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 evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective:To evaluate the performance of three mainstream large language models (LLMs) in the review of drug reimbursement indications in hospitals, and to explore their potential in improving audit quality and efficiency, thereby safeguarding the medical insurance fund.Methods:A total of 3 247 outpatient prescription records were retrospectively collected from a specialized oncology hospital between January 2, 2022, and June 30, 2023. Manual assessment of the consistency between clinical diagnoses and drug reimbursement indications was used as the gold standard. Three LLMs, Baidu′s ERNIE Bot, Alibaba′s Tongyi Qianwen, and OpenAI′s ChatGPT-4o, were evaluated on the same task. Performance metrics included accuracy, precision, sensitivity, specificity, F1 score, and area under the curve (AUC).Results:The ERNIE Bot model returned 3 242 valid data, which took 314 min; The Tongyi Qianwen model returned a total of 3 162 valid data, taking 384 min; The ChatGPT-4o model returned a total of 3 218 valid data, taking 150 min. ChatGPT-4o demonstrated the best performance, with an accuracy of 88.41%, precision of 60.48%, sensitivity of 78.75%, specificity of 90.24%, F1 score of 0.68, and an AUC of 0.88.Conclusions:LLMs demonstrate stable performance in determining whether prescriptions align with reimbursement indications, with ChatGPT-4o approaching human-level accuracy and exhibiting more conservative specificity. These findings suggest that LLMs have practical value as auxiliary tools in drug indication reviews, contributing to improved audit efficiency and more refined management of medical insurance funds.

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

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