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.

Tripterygium wilfordii is a traditional Chinese medicinal herb belonging to the genus Tripterygium in the Celastraceae family， which has the effects of clearing heat and detoxifying， dispelling wind and dampness， and invigorating blood circulation to relieve pain， and is used to treat diseases such as rheumatoid arthritis， glomerulonephritis， nephrotic syndrome， lupus erythematosus， scabies， and stubborn tinea. Its chemical composition is diverse. Among them， triptolide（TP） is one of the main active and toxic components of T. wilfordii. It has significant biological activities such as anti-inflammation， anti-tumor， and immunosuppression. However， it causes serious adverse reactions such as liver and kidney function damage and reproductive system disorders. At the same time， TP has poor water solubility and low bioavailability， and the enhancement of bioavailability by increasing the dosage undoubtedly improves the exposure of the drug in non-target organs， leading to the occurrence of adverse reactions， and these largely limit the clinical application of TP. Based on this， this article extracted relevant data from the Web of Science， PubMed， and China National Knowledge Infrastructure（CNKI） databases， summarized the research on the adverse reactions of TP in recent years， and reviewed the progress of toxicity reduction research from the perspectives of structural modification， novel drug delivery systems， and compatibility. Structural modification can precisely alter the chemical structure of TP， reduce the activity of its toxic groups， and retain its biological activity while fundamentally reducing the occurrence of adverse reactions. New drug delivery systems can achieve targeted delivery of TP， increase its concentration in target organs， and reduce its exposure in non-target organs， thereby enhancing therapeutic efficacy and reducing adverse effects. In addition， the combination of TP with Chinese medicine compound， single-flavored Chinese medicine or monomer can reduce the adverse effects of TP and enhance the efficacy to different degrees， which is of clinical value. This paper systematically explains attenuation research from the above three perspectives， aiming to provide a theoretical basis for the full utilization of biological activity and drug development of TP.

Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

Objective To investigate the prevalence of common diseases among primary and secondary school students in Yichang City from 2019 to 2022, and to provide a scientific basis for formulating effective intervention measures in the future. Methods By random cluster sampling , 7 schools in urban areas and 5 schools in suburban counties were selected to screen common diseases such as myopia, dental caries, obesity and abnormal spinal curvature. Descriptive epidemiological methods were employed for statistical analysis. Results A total of 17 023 primary and secondary school students were screened from 2019 to 2022. The overall detection rate of common diseases from high to low was myopia (54.12%), caries (36.75%), overweight (15.17%), obesity (11.88%), malnutrition (5.80%), and abnormal spinal curvature (3.49%). The detection rates of myopia and abnormal curvature of the spine showed an increasing trend with years and school stages, while the detection rates of malnutrition and dental caries showed a decreasing trend with years and school stages. The detection rates of overweight and obesity showed no trend difference with years, and the detection rates of obesity showed a decreasing trend with school stages. The rates of myopia, overweight and obesity were higher in urban areas than those in suburban counties, and the rate of dental caries was higher in suburban counties than that in urban areas. The prevalence of overweight, obesity, and malnutrition in boys was higher than that in girls. The prevalence of myopia and dental caries in girls was higher than that in boys. The above differences were statistically significant (all P<0.05). Conclusion Myopia, dental caries, obesity, and abnormal curvature of the spine are the current focus of the prevention and treatment of common diseases in students. There are great differences between different regions, school stages, and genders. The ^“tripartite linkage^” of schools, families, and communities should be achieved with the joint efforts of the education and health departments to actively take targeted intervention measures to reduce the prevalence.

Neurogastroenterology and motility disorders of the upper gastrointestinal (GI) tract represent a complex and heterogeneous group of conditions that involve the interaction between the GI tract and the central nervous system. They constitute a significant number of outpatient gastroenterology visits, resulting in a high healthcare burden. These disorders often occur in the absence of identifiable structural causes on routine endoscopy and radiological imaging. A more targeted approach in the assessment of functional GI disorders is increasingly being integrated into routine clinical practice, given the recent advancements in technology and physiologic testing. When used in the appropriate clinical context, these tests not only elucidate the physiological basis for the patient's symptoms, but also prevent inappropriate treatment and repeated investigations. This review aims to summarise the advances in clinically available diagnostic tools for the evaluation of upper GI functional disorders.
Humans ; Gastrointestinal Diseases/physiopathology* ; Upper Gastrointestinal Tract/physiopathology* ; Gastrointestinal Motility ; Endoscopy, Gastrointestinal

INTRODUCTION: During the coronavirus disease 2019 (COVID-19) pandemic, contact tracers were under immense pressure to deliver effective and timely contact tracing, raising concerns of higher susceptibility to burnout. Our study aimed to determine burnout prevalence among hospital-based contact tracers and associated risk factors, so that interventions to reduce burnout risk could be formulated. METHODS: One hundred and ninety-six active contact tracers across three hospitals within a healthcare cluster were invited to complete an anonymous online survey. To identify burntout, data such as demographics, work-related variables and contact tracing-related variables were collected using the Copenhagen Burnout Inventory. Associated factors were identified using multivariate statistics. Open-ended questions were included to understand the challenges and potential improvements through qualitative analysis. RESULTS: A total of 126 participants completed the survey, giving a completion rate of 64%, and almost half of these participants (42.9%) reported burnout. Protective factors included being on work-from-home arrangements (adjusted odds ratio [OR] 0.22, 95% confidence interval [CI] 0.08-0.56), perception of being well supported by their institution (adjusted OR 0.25, 95% CI 0.08-0.80) and being married (adjusted OR 0.28, 95% CI 0.12-0.64). Risk factors included having an administrative role pre-COVID-19 (adjusted OR 3.62, 95% CI 1.33-9.83). Work-related burnout was related to being activated for more than 1 day in the preceding week (unadjusted OR 3.25, 95% CI 1.33-7.94) and multiple activations in a day (unadjusted OR 3.54, 95% CI 1.44-4.41). Biggest challenges identified by participants were language barrier (62.7%), followed by workflow-related issues (42.1%). CONCLUSION Our study demonstrated burnout and other challenges faced by a team of mostly hospital-based administrative staff redeployed on a part-time basis to ensure timely contact tracing. To mitigate burnout, we recommend choosing staff on work-from-home arrangements and ensuring adequate manpower and rostering arrangements.
Humans ; COVID-19/epidemiology* ; Burnout, Professional/epidemiology* ; Singapore/epidemiology* ; Female ; Male ; Cross-Sectional Studies ; Adult ; Middle Aged ; Risk Factors ; Surveys and Questionnaires ; Contact Tracing/methods* ; SARS-CoV-2 ; Prevalence ; Pandemics

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

Objective To investigate the epidemiological and demographic characteristics of Mycoplasma pneumoniae(Mp),respiratory syncytial virus(RSV),influenza A(FluA),and influenza B(FluB)in a single center in Minhang District,Shanghai after the end of the COVID-19 pandemic.Methods A retrospective analysis of data from Apr 2023 to Jul 2024 of patients who underwent testing for Mp,RSV,FluA,and FluB due to respiratory tract infections in Minhang Hospital,Fudan University was conducted.Differences in pathogen infections were analyzed among different seasons and age groups.Results A total of 39 103 individuals of respiratory tract infections with simultaneous testing for all four pathogens were included in this analysis,with a total detection rate of 44.7%(17 490/39 103).The detection rates were as follows:Mp 25.2%,FluA 13.1%,FluB 10.9%,and RSV 1.5%.Co-infections accounted for 5.9%,predominantly with Mp and FluA.The detection rate of Mp was>38%in children under 14 years old,gradually decreasing with age.In the child group(≤14 years),both FluA and FluB had the highest detection rates in the 7-14 years age group(FluA,16.5%;FluB,10.4%).In the adult group(≥15 years),the highest detection rates for FluA and FluB were found in the 15-24 years age group(12.5%)and the 35-44 years age group(15.9%),respectively.The detection rates of pathogens varied significantly across different months(P<0.001),with an increasing trend in the total number and overall detection rate of the four pathogens after Sept 2023(P<0.001).Conclusion After the end of the COVID-19 pandemic,there was an abnormal increase in Mp in a single center in Minhang District,Shanghai.Mp,along with influenza viruses,became the main pathogens causing respiratory tract infections.Targeted prevention and control measures based on the epidemiological characteristics of infections should be implemented to guide clinical diagnosis and treatment.

Objective To investigate the peripheral blood cytokine levels in patients with acute myocardial infarction(AMI),and to analyze its correlation with Killip classification,N-terminal brain natriuretic peptide precursor(NT-proBNP),cardiac troponin I(cTnI),creatine kinase isoenzymes(CK-MB),and to provide a theoretical basis for assessing the severity and prognosis of the disease.Methods A total of 312 patients with AMI admitted to Minhang Hospital,Fudan University from Jul 2021 to Oct 2023 were enrolled as the case group,and 201 patients with unstable angina pectoris were selected as the control group.General clinical data of the subjects were collected,and the concentrations of cytokines(IL-5,IFN-α,IFN-γ,IL-10,IL-12p70,IL-17,IL-1β,IL-2,IL-4,IL-6,IL-8,and TNF-α)in peripheral blood were detected by multiplex bead-based flow cytometry.NT-proBNP,cTnI and CK-MB were measured by chemiluminescence methods.The levels of cytokines between the two groups were compared,and their correlations with Killip classification,NT-proBNP,cTnI and CK-MB were analyzed.The predictive efficacy of cytokines for AMI was evaluated by receiver operating characteristic(ROC)curves.Results There were no significant differences in baseline data between the AMI group and the control group(P>0.05),with the exception of age.The levels of IL-6,IL-8 and TNF-α in the AMI group were higher than those in the control group(all P<0.01).The correlation analyses showed that IL-6 was positively correlated with Killip classification,NT-proBNP,cTnI and CK-MB(all P<0.01).ROC analyses showed that IL-6 levels had good predictive efficacy for AMI(AUC=0.882 9,P<0.01).Conclusion The expression of IL-6 was significantly increased in patients with AMI,and it was positively correlated with Killip classification,NT-proBNP,cTnI and CK-MB,suggesting that IL-6 may serve as a potential biomarker for assessing the severity of AMI.