ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective To observe the association between afterschool physical exercise and sleep quality among preschool children,and to explore the proper afterschool physical exercise model for better sleep quality.Methods A cross-sectional study was conducted.From Apr to Jun 2024,a total of 1 430 children from three public kindergartens in Minhang district were enrolled to participate in the survey.Parents were invited to complete the basic sociodemographic information,afterschool physical exercise information and the Children's Sleep Habits Questionnaire.One-way ANOVA and linear mixed effects models were used to explore the relationship between afterschool exercise and sleep quality.Results A total of 1 430 questionnaires were sent out and 1 384 were recovered with a recovery rate of 96.78%.Among them 1 366 were valid,with an effective rate of 95.52%.The average age of the children was(5.19±0.87)years old with gender ration of 1.07∶1(male:female).The prevalence of poor sleep quality was 80.60%(regarding a CSHQ total score>41 as cutoff).A one-way ANOVA indicated that time on afterschool physical exercise was significantly associated with sleep duration,Night waking,and sleep onset delay(P<0.05).After adjusting for age,gender,the only child or not,main caregiver,and parental education and occupation,linear mixed effects models showed that engaging in afterschool physical activity for at least 180 mins per week has a statistically significant predictive effect on sleep duration scores(β=-0.50,z=-4.52,95%CI:-0.72,-0.28,P<0.001),night waking scores(β=-0.16,z=-2.34,95%CI:-0.29,-0.02,P=0.020),and sleep onset delay scores(β=-0.14,z=-2.35,95%CI:-0.26,-0.02,P=0.019).Conclusion Afterschool exercise was significantly associated with sleep quality among preschool children in Minhang district of Shanghai.The time≥180 min on afterschool exercise per week in preschool children was significantly positively associated with maintaining sleep duration,reducing night wakings and shortening the latency to fall asleep.The habit of afterschool exercise and the time on afterschool exercise should be emphasized by parents and the society to improve sleep quality among preschool children.

Objective·To analyze the clinicopathologic characteristics,gene mutation profile,and prognostic factors of patients with adrenal diffuse large B-cell lymphoma(DLBCL).Methods·From March 2002 to December 2022,a total of 105 patients with adrenal DLBCL admitted to Ruijin Hospital,Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data,survival outcomes,and prognostic factors.Patients'gene mutation profiles were evaluated by targeted sequencing of 152 lymphoma-related genes.Results·The median age of the patients was 62(15?82)years and the male-to-female ratio was 2.3∶1.Among them,63 patients(60.0%)were over 60 years old,22 patients(21.0%)had an Eastern Cooperative Oncology Group(ECOG)performance status of two or higher,87 patients(82.9%)were staged Ann Arbor Ⅲ?Ⅳ,92 patients(87.6%)had elevated serum lactate dehydrogenase(LDH)levels(above the upper limit of reference),84 patients(80.0%)had extranodal invasion in at least two organs,67 patients(63.8%)were of non-germinal center B-cell(non-GCB)origin,and 95 patients(90.5%)had an international prognosis index(IPI)scored over 2.With a median follow-up of 28.3(0.7?191.9)months,the estimated 2-year overall survival(OS)rate and progression-free survival(PFS)rate were 68.3%and 53.1%,respectively.The estimated 5-year OS rate and PFS rate were 52.6%and 44.0%,respectively.Among 93 patients who could be evaluated for clinical outcomes,62(66.7%)got a complete response(CR).Univariate analysis and multivariate Cox analysis revealed that age over 60 years was an adverse prognostic factor for PFS,and ECOG performance status of two or higher was an adverse prognostic factor for both OS and PFS.Targeted gene sequencing in 46 adrenal diffuse DLBCL patients showed high mutation frequencies in lysine methyltransferase 2D(KMT2D;n=17,37%),Pim-1 proto-oncogene,serine/threonine kinase(PIM1;n=17,37%),MYD88 innate immune signal transduction adaptor(MYD88;n=15,33%),CD79b molecule(CD79B;n=13,28%),and BTG anti-proliferation factor 2(BTG2;n=10,22%).Conclusion·Age over 60 years is an adverse prognostic factor for PFS,and ECOG performance status of two or higher is an adverse prognostic factor for both OS and PFS in patients with adrenal DLBCL.Patients exhibited high frequencies of KMT2D,PIM1,MYD88,CD79B,and BTG2 mutations,as well as an increased proportion of the MCD-like subtype.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.

