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.

An efficient analytical method was developed for simultaneous detection of alkylamines and alkylamides in food packaging plastics using liquid chromatography-high resolution mass spectrometry(LC-HRMS).Based on the physicochemical properties of alkylamines and alkylamides,as well as the complexity of plastic samples,sample pretreatment and chromatographic-mass spectrometric parameters were optimized.The samples were extracted by vortex-ultrasonic extraction with a methanol-acetonitrile mixture for 15 min,followed by nitrogen evaporation to concentrate the extract,reconstitution,and analysis.The chromatographic mobile phase consisted of 0.1%formic acid aqueous solution and acetonitrile,and a gradient elution was used.The electrospray ionization(ESI)source was operated in positive ion mode,and mass spectrometry data were collected in full scan and data-dependent acquisition modes.Quantification was performed using an isotope-labeled internal standard method.The results showed that within the quantification range of 1-1000 ng/mL,the calibration curves exhibited good linearity(R2>0.99).Some compounds interfered with the validation experiments at higher concentrations,so only 10 kinds of target analytes were validated.Using a mixed food packaging plastic matrix,the recoveries at spiking levels of 40,400,and 4000 ng/g were mostly between 66.0%and 117.1%,with relative standard deviations ranging from 0.6%to 10.6%.The method was applied to detect 14 food packaging plastic samples,and the results showed that the concentrations of alkylamines and alkylamides ranged from not detected to 8924 ng/g.This method offered high sensitivity and accuracy,and was suitable for the screening and quantitative determination of alkylamines and alkylamides in plastics.

Coronary artery bypass grafting(CABG) remains a cornerstone treatment for complex coronary artery disease, with long-term graft patency being essential for clinical success. In 2024, the European Society of Cardiology(ESC) and the European Association for Cardio-Thoracic Surgery(EACTS) jointly released an expert consensus document on the intraoperative and postoperative management of CABG grafts. This article provides a comprehensive Chinese translation and interpretation of the consensus, covering key topics including graft harvesting techniques(such as skeletonized vs. pedicled, endoscopic vs. open harvesting), optimal preservation solutions, mechanisms and prevention of graft spasm, and secondary prevention strategies involving antithrombotic and lipid-lowering therapies. Additionally, based on the current situation of clinical practice in China and the characteristics of the Chinese population, the article discussed some key issues in depth, put forward adaptive suggestions, and pointed out the future research direction. The translated consensus and accompanying commentary aim to facilitate the dissemination and application of ESC-endorsed recommendations in Chinese clinical settings, promoting more standardized and evidence-based graft management in CABG surgery.

Coronary artery bypass grafting(CABG) remains a cornerstone treatment for complex coronary artery disease, with long-term graft patency being essential for clinical success. In 2024, the European Society of Cardiology(ESC) and the European Association for Cardio-Thoracic Surgery(EACTS) jointly released an expert consensus document on the intraoperative and postoperative management of CABG grafts. This article provides a comprehensive Chinese translation and interpretation of the consensus, covering key topics including graft harvesting techniques(such as skeletonized vs. pedicled, endoscopic vs. open harvesting), optimal preservation solutions, mechanisms and prevention of graft spasm, and secondary prevention strategies involving antithrombotic and lipid-lowering therapies. Additionally, based on the current situation of clinical practice in China and the characteristics of the Chinese population, the article discussed some key issues in depth, put forward adaptive suggestions, and pointed out the future research direction. The translated consensus and accompanying commentary aim to facilitate the dissemination and application of ESC-endorsed recommendations in Chinese clinical settings, promoting more standardized and evidence-based graft management in CABG surgery.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

Objective To establish an artificial intelligence(AI)diagnostic model for the histopathologic diagnosis of extramammary Paget's disease(EMPD)and to evaluate its efficiency for the diagnosis and differential diagnosis of EMPD.Methods All non-tumor skin disease patients who underwent skin tissue biopsy in Department of Dermatology of First Affiliated Hospital of Army Medical University from September 2003 to February 2023 were recruited,and their pathological data were collected,including EMPD,Bowen's disease(BD),squamous cell carcinoma(SCC),and epidermal hyperplasia and hypertrophy.With EMPD as the main research subject,the histopathological images of BD,SCC,and non-tumor skin diseases were included in the study.The histopathological data of 4 types of diseases was classified and diagnosed by ResNet101 and DenseNet121 deep learning neural networks,and the performance of these models was evaluated.Results The AUC values of the ResNet101 diagnostic model for the diagnosis of EMPD,BD,SCC and non-tumor skin diseases on the images at x20 magnification were 0.97,0.98,1.00 and 0.96,respectively,with an accuracy of 0.925±0.011,while the AUC values on the images at x40 magnification were 1.00,0.99,1.00 and 0.97,respectively,with an accuracy of 0.943±0.017.The AUC values of the DenseNet121 diagnostic model for the diagnosis of 4 diseases on the images at x20 magnification were 0.98,0.95,0.99 and 1.00,respectively,with an accuracy of 0.912±0.034,while the AUC values on the images at x40 magnification were 0.99,0.96,1.00 and 1.00,respectively,with an accuracy of 0.971±0.012.Our results indicated that the histopathologic diagnostic model could effectively differentiate EMPD from BD,SCC and non-tumor skin diseases at low power magnification.The FLPOs of ResNet101 was 786.6 M,and the parameter was 4.5 M;The FLPOs of DensNet121 was 289.7 M,and the parameter was 0.8M.Conclusion Our AI diagnostic model is of good effectiveness in the diagnosis and differential diagnosis of EMPD.DenseNet121 is recommended as the dermatopathological diagnostic model of this study.

