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.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

In recent years, cancer treatment methods and means are becoming more and more diversified, and single treatment methods often have limited efficacy, while the synergistic effect of immunity combined with chemotherapy can inhibit tumor growth more effectively. Based on this, we constructed a sodium alginate hydrogel composite system loaded with chemotherapeutic agents and tumor vaccines (named SA-DOX-NA) with a view to the combined use of chemotherapeutic agents and tumor vaccines. Firstly, the tumor vaccine (named NA) degradable under acidic conditions was constructed by in situ polymerization using chicken ovalbumin (OVA), acrylamide (AAM) and 2-(dimethylamino) ethyl methacrylate (DMAEMA) monomer. Then a hydrogel composite system SA-DOX-NA co-loaded with chemotherapeutic drug doxorubicin (DOX) and NA was prepared using sodium alginate as a matrix. The results showed that SA-DOX-NA had good in situ gel-forming ability and formed a mesh structure that could realize the co-loading of DOX and NA as well as the slow drug release. The electron microscopy results showed that SA-DOX-NA had good in situ gel-forming ability with good internal connectivity, and the three-dimensional mesh structure could realize the co-loading of DOX and NA as well as the slow drug release. The antitumor and immunomodulatory results showed that SA-DOX-NA both effectively inhibited the growth of tumor cells and efficiently promoted the proliferation and activation of DC2.4 dendritic cells without additional adjuvant. In summary, SA-DOX-NA exerts the dual efficacy of chemotherapy and immunotherapy for tumor treatment, and has a good application prospect in local tumor treatment.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Portal vein embolization （PVE） can induce atrophy of the embolized lobe and compensatory regeneration of the non-embolized lobe. However， due to inadequate regeneration of future liver remnant （FLR） after PVE， some patients remain unsuitable for hepatectomy after PVE. In recent years， liver venous deprivation （LVD）， which combines PVE with hepatic vein embolization （HVE）， has induced enhanced FLR regeneration. Compared with associating liver partition and portal vein ligation for staged hepatectomy （ALPPS）， LVD triggers faster and more robust FLR regeneration， with lower incidence rate of postoperative complications and mortality rate. By reviewing related articles on LVD， this article introduces the effectiveness of LVD and analyzes the differences and safety of various technical paths， and it is believed that LVD is a safe and effective preoperative pretreatment method.

Objective:To investigate the situation of computed tomography(CT)equipment and socio economic development of various grades and classifications of medical institutions in Jiangsu Province,and to analyze the interrelationship between them.Methods:From October 20,2023 to November 20,2023,a questionnaire survey was conducted on imported and domestic CT equipment of various grades and classifications of medical institutions in 13 prefecture-level cities in Jiangsu Province through online questionnaire survey of"questionnaire star".The gross domestic product(GDP)of each prefecture-level city in Jiangsu province was used as an indicator of measuring the level of socio-economic development in the region.The CT number,the row number of detector,quality of image,the total examination case number of daily average and the daily average case number of single machine examination of medical institutions of various grades and classifications of 13 prefecture-level cities were used to conduct correlation analysis with GDP values of various districts.Results:A total of 910 questionnaires were distributed,and 512 questionnaires were retrieved.There were 482 valid questionnaires in the 512 questionnaires,and the valid rate was 94.15,which involved to 482 various grade and classification institutions of 13 prefecture-level cities in Jiangsu province.The number of imported and domestic CT equipment in the 13 prefecture-level cities of Jiangsu Province positively correlated with the GDP of each city(r=0.882,0.880,P<0.001).The number of imported CT equipment with 64 rows and more than 64 rows,and with less than 64 rows,and the number of domestic CT equipment with 64 rows and more than 64 rows,and with less than 64 rows all positively correlated with the GDP of each city(r=0.880,0.881,0.736,0.897,P<0.05).The total number of daily average of examinations for imported and domestic CT equipment of 13 prefecture-level cities positively correlated with the GDP of each city(r=0.774,0.814,P<0.05).There were no significant difference in the image quality and the daily average case number of single machine examination between the domestic CT equipment and the imported CT equipment(P>0.05).Conclusion:The medical institutions of city with high level of economic development have more quantitative and more high-end CT equipment,and the quality of image of domestic CT equipment is equal to that of imported CT equipment regardless of the high and low level of economic development.

