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 compare the performance of 7 Chinese-developed GenAI models (DeepSeek, Wenxin Yiyan, Tongyi, Doubao, Kimi, Hunyuan, and iFLYTEK Spark) in responding to common diseases of the pediatric genitourinary system and to explore their potential applications.Methods A total of 80 questions covering basic disease information, diagnosis, treatment, and prognosis related to “hypospadias, hydronephrosis, and cryptorchidism” were developed as prompts.The models were tested under 3 modes:“quick thinking, ”“deep thinking, ” and “deep thinking + internet access.” The results were evaluated in a blinded review by two pediatric urologists.The responses were graded into 4 levels—A, B, C, and D—based on accuracy, completeness, and relevance.The proportions of responses rated as A and A+B were statistically analyzed and compared across the different models/modes.Results The “deep thinking” mode of DeepSeek demonstrated the best performance, with 88% of responses rated as A and 96% rated as A+B.DeepSeek (deep thinking + internet access), Doubao (quick thinking), Hunyuan (deep thinking), and Doubao (deep thinking + internet access) followed closely, also showing excellent response capabilities.Among the top 5 models/modes, significant differences were observed in the proportion of Alevel responses (P＜0.05), while differences in the proportion of A+B-level responses were not statistically significant (P＞0.05).Conclusion Certain Chinese-developed GenAI models, represented by DeepSeek (deep thinking), demonstrate significant application potential.However, they still cannot consistently provide recommendations rated at the A+B level (recommended grade or higher) with 100% accuracy.In clinical practice, both doctors and patients should view GenAI as an auxiliary tool for education and information acquisition rather than as a final decision-making authority.All information must be reviewed and confirmed by professional physicians.

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 evaluate the effects and underlying mechanisms of preoperative intestinal microbiota modulation on the recovery of prolonged postoperative ileus(PPOI)in gastric cancer patients with sarcopenia Methods:Skeletal muscle mass(SMM)was assessed using bioelectrical impedance analysis(BIA),and the skeletal muscle index(SMI)was calculated.A total of 156 gastric cancer patients with sarcopenia who underwent surgery at the Department of Gastrointestinal Surgery,Liyang People's Hospital,from January 2022 to December 2024 were randomly assigned to either the control group or the experimental group.The control group received conventional prehabilitation interventions,including nutritional support,respiratory function training,and physical exercise.The experimental group received probiotic-based intestinal microbiota modulation in addition to conventional prehabilitation interventions.Postoperative recovery indicators,including time to first flatus,incidence of postoperative complications,length of hospital stay,and hospitalization costs,were compared between the two groups.Results:Among the 156 sarcopenic gastric cancer patients,121 were male,and 35 were female.Statistically significant differences were observed between the two groups in terms of time to first flatus,incidence of postoperative complications,and length of hospital stay(P<0.05).Postoperative complications occurred in 38 patients(24.3%),with 10 cases(6.4%)in the experimental group and 28 cases(17.9%)in the control group.The time to first flatus in the experimental group was significantly shorter than in the control group(48.0 hours vs 72.0 hours,P<0.001).Conclusion:Preoperative intestinal microbiota modulation significantly reduces the incidence of PPOI and postoperative complications in gastric cancer patients with low SMI,thereby promoting postoperative gastrointestinal function recovery.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the coordinated development status of the medical service supply-economy-society trinity systems in Zhejiang Common Prosperity Demonstration Zone,and to offer references for formulating policies conducive to the efficient and coordinated development of these three systems.Methods:Based on the panel data from 2013 to 2022,this research was conducted on the 11 prefectural-level cities in Zhejiang Province.Firstly,an evaluation index system for the three systems was established,and the entropy method was employed to determine the weights of each index and calculate the comprehensive evaluation index.Secondly,a triangular model was introduced to delineate the relative relationships among the three systems,and the coupling coordination degree model was utilized to disclose the coordination degree of the three systems.Finally,the spatial autocorrelation analysis method was applied to investigate the spatial autocorrelation of the coupling coordination degree of the three systems.Results:(1)On the whole,the development status of the three systems has improved over time,yet the comprehensive development level remains to be improved.(2)Overall,each prefectural-level city has transited from a medical service supply-society-dominated development to a balanced and coordinated development of the medical service supply-economy-society trinity systems.The coupling coordination degree of the three systems has risen from 0.468(on the verge of imbalance)in 2013 to 0.609(primary coordination)in 2022,presenting an upward trend in general.However,the coordination level remains to be improved and there exist imbalances among regions.(3)The coupling coordination degree of the three systems in Zhejiang Province exhibits a significant positive spatial correlation,and the spatial distribution characteristics are relatively stable. Conclusion:The coupling coordination degree of the medical service supply-economy-society trinity systems in Zhejiang Province awaits further enhancement. At the level of Zhejiang Province,favorable policy support should be provided,the layout of medical resources should be rationally planned,and high-quality economic and social development should be promoted. Each prefectural-level city should formulate strategies for medical service supply,economic,and social development in accordance with its own development level and local conditions,strengthen inter-city linkage and cooperation,and thereby elevate the coordinated development level of the three systems.

