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 explore the teaching effectiveness of BOPPPS (bridge-in, objective, pre-assessment, participatory-learning, post-assessment, and summary) teaching model in the undergraduate education of pediatric surgery, compare the BOPPPS teaching model with the traditional teaching model, and examine the differences in students' understanding and mastery of knowledge, as well as their ability improvement.Methods:A total of 621 undergraduate students majoring in pediatrics at Chongqing Medical University in the 2021-2023 academic years were selected as the experimental group, and 552 undergraduate students majoring in pediatrics at Chongqing Medical University in the 2018-2020 academic years were selected as the control group. The traditional teaching method was used in the pediatric surgery teaching of the control group, while the BOPPPS teaching model was used in the experimental group. The two groups were compared based on theoretical examination scores, routine assessment scores, overall performance, and teaching satisfaction. A statistical analysis was conducted using SPSS 24.0 software. Continuous data conforming to a normal distribution were expressed as ( x?±s). Two independent samples mean t test was used for analysis. Results:The experimental group demonstrated significantly higher theoretical examination scores [(70.21±10.03) vs. (62.58±8.40)], routine assessment scores [(96.38±2.10) vs. (84.11±2.02)], and total scores [(80.68±11.30) vs. (71.19±9.50)] compared to the control group ( P<0.05). The overall satisfaction with teaching was significantly higher in the experimental group than in the control group [(91.60±1.75) vs. (90.57±0.80)] ( P<0.05). Conclusions:The application of BOPPPS teaching model in pediatric surgery teaching can improve undergraduate students' self-learning ability, clinical thinking ability, and team cooperation ability, thereby enhancing teaching quality.

Objective:To establish a TaqMan-MGB probe-based method for detecting the polymorphic loci C677T and A1298C of the MTHFR gene.Methods:Specific primers and TaqMan-MGB probes targeting the C677T and A1298C polymorphic loci of the MTHFR gene were designed and optimized based on the gene sequence information.A real-time quantitative PCR detection system was established.Gradient dilution experiments were conducted to determine the limit of detection,and reproducibility experiments were performed to evaluate detection consistency.Specificity was validated using wild-type and mutant plasmid templates.The method was applied to detect 56 clinical samples,and its accuracy and practicality were assessed through comparison with traditional Sanger sequencing.Results:The TaqMan-MGB probe method demonstrated high specificity for detecting the C677T and A1298C loci,with no cross-reactivity between wild-type and mutant probes,enabling accurate genotype differentiation.Sensitivity experiments revealed detection limits of 1.13 × 103 copies/μL for C677T and 8.39 × 101 copies/μL for A1298C.Reproducibility experiments showed coefficients of variation below 1％,indicating stable and reliable results.Among the 56 clinical samples,the overall detection rate for the C677T locus was 86.99％,and for the A1298C locus,it was 97.92％.The TaqMan-MGB method exhibited good concordance with Sanger sequencing results.Conclusion:The TaqMan-MGB method exhibits high specificity,sensitivity,and excellent reproducibility in detecting the polymorphic loci C677T and A1298C of the MTHFR gene,making it suitable for rapid detection in large-scale clinical samples.This method provides an effective molecular diagnostic tool for the early diagnosis and prevention of folate-related diseases.

Objective:To investigate the effect of mild moxibustion on transient receptor potential vanilloid type 1(TRPV1)channel expression in primary dysmenorrhea(PD)rats and explore its mechanism in alleviating central pain sensitization.Methods:Thirty-two female non-pregnant Wistar rats were randomized into a blank group,a model group,a mild moxibustion group,and a capsazepine group,with 8 rats in each group.Except for the blank group,the other three groups used estradiol benzoate,ice-water bath,and oxytocin to establish the rat PD model of cold-dampness stagnation pattern.The interventions began on day 1 of modeling,once a day,and lasted 10 d.The mild moxibustion group received mild moxibustion at Shenque(CV8)and Guanyuan(CV4),20 min/time;in the capsazepine group,capsazepine was injected at a dose of 2 mg/(kg·bw).The abdominal pain threshold was measured 10-30 min after oxytocin injection on day 11;enzyme-linked immunosorbent assay was used to detect serum prostaglandin F2α(PGF2α)level;the expression of TRPV1,cluster of differentiation 11B(CD11B),and proto-oncogene c-Fos in the spinal dorsal horn and hypothalamus was detected by immunofluorescence and Western blotting.Results:Compared to the blank group,the model group showed a decreased pain threshold(P<0.05)and an increased serum PGF2α level with elevated TRPV1,CD11B,and c-Fos protein expression in the spinal dorsal horn and hypothalamus(P<0.05).Compared to the model group,both the mild moxibustion group and capsazepine group showed significantly increased pain thresholds(P<0.05),along with decreased serum PGF2α levels and reduced protein expression levels of TRPV1,CD11B,and c-Fos in the spinal dorsal horn and hypothalamus(P<0.05).Rat pain threshold in the capsazepine group was higher than that in the mild moxibustion group(P<0.05).Serum PGF2α level,the expression levels of CD11B and c-Fos proteins in the spinal dorsal horn,as well as TRPV1,CD11B,and c-Fos proteins in the hypothalamus of the capsazepine group were lower than those in the mild moxibustion group(P<0.05).Conclusion:Mild moxibustion at Shenque(CV8)and Guanyuan(CV4)may alleviate the central pain sensitization in PD rats by down-regulating TRPV1 channel expression in the spinal dorsal horn and hypothalamus,thus playing an analgesic effect.

Objective:This study aims to investigate the expression of uridine diphosphate-glucose[]pyrophos-phorylase 2(UGP2)in breast cancer(BC)tissues and its oncogenic mechanism,assessing its potential value as a diag-nostic and prognostic biomarker for breast cancer.Methods:(1)Online database analysis was conducted to assess UGP2 mRNA and protein expression levels in breast cancer and explore their correlation with clinical characteristics.Im-munohistochemistry(IHC)was used to verify UGP2 expression in human breast cancer tumor tissues and evaluate its relationship with clinicopathological features.(2)Kaplan-Meier survival analysis and COX regression models were used to analyze the impact of UGP2 expression on breast cancer patient prognosis.(3)Bioinformatics methods were em-ployed to investigate the correlation between UGP2 and tumor immune cell infiltration,and to predict the biological func-tions and associated signaling pathways of UGP2 in breast cancer.Results:(1)The mRNA and protein expression levels of UGP2 were upregulated in breast cancer tissues(both P<0.05),and were negatively correlated with ER-positive and PR-positive status(OR<1,P<0.05),while positively correlated with Ki-67 levels and the triple-negative breast cancer(TNBC)subtype(OR>1,P<0.05).(2)Elevated expression levels of UGP2 were associated with poorer survival rates in breast cancer patients(both P<0.05)and were identified as an independent adverse prognostic factor for breast cancer(HR=1.40,P<0.05).(3)Functional analysis results suggested that UGP2 may promote tumor progression by regulating metabolism,hormone signaling,and the immune microenvironment.Additionally,UGP2 expression was negatively cor-related with NK cell activation status and positively correlated with the inhibitory state.Conclusion:UGP2 expression is elevated in breast cancer tissues and is closely associated with poor patient prognosis.It may promote cancer pro-gression through mechanisms such as metabolic reprogramming and immune suppression.UGP2 shows promise as a potential biomarker and therapeutic target in breast cancer,providing a basis for personalized treatment.

Objective:To establish a TaqMan-MGB probe-based method for detecting the polymorphic loci C677T and A1298C of the MTHFR gene.Methods:Specific primers and TaqMan-MGB probes targeting the C677T and A1298C polymorphic loci of the MTHFR gene were designed and optimized based on the gene sequence information.A real-time quantitative PCR detection system was established.Gradient dilution experiments were conducted to determine the limit of detection,and reproducibility experiments were performed to evaluate detection consistency.Specificity was validated using wild-type and mutant plasmid templates.The method was applied to detect 56 clinical samples,and its accuracy and practicality were assessed through comparison with traditional Sanger sequencing.Results:The TaqMan-MGB probe method demonstrated high specificity for detecting the C677T and A1298C loci,with no cross-reactivity between wild-type and mutant probes,enabling accurate genotype differentiation.Sensitivity experiments revealed detection limits of 1.13 × 103 copies/μL for C677T and 8.39 × 101 copies/μL for A1298C.Reproducibility experiments showed coefficients of variation below 1％,indicating stable and reliable results.Among the 56 clinical samples,the overall detection rate for the C677T locus was 86.99％,and for the A1298C locus,it was 97.92％.The TaqMan-MGB method exhibited good concordance with Sanger sequencing results.Conclusion:The TaqMan-MGB method exhibits high specificity,sensitivity,and excellent reproducibility in detecting the polymorphic loci C677T and A1298C of the MTHFR gene,making it suitable for rapid detection in large-scale clinical samples.This method provides an effective molecular diagnostic tool for the early diagnosis and prevention of folate-related diseases.

Objective To analyze the trends and changes in the burden of chronic kidney dis-ease(CKD)in China from 1990 to 2021.Methods Data related to the burden of CKD in China from the 2021 Global Burden of Disease(GBD)Study public database were downloaded.Descriptive analyses were conducted using indicators such as age-standardized incidence rates,mortality rates,years of life lost(YLL)rates,years lived with disability(YLD)rates,and disability-adjusted life years(DALY)rates.The Joinpoint regression model was employed to analyze the trends in CKD.The Nordpred model was used to predict the standardized mortality rates,prevalence rates,and inci-dence rates of CKD in China over the next 20 years.Results The age-standardized incidence rate of CKD in China increased from 147.29 per 100,000 in 1990 to 163.74 per 100,000 in 2021,while the age-standardized prevalence rates,mortality rates,YLL rates,YLD rates,and DALY rates all ex-hibited downward trends.The incidence and prevalence of CKD were higher in Chinese women than in men,while mortality rates and DALY rates were lower in women than in men.The burden of CKD increased with age.It is estimated that by 2045,the incidence and prevalence of CKD in China will continue to rise,but the standardized mortality rate and standardized prevalence rate will decline.Conclusion Based on the current status and trends in the burden of CKD in China,implementing precise health management for different populations can help reduce the burden of CKD in China.

Objective To establish a human intestinal organ-on-a-chip model using a multi-array chip array to simulate the microphysiological structure of the human intestine and to investigate the impact of ionizing radiation on radiation-induced damage to human intestinal cells.Methods Caco-2 and human umbilical vein endothelial cells(HUVECs)were co-cultured in an organ chip.The cells were subjected to fluid shear stress via a precision shaker.After 7 days of dynamic culture,the morphological structure of intestinal epithelial cells and venous endothelial cells within the intestinal organ chip was examined using phase contrast microscopy,immunofluorescence staining,and confocal microscopy for three-dimensional(3D)imaging.γ-H2AX and TUNEL immunofluorescence staining were employed to assess DNA damage and apoptosis in intestinal epithelial cells two days post-irradiation.Villin immunofluorescence staining was used to evaluate villus height three days post-irradiation.EdU incorporation assay and Ki67 immunofluorescence staining were conducted to observe the effects of ionizing radiation on the proliferation of intestinal epithelial cells.Results After 7 days of dynamic culture,phase contrast microscopy and immunofluorescence staining combined with confocal 3D imaging revealed that the upper intestinal epithelial cells in the middle compartment of the chip formed a 3D intestinal villus structure,while the vascular endothelial cells in the lower compartment developed a vascular network structure.The chip was subsequently irradiated by 10 Gy X-ray.Immunofluorescence staining results indicated that the mean fluorescence intensity of γ-H2AX and TUNEL in the irradiated group was significantly higher than in the non-irradiated group 2 days after irradiation(P＜0.01),and that the proportion of EDU+and Ki67+cells in the irradiated group was significantly lower than in the non-irradiated group three days after irradiation(P＜0.05).Conclusion Caco-2 cells and HUVECs co-culture on an organ chip can generate the biomimetic structure of human intestinal villus.Ionizing radiation has been found to shorten intestinal villus,increase DNA damage and apoptosis in intestinal epithelial cells,and inhibit the proliferation of these cells.

Objective:To identify the risk factors for postoperative sleep disturbance (PSD) in patients undergoing spine surgery.Methods:In this case-control study, patients who underwent spine surgery from December 2023 to June 2024 at Beijing Tiantan Hospital of Capital Medical University, were selected as the subjects of the study. The quality of postoperative sleep was assessed using the Athens Insomnia Scale (AIS). The baseline characteristics and various perioperative indicators of the patients were collected. The patients were divided into PSD group and non-PSD group according to whether they had PSD. The variables with statistically significant differences from the univariate analysis were included in a multivariate logistic regression to identify the risk factors for PSD.Results:The results of the multivariate logistic regression analysis showed that preoperative sleep disturbance (odds ratio [ OR]=2.23, 95% confidence interval [ CI] 1.06-4.72, P=0.036), course of disease > 12 months ( OR=2.20, 95% CI 1.14-4.24, P=0.019) and AIS score > 2 on the night before surgery ( OR=2.06, 95% CI 1.02-4.16, P=0.045) were the independent risk factors for PSD in patients undergoing spine surgery. Conclusions:Preoperative sleep disturbance, course of disease > 12 months and AIS score > 2 on the night before surgery are independent risk factors for PSD in patients undergoing spine surgery.