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.

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.

Objective To compare the effects of sequential Exoview and Mimics three-dimensional reconstruction with fluorescence method in thoracoscopic pulmonary segmentectomy.Methods The clinical data of 160 patients with lung cancer admitted to our hospital from January 2020 to June 2023 were retrospectively analyzed.Among them,79 patients who underwent thoracoscopic pulmonary segmentectomy with the sequential Exoview three-dimensional reconstruction and fluorescence method before the operation were classified as the Exoview group,and 81 patients who underwent thoracoscopic pulmonary segmentectomy with the sequential Mimics three-dimensional reconstruction and fluorescence method before the operation were classified as the Mimics group.The surgical completion status,the coincidence rate between the number of left and right pulmonary artery branches evaluated before operation and intraoperative findings,reconstruction time,segment display effect,general indicators of operation(operation time,intraoperative blood loss,number of lymph node dissection,thoracic tube placement time,postoperative hospital stay),pulmonary function[forced expiratory volume in one second(FEV1),percentage of forced expiratory volume in one second(FEV1%)]and complications were compared between the two groups.Results All patients in the two groups successfully completed thoracoscopic pulmonary segmentectomy,and indocyanine green was injected once in each group.The operation process was roughly consistent with the preoperative simulation,and no thoracotomy was performed.There was no statistically significant difference in the resection of lung segment between the two groups of patients(P>0.05).The coincidence rate between the number of left and right pulmonary artery branches evaluated before operation and intraoperative findings in the Exoview group was higher than that in the Mimics group(P<0.05).There was no significant difference in the segment display effect between the Exoview group and the Mimics group(P>0.05).The operation time and the reconstruction time in the Exoview group were shorter those that in the Mimics group,and the intraoperative blood loss was less than that in the Mimics group(P<0.05).There was no significant difference in the number of lymph node dissection,the thoracic tube placement time,or the postoperative hospital stay between the two groups(P>0.05).There was no statistically significant difference in FEV1 or FEV1%7 days after surgery compared with those before surgery(P>0.05).The FEV1 and FEV1%of patients in the Mimics group 7 days after surgery were lower than those beforesurgery(P<0.05).There was no statistically significant difference in FEV1 or FEV1%between the Exoview group and the Mimics group before and 7 days after surgery(P>0.05).The total incidence of complications in the Exoview group was 1.27%,compared with 4.94%in the Mimics group,the difference was not statistically significant(P>0.05).Conclusion Both sequential Exoview and Mimics three-dimensional reconstruction with fluorescence method are safe and effective for thoracoscopic pulmonary segmentectomy,while Exoview has more advantages in preoperative assessment of the number of pulmonary artery branches,and it has shorter reconstruction time and operation time,with less impact on lung function.

Objective:This study aims to analyze the focus and existing shortcomings of informal elderly care policy in China,and to provide references for policy system optimization.Methods:A two-dimensional analysis framework of"policy instruments-participating actors"was constructed and a content analysis method was applied to quantitatively analyze 34 relevant policy texts on informal elderly care(2011-2025),aiming to reveal the structural features and evolution logic of the policy system.Results:The policy evolution has undergone three stages,including institutional initiation,regulated development,and systematic deepening.In terms of policy tools,supply-side,environmental,and demand-side tools accounted for 39.6%,33.6%,and 26.8%,respectively,with the structure transitioning from a"supply-dominated"to a diversified synergistic model of"supply optimization+environmental empowerment+demand stimulation".In terms of participating actors,government departments(27.7%)played a dominant role,technology enterprises showed increased participation(20.6%),while family members remained underrepresented(9.2%).Conclusion:It is necessary to further optimize the structure of policy tool,strengthen social participation and family support systems,promote the deep integration of technology and humanistic care,and enhance the systematicness and effectiveness of the policy system.

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 aims to analyze the focus and existing shortcomings of informal elderly care policy in China,and to provide references for policy system optimization.Methods:A two-dimensional analysis framework of"policy instruments-participating actors"was constructed and a content analysis method was applied to quantitatively analyze 34 relevant policy texts on informal elderly care(2011-2025),aiming to reveal the structural features and evolution logic of the policy system.Results:The policy evolution has undergone three stages,including institutional initiation,regulated development,and systematic deepening.In terms of policy tools,supply-side,environmental,and demand-side tools accounted for 39.6%,33.6%,and 26.8%,respectively,with the structure transitioning from a"supply-dominated"to a diversified synergistic model of"supply optimization+environmental empowerment+demand stimulation".In terms of participating actors,government departments(27.7%)played a dominant role,technology enterprises showed increased participation(20.6%),while family members remained underrepresented(9.2%).Conclusion:It is necessary to further optimize the structure of policy tool,strengthen social participation and family support systems,promote the deep integration of technology and humanistic care,and enhance the systematicness and effectiveness of the policy system.

