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 of positive emotions,engagement,relationships,meaning and accom-plishments(PERMA)psychological intervention mode on stigma of illness and sleep quality in elderly patients with chronic heart failure.Methods:This randomized controlled study enrolled 116 elderly patients with chronic heart failure admitted to Tangdu Hospital,Air Force Medical University of PLA between May 2021 and May 2023.Pa-tients were randomly divided into control group(n=58,routine intervention)and intervention group(n=58,addi-tional PERMA mode intervention).After 2-month intervention,cardiac function[stroke volume(SV),left ven-tricular ejection fraction(LVEF),New York Heart Association(NYHA)class],stigma of illness[social impact scale(SIS)score],sleep quality[Pittsburgh sleep quality index(PSQI)score],mental state[profile of mood states-short form(POMS-SF)and Warwick-Edinburgh mental well-being scale(WEMWBS)scores]and self-efficacy[self-efficacy for managing chronic disease 6-item scale(SECD6)score]were compared between two groups.Results:Compared to patients in the control group,those in the intervention group had significantly higher SV[(69.87±5.63)ml vs.(64.33±4.21)ml],LVEF[(59.67±5.41)％vs.(50.23±5.33)％],scores of WEMWBS[(49.30±3.75)points vs.(39.64±5.83)points],SECD6[(6.80±0.60)points vs.(4.90±0.75)points](P＜0.001 all),and significantly lower scores of SIS[(58.61±4.57)points vs.(72.30±5.82)points],PSQI[(6.87±1.33)points vs.(11.54±1.78)points],POMS-SF[(122.93±4.16)points vs.(136.91±5.27)points],proportion of NYHA class Ⅲ(17.9％vs.33.9％)(P＜0.001 all).Conclusion:PERMA psychological intervention mode may relieve sigma of illness,improve heart function,sleep quality,promote the transformation of mental state and enhance self-efficacy in elderly patients with chronic heart failure.

Aim To explore the compatibility and po-tential mechanism of effective components of Biejia-Ezhu against triple negative breast cancer(TNBC)and verify it by experiments.Methods Effective compo-nents and targets of Biejia-Ezhu were obtained by TC-MSP and Swiss Target Prediction.Disease targets of TNBC were obtained from OMMI and GeneCards data-bases.The PPI network was constructed using STRING database.GO and KEGG path enrichment analysis was performed using DAVID database.Cytoscape3.9.1 software was used to construct the"drug-component-target-disease"network,screen key targets and compo-nents for molecular docking,and further verify the com-patibility of key components and targets in vitro.Re-sults ① A total of 71 effective components were iden-tified in the Biejia-Ezhu drug pair.There were 146 drug targets associated with the disease.A total of 113 signaling pathways were identified by KEGG analysis.The 71 potential active components of Biejia-Ezhu mainly acted on key targets such as mTORC1,ULK1,TNF,EGFR,ESR1,STAT3,HIF1A,and PTGS2.Mo-lecular docking results showed that glycine and curcu-min were the key active components of Biejia-Ezhu,and both had strong docking activity against key target proteins mTORC1 and ULK1.②The results of in vitro experiment showed that glycine combined with curcu-min significantly inhibited the proliferation and clonal formation ability of TNBC cells(P＜0.05),up-regula-ted the expression of autophagy marker LC3 Ⅱ/Ⅰ,down-regulated the expression of EGFR,down-regula-ted the expression of pathway protein mTORC1,p-mTOR,p-ULK1,and promoted the expression of path-way protein ULK1(P＜0.05).Conclusion The key component of Biejia-Ezhu against triple-negative breast cancer is glycine-curcumin,the mechanism of which may be related to the regulation of the mTORC1/ULK1 signaling pathway to promote autophagy.

Recent studies have shown that the physiological homeostasis of oral mucosal cells is regulated by the circadian clock.Dis-ruption or dysfunction of the circadian clock is closely associated with the development of oral squamous cell carcinoma(OSCC).Research based on the circadian clock offers a novel perspective on the pathogenesis and therapeutic strategies for OSCC.However,there is current-ly limited research on this topic,and people generally have insufficient understanding and recognition of the circadian clock.Given the complexity and challenges of circadian clock which is the fourth dimension of medical research,we organize relevant experts based on summarizing the current research results of circadian clock in the pathogenesis and precision diagnosis and treatment of OSCC,combining the scientific principles of the circadian clock's role and their long-term research experience,then summarizes and recommends the con-sensus opinions for the research of circadian clock in the pathogenesis mechanism and precision diagnosis and treatment of human OSCC,with the hope of providing guidance for the basic research and clinical application of circadian clock or circadian rhythm in the pathogene-sis mechanism and precision diagnosis and treatment of oral and maxillofacial squamous cell carcinoma.

