ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

ObjectiveAbnormal lipids in neurons can cause the accumulation of α-synuclein（α-syn）. This study aimed to explore the mechanism of Acanthopanacis Senticosi Radix et Rhizoma seu Caulis extract （ASH） in treating Parkinson's disease （PD） mice using lipidomics combined with network pharmacology. MethodsMice were divided into the blank group， model group and ASH （45.5 mg·kg^-1） group. Motor ability was evaluated by pole climbing time and autonomous activity count； The oxidative stress indicators were detected by enzyme-linked immunosorbent assay （ELISA）. Lipid biomarkers in brain tissues were screened and identified by ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）， and metabolic pathway analysis was conducted. The key targets of ASH for PD treatment were explored using network pharmacology. The Kyoto Encyclopedia of Genes and Genomes （KEGG） database was used for pathway enrichment analysis， and the "compound-reaction-enzyme-gene" network was constructed using the MetScape plugin. The protein expression levels of glutathione S-transferase P1 （GSTP1）， glutathione S-transferase Mu 2 （GSTM2）， prostaglandin peroxide synthase 1 （PTGS1）， prostaglandin peroxide synthase 2 （PTGS2）， and prostaglandin E synthase （PTGES） were validated by Western blot. ResultsCompared with the blank group， the model group showed significantly prolonged pole climbing time and reduced autonomous activity count （P<0.01）. Compared with the model group， the ASH group demonstrated significantly faster pole climbing and increased autonomous activity count （P<0.01）. The model group exhibited significantly decreased superoxide dismutase （SOD） and glutathione peroxidase （GSH-Px） levels， and increased malondialdehyde （MDA） level in brain tissues compared with the blank group （P<0.01）. The ASH group showed increased SOD and GSH-Px levels and decreased MDA level compared with the model group （P<0.05， P<0.01）. Lipidomics analysis identified 10 differential metabolites and 8 differential metabolic pathways. Network pharmacological analysis revealed 213 intersection targets between ASH components and PD， with KEGG enrichment involving the sphingolipid signaling pathway， lipid arteriosclerosis， phosphoinositide 3-kinase/protein kinase B（PI3K/Akt） signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway， and hypoxia inducible factor-1（HIF-1） signaling pathway. Integrated lipidomics and network pharmacology analysis highlighted the central role of the arachidonic acid metabolic pathway. The Western blot results showed that ASH effectively up-regulated GSTP1， GSTM2， and PTGS1 protein expression， and down-regulated PTGS2 and PTGES protein expression. ConclusionASH can ameliorate behavioral deficits， exert antioxidant effects， regulate lipid differential metabolites and the arachidonic acid metabolic pathway， thereby exerting therapeutic effects in PD model mice.

