,and had good application prospect.

Nano/microplastics(NMPs),due to their environmental persistence and resistance to degradation,have emerged as a major contributor to global pollution.NMPs are capable of adsorbing various hazardous chemicals and heavy metals,thereby posing threats to aquatic ecosystem health,which may ultimately cause potential risks to human health.Conventional analytical methods suffered from limited resolution,insufficient chemical information,or destruction of sample,invalidating these assays for on-site detection of NMPs.Surface-enhanced Raman scattering(SERS)offers distinct advantages such as high sensitivity,superior specificity,rich fingerprint information,and non-destructive analysis,thus facilitating the on-site analysis of NMPs in complex matrices.This review summarized recent advances in SERS substrates for detection of NMPs,discussed the construction and applications of SERS-based multimodal detection strategies,and introduced the research progress of SERS detection of NMPs in food safety,environmental pollution,and bioanalysis.Moreover,the main challenges and future directions of SERS-based NMP detection were outlined.

Under the background of forensic medicine becoming a first-level discipline,the opportuni-ties and challenges of discipline development coexist.Starting from the actual situation and characteris-tics of local medical colleges and universities,this paper discusses the problems and solutions for the development of forensic medicine discipline from the perspective of building a regional high-level medical university.Combined with the experiences of carrying out forensic medicine education in our college,this paper supplies our thoughts and practices on improving the discipline system,enhancing the ability to serve society,perfecting the talent cultivation model and promoting forensic culture,to provide reference and inspiration for the development of forensic medicine in other universities,jointly promote the advancement of forensic medicine in China to a new stage,and contribute the wisdom and strength of forensic medical experts to the construction of a law-based China,a safe China and a healthy China.

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 verify the efficacy of a domestic human DNA quantification kit based on real-time fluorescence quantitative PCR in detecting the total human DNA concentration,male DNA concen-tration in mixed male/female DNA samples,the degree of DNA degradation and inhibitor tolerance.Methods Samples with different concentrations,different male/female ratios,different concentrations of inhibitors,and different degradation degrees were tested using the domestic human DNA quantification kit based on real-time fluorescence quantitative PCR.This kit was compared with a similar product on the market and was applied to the detection of DNA from real cases.Results This human DNA quan-tification kit can effectively detect human DNA as low as 0.001 65 ng/μL,and 6.25 pg/μL of male DNA in mixed samples with a male-to-female ratio of 1∶15 000.Even when the sample contains as high as 400 ng/μL of humic acid or 1 000 μmol/L of hemin alone,the DNA concentration can still be accurately detected.The degradation index can effectively characterize the degradation degree of the sample.This kit has been successfully applied in forensic practice.Conclusion This human DNA quan-tification kit is accurate and reliable in detection.It can accurately reflect the degradation of DNA and inhibitor tolerance.It has good performance in quantitative accuracy,determination of the male/female ratio in mixed samples,and inhibitor tolerance.It has application potential in forensic case examination.

Objective:To establish the quality standard of Galla Turcica standard decoction; To provide a reference for the quality evaluation of its decoction granules.Methods:The moisture, total ash, acid-insoluble ash, and extract of Galla Turcica were assessed according to the guidelines specified in the Chinese Pharmacopoeia (Volume Ⅳ); high-performance liquid chromatography (HPLC) was employed to quantify the gallic acid content in sixteen batches of Galla Turcica and standard decoction, from which the transfer rate was calculated; the paste rate, moisture, and extract yield were quantitatively analyzed, establishing the comprehensive fingerprint of Galla Turcica standard decoction. The quantitative value transfer rules of common peaks from medicinal materials to standard decoction were studied through similarity evaluation and stoichiometric analysis. Results:The gallic acid content of the sixteen batches of Galla Turcica standard decoction ranged from 76.79 mg/g to 115.04 mg/g, the range of transfer rate was 24.02% to 47.82%, the extraction rate was 34.04% to 63.23%, the moisture was 1.11% to 2.06%, and the extract was 94.44% to 101.75%. A total of nine characteristic peaks were identified in the fingerprints of the sixteen batches of Galla Turcica and standard decoction, and four characteristic peaks were identified: gallic acid (GA), 1, 2, 3, 6 - tetragalloylglucose (TeGG), ellagic acid (EA) and 1, 2, 3, 4, 6, - pentagalloylglucose (PGG). Clustering analysis revealed that at a measurement distance of fifteen, the sixteen batches could be grouped into two categories. Principal component analysis (PCA) showed that three principal components were extracted with a cumulative variance contribution rate of 84.204%, which could represent most of the information of the samples.Conclusions:The standard decoction preparation process developed in this study adheres to the requirements of traditional decoction methods and has proven to be both effective and feasible. This method can be used for the research and quality evaluation of standard decoction of Galla Turcica, and provide a basis for subsequent formulation granules and related research.

