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.

Inflammatory response,immunosuppression,and drug sensitivity have been reported to have a significant correlation with the disulfidptosis levels in cancer patients.However,the value of disulfidpto-sis in colorectal cancer therapy remains unclear.Therefore,we classified the CRC cells into different cell types using single-cell sequencing data and cell-specific markers and analyzed their relationship with the cell disulfidptosis level.We found that the high disulfidptosis regions were concentrated in epithelial-like CRC cells.Further exploration using the disulfidptosis and programmed cell death 1 inhibitor therapy treated differential expression genes indicated that CRC patients with high disulfidptosis levels exhibited a lower risk profile and increased sensitivity to immunotherapy.By using the spatial transcriptomic analy-sis,we found that ubiquinol-cytochrome c reductase core protein 1(UQCRC1),a disulfidptosis-related gene,is highly expressed in epithelial-like CRC cells and co-localized with immune-infiltrated tumor re-gions.Additional bioinformatic analyses and experimental validation further confirmed that UQCRC1 was downregulated in CRC tissues.Overexpression of UQCRC1 suppressed CRC cell proliferation and migra-tion.These findings indicate that UQCRC1 is a potential target for CRC diagnosis and treatment.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

Inflammatory response,immunosuppression,and drug sensitivity have been reported to have a significant correlation with the disulfidptosis levels in cancer patients.However,the value of disulfidpto-sis in colorectal cancer therapy remains unclear.Therefore,we classified the CRC cells into different cell types using single-cell sequencing data and cell-specific markers and analyzed their relationship with the cell disulfidptosis level.We found that the high disulfidptosis regions were concentrated in epithelial-like CRC cells.Further exploration using the disulfidptosis and programmed cell death 1 inhibitor therapy treated differential expression genes indicated that CRC patients with high disulfidptosis levels exhibited a lower risk profile and increased sensitivity to immunotherapy.By using the spatial transcriptomic analy-sis,we found that ubiquinol-cytochrome c reductase core protein 1(UQCRC1),a disulfidptosis-related gene,is highly expressed in epithelial-like CRC cells and co-localized with immune-infiltrated tumor re-gions.Additional bioinformatic analyses and experimental validation further confirmed that UQCRC1 was downregulated in CRC tissues.Overexpression of UQCRC1 suppressed CRC cell proliferation and migra-tion.These findings indicate that UQCRC1 is a potential target for CRC diagnosis and treatment.

Objective:To investigate the drug resistance gene characteristics, plasmid characteristics and genome tracing of Shigella sonnei causing a bacillary dysentery outbreak in Shandong Province. Methods:Sixty-five Shigella sonnei strains isolated from a 2021 outbreak in a county of Shandong Province were analyzed using antimicrobial susceptibility testing, whole genome sequencing (WGS), characterization of resistance and virulence genes, plasmid profiling, core genome multilocus sequence typing (cgMLST), and single nucleotide polymorphism (SNP) analysis. Results:All isolates had the same resistance phenotype and genotypes and were multidrug-resistant ESBL-producing Shigella sonnei, carrying important virulence genes. Plasmid analysis revealed a conserved genetic arrangement, pil( M/ N/ O2/ P)-tra( F/ H/ J/ K/ N/ O/ P/ Q)-IS Ecp1- blaCTX-M-14-Tn 903- yub( J/ I/ F/ G/ E/ D), and shared across strains from diverse regions and bacterial species. The cgMLST and SNP analyses demonstrated concordant clustering, with all 65 outbreak-related strains forming a single cluster alongside human-derived strains from Guangxi. Conclusion:The ESBL-producing Shigella sonnei responsible for the outbreak shares a homologous relationship with Guangxi human-derived strains, and the detected resistance plasmids and virulence genes underscore the need to strengthen drug resistance surveillance and genome tracing.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

This study aims to isolate and culture primary rabbit spinal cord microvascular endothelial cells in vitro,providing a practical source of test cells for spinal cord injury research.Spinal cord tissue was aseptically extracted from one-month-old rabbits and processed sequentially through mincing,bovine serum albumin density gradient centrifugation,mesh filtration,and type Ⅱ collagenase digestion to ob-tain purified spinal cord microvascular segments.The microvascular segments were homogeneously mixed with an apprapriate volume of M199 complete culture medium and seeded into a culture dish for primary culture.Throughout the culture period,cell growth performance were continuously observed and recor-ded.Additionally,immunocytochemical staining was performed to evaluate the expression of factor Ⅷ-re-lated antigen.The results showed that after 24 hours of inoculation,a small amount of endothelial-like cells were observed to emerge from the spinal cord microvascular segments.Within 36～60 hours,the cell colonies gradually expanded and fused.After 72 hours,the cells spread across the base of the dish,forming a"cobblestone-like"monolayer.Immunocytochemical staining showed that more than 99％of the cells showed brown-red cytoplasm and were positive for factor Ⅷ-related antigen.It is these results that suggest this study has successfully established a convenient and stable primary rabbit spinal cord micro-vascular endothelial cells culture method.