ObjectiveTo observe the effects of Jiangtang No. 3 prescription on inflammatory pathways and insulin resistance-related indicators in rats with type 2 diabetes mellitus （T2DM）， and to elucidate its molecular mechanism in combating diabetes. MethodsA T2DM rat model was established using a high-fat diet combined with intraperitoneal injection of streptozotocin （STZ）. Successfully modeled rats were randomly assigned to the model group， metformin group， and low-， medium-， and high-dose Jiangtang No. 3 prescription groups， and a normal group was also set. Daily gavage was administered for 8 weeks as follows： metformin at 0.1 g·kg^-1·d^-1， Jiangtang No. 3 prescription granules at 1.62， 3.24， 6.48 g·kg^-1·d^-1 for the respective dose groups， and sterile water for the normal and model groups. Rat body weight， fasting blood glucose （FBG）， oral glucose tolerance test （OGTT）， and insulin tolerance test （ITT） were measured. After drug intervention， enzyme-linked immunosorbent assay （ELISA） was used to determine serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL）， high-density lipoprotein cholesterol （HDL）， non-esterified fatty acids （NEFA）， interleukin （IL）-1β， IL-18， and insulin （INS）. Hematoxylin-eosin （HE） staining was used to observe morphological changes in adipose tissue. Real-time quantitative PCR was used to detect the mRNA expression of Toll-like receptor 4 （TLR4）， nuclear factor-κB （NF-κB）， NOD-like receptor protein 3 （NLRP3）， Caspase-1， IL-1β， IL-18， and gasdermin D （GSDMD） in adipose tissue. Western blot was used to measure the corresponding protein expression levels. ResultsCompared with the model group， Jiangtang No. 3 prescription groups exhibited significantly increased body weight （P<0.05， P<0.01）， significantly reduced FBG （P<0.05， P<0.01）， significant reductions in TC， TG， NEFA， and LDL （P<0.05， P<0.01）， and a significant increase in HDL （P<0.01）. Serum levels of inflammatory mediators IL-1β and IL-18 were significantly decreased （P<0.01）， the homeostatic model assessment of insulin resistance （HOMA-IR） index was significantly reduced （P<0.05， P<0.01）， and adipose tissue pathology was improved. The protein expression levels of TLR4， NF-κB， NLRP3， Caspase-1， IL-1β， IL-18， and GSDMD were markedly decreased （P<0.05， P<0.01）， and the mRNA expression levels of these indicators were also significantly downregulated （P<0.05， P<0.01）. Some effects were superior to those of the positive control drug metformin， and certain indicators exhibited dose-dependent improvements. ConclusionT2DM rats display significant inflammatory responses， disordered glucose and lipid metabolism， and insulin resistance. Jiangtang No. 3 prescription effectively suppresses inflammatory mediators， improves glucose and lipid metabolism and insulin resistance， and ameliorates pathological changes in adipose tissue. Its mechanism may be related to the regulation of the TLR4/NF-κB/NLRP3 signaling pathway in visceral adipose tissue， thereby influencing downstream inflammatory mediators.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Objective To elucidate the changes in the gut microbiota and molecular mechanism of huaier in enhancing the efficacy of oxaliplatin (OXA) chemotherapy in gastric cancer (GC). Methods The effects of huaier on the gut microbiota structure and intestinal barrier function in MKN45-bearing mice were analyzed by using 16S rRNA sequencing, RT-qPCR, and IHC. UPLC-MS and network pharmacology, as well as in vivo experimental approaches, were employed to investigate the key bioactive constituents of huaier systematically and elucidate the underlying mechanisms by which huaier exerts therapeutic effects against GC. The expression of the PI3K/AKT/SREBP pathway was detected in cancer cells and tissues via Western blot analysis. The safety profile of huaier combined with OXA was verified through serum biochemistry and HE-stained tissue section analyses. Results Huaier inhibited the PI3K/AKT/SREBP pathway by increasing the abundance of Akkermansia muciniphila, reduced lipid droplet deposition, and ultimately enhanced the sensitivity to OXA in the treatment of GC. Conclusion This study demonstrates the value of huaier in gastric cancer treatment by enhancing chemosensitivity and provides novel insights into its systemic therapeutic effects through molecular mechanisms and gut microbiota modulation.

ObjectiveTo construct a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. MethodsLiterature related to Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease was retrieved from CNKI， VIP， and Wanfang databases. Diagnostic information from four diagnostic methods was extracted and standardized， with items having a frequency of ≥15 included in the item pool. A three-round Delphi expert consultation was conducted， screening items using support degree， mean score， rank sum， and coefficient of variation. Item weights were determined using analytic hierarchy process （AHP）， gactor analysis （FA）， and combined weighting method （CWM）. The optimal weighting method was selected by comparing the area under the receiver operating characteristic （ROC） curve （AUC）. The Youden index was calculated to establish the diagnostic cutoff value， which was proportionally scaled. ResultsA total of 102 studies were included. Thirty-five items were incorporated into the item pool. The authority coefficients for the three Delphi rounds were 0.82， 0.85， and 0.86， with coordination coefficients of 0.648， 0.538， and 0.506， respectively. Fifteen items were retained after screening. ROC curve analysis showed the AUC ranking as FA > CWM > AHP. The maximum Youden index was 0.814， corresponding to a diagnostic cutoff of 8.361 （scaled to 40 points）. The final scale adopted a structured diagnostic framework： the symptom dimension requires at least 2 items， and the tongue or pulse dimension requires at least 1 category. ConclusionThis study developed a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. Core items were screened via the Delphi method， with factor analysis identified as the optimal weighting method through AUC comparison. The diagnostic threshold （40 points） and structured diagnostic framework provide a quantitatively clear， clinically practical tool.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

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.