Objective: To explore the value of contrast-enhanced computed tomography (CT) radiomics combined with machine learning algorithms in the preoperative prediction of perineural invasion (PNI) in oral squamous cell carcinoma (OSCC), aiming to provide evidence for assisting clinical treatment decision-making. Methods​: This study was approved by the Ethics Committee of the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. A total of 250 OSCC patients confirmed by postoperative pathology were included, comprising 128 PNI-positive and 122 PNI-negative cases. The dataset was randomly divided into training (n=175), validation (n=38), and independent testing (n=37) sets in a ratio of 7:1.5:1.5. Regions of interest were delineated on preoperative images, and radiomic features were extracted. After dimensionality reduction and feature selection using methods like Least Absolute Shrinkage and Selection Operator (LASSO) regression, multiple machine learning models, including support vector machine (SVM), random forest, Light gradient boosting machine (LightGBM), and a Stacking ensemble model, were constructed. Model performance was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, calibration curves, and decision curve analysis (DCA). Model interpretability was analyzed using Shapley additive explanations (SHAP) and grouped permutation feature importance analysis. Results ​: ​ Among the 250 samples analyzed, the LightGBM model based on radiomics demonstrated the best performance on the independent test set, with an AUC of 0.781, outperforming models like SVM (AUC = 0.730) and Random Forest (AUC = 0.691), as well as clinical models (AUCs ranging 0.549-0.711). The LightGBM model showed good calibration (Brier score 0.198), and DCA indicated high clinical net benefit over a wide threshold probability range. Paired DeLong tests revealed no statistically significant differences in AUC between the ensemble (Stacking) model and the corresponding best-performing radiomics-based model. SHAP analysis and grouped permutation feature importance analysis further indicated that the primary discriminative information for the model came from radiomic texture features. Conclusion ​ The LightGBM model based on contrast-enhanced CT radiomics demonstrated good discriminative ability for preoperative prediction of PNI in OSCC. In the independent test set, it achieved the highest AUC. This model holds promise as a non-invasive auxiliary tool for preoperative risk assessment. Given the limited sample size of the independent test set, these results require further validation in larger cohorts and external datasets.

ObjectiveCell adhesion is a critical process that regulates cellular physiological functions. Quantitative characterization of adhesion dynamics is essential for elucidating the intrinsic mechanical mechanisms underlying cellular activities. Although atomic force microscopy-based single-cell force spectroscopy is widely used for single-cell adhesion measurements, it requires complex chemical modifications for preparation of live-cell probes, leading to limitations such as cumbersome operation, low throughput, and potential impacts on cell viability. Fluidic force microscopy, which combines atomic force microscopy with microfluidic probes, is a technique allowing the operation of force-controlled nanopipettes in aqueous environments. By applying negative or positive pressure via a pressure controller, a single living cell can be captured onto or released from the cantilever under physiological conditions. This procedure offers a simple workflow and high assay throughput for single-cell adhesion measurements without the need for chemical functionalization. In this study, fluidic force microscopy-based single-cell force spectroscopy was adopted to achieve long-term quantitative characterization of single-cell adhesion dynamics in a simpler and more efficient manner, comparing the dynamic differences in adhesion establishment between two cell lines with different differentiation levels. MethodsHEK 293T and hTERT RPE-1 cells were non-invasively captured on the cantilever of a fluidic force microscope via its integrated microfluidic system during 40 h of adhesion culture. Cell-substrate detachment assays were performed, and force-distance curves were recorded to extract key mechanical adhesion parameters, including adhesion force, adhesion energy, and maximum detachment distance. These measurements were combined with real-time monitoring of cell spreading area to systematically characterize the dynamic evolution of single-cell adhesion. ResultshTERT RPE-1 cells rapidly entered a stable adhesion phase within 1 h after seeding, with both area-normalized adhesion force and area-normalized adhesion energy reaching peak values. In contrast, HEK 293T cells required 4 h to achieve stable adhesion. Subsequently, the adhesion force, adhesion energy and maximum detachment distance of hTERT RPE-1 and HEK 293T cells stabilized at approximately 240 nN vs. 30 nN, 2.2 pJ vs. 0.12 pJ and 6 μm vs. 4 μm, respectively. hTERT RPE-1 cells reached the peak of area-normalized adhesion parameters earlier than HEK 293T cells, with their peak area-normalized adhesion force and area-normalized adhesion energy being substantially elevated relative to HEK 293T cells. HEK 293T cells presented stronger linear correlations among adhesion energy, maximum detachment distance and adhesion force compared with hTERT RPE-1 cells. For both cell lines, cell spreading area exhibited a weak correlation with adhesion force. Whereas the area-normalized adhesion parameters of HEK 293T cells remained relatively constant throughout the adhesion process, hTERT RPE-1 cells exhibited elevated values in the early phase, followed by a gradual decline. These results indicated distinct dynamic adhesion patterns between the two cell types, with hTERT RPE-1 cells exhibiting stronger adhesion strength and higher adhesion efficiency. ConclusionIn this study, fluidic force microscopy-based single-cell force spectroscopy was successfully applied to perform long-term in situ quantitative measurement of the adhesion dynamics in single adherent cells. The approach revealed divergent adhesion patterns between HEK 293T and hTERT RPE-1 cells, suggesting a close association between cell differentiation and adhesion behaviors. These findings provide quantitative mechanical evidence for further understanding the underlying mechanisms of cell adhesion.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

