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 mechanism of puerarin in the treatment of rheumatoid arthritis(RA) by network pharmacology and animal experiments. Methods : Traditional Chinese Medicine Systems Pharmcolog Database(TCMSP) and SwissTargetPrediction database were used to collect puerarin targets, and the targets of RA were obtained from GeneCards database and OMIM database. The PPI network was established by Cytoscape 3.7.2 software. Gene ontology(GO) function and Kyotoencyclopedia of genes(KEGG) enrichment analysis were performed through the Metascape database. RA rat-collagen-induced arthritis(CIA) model was reproduced using type Ⅱ collagen emulsion, 49 Wistar rats were randomly assigned to seven groups: control group, CIA model group, low-dose, medium-dose and high-dose puerarin group, methotrexate group, Tripterysium Glycosides Tablets group. Except for the control group, the other groups were given continuous gavage for 28 days after the CIA in rats model were prepared. The redness and swelling of the joints and ankle joint pathological changes were observed in each group. Western blot was used to detect the expression of Glycogen synthase kinase3β(GSK-3β), beta-catenin(β-catenin) proteins in the synovium. Real-time quantitative polymerase chain reaction(qPCR) was used to detect the expression of GSK-3β, β-catenin and c-Myc mRNA in the synovium. Results : Puerarin had 134 targets genes, RA had 5 821 target genes, and there were 102 overlapping target genes of puerarin and RA. It involved 184 signaling pathways, including JAK-STAT signaling pathway, NF-κB signaling pathway, Wnt signaling pathway, et al. The results of animal experiments showed that after the intervention of M-puerarin and MTX, the symptoms of redness and swelling of the hind foot were alleviated, the inflammatory cell infiltration in the synovium of the joint was significantly reduced, and the damage of cartilage and bone tissue was reduced. Compared with CIA group, the expressions of GSK-3β, β-catenin protein and GSK-3β, β-catenin and c-Myc mRNA in synovial tissue of rats after M-puerarin intervention decreased(P<0.05). Conclusion Puerarin has the characteristic of multi-components, multi-targets and multi-pathway intervention in RA. Puerarin may alleviate synovial hyperplasia, reduce articular cartilage erosion and bone destruction in CIA in rats by inhibiting Wnt/β-catenin signaling pathway.

Artificial intelligence （AI） and population pharmacokinetics （PPK） technologies have demonstrated significant potential in the personalized medication of immunosuppressants after organ transplantation, enabling precise prediction of drug dosages. This article provides a comprehensive review of the application status of AI and PPK in the individualized administration of immunosuppressants after organ transplantation， focuses on monitoring blood drug concentration， predicting efficacy/adverse reactions， and establishing individualized dosing models for organ transplant recipients after immunosuppressant administration， and analyzes and compares the application characteristics of different methods in different organ transplant patients as well as the integration and future development of AI and PPK technologies. AI and PPK technologies can not only significantly reduce the dependence on human resources， but also greatly improve the level of individualized treatment of immunosuppressants after organ transplantation， and reduce the discomfort and burden caused by frequent blood concentration monitoring to patients.

Glucagon-like peptide-1 （GLP-1） receptor agonists are a novel class of antidiabetic drugs that also possess lipid- lowering and cardiovascular protective effects， with liraglutide and semaglutide being their representative medications. Based on a systematic literature search， this review summarizes the lipid-lowering mechanisms by which liraglutide and semaglutide exert direct effects on the liver and kidney （regulating autophagy， key lipid metabolism pathways， reverse cholesterol transport， etc.）， direct actions on adipose tissue （affecting adipocyte proliferation and differentiation， expression of lipid metabolism proteins， and gene transcription）， activation of sympathetic pathways through the central nervous system， and modulation of the gut microbiota. Additionally， it summarizes the clinical evidence of their lipid-lowering effects in populations with type 2 diabetes mellitus， overweight individuals， and others. These findings indicate that GLP-1 receptor agonists exert lipid-lowering effects by acting on multiple tissues or systems， providing crucial evidence for further elucidating the molecular mechanisms of these drugs in lipid regulation and exploring potential new ideas for their clinical applications.

