ObjectiveTo investigate the effects of exogenous nitric oxide （NO） on the accumulation and quality formation mechanism of flavonoids in Scutellariae Radix. MethodsFresh roots of Scutellaria baicalensis were treated with sodium nitroprusside （SNP） solutions at concentrations of 0.0， 7.5， and 20 mmol·L^-1， respectively. Kits and supporting reaction systems were used to determine the following indicators of samples in each group， including （1） reactive oxygen species： changes in the content of nitric oxide （NO）， superoxide anion （O2-·）， and hydrogen peroxide （H₂O₂）， （2） lipid oxidation products： changes in the content of malondialdehyde （MDA）， （3） antioxidant enzymes： changes in the activity of superoxide dismutase （SOD）， catalase （CAT）， and peroxidase （POD）， and （4） metabolic key enzymes and metabolic intermediates： Changes in the activity of phenylalanine ammonia-lyase （PAL） and the content of 1，3-diphosphoglycerate （1，3-DPG）. High-performance liquid chromatography （HPLC） was used to determine the changes in the content of secondary metabolites in flavonoids such as baicalin， wogonoside， baicalein， and wogonin in each group. ResultsCompared with that on day 0， during the treatment with 20 mmol·L^-1 SNP solution， the content of NO， O2-·， H₂O₂， and MDA in fresh roots of Scutellaria baicalensis increased significantly （P<0.01）， by 138.7%， 75.7%， 292.9%， and 140.3% respectively. The activity of SOD， CAT， and POD increased by 100.7%， 41.4%， and 70.4% respectively （P<0.01）， and that of PAL increased by 111.1% （P<0.01）. The content of the secondary metabolites baicalin and wogonoside remained basically unchanged， while that of baicalein and wogonin increased by 401.3% and 457.9% respectively （P<0.01）. The content of 1，3-DPG increased by 165.0% （P<0.01）. In the 7.5 mmol·L^-1 SNP solution treatment group， the stress degree was relatively mild. Compared with that on day 0， the content of NO， O2-·， H₂O₂， and MDA increased by 76.2%， 57.7%， 221.4%， and 99.7% respectively （P<0.01）. The activity of antioxidant enzymes SOD， CAT， and POD increased by 79.5%， 55.6%， and 51.9% respectively （P<0.01）， and that of PAL increased by 69.0% （P<0.01）. The content of baicalein and wogonin increased by 204.7% and 272.2% respectively （P<0.01）， and that of 1，3-DPG increased by 128.0% （P<0.01）. The 20 mmol·L^-1 SNP group showed better performance than the 7.5 mmol·L^-1 SNP group. ConclusionSNP can simulate the physiological state of Scutellaria baicalensis under stress conditions， activate the antioxidant protection mechanism， promote the biosynthesis of flavonoids in Scutellariae Radix， and significantly improve the quality of medicinal materials in Scutellariae Radix.

Objective: To analyze changes in Rh system antibodies among antibody-positive patients and evaluate the efficacy of Rh phenotype-matched electronic cross-matching (hereinafter referred to as Rh-ECM). Methods: A retrospective analysis was performed on antibody screening data of 48 254 patients in our hospital from December 2023 to March 2025. The antibody screening results were compared between the pre-application phase (n=46 346, control group) and post-application phase (n=48 254, experimental group) of Rh-ECM technology, focusing on the changes in the proportion of Rh system antibodies, with statistical analysis conducted using SPSS 26.0 software. Meanwhile, the initial and re-examination situations of Rh antibody in the antibody screening of approximately 20 000 person-times each before (June 2019 to June 2020, n=21 048) and after (July 2020 to April 2021, n=20 965) of Rh-ECM were evaluated to explore the influence of Rh-ECM on the detection rate of Rh antibody. Results: After Rh-ECM implementation, 345 positive cases (0.7%) (345/48 254) were detected among 48 254 patients, primarily consisting of mns system antibodies (128 cases, 37.1%) (128/345) and rh system antibodies (95 cases, 27.5%) (95/345). Before Rh-ECM implementation, 199 positive cases (0.4%) (199/46 346) were detected among 46 346 patients, with rh system antibodies accounting for 97 cases (48.7%) (97/199). The difference in the composition ratio of Rh antibodies between the two phases was statistically significant (P<0.001), and the relative risk ratio of Rh antibody detection after Rh-ECM implementation was 56.5% compared to before. Another set of data analysis showed that before Rh-ECM, there were 37 cases with initial positive results and 8 cases with re-examination positive results; after Rh-ECM, these numbers were 44 and 2 respectively There was a statistically significant difference in the re-examination positive rate of Rh antibodies between the two stages (P<0.05). Conclusion: The implementation of Rh-ECM technology significantly reduced the proportion of Rh system antibodies among patients with positive antibody screening results. This suggests that Rh-ECM can effectively reduce the detection rate of Rh antibodies, which may be related to the reduced risk of antibody production due to Rh-matched transfusion, thus improving transfusion safety. Therefore, Rh-ECM is worthