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/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective:To compare the efficacy of O-arm navigation-assisted and conventional posterior cervical expansive open-door laminoplasty (CEOL) via the intermuscular approach in the treatment of cervical spinal cord injury without fracture-dislocation (CSCIWFD).Methods:A prospective cohort study was conducted to analyze the clinical data of 60 CSCIWFD patients who were admitted to Zhengzhou Orthopedic Hospital from May 2021 to May 2023, with compression at C3-C6. Patients were randomly divided into two groups: 30 patients underwent O-arm navigation-assisted intermuscular approach CEOL (navigation-assisted group) and 30 patients underwent conventional intermuscular approach CEOL (conventional surgery group). Surgical duration, intraoperative blood loss, postoperative drainage volume, and total surgical blood loss were compared between the two groups. At 2 weeks postoperatively, CT scan was performed to evaluate the accuracy of hinge or open-door position preparation of the surgical segments. Visual analogue scale (VAS) for neck and shoulder pain and Japanese Orthopedic Association (JOA) scores were compared between the two groups preoperatively, at 2 weeks, 6 months postoperatively, and at the last follow-up. Complication rates were also evaluated.Results:A total of 60 patients with CSCIWFD were included, comprising 35 males and 25 females, aged 35-77 years [(50.9±8.6)years]. All the patients were followed up for 12-24 months [(16.9±3.1)months]. The surgical duration and intraoperative blood loss were (121.6±17.9)minutes and (144.7±44.2)ml in the navigation-assisted group, shorter or less than (132.3±14.6)minutes and (178.7±48.7)ml in the conventional surgery group ( P<0.05). There were no statistically significant differences in postoperative drainage volume and total surgical blood loss between the two groups ( P>0.05). CT scan reviewed at 2 weeks postoperatively revealed that the accuracy rate of hinge and open-door position preparation of the surgical segments in the navigation-assisted group was 99.2% (119/120), significantly higher than 86.7% (104/120) in the conventional surgery group ( P<0.01). Before operation and at 2 weeks, 6 months postoperatively, and at the last follow-up, the VAS scores for neck and shoulder pain and JOA scores in the navigation-assisted group were 5.0(4.0, 7.0)points and (8.7±2.8)points, 3.0(2.0, 4.0)points and (10.2±2.5)points, 2.0(1.0, 2.0)points and (1 3.0±1.8)points, and 1.0(1.0, 2.0)points and (13.9±1.5)points respectively, while in the conventional surgery group, the VAS scores and JOA scores were 5.5(5.0, 6.3)points and (8.8±2.6)points, 4.0(3.0, 4.0)points and (10.4±2.5)points, 2.0(1.0, 3.0)points and (12.9±2.2)points, and 2.0(1.0, 2.0)points and (13.8±2.0)points ( P>0.05). Both groups showed improvement in neck and shoulder VAS scores and JOA scores at 2 weeks, 6 months postoperatively, and at the last follow-up, compared to preoperative scores ( P<0.05); further improvement was observed at 6 months postoperatively and at the last follow-up compared to that at 2 weeks postoperatively ( P<0.05). There were no significant differences between neck and shoulder VAS scores or JOA scores at 6 months postoperatively and at the last follow-up ( P>0.05). In the navigation-assisted group, 2 patients had axial neck-shoulder pain postoperatively, with a complication rate of 7% (2/30); while in the conventional surgery group, 7 patients had axial neck-shoulder pain and one patient developed cerebrospinal fluid leakage and low-pressure headache, with a complication rate of 27% (8/30) ( P<0.05). Conclusion:Compared to the conventional intermuscular approach, O-arm navigation-assisted intermuscular approach CEOL for CSCIWFD reduces surgical duration and intraoperative blood loss, improves the accuracy of hinge and open-door position preparation, and lowers complication rates.