The"capitation payment with retained surplus and shared accountability for reasonable overruns"mechanism constitutes a pivotal institutional framework for advancing the high-quality development of County Medical Communities(CMCs).This study addresses two critical operational challenges:identifying the sources of medical insurance fund surplus and optimizing the governance of fund retention processes.Grounded in transaction cost theory,we develop an analytical framework examining the formation of medical insurance fund surplus through the dual lenses of intra-organizational dynamics within CMCs and external medical insurance payment mechanism design.Utilizing Deqing County,Zhejiang Province as an empirical case,this research proposes a five-pronged strategy:Clarifying generation channels of insurance fund surplus,scientifically determining regional medical insurance budgets,implementing bundled payment mechanisms for CMCs,adopting hybrid payment models integrating unified and differentiated approaches,and establishing performance-based incentive systems.These findings elucidate the formative pathways of medical insurance fund surplus while offering theoretical and practical insights for enhancing payment system reforms to support CMC development.

Objective:To detect the serum levels of 25(OH)D,miR-125b-5p,hypoxia-inducible factor-1α(HIF-1α)and vascular endothelial growth factor A(VEGFA)in patients with multiple myeloma(MM),and explore the role of miR-125b-5p/HIF-1α pathway in the involvement of vitamin D deficiency in the pathogenesis of MM.Methods:Fifty three newly diagnosed/relapsed MM patients admitted to the department of hematology of our hospital from October 2021 to December 2023 were included.Meanwhile,25 healthy individuals matched in gender and age from our hospital's Health Management Center were selected as controls.The serum level of 25(OH)D was monitored by mass spectrometry,the serum level of miR-125b-5p was detected by real-time fluorescence quantitative PCR,and serum levels of HIF-1α and VEGFA were measured by enzyme-linked immunosorbent assay.The levels of 25(OH)D,miR-125b-5p,HIF-1α,and VEGFA were compared between the two groups.According to the level of 25(OH)D,the MM patients were divided into vitamin D deficiency group(＜20 ng/ml)and vitamin D non-deficiency group(≥ 20 ng/ml),and the levels of miR-125b-5p,HIF-1α,and VEGFA were compared between the two groups.The correlations between 25(OH)D,miR-125b-5p,HIF-1α and VEGFA were analyzed.The receiver operating characteristic(ROC)curve analysis was used to determine the diagnostic value of25(OH)D combined with miR-125b-5p for newly diagnosed MM.Results:The level of 25(OH)D in MM patients was significantly lower than that in control group(P＜0.01).There was no significant difference in 25(OH)D level between newly diagnosed and relapsed MM patients(P＞0.05).Compared with the control group,the level of miR-125b-5p was significantly reduced in MM patients(P＜0.01),while the levels of HIF-1α and VEGFA were significantly increased(both P＜0.001).In MM patients,the miR-125b-5p level in the vitamin D deficiency group was significantly decreased than that in the non-deficiency group(P＜0.01),while the levels of HIF-1 α and VEGFA were significantly increased(both P＜0.05).In MM patients,25(OH)D was positively correlated with miR-125b-5p,while negatively correlated with HIF-1α and VEGFA(both P＜0.05).Moreover,miR-125b-5p was negatively correlated with HIF-1α and VEGFA(both P＜0.05).The area under the curve(AUC)for diagnosing MM with 25(OH)D,miR-125b-5p,and their combination were 0.699,0.751,and 0.791,respectively.Conclusion:The incidence of vitamin D deficiency is high in MM patients.Vitamin D deficiency may promote angiogenesis and participate in the occurrence and development of MM by downregulating miR-125b-5p and upregulating HIF-1α and VEGFA expression.

OBJECTIVE To investigate the impact of inflammatory cytokines related to different endotypes of chronic rhinosinusitis on the transcriptome of nasal epithelial cells.METHODS Human primary nasal epithelial cells were cultured in vitro,and treated with type 1,type 2,and type 3 inflammatory cytokines IFN-γ(10 ng/ml),IL-4(50 ng/ml),and IL-17A(50 ng/ml),respectively.After 48 hours,cells were collected for RNA extraction and transcriptome analysis.Differentially expressed genes were identified,followed by functional annotation and pathway enrichment analysis.Additionally,common regulated genes among different cytokines were analyzed.RESULTS Treatment of primary nasal epithelial cells with IFN-γ,IL-4,and IL-17A induced significant transcriptomic alterations,with 650,540,and 192 differentially expressed genes,respectively,compared to the control group.Functional annotation and pathway enrichment analysis showed that IFN-γ was mainly associated with defense response to virus,antigen processing and presentation,leukocyte and lymphocyte mediated immunity,and NOD-like receptor signaling pathway;IL-4 was mainly related to the regulation of leukocyte chemotaxis,cell-cell adhesion,ECM-receptor interaction,and MAPK signaling pathway;IL-17A was involved in the regulation of neutrophil chemotaxis,response to molecule of bacterial origin,chemokine signaling pathway,and NF-κB signaling pathway.Genes commonly regulated by IFN-γ,IL-4,and IL-17A were identified,with DUOX2 being upregulated by all the three cytokines.CONCLUSION IFN-γ,IL-4,and IL-17A reshapes the transcriptomic profile of nasal epithelial cells,which mainly regulates signaling pathways related to defense response to virus,leukocyte chemotaxis,and response to bacteria,respectively.

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.