Objective:To explore the risk factors for recurrence of thyroid cancer after radical resection via areola endoscopy,and to construct a visual risk prediction model.Methods:The clinical data of 350 thyroid cancer patients who underwent radical surgery via areola endoscopy in our hospital from January 2016 to October 2018 were retro-spectively analyzed,and they were randomly divided into the modeling group(233 cases)and the internal validation group(117 cases)in a 2:1 ratio.All patients were followed up for 3 years after surgery,and the patients of modeling group were further divided into recurrent group(51)and non recurrent group(182)according to whether they with or not recurrence.Another 163 patients with thyroid cancer who underwent laparoscopic radical mastectomy at our hos-pital from January 2019 to May 2020 were selected as the external validation group.The risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy was analyzed by using Cox regression method,and a risk prediction nomogram model was established based on this.Internal validation of the nomogram model was conducted by using the Bootstrap method,and the calibration,predictive efficacy and clinical net benefit of the nomogram model were evaluated by the calibration curve,receiver operating characteristic(ROC)curve and decision curve analysis(DCA).The external validation group data was used for external validation.Results:The recurrence rate of thyroid cancer patients after 5 years of radical surgery via areola endoscopy was 21.64％(111/513).The proportions of multiple le-sions,preoperative lymph node metastasis,TNM stages Ⅲ-Ⅳ and maximum tumor diameter,the levels of thyro-globulin(TG),triiodothyronine(T3),thyroxine(T4),free triiodothyronine(FT3),free thyroxine(FT4)and thyroid stimulating hormone(TSH)in the recurrence group were higher than those in the non recurrence group(P<0.05).The Cox regres-sion analysis results showed that the maximum tumor diameter,multiple lesions,preoperative lymph node metasta-sis,TNM stage Ⅲ-Ⅳ and TG,T3,T4,FT3,FT4 and TSH levels were all risk factors for recurrence of thyroid cancer after radical surgery via areola endoscopy(P<0.05).The risk prediction nomogram model of recurrence of thyroid cancer af-ter radical surgery under areola endoscopy was constructed based on the above influencing factors.After internal and external validation,the consistency indices of the modeling group,internal verification group and external verification group were 0.832,0.825 and 0.41 respectively,and the calibration curves of three groups were close to the standard curve.The ROC curve analysis and verification showed that the area under the curve predicted by the nomogram model of the modeling group,internal verification group and external verification group were 0.859,0.847 and 0.853 respectively.The DCA curve showed that the nomogram model had good clinical net benefits when the threshold probability of the modeling group,internal verification group and external verification group were 0.03-0.82,0.02-0.78 and 0.06-0.88 respectively.Conclusion:The maximum tumor diameter,multiple lesions,preoperative lymph node metastasis,TNM staging stage Ⅲ-Ⅳ and levels of TG,T3,T4,FT3,FT4 and TSH are all risk factors for recurrence of thy-roid cancer after radical surgery via areola endoscopy,and the risk prediction visualization nomogram model con-structed based on this is helpful for clinical screening of high-risk patients to guide early intervention and reduce the risk of recurrence.

Objective:To analyze the exercise rehabilitation preference of stroke patients, and provide reference for clinical medical staff to formulate personalized exercise rehabilitation scheme, construct precise rehabilitation decision support system, and develop exercise rehabilitation intelligent service platform.Methods:A convenience sampling approach was employed to select the stroke patients in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from June to December 2024, a face to face cross-sectional survey was conducted using the questionnaire on exercise rehabilitation preferences of stroke patients based on the method of discrete choice experiments. The obtained data were analyzed using conditional Logit model.Results:Finally, 242 stroke patients were included, including 152 males and 90 females, aged 64 (56, 69) years. The six attributes included in this study: rehabilitation goal, rehabilitation setting, exercise intensity, exercise duration, exercise supervision method, and payment method. The relative importance of each attribute was ranked as follows: payment method (37.1%), exercise duration (15.5%), supervision method (14.3%), rehabilitation setting (14.1%), exercise intensity (11.4%), and rehabilitation goal (7.6%). The most preferred combination was identified as a rehabilitation goal of ≥70% recovery, professional institution/hospital as the setting, supervision by wearable device combined with professional guidance, low-intensity exercise, a duration of 30-60 minutes per session, and a self-payment rate of <30%. Under this combination, the probability of patients choosing the rehabilitation program was 75.4%.Conclusions:Stroke patients' preferences for exercise rehabilitation are influenced by multiple factors, with substantial heterogeneity observed across individuals. Rehabilitation programs should be tailored according to patients' preferences regarding goals, settings, duration, and other key attributes to enhance adherence and optimize rehabilitation outcomes.

Aim To explore the possible regulatory effect of leptin on acyl-CoA synthetase long chain fami-ly member ACSL5 and their effect on migration and in-vasion of breast cancer cell,and to explore the underly-ing mechanism.Methods The expression of leptin receptor was detected by immunofluorescence assay.The migration and invasion ability of MCF-7 cells were detected by wound healing assay and Transwell assay respectively.The downstream target gene of leptin was analyzed by PCR microarray data.The expression of ACSL5 in breast cancer and its correlation with the staging and prognosis of breast cancer patients were as-sessed uing bioinformatics methods.The expression of ACSL5 in MCF-7 cells treated with different concentra-tions of leptin was detected using real time fluorescence quantitative polymerase chain reaction(RT-qPCR).Overexpressing ACSL5 was constructed by lentiviral transfection;the expressions of EMT related proteins,AMPK-α and p-AMPK-α were detected by Western blot.Results Leptin promoted breast cancer cell mi-gration and invasion and EMT.ACSL5 was significant-ly low expressed in breast cancer and related to progno-sis.Leptin downregulated the expression of ACSL5 through OBR.Leptin activated AMPK pathway to downregulate ACSL5 and promote migration,invasion and EMT of breast cancer cells.Conclusions Leptin may promote the migration,invasion and EMT of breast cancer by downregulating ACSL5 through activating AMPK pathway.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.