Objective:To explore the longitudinal predictive relationship between self-neglect and frailty among older adults.Methods:Data were drawn from the Chinese Longitudinal Healthy Longevity Survey conducted in 2011 (T1), 2014 (T2), and 2018 (T3). A total of 1 495 older adults aged≥65 years at T1 who participated in three consecutive surveys and had no missing key variables were included. General demographic information, self-neglect scores, and frailty status were extracted. Spearman correlation analysis was used to examine the association between self-neglect and frailty. Cross-lagged analysis was employed to investigate the potential causal relationship between the two variables.Results:The self-neglect scores for 1 495 older adults at T1, T2, and T3 were (2.84±1.39), (2.47±1.30), and (2.41±1.20), respectively, showing a declining trend. The frailty scores at T1, T2, and T3 were 0 (0, 1.00), 0 (0, 2.00), and 1.00 (0, 2.00), respectively, indicating an increasing trend. Cross-lagged analysis revealed that self-neglect at T1 positively predicted frailty at T2 (β=0.076, P=0.004). Frailty at both T1 and T2 positively predicted self-neglect at T2 (β=0.057, P=0.044) and T3 (β=0.058, P=0.029), respectively. Conclusions:Frailty among older adults positively predicts self-neglect, and self-neglect also has a certain predictive effect on frailty. Medical staff should strengthen early screening and intervention for frailty in older adults to delay the occurrence and progression of self-neglect.

Objective:To investigate the efficacy of fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), aspartate aminotransferase to platelet count ratio (APRI), liver stiffness value (LSM), and Agile 3+ score and their combined model in predicting advanced-stage liver fibrosis in patients with chronic hepatitis B (CHB) combined with metabolic-associated fatty liver disease (MAFLD).Methods:A multicenter retrospective cohort study was conducted on the BMOVE population.Nine hundred twenty CHB cases combined with MAFLD who underwent liver biopsy at seven medical centers in China from April 2006 to December 2023 were included. The patients were divided into advanced-stage liver fibrosis (159 cases) and non-advanced-stage liver fibrosis (761 cases) according to the Scheuer's scoring system.The area under the receiver operating characteristic curve (AUROC), decision curve, and calibration curve analysis were used to evaluate the efficacy of the firbrosis-4 index (FIB-4) score, NFS score, APRI index, LSM, and Agile 3+ score and their combined model in predicting advanced-stage fibrosis. The liver fibrosis grade of all patients was diagnosed by liver biopsy. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each scoring model and combined model, as well as the proportion of correctly classified patients, were calculated based on different cutoff values.Results:AUROC analysis showed that Agile 3+ (0.814, 95% CI: 0.787-0.838) and LSM (0.805, 95% CI: 0.778-0.829) had similar accuracy and were superior to FIB-4 (0.721, 95% CI: 0.691-0.749), NFS (0.687, 95% CI: 0.656-0.716) and APRI ( 0.689, 95% CI: 0.658-0.718); however, HBV DNA level and HBV e antigen status had no effect on this outcome. Decision curve analysis showed that interventions based on LSM and Agile 3+ had provided higher net benefits compared with serological scores. Calibration curves showed that Agile 3+ had better predicitive accuracy than all other models. Agile 3+ had the highest PPV (0.54), minimal uncertainty interval (11.6%), and the highest proportion of correctly classified patients (76%); followed by LSM (PPV: 0.43, uncertainty interval: 15.5%, correct classification rate: 66%), and FIB-4 (PPV: 0.42, uncertainty interval: 26.1%, correct classification rate: 62.6%) in terms of identifying advanced-stage liver fibrosis. Combined model analysis demonstrated that FIB-4 combined with Agile 3+ had improved the correct classification rate and reduced the proportion of missed patients compared with FIB-4 combined with LSM. Conclusion:The Agile 3+ score is superior than LSM, FIB-4, NFS, and APRI index at identifying advanced-stage fibrosis in patients with CHB combined with MAFLD. This study supports the use of FIB-4 index combined with Agile 3+ for risk stratification in patients with CHB combined with MAFLD.