Background and purpose:Human epidermal growth factor receptor 2(HER2)serves as one of the paramount drivers of breast cancer metastasis,with roughly 20%-30%of breast cancer patients exhibiting high expression of HER2.The expression level of HER2 is regulatable at multiple molecular levels and determines the metastatic potential of breast cancer cells;however,the manner in which HER2 expression is modulated at the mRNA level remains ambiguous.Circ-0007766 is a circRNA originated from the coding gene ERBB2 for HER2,and whether circ-0007766 can regulate HER2 expression via the ceRNA mechanism has not been reported.This study aimed to analyze whether circ-0007766 acts as a miR-1972 sponge to promote breast cancer cell migration and invasion via upregulation of HER2 expression.Methods:In this study,a high-throughput circRNA chip was employed to screen for circRNAs that exhibited highly specific expression in HER2-positive breast cancer cells.RNA fluorescence in situ hybridization(FISH)was utilized to detect the subcellular localization of circ-0007766.The BaseScope experiment was conducted to analyze the expression level of circ-0007766 in breast cancer tissues and its clinical diagnostic significance.Breast cancer cell models with overexpression and knockdown of circ-0007766 were constructed by transfecting cloning plasmids and siRNA in vitro.The effect of circ-0007766 on the migration and invasion of breast cancer cells was assessed using transwell migration and invasion experiments,and the migration and invasion abilities of MDA-MB-231 and SK-BR-3 cells were measured.Additionally,it was evaluated whether circ-0007766 could promote the migration and invasion of breast cancer cells through miR-1972.A dual luciferase reporter gene assay was used to verify whether circ-0007766 could regulate HER2 expression by binding to miR-1972.The direct interaction between circ-0007766 and miR-1972 was further verified through the RAP experiment.RIP detection was performed in MDA-MB-231 cells,and the relative 3'UTR of HER2 mRNA was measured by real-time fluorescence quantitative polymerase chain reaction(RTFQ-PCR).Western blot was used to detect the protein expressions.Results:Circ-0007766 was conspicuously highly expressed in HER2-positive breast cancer cells and distributed in both the cytoplasm and nucleus of cells,with the preponderance being in the cytoplasm.The expression level of circ-0007766 was strikingly higher in breast cancer tissues than in para-cancerous tissues.The expression of circ-0007766 was significantly elevated in HER2-positive breast cancer samples compared with HER2-negative samples.The overexpression(knockdown)of circ-0007766 in HER2-negative breast cancer cells(in HER2-positive breast cancer cells)was capable of promoting(inhibiting)the migration and invasion of breast cancer cells.Circ-0007766 directly bound to miR-1972,which inhibited breast cancer cell migration and invasion,thereby forming an endogenous competitive RNA(ceRNA)regulatory network and impeding the downregulation of HER2 mRNA and protein expression mediated by miR-1972.Circ-0007766 could potentiate the inhibitory effect of miR-1972 on HER2-mediated breast cancer cell migration and invasion that was negatively regulated by miR-1972.CircRNAs sequestered miRNAs to function as ceRNAs,thereby regulating gene expression at both the transcriptional and translational levels.Finally,we discovered that the expressions of circ-0007766 and HER2 were positively correlated in breast cancer cell and tissue samples,while the expression levels of miR-1972 and HER2 were negatively correlated.Circ-0007766 could specifically target miR-1972 to hinder its regulatory effect on HER2 expression.Conclusion:This study discovers that circ-0007766 facilitates the migration and invasion of breast cancer cells via the miR-1972/HER2 signal axis,offering a novel biomarker and potential therapeutic target for patients with metastatic HER2-positive breast cancer.

Perihilar cholangiocarcinoma(PHC)is a common malignancy of biliary tract,for which surgery is the most effective treatment.However,its prognosis is not satisfactory even after surgical resection.In recent years,there have been some new advances in the surgical treatment of PHC.In this paper,we reviewed the existing literatures,demonstrated the current situation of preoperative biliary drainage,liver hyperplasia,hepatic resection,liver transplantation and minimally invasive surgery in the treatment of PHC,and prospected the future research direction.

Post-endoscopic retrograde cholangiopancreatography pancreatitis(PEP)is one of the most common complications after endoscopic retrograde cholangiopancreatography(ERCP).Numerous PEP prediction models have been established based on different statistical methods at home and abroad.The PEP prediction model,as a tool for evaluating and screening high-risk populations,can provide a basis for medical staff to find high-risk PEP patients early and take effective preventive measures.In recent years,new PEP prediction models have appeared one after another,but there is still a lack of recognized reliable prediction models in clinic.This article reviews the research status of PEP risk prediction models,aim to provide a direction for establishing a more reliable,accurate,and practical PEP risk prediction model in the later period.