Objective:To identify key genes involved in LPS-induced acute lung injury(ALI)using GEO database,to eluci-date its pathogenesis and discover potential therapeutic drugs.Methods:Gene expression data from LPS-induced ALI was collected by GEO database,and microbiotics online analysis platform was employed to identify differential expression genes,from which core genes were obtained.Metascape and DAVID were used for GO and KEGG enrichment analysis of these core genes to identify pathways associated with ALI.GSEA and protein interaction analysis were performed for these pathways for identification of core targets.Poten-tial therapeutic drug,kaempferol-3-O-α-L-(4″-E-p-coumaroyl)-rhamnoside(KAE)was validated by animal experiments.Results:Two GEO datasets were incorporated and 261 core genes with differential expression were identified.Data visualization indicated that LPS-induced ALI predominantly involved inflammatory pathways,such as TNF and NF-κB.In vivo validation was conducted in mice on two core targets within this pathway:NF-κB and NLRP3,potential therapeutic drug KAE was administered,which was found to mitigate LPS-induced lung tissue damage.Further investigations demonstrated that KAE could effectively improve ALI by reducing expressions of p-NF-κB,NLRP3 and other proteins.Conclusion:This study markes screening of LPS-induced ALI model within GEO database.Above findings reveal predominant involvement of NF-κB and NLRP3 within TNF and NF-κB signaling pathways in LPS-in-duced ALI.KAE has potential for ALI treatment by down-regulating expressions of p-NF-κB,NLRP3 and other proteins,expecting to be a candidate drug for ALI treatment.

Objective:To identify key genes involved in LPS-induced acute lung injury(ALI)using GEO database,to eluci-date its pathogenesis and discover potential therapeutic drugs.Methods:Gene expression data from LPS-induced ALI was collected by GEO database,and microbiotics online analysis platform was employed to identify differential expression genes,from which core genes were obtained.Metascape and DAVID were used for GO and KEGG enrichment analysis of these core genes to identify pathways associated with ALI.GSEA and protein interaction analysis were performed for these pathways for identification of core targets.Poten-tial therapeutic drug,kaempferol-3-O-α-L-(4″-E-p-coumaroyl)-rhamnoside(KAE)was validated by animal experiments.Results:Two GEO datasets were incorporated and 261 core genes with differential expression were identified.Data visualization indicated that LPS-induced ALI predominantly involved inflammatory pathways,such as TNF and NF-κB.In vivo validation was conducted in mice on two core targets within this pathway:NF-κB and NLRP3,potential therapeutic drug KAE was administered,which was found to mitigate LPS-induced lung tissue damage.Further investigations demonstrated that KAE could effectively improve ALI by reducing expressions of p-NF-κB,NLRP3 and other proteins.Conclusion:This study markes screening of LPS-induced ALI model within GEO database.Above findings reveal predominant involvement of NF-κB and NLRP3 within TNF and NF-κB signaling pathways in LPS-in-duced ALI.KAE has potential for ALI treatment by down-regulating expressions of p-NF-κB,NLRP3 and other proteins,expecting to be a candidate drug for ALI treatment.

Objective:To investigate the causal effects of plasma lipidomics on pancreatitis using Mendelian ran-domization(MR)and evaluate the roles of intra-pancreatic fat deposition(IPFD)and gallstone disease in this relation-ship.Methods:A bidirectional MR analysis was conducted,with 179 plasma lipids as exposures and acute pancreati-tis(AP)and chronic pancreatitis(CP)as outcomes.Data were sourced from genome-wide association studies(GWAS),the UK Biobank,and the FinnGen project.Two-step Mendelian randomization(TSMR)and multivariable Mendelian ran-domization(MVMR)analyses were applied to assess the mediating roles of IPFD and gallstone disease in the associa-tion between plasma lipids and pancreatitis.Results:MR analysis identified two sterols negatively associated with AP(P＜0.05)and seven sterols negatively associated with CP(P＜0.05).One phospholipid showed a positive association with CP(P＜0.05).IPFD was positively associated with both AP and CP.Gallstone disease was confirmed as a risk fac-tor for AP.However,TSMR analysis indicated that neither IPFD nor gallstone disease mediated the relationship be-tween plasma lipids and pancreatitis.Conclusion:The causal relationship exists among plasma lipomics and AP/CP,also between IPFD,cholelithiasis and pancreatitis.These findings highlight novel risk factors and potential biomarkers to support early diagnosis and intervention for pancreatitis.

Aim To investigate the anti-Zika virus(ZIKV)mechanism of diterpenoid compound 9 from Euphorbia helioscopia in vitro.Methods The cytotox-icity of compound 9 was evaluated using the CCK-8 as-say.A ZIKV-infected Vero cell model was established,and the antiviral activity was assessed through RT-qPCR,plaque assay,Western blot,and immunofluores-cence.Furthermore,the mechanism of action was elu-cidated using multi-cell line validation,nanoparticle tracking analysis,cellular thermal shift assay,and mo-lecular docking.Results In Vero cells,compound 9 exhibited an EC50 of(3.95±0.15)μmol·L-1 and a CC50 of(272.12±8.56)μmol·L-1,demonstrating significantly higher antiviral efficacy than the positive control drug ribavirin(RBV).Its virus inactivation effect was time-dependent and could significantly re-duce viral load and plaque formation.Studies revealed that compound 9 altered the physicochemical properties of ZIKV particles,including reducing surface charge and increasing particle size distribution.Additionally,it significantly enhanced the thermal stability of the prM protein.Molecular docking analysis indicated that compound 9 formed a high-affinity interaction with the prM protein(binding energy:-38.52 kJ·mol-1)and stabilized its structure through hydrophobic interac-tions.Conclusion Compound 9 exerts in vitro anti-ZIKV activity by directly inactivating the virus,disrup-ting viral particle integrity,and targeting the prM pro-tein.