Abstract Tumor immune escape represents a pivotal determinant of cancer immunotherapy failure. It's mechanistically linked to immunosuppressive tumor microenvironment(TME). The TME comprises tumor cells, immune cells, stromal components and extracellular matrix. These components interact synergistically to suppress antitumor immunity through multiple pathways, thereby promoting immune evasion. As crucial chromosomal stability regulators, centromere proteins(CENPs) remodel the TME via multifaceted mechanisms to potentiate immune evasion. This review synthesizes current knowledge on CENPs' role in tumor immune evasion, offering novel insights for cancer diagnostics and immunotherapy.

BACKGROUND:Various proteins,signaling pathways,and inflammatory mediators are involved in the pathophysiological process of osteoarthritis.The development of small molecule drugs targeting these proteins,signaling pathways,and inflammatory mediators can effectively delay the progression of osteoarthritis and ameliorate its clinical manifestations. OBJECTIVE:To review the research progress of small molecule drugs in the treatment of osteoarthritis based on the pathogenesis of osteoarthritis. METHODS:PubMed,CNKI,and WanFang databases were searched with English search terms"osteoarthritis,arthritis,osteoarthrosis,degenerative,arthritides,deformans,small molecule drugs,small molecule inhibitors,small molecule agents"and Chinese search terms"osteoarthritis,small molecule drugs,small molecule inhibitors."A total of 68 articles were included for review according to the inclusion and exclusion criteria. RESULTS AND CONCLUSION:(1)Currently,studies concerning the pathogenesis of osteoarthritis remain unclear.The occurrence and development of osteoarthritis are strongly associated with proteins,cytokines,and signal transduction pathways,so its therapeutic mechanism is relatively complex.Currently,targeting proteins,cytokines,and signal transduction pathways related to osteoarthritis with small molecule drugs has become a major research focus.(2)Small molecule drugs frequently possess visible intracellular or extracellular targets and efficacy,containing enhancing cartilage repair,resisting joint degradation,attenuating inflammation,and relieving pain.Other anti-osteoarthritis small molecule drugs have shown promise in promoting stem cell chondrogenic differentiation and cartilage matrix reconstruction.(3)At present,small molecule drugs targeting the pathophysiological process of osteoarthritis to delay the progression of osteoarthritis are still in the experimental stage,but most of these small molecule drugs have shown the expected results in the experimental process,and there are no relevant studies to illustrate the efficacy of small molecule drugs in the treatment of osteoarthritis.(4)Small molecule drugs for the treatment of osteoarthritis have reached the expected experimental results in the basic experimental stage.Numerous studies have exhibited that small molecule drugs can target the suppression of specific proteins,cytokines,and signal transduction pathways that cause osteoarthritis,so as to treat osteoarthritis.Nevertheless,its safety and effectiveness still need to be identified by further basic and clinical studies.This process needs to be investigated and studied by more scholars.(5)At present,many scholars in and outside China have made contributions to the treatment of osteoarthritis.Compared with traditional treatment methods,small molecule drugs reveal better efficacy and safety in the basic experimental stage,and it is expected to become an emerging method for the treatment of osteoarthritis in the future to rid patients of pain.