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.

Objective:To analyze the key factors,hierarchical structure and internal action paths that affect the ability improvement of medical insurance management personnel in public hospitals,and to provide theoretical basis and practical reference for strengthening the construction of medical insurance management talent teams in hospitals.Methods:Through the mutual verification of literature analysis,policy interpretation and interview results,an index system of influencing factors for the ability improvement of medical insurance management personnel in public hospitals was constructed.A hybrid method combining DEMATEL-ISM-MICMAC was adopted to define the relationships,divide the levels and conduct driving force-dependence analysis of the influencing factors.Results:There are a total of 12 key factors influencing the ability improvement of medical insurance management personnel in public hospitals.Through the ISM model,these influencing factors can be classified into four levels:surface factors,intermediate factors,deep factors,and essential factors.With the help of MICMAC analysis,it can be classified into the spontaneous factor group of"low driving force-low dependence",the independent factor group of"high driving force-low dependence"and the dependent factor group of"low driving force-high dependence".Conclusion:Policy interpretation and knowledge reserve are the fundamental driving factors for ability improvement;Professional ethics and responsibilities are the deep-seated supporting factors of the ability system.The regulatory capacity of medical insurance funds is a key outcome and performance manifestation.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

Objective To evaluate the efficacy and safety of transcatheter aortic valve implantation(TAVI)for the treatment of primary aortic valve regurgitation(NAVR)and to compare the difference in the choice of prosthetic valve size and the difference in complications with aortic stenosis(AS).Methods According to the definition of Valve Academic Research Consortium(VARC-3),143 patients with NAVR/AS treated with TAVI and patients with NAVR treated with surgical aortic valve replacement(SAVR)at Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,China,from March 2019 to September 2024 were selected,and clinical data on baseline,perioperative,and primary endpoint events were were retrospectively collected and compared.Results Forty-three patients with NAVR were treated with TAVI,with a device success rate of 86.0％and a surgical success rate of 95.3％.Subgroup comparisons:(1)NAVR-TAVI group than NAVR-SAVR group:patients in the TAVI group had a significantly shorter operative time than those in the SAVR group(P＜0.001);complete left bundle branch block was more likely to occur after TAVI(P=0.042),and complete right bundle branch block was more likely to occur after SAVR(P=0.044).SAVR postoperatively The incidence of congestive heart failure was higher(P=0.013),and the mortality rate was significantly higher in the SAVR group than in the TAVI group(P=0.019).(2)NAVR-TAVI group than AS-TAVI group:the differences in access selection,THV size[28(22,34)mm vs.24(22,32)mm,P=0.044]and proportion of THV overdiameter[14％(7％,20％)vs.7％(3％,11％),P＜0.001]were statistically significant.patients in AS and NAVR groups had 1 case of permanent pacing after TAVI treatment.In the AS and NAVR groups,there was 1 case of permanent pacemaker implantation after TAVI.2 patients in the AS group were converted to surgical treatment,and 6 patients died.Conclusions The use of"off-label"(transfemoral)and"on-label"(transapical)TAVI devices(both from domestic sources)is safer than SAVR for the treatment of NAVR,especially in elderly and high-risk patients.Compared with patients with AS treated with TAVI,larger diameter annulas are usually selected for NAVR,with higher rates of valve migration,but overall safety and efficacy are comparable to AS.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

Objective:To analyze the key factors,hierarchical structure and internal action paths that affect the ability improvement of medical insurance management personnel in public hospitals,and to provide theoretical basis and practical reference for strengthening the construction of medical insurance management talent teams in hospitals.Methods:Through the mutual verification of literature analysis,policy interpretation and interview results,an index system of influencing factors for the ability improvement of medical insurance management personnel in public hospitals was constructed.A hybrid method combining DEMATEL-ISM-MICMAC was adopted to define the relationships,divide the levels and conduct driving force-dependence analysis of the influencing factors.Results:There are a total of 12 key factors influencing the ability improvement of medical insurance management personnel in public hospitals.Through the ISM model,these influencing factors can be classified into four levels:surface factors,intermediate factors,deep factors,and essential factors.With the help of MICMAC analysis,it can be classified into the spontaneous factor group of"low driving force-low dependence",the independent factor group of"high driving force-low dependence"and the dependent factor group of"low driving force-high dependence".Conclusion:Policy interpretation and knowledge reserve are the fundamental driving factors for ability improvement;Professional ethics and responsibilities are the deep-seated supporting factors of the ability system.The regulatory capacity of medical insurance funds is a key outcome and performance manifestation.

This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

Objective:To construct a key item checklist for the Mini-HTA report specification,providing scientific guidance for drafting each section of Mini-HTA research reports,enhancing their standardization,scientific rigor,and completeness,thereby improving the efficiency and quality of health decision-making.Methods:Based on preliminary literature review and qualitative systematic review,a pool of problem items for the Mini-HTA report specification was formed.Delphi questionnaires were distributed,and the Delphi technique was employed through two rounds of expert consultation to optimize and select key items.Results:Through two rounds of Delphi expert consultation,the initial Mini-HTA report specification item checklist was screened,integrated,and supplemented.A finalized key item checklist was constructed,comprising 8 first-level items(Title,Abstract,Introduction,Methods,Results,Discussion,Conclusion,and Other Relevant Information)and 48 second-level items.Conclusion:The constructed key item checklist for the Mini-HTA report specification provides scientific guidance for drafting Mini-HTA research reports.It helps enhance the standardization and transparency of the assessment process and the reliability of results,thereby optimizing the efficiency and quality of health decision-making.