Objective To explore current status and potential subtypes of elderly stroke patients' medication literacy among,and to analyze related influencing factors of different subtypes.Methods A total of 285 elderly stroke patients admitted in the First Affiliated Hospital of Zhengzhou University from November 2023 to June 2024 were selected as subjects.General Information questionnaire,medication literacy scale for elderly patients with chronic diseases,and perceived social support scale were conducted.Latent profile analysis(LPA)of elderly stroke patients' medication literacy was conducted,and Logistic regression analysis was used to explore influencing factors of different profiles.Results Score of medication literacy scale for elderly stroke patients was(48.26±12.51)points.Medication literacy among elderly stroke patients can be divided into 3 profiles,namely proactive-high literacy type(51.9％),balanced-medium literacy type(34.0％),and dependent-low literacy type(14.1％).Logistic regression analysis showed that recent medication types,current place of residence,educational level,diabetes,and social support were the influencing factors of elderly stroke patients' medication literacy(P＜0.05).Conclusion The level of medication literacy among elderly stroke patients is medium,which is characterized by 3 categories.Medical staffs targeted intervention should be adopted according to different category characteristics,so as to accurately meet their nursing needs,finally improve the level of elderly stroke patients' medication literacy.

A single-center, randomized, double-blind, dose-controlled trial of modified Sini Powder in treating mild to moderate generalized anxiety disorder(GAD) in the patients with syndrome of liver depression transforming into fire was conducted at Xiyuan Hospital, China Academy of Chinese Medical Sciences. A total of 80 patients with mild to moderate GAD and the syndrome of liver depression transforming into fire were included. Patients were assigned by the central randomization system at a ratio of 3∶1 into an observation group(n=60, receiving a conventional-dose of granules of modified Sini Powder) and a control group(n=20, receiving low-dose granules with the active ingredients being 50% of that in observation group). Assessments were conducted before treatment(baseline), after 2 weeks of introduction, after 2/4/8 weeks of treatment, and after 4 weeks of follow-up. The results were summarized as follows. In terms of primary outcome indicators, the observation group(62.2%) showed higher total response rate than the control group(26.6%)(P<0.05), and greater Hamilton anxiety scale(HAMA) score reduction after 8 weeks of treatment(P<0.05). In terms of secondary outcome indicators, the HAMA score(somatic anxiety score), traditional Chinese medicine(TCM) syndrome scores, Pittsburgh sleep quality index(PSQI) scale, and clinical global impression(CGI) scale score in the observation group showed a significant compared to the control group at each visit points(P<0.05). Adverse events occurred in 10 cases, including 9(16.9%) cases in the observation group and 1(6.6%) case in the control group. No adverse reaction was observed. In conclusion, conventional-dose modified Sini Powder demonstrated superior efficacy and favorable safety for mild and moderate GAD in the patients with the syndrome of liver depression transforming into fire over low-dose treatment.
Humans ; Male ; Female ; Adult ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/administration & dosage* ; Anxiety Disorders/drug therapy* ; Treatment Outcome ; Young Adult ; Powders ; Aged ; Liver/drug effects* ; Generalized Anxiety Disorder

Receptor-interacting protein kinase 1 (RIPK1) plays an essential role in regulating the necroptosis and apoptosis in cerebral ischemia-reperfusion (I/R) injury. However, the regulation of RIPK1 kinase activity after cerebral I/R injury remains largely unknown. In this study, we found the downregulation of protein arginine methyltransferase 1 (PRMT1) was induced by cerebral I/R injury, which negatively correlated with the activation of RIPK1. Mechanistically, we proved that PRMT1 directly interacted with RIPK1 and catalyzed its asymmetric dimethylarginine, which then blocked RIPK1 homodimerization and suppressed its kinase activity. Moreover, pharmacological inhibition or genetic ablation of PRMT1 aggravated I/R injury by promoting RIPK1-mediated necroptosis and apoptosis, while PRMT1 overexpression protected against I/R injury by suppressing RIPK1 activation. Our findings revealed the molecular regulation of RIPK1 activation and demonstrated PRMT1 would be a potential therapeutic target for the treatment of ischemic stroke.

Wang Ji is an outstanding representative of Xin'an medicine,he has made a lot of achievements in academic thought of acupuncture and moxibustion,which mainly contains the academic features such as"acupuncture treatment mainly purging excessive pathogen"and"use of moxibustion with caution for the disease-free person",as well as"no selection of fixed acupoints for treating diseases".The scholars in past dynasties did a lot of research on his theory of"acupuncture treatment mainly purging excessive pathogen"and"use of moxibustion with caution for the disease-free person",but did less research on his theory of"no selection of fixed acupoints for treating diseases",this paper explores Wang Ji's life and his representative works,and analyzes the theory of"no selection of fixed acupoints for treating diseases".Wang Ji advocates the disease treatment principle of differentiation of meridians and collaterals,qi and blood,as well as yin and yang,and his acupoint selection rules focuses on flexible prescription according to syndrome differentiation,point selection according to disease differentiation,which critically criticizes the dogmatic behavior of the conventional theory that"a certain acupoint corresponding treatment for a certain disease",he reminded the physicians that in treating disease by acupuncture and moxibustion,syndrome differentiation should be according to meridians and collaterals differentiation,acupoint application should be flexible and changeable.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.