Objective:To explore the CT manifestation characteristics of peripancreatic aneurysms related to pancreatitis (PRPA).Methods:A retrospective analysis was conducted on the clinical data of 15 patients with pancreatitis-related aneurysms collected in Deyang People's Hospital from June 2017 to February 2025. Among them, there were 11 males and 4 females, with an age of (56.5±16.9) years. Record the CT manifestations of the patients, and observe the PRPA tumor-carrying arteries, morphology, quantity, bleeding, calcification, dynamic changes, etc.Results:The CT results showed that there were a total of 26 PRPAs in 15 patients. The aneurysm walls of the PRPAs had no calcification, among which 12 cases were single and 1 case was double. Two cases were multiple. The patients were pancreatitis complicated with muscle fiber dysplasia. Among them, one case had 5 PRPAs and the other had 7 PRPAs. Of the 26 PRPAs, 12 were sac-like, 8 were beaded, 4 were fusiform, and 2 were columnar in shape. The numbers of aneurysm-carrying arteries and PRPA were as follows: 8 in the pancreaticoduodenal artery, 7 in the hepatic artery and its branches, 6 in the splenic artery and its branches, 2 in the left gastric artery, 1 in the gastroduodenal artery, 1 in the middle colonic artery, and 1 in the ileocolonic artery. The CT diagnosis report missed 16 PRPAs, with a missed diagnosis rate of 61.5% (16/26). Among the 11 ruptured PRPAs, 4 were missed, with a missed diagnosis rate of 36.4%. Three missed aneurysms were diagnosed by digital subtraction angiography, and one was retrospectively analyzed by CT. Among the 15 unruptured PRPAs, 12 were missed, with a missed diagnosis rate of 80.0%. All the missed aneurysms were detected by retrospective CT analysis. There were 2 images without re-examination and 24 images with re-examination. Among the PRPAs with re-examination images, 4 disappeared after interventional embolization on the same day, 1 relapsed after interventional embolization on the same day, with a reduction in volume and disappeared after 3 days. Three cases underwent elective interventional embolization, among which two shranked and one enlarged before interventional embolization. Among the 16 cases that did not receive interventional treatment, 7 disappeared on their own, 1 was completely liquefied, 5 shrank but did not disappear, 2 remained stable in size without any change, and 1 increased. Among the re-examined PRPA images, 7 showed signs of enlargement.Conclusion:The main characteristics of PRPA are high rupture rate, prone to missed diagnosis and dynamic changes in size.

Isoflavones which mainly distributed in leguminous plants have plenty of health benefits.Isoflavone synthase(IFS)is a membrane-associated cytochrome P450 enzyme(CYP450)which carries out the unique aryl-ring migration and hydroxylation.So far,few crystal structures of plant P450s have been obtained.We determined the crystal structure of IFS from Medicago truncatula at 1.9 ? by MAD method using a selenomethionine substituted crystal and conducted molecular docking and mutagenesis study.The structure of IFS complexed with imidazole exhibits the helix Ⅰa-loop-helix Ⅰβ motif which cor-responds to helix Ⅰ of other P450s.Compared with structures of common P450s,IFS/imidazole structure contains an extra domain,i.e.,the γ-domain.The structure reveals a homodimer in which the γ-domain of one molecule interacts with the β-domain of another.The plane of heme group makes an angle of ap-proximately 40° with the helix Ⅰa-loop-helix Ⅰβ motif.Molecular docking combined with mutagenesis study suggested that Trp-128 and Asp-300 might play important roles in substrate binding and recogni-tion.Phe-301,Ser-303 and Gly-305 from the helix Ⅰa-loop-helix Ⅰβ motif may play important roles in the aryl-ring migration.These novel structural features reveal insights into the unique reaction mechanism of IFS and provide a basis for engineering IFS in leguminous crops for health purpose.

Under the background of rapid development of artificial intelligence(AI),this paper systematically proposes AI-based education(AIBE).It empowers the teaching process,learning process,research process,and teaching management with AI,and constructs an AI-based educational paradigm,including AI-based teaching(AIBT),AI-based learning(AIBL),AI-based re-search(AIBR),and AI-based management(AIBM).Taking the AI course of immunology teaching as an example,this paper deeply analyzes the practices and explorations of implementing AIBT,AIBL,AIBR and AIBM based on the AI course,so as to accelerate the promotion of the transformation of the fourth generation of medical education.