Objective To explore the value of the time to positivity(TTP)combined with inflammatory indicators for identifying coagulase-negative Staphylococcus(CoNS)bloodstream infection and contamination in tumor patients.Methods A retrospective analysis was performed on totally 368 tumor patients with blood culture-positive admitted to the hospital from September 2022 to April 2023,and 47 patients with blood cul-ture-positive CoNS and complete clinical data were selected as research objects.The patients were divided into CoNS infection group(24 cases)and CoNS contamination group(23 cases)according to the diagnostic criteria of bloodstream infection and in combination with the clinical manifestations and laboratory examination re-sults.In addition,5 tumor patients with blood culture Staphylococcus aureus positive admitted to the hospital during the same period were selected as the control group.The TTP,percentage of immature granulocytes(IG%),absolute value of immature granulocytes(IG#),white blood cell count(WBC),neutrophil percent-age(NE%),neutrophil-to-lymphocyte ratio(NLR),C-reactive protein(CRP)and procalcitonin(PCT)levels in all groups were compared.Results Among the 47 patient isolates of CoNS from blood cultures,Staphylo-coccus hominis was the most common,accounting for 42.55%.There were significant differences in TTP,NE%,NLR and CRP levels between CoNS infection group,CoNS contamination group and control group(P<0.05).The TTP in CoNS infection group was shorter than that in CoNS contamination group,and the levels of NE%,NLR,CRP and PCT were higher than those in CoNS contamination group,with statistical sig-nificance(P<0.05).TTP combined with NLR,CRP and PCT had the largest area under the curve,which was 0.971(P<0.000 1),with a sensitivity of 91.67%,specificity of 95.65%,likelihood ratio of 21.08,positive predictive value of 91.67%,negative predictive value of 95.65%,and an accuracy of 93.62%.Conclusion TTP combined with NLR,CRP and PCT have important clinical value in the differential diagnosis of CoNS blood-stream infection and contamination in tumor patients.

Cardiovascular disease and cancer are the two leading chronic conditions contributing to global mortality. With the rising incidence of cancer, the prevalence of cancer therapy-related cardiovascular complications has also increased, driving the development of the emerging field of cardio-oncology. The advancement of precision medicine offers new opportunities for the individualized and targeted management of cardiovascular toxicities associated with cancer treatment. Artificial intelligence (AI) has the potential to overcome traditional limitations in medical data integration, dynamic monitoring, and interdisciplinary collaboration, thereby accelerating the application of precision medicine in cardio-oncology. By enabling personalized treatment and reducing cardiovascular complications in cancer patients, AI serves as a critical tool in this domain. This article provides an in-depth interpretation of the 鈥淎rtificial intelligence to enhance precision medicine in cardio-oncology: a scientific statement from the American Heart Association鈥?aiming to inform the integration of AI into precision medicine in China. The goal is to promote its application in the management of cardiovascular diseases related to cancer therapy and to achieve precision management in this context.

Objective:To evaluate the music perception ability and appraisal status of cochlear implant adult users, then to compare those with normal-hearing subjects.Methods:The Iowa Musical Background and Appreciation Questionnaire (IMBAQ) was conducted to evaluate 20 cases of post-lingual deafness cochlear implant recipients (9 males, 11 females) aged 12-61(mean=28.8 yrs). Those music perception abilities were tested via Music Perceptional Evaluation Platform. Two kinds of tone(C#3, C#5)were carried out in the music perception test, including the Just Noticeable Difference (JND) Test, the Pitch-Direction Discrimination (PDD) Test and the Melody Contour Identification (MCI) Test. Meanwhile, the timbre identification tests were received by both normal hearing and cochlear implant patients.Results:The total outcomes of cochlear implant recipients were inferior to the normal hearing subjects ( P<0.05). Both of the thresholds of JND ( P=0.001) and PDD ( P<0.001) had a significant difference, while comparing the two frequency values (C#3 and C#5) in cochlear implant adult users. IMBAQ results indicated the lower post-implantation music appreciation and engagement compared to pre-deafness levels. The longer duration of formal music training was positively correlated with better music perception performance in CI recipients. Conclusions:There still has a big gap between the cochlear implant group and normal hearing group in the music perception test. And different frequency value causes effect on the result of cochlear implant patient group.

Iodine is an indispensable trace element in the human body and its intake level is closely related to thyroid function. Iodine deficiency or iodine excess will lead to iodine-related diseases. The implementation of the universal salt iodization policy of China has achieved remarkable results, yet it is still facing the problems of iodine deficiency and iodine excess at present. Since iodine in the human body is mainly metabolized by the kidneys and excreted in urine, urinary iodine test has become an effective way to reflect the recent iodine nutrition status of the body. This article will discuss the current iodine nutrition status of the population in China, the hazards of iodine deficiency and iodine excess, as well as the clinical application of urinary iodine test.