Objective:To investigate the factors influencing left atrial fibrosis in patients with atrial fibrillation(AF)and the association of Periostin protein,serum transforming growth factor-β2(TGF-β2)with left atrial fibrosis.Methods:We enrolled 100 AF patients admitted to Gansu Provincial People's Hospital between March 2021 and March 2023.They were divided into control group(＜10％,n=53)and fibrosis group(≥10％,n=47)according to their left atrial low voltage region.Univariate and multivariate Logistic regression were used to analyze the influ-encing factors of left atrial fibrosis in AF patients and construct a nomogram model.The diagnostic value of related factors and their combined detection for left atrial fibrosis in AF patients were analyzed by receiver operating char-acteristic curve(ROC).Spearman correlation analysis was used to analyze the association of Periostin protein,TGF-β2 with left atrial fibrosis in AF patients.Results:Compared to patients in the control group,those in the fibrosis group had significant higher left atrial diameter(LAD)[(37.08±3.19)mm vs.(33.45±2.45)mm],levels of ser-um uric acid(SUA)[(313.75±49.06)μmol/L vs.(279.88±38.15)μmol/L],Periostin protein[(83.27±3.98)ng/L vs.(75.21±3.04)ng/L],TGF-β2[(4346.84±321.34)ng/L vs.(4186.02±306.91)ng/L],and signifi-cant lower left atrial ejection fraction(LVEF)[(62.28±5.00)％vs.(67.24±3.07)％](P＜0.05 or＜0.01).Multivariate Logistic regression analysis showed that LAD(OR=1.663,95％CI 1.238～3.887,P=0.001),SUA(OR=1.586,95％CI 1.164～2.892,P＜0.001),Periostin protein(OR=1.997,95％CI 1.513～4.585,P=0.001),TGF-β2(OR=2.013,95％CI 1.543～5.864,P＜0.001)were independent risk factors for left atrial fi-brosis in AF patients,while LVEF was an independent protective factor(OR=0.524,95％CI 0.141～0.920,P=0.002).The nomogram model for left atrial fibrosis in AF patients:logit(P)=4.631+0.445 × LVEF+0.546 × LAD+0.575 × SUA+0.530 × Periostin protein+0.347 × TGF-β2.ROC curve showed that the area under the curve(AUC)of combined detection(0.893,95％CI 0.842～0.932)was significantly higher than SUA(AUC=0.637,95％CI 0.566～0.704),LVEF(AUC=0.701,95％CI 0.632～0.763),LAD(AUC=0.649,95％CI 0.579～0.715),Periostin protein(AUC=0.676,95％CI 0.606～0.740),TGF-β2(AUC=0.641,95％CI 0.570～0.707)alone(Z=5.265,6.399,6.379,6.040,6.483,P＜0.001 all).Spearman correlation analysis showed that Perios-tin protein and TGF-β2 were significantly positive correlated with left atrial fibrosis in AF patients(r=0.536,0.578,P＜0.001 all).Conclusion:Periostin protein and TGF-β2 were independent risk factors for left atrial fi-brosis in AF patients and were significantly positive correlated with it,a combination of above-mentioned indexes,cardiac function indexes and uric acid had good diagnostic value for left atrial fibrosis.

Objective:To analyze the preferences of medical staff in TCM hospitals in Beijing regarding the achievements transformation of hospital traditional Chinese medicine preparations,and to provide a reference for formulating incentive policies.Methods:233 medical staff from five TCM hospitals in Beijing were taken as the research objects,and surveyed with a questionnaire designed based on the discrete choice experiment(DCE).Mixed logit models and latent class models were then used to analyze their transformation preferences.Results:The mixed Logit model revealed that seven key attributes significantly influenced medical staff's preferences for the achievements transformation of traditional Chinese medicine preparations(P<0.05).Latent class analysis identified three distinct preference groups among respondents:an organization-dependent group(27.0%),a pro-transformation group(61.4%),and a conservative group(11.6%).Conclusions:Medical Staff preferred transformation conditions that increased monthly income;utilized"human use+re-experimentation";involved the hospital's achievements transformation department as the entity;were funded by the hospital;offered a 70%profit share;enabled promotion three years earlier,and assigned patents to the hospital.The study recommends implementing diverse incentive measures and developing differentiated strategies tailored to the distinct Medical Staff categories to facilitate the transformation of hospital traditional Chinese medicine preparations into new drugs.