BACKGROUND:In recent studies,hydrogel loaded with exosomes has attracted wide attention as an emerging therapeutic strategy in the field of tissue engineering and regenerative medicine,and is considered as a promising means for the treatment of nerve regeneration and wound healing.OBJECTIVE:To review the application of hydrogel loaded with exosomes in nerve regeneration and wound healing and to provide reference and guidance for future research and clinical application.METHODS:The first author used a computer in May 2024 to retrieve the relevant literature published from January 2000 to May 2024 on PubMed and CNKI,searching for"exosome,hydrogel,nerve,nerve regeneration,wound,wound healing"in Chinese and English,eventually incorporating 66 papers for analysis.RESULTS AND CONCLUSION:(1)Hydrogel loaded with exosomes provides a promising path for nerve injury repair by exerting anti-inflammatory and anti-oxidation,stimulating axon growth and myelin regeneration.(2)Exosome-loaded hydrogel suppresses the level of inflammation and oxidative stress,accelerates the proliferation and migration of skin cells,collagen expression,and promotes blood vessel formation,significantly accelerates the wound healing process,and improves the healing quality.(3)The role of hydrogel loaded with exosomes in nerve regeneration and wound repair is still limited to cell and animal experiments,and does not involve clinical practice.In the future,more mechanistic studies,safety evaluation,and supplementary related clinical trials are still needed in the future.

AIM:To investigate the role of BRCA2 and CDKN1A interacting protein(BCCIP)in gastric can-cer(GC)and elucidate its mechanism in mediating cisplatin resistance.METHODS:The BCCIP mRNA expression was assessed in GC tissues(n=415)and normal tissues(n=34)using The Cancer Genome Atlas(TCGA)database.In an in-ternal cohort(n=36 for RT-qPCR;n=5 for Western blot;n=30 for immunohistochemistry),BCCIP expression at both mRNA and protein levels was examined in GC tissues and paired adjacent normal tissues.Human GC cell lines AGS and HGC27 were cultured in vitro and treated with cisplatin in a dose(0,2,4,6,8 and 10 μmol/L)-and time(0,6,24 and 48 h)-dependent manner,followed by Western blot analysis of BCCIP expression.Stable BCCIP knockdown cell lines(shRNA#1 and shRNA#2 groups)were generated via lentiviral transfection,with empty vector-transfected cells serving as controls(vector group).Flow cytometry and colony formation assay were performed to evaluate the effects of BCCIP on apoptosis and colony-forming ability of GC cells treated with cisplatin.Western blot was utilized to detect the changes of BCCIP protein expression levels in the cytoplasm and nucleus of GC cells after cisplatin(2.5 and 1.0 μmol/L)treatment,as well as the effects of BCCIP on the expression of DNA damage marker γ-H2AX and apoptosis-related proteins cleaved caspase-9 and cleaved caspase-3,and the activation of checkpoint kinase 1(CHK1)after cisplatin(2.5 and 1.0 μmol/L)treatment.Immunofluorescence was conducted to observe the effect of BCCIP on γ-H2AX expression in GC cells treated with cisplatin(2.5 and 1.0 μmol/L).RESULTS:The BCCIP expression was significantly up-regulated in GC tissues compared with normal tissues(P<0.01).Cisplatin induced up-regulation of BCCIP expression in a dose-and time-depen-dent manner.Knockdown of BCCIP significantly enhanced cisplatin-induced apoptosis(P<0.01)and reduced colony-forming ability(P<0.05)of GC cells.Knockdown of BCCIP promoted the expression of γ-H2AX,but inhibited the activa-tion of CHK1 after cisplatin treatment,with increased protein levels of cleaved caspase-9 and cleaved caspase-3(P<0.01).CONCLUSION:Cisplatin promotes the expression of BCCIP in GC cells.BCCIP confers cisplatin resistance in GC cells by suppressing apoptosis through modulation of DNA damage response pathways.