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 investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

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.

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.

Objective:To explore the distribution of pathogenic bacteria causing postoperative infections in chil-dren undergoing surgery for Hirschsprung's disease(HD),and the clinical significance of serum triggering receptor ex-pressed on myeloid cells-1(sTREM-1)and high mobility group box 1(HMGB1).Methods:98 children with HD admit-ted from January 2021 to January 2025 were divided into infection group(n=42)and non-infection group(n=56)accord-ing to whether the children were complicated with infection after operation.Automatic bacterial identification system was used to detect the distribution of pathogenic bacteria in secretion samples from infected sites of HD children after operation.ELISA was used to measure serum sTREM-1 and HMGB1.ROC was used to explore the diagnostic value of serum sTREM-1 and HMGB1 for severe infection in children with HD.Results:A total of 49 strains of pathogenic bac-teria were isolated from 42 children with HD in infection group,of which 63.27%(31/49)were gram-negative bacteria,accounting for the highest proportion,followed by Gram positive bacteria at 30.61%(15/49)and fungi at 6.12%(3/49).Among them,Pseudomonas aeruginosa had the highest proportion of 24.49%(12/49)among Gram negative bacteria.there were 15 cases of mild infection(15 strains of pathogens),16 cases of moderate infection(17 strains of pathogens)and 11 cases of severe infection(17 strains of pathogens).With the aggravation of the infection degree of HD children,the distribution pattern of pathogenic bacteria changed,and gradually changed to mainly gram-negative bacteria infec-tion.Compared with non infected group,the levels of serum sTREM-1 and HMGB1 in infected group were higher(P<0.05).The levels of serum sTREM-1 and HMGB1 in children with severe HD infection are higher than those in children with mild and moderate HD infection(P<0.05).The AUC of the combined diagnosis of serum sTREM-1 and HMGB1 for severe infection in HD children was the highest,at 0.985,which was superior to the separate diagnosis of serum sTREM-1 and HMGB1(Zcombination-sTREM-1=1.988,P=0.047;Zcombination-HMGB1=2.126,P=0.034).Conclusion:Serum sTREM-1 and HMGB1 are elevated in HD children with postoperative infection,and the pathogenic bacteria are mainly gram-negative bacteria.In addition,the combined detection of the two provides a reference for the clinical diagnosis of severe infection in HD children.

Ulcerative colitis(UC)is a chronic inflammatory dis-ease of the colon and rectum with an unclear etiology.Early di-agnosis and effective treatment of UC are still urgent challenges that need to be addressed in clinical practice.More and more studies have found that galectin-3 is involved in the occurrence and development of UC,which may become a biomarker for the diagnosis and treatment of UC.Galectin-3,widely expressed in colonic epithelial cells and immune cells,can regulate intestinal immunity and play an important role in the occurrence and de-velopment of inflammation.This article provides a brief intro-duction to the structure and function of galectin-3,and summari-zes and discusses the expression changes and roles of galectin-3 in UC.At present,most literature reports believe that galectin-3 plays a pro-inflammatory role in UC,but there are still some re-ports that hold the opposite view.This article analyzes the rea-sons for this controversy and provides a reference for further de-termining whether galectin-3 may become a diagnostic indicator and therapeutic target for UC.

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

Objective To evaluate the efficacy and safety of a novel intravascular lithotripsy(IVL)balloon—Vesscrack shockwave balloon—for vascular preparation before stent implantation in patients with severe coronary artery calcification(CAC).Methods This was a prospective,single-arm,multicenter study conducted in China from June 2022 to October 2022.Patients with severe CAC were treated with the Vesscrack shockwave balloon for lesion preparation,followed by drug-eluting stent(DES)implantation.Of these,33 patients underwent optical coherence tomography(OCT).The primary endpoint was procedural success,defined as successful stent implantation with residual stenosis≤30％and the absence of in-hospital major adverse events,including cardiac death,target vessel-related myocardial infarction,or target lesion revascularization.Results A total of 170 patients[mean age:(65.9±7.9)years,116 males]were enrolled.After treatment with IVL and DES,the minimum lumen diameter increased significantly compared to baseline[(2.34±0.40)mm vs.(0.95±0.33)mm,P＜0.001],the degree of stenosis was significantly reduced[(13.24±6.60)％vs.(65.18±10.59)％,P＜0.001].Procedural success was achieved in 100％of cases,and device success was 98.8％.The 30-day patient-related cardiovascular clinical composite endpoint(POCE)rate was 0.0,with no target lesion failure,no confirmed or potential thrombotic events were observed.The shockwave energy generator demonstrated excellent stability and ease of use.Among the 33 patients assessed with OCT,after IVL intervention,the maximum calcified area of the lumen[(3.51±1.51)mm2 vs.(2.85±1.80)mm2,P＜0.001],and the minimum lumen area within the target lesion[(3.08±1.04)mm2 vs.(2.02±0.75)mm2,P＜0.001],and after DES intervention,the luminal area of the largest calcified site[(6.59±1.64)mm2 vs.(2.85±1.80)mm2,P＜0.001]and the minimum luminal area within the target lesion[(6.19±1.45)mm2 vs.(2.02±0.75)mm2,P＜0.001]were significantly increased,and the differences were statistically significant.Conclusions The Vesscrack shockwave balloon is effective and safe for vascular preparation in patients with severe CAC prior to stent implantation.It achieves significant calcified plaque modification,high procedural success rates,and minimal complications.

Objective To conduct a bibliometric analysis of relevant literature on liver failure caused by viral hepatitis from the past five years,and to help researchers understand the current status and hotspots in this field,and to provide insights into future research trends.Methods Based on the Science Citation Index Expanded(SCI-Expanded)data from Web of Science Core Collection,visualization analysis and mapping were conducted through VOSviewer and CiteSpace software to generate visual representations of international research collaboration networks,keyword co-occurrence clustering,and keyword bursts.Results From 2019 to 2023,a total of 873 relevant literature were included,with a total citation frequency of 7 364 and an average citation frequency of 8.44.Among them,China had the highest number of publications(458 articles,52.46%)and had the most cooperation with the United States.The research hotspots of viral hepatitis induced liver failure were mainly divided into three categories:basic and clinical research on liver failure caused by non-hepatitis B virus(HBV),the pathogenesis of HBV related liver failure,and treatment and prediction models of liver failure.The keyword time overlay map and burst map showed that the research hotspots had gradually shifted from the prevention and control of new infections to the treatment and prognosis assessment of patients with chronic infection.Conclusion China is a major international research entity in liver failure caused by viral hepatitis and actively participates in international scientific collaborations.The research hotspots on liver failure caused by viral hepatitis have gradually shifted from preventing viral hepatitis infections and expanding treatment options to the treatment of chronic infection patients and prognostic prediction.