Objective:To investigate the effects of positive emotions,engagement,relationships,meaning and accom-plishments(PERMA)psychological intervention mode on stigma of illness and sleep quality in elderly patients with chronic heart failure.Methods:This randomized controlled study enrolled 116 elderly patients with chronic heart failure admitted to Tangdu Hospital,Air Force Medical University of PLA between May 2021 and May 2023.Pa-tients were randomly divided into control group(n=58,routine intervention)and intervention group(n=58,addi-tional PERMA mode intervention).After 2-month intervention,cardiac function[stroke volume(SV),left ven-tricular ejection fraction(LVEF),New York Heart Association(NYHA)class],stigma of illness[social impact scale(SIS)score],sleep quality[Pittsburgh sleep quality index(PSQI)score],mental state[profile of mood states-short form(POMS-SF)and Warwick-Edinburgh mental well-being scale(WEMWBS)scores]and self-efficacy[self-efficacy for managing chronic disease 6-item scale(SECD6)score]were compared between two groups.Results:Compared to patients in the control group,those in the intervention group had significantly higher SV[(69.87±5.63)ml vs.(64.33±4.21)ml],LVEF[(59.67±5.41)％vs.(50.23±5.33)％],scores of WEMWBS[(49.30±3.75)points vs.(39.64±5.83)points],SECD6[(6.80±0.60)points vs.(4.90±0.75)points](P＜0.001 all),and significantly lower scores of SIS[(58.61±4.57)points vs.(72.30±5.82)points],PSQI[(6.87±1.33)points vs.(11.54±1.78)points],POMS-SF[(122.93±4.16)points vs.(136.91±5.27)points],proportion of NYHA class Ⅲ(17.9％vs.33.9％)(P＜0.001 all).Conclusion:PERMA psychological intervention mode may relieve sigma of illness,improve heart function,sleep quality,promote the transformation of mental state and enhance self-efficacy in elderly patients with chronic heart failure.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

OBJECTIVES: To investigate the expression of parathyroid hormone-like hormone (PTHLH) in hepatocellular carcinoma (HCC) and analyze its correlation with clinical prognosis, its regulatory effects on HCC cell behaviors, and the signaling pathways mediating its effects. METHODS: We analyzed the differential expression of PTHLH in HCC and adjacent tissues and its association with patient prognosis based on data from TCGA and GEO databases and from 70 HCC patients treated in our hospital. The effects of PTHLH knockdown and overexpression on proliferation, migration, and invasion of cultured HCC cells were investigated using CCK-8 assay, colony formation assay, Transwell migration and invasion assays, and the signaling pathways activated by PTHLH were detected using Western blotting. RESULTS: TCGA and GEO database analysis showed significant overexpression of PTHLH mRNA in HCC tissues, which was associated with poor prognosis of the patients (P<0.05). High PTHLH mRNA expression was a probable independent prognostic risk factor for HCC (P<0.05). In the clinical samples, PTHLH mRNA and protein expressions were significantly higher in HCC tissues than in the adjacent tissues (P<0.001 or 0.01). Univariate and multivariate Cox regression analyses suggested that high PTHLH mRNA expression was an independent risk factor to affect postoperative disease-free survival of HCC patients (P<0.05). The prognostic prediction model based on PTHLH mRNA expression showed an improved accuracy for predicting the risk of postoperative recurrence in HCC patients. In cultured HCC cells, PTHLH overexpression significantly promoted cell proliferation, colony formation, migration and invasion, and caused activation of the ERK/JNK signaling pathway in Huh7 and Hep3B cells. CONCLUSIONS High PTHLH expression promotes HCC progression and is associated with poor patient prognosis. Its pro-tumor effects may be mediated by activation of the ERK/JNK signaling pathway.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Prognosis ; Cell Proliferation ; Parathyroid Hormone-Related Protein/genetics* ; Cell Line, Tumor ; Cell Movement ; Disease Progression ; Signal Transduction ; Male ; RNA, Messenger/genetics* ; Female