BACKGROUND:Knee osteoarthritis is a common degenerative disease that significantly impacts patients'quality of life and increases the societal healthcare burden.Early and accurate diagnosis of knee osteoarthritis is crucial for the treatment and prognosis of patients.Traditional diagnostic methods are not only subjective and time-consuming but also do not guarantee consistently high accuracy.OBJECTIVE:To develop an automatic diagnostic method for knee osteoarthritis based on deep learning,utilizing deep learning networks to improve diagnostic accuracy and efficiency.METHODS:A new network model,YOLOV8-ViT,was proposed by replacing the backbone network of YOLOv8n with the Efficient-ViT network and incorporating attention mechanisms for the automatic identification and classification of X-ray images of knee osteoarthritis.The experimental dataset included 5 078 X-ray images of patients with knee osteoarthritis obtained from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine.Three imaging physicians annotated the sites of knee osteoarthritis and classified them according to the Kellgren-Lawrence grading standard using Labelme software,and the results were combined.The evaluation indicators used in this study included Precision,F1 score,mean average precision(mAP),Recall,val/box_loss,val/cls_loss,and val/dfl_loss.RESULTS AND CONCLUSION:The experimental results showed that the YOLOV8-ViT model outperformed the YOLOv5n,YOLOv8n,and YOLOv9n models in terms of precision,mAP50,mAP50-95,F1 score,and Recall,while lowering val/box_loss,val/cls_loss,and val/dfl_loss by 0.496,0.45,and 0.523;1.037,0.305,and 0.728;and 0.267,0.654,and 0.854,respectively.These experimental data validate that this model has high detection accuracy.

Objective To study the regulatory effect of Qufeng Xiaodian Formula on serum differential metabolites of allergic purpura,and provide scientific basis for the diagnosis and treatment of allergic purpura in traditional Chinese medicine.Methods Sixty rats were randomly divided into a blank control group(referred to as the blank group),a model group,a compound glycyrrhizin group,a low-dose Qu Feng Xiao Dian Fang group,a medium dose Qu Feng Xiao Dian Fang group,and a high-dose Qu Feng Xiao Dian Fang group according to a random number table method,with 10 rats in each group.The model group was constructed by combining dried ginger,pepper,and long pepper with ovalbumin to create an allergic purpura rat model.After successful modeling,each treatment group was intervened with corresponding drugs for 4 weeks.After 4 weeks,serum was collected and non targeted metabolomics screening of serum differential metabolites was performed using ultra-high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer(UPLC-QTOF/MS).Subsequently,data extraction and multivariate statistical analysis will be conducted to identify potential metabolic pathways.Results Compared with the control group,there were 91 possible differential metabolites in the serum of the model group rats,corresponding to 20 metabolic pathways;Compared with the model group,there were a total of 43 possible differential metabolites in the serum of rats in the wind dispelling and disease eliminating group,corresponding to 15 metabolic pathways.Among them,there are a total of 12 metabolic pathways.Inflammatory metabolites such as arachidonic acid and ceramide can damage vascular endothelium.Ten biomarkers,including arachidonic acid and ceramide,were significantly abnormal in the serum of the model group rats compared to the normal group.The Qufeng Xiaodian formula can significantly reverse these metabolites and significantly enrich them in arachidonic acid metabolism and sphingolipid metabolism pathways.Conclusion Qufeng Xiaodian Formula has a certain regulatory effect on metabolites such as arachidonic acid and ceramide that affect vascular endothelial injury.

Objective To observe MRI manifestations of temporomandibular joint(TMJ)involvement of juvenile idiopathic arthritis(JIA).Methods Sixteen children with JIA who underwent MR examination of TMJ were retrospectively enrolled.Clinical data were collected,MRI manifestations of inflammation domain and damage domain of TMJ were observed,and evaluation based on JIA MRI scoring system for TMJ(JAMRIS-TMJ)was performed.Results Among 16 children with JIA,14 exhibited symptoms associated with TMJ involvement.One or multiple abnormal MRI manifestations were noticed in 25(25/32,78.13％)TMJ,including bone marrow edema in 12(12/32,37.50％),effusion in 8(8/32,25.00％)and synovial thickening in 6(6/32,18.75％),condylar flattening in 10(10/32,31.25％),bone erosion in 6(6/32,18.75％)and articular disc abnormalities in 2(2/32,6.25％)TMJ,while no obvious abnormality was observed in 7(7/32,21.88％)TMJ.Among 4 JIA children who underwent enhanced MR scanning,enhanced bone marrow was found in 2(2/8,25.00％),while synovial enhancement was observed in 4(4/8,50.00％)TMJ.According to JAMRIS-TMJ scoring,for inflammation domain,there were 7(7/32,21.88％)normal TMJ,17(17/32,53.13％)mild and 8(8/32,25.00％)moderate/severe inflammation TMJ,while for damage domain,there were 12(12/32,37.50％)normal TMJ,14(14/32,43.75％)mild and 6(6/32,18.75％)moderate/severe damage TMJ.Conclusion MRI manifestations of TMJ involvement of JIA mainly included bone marrow edema,joint effusion,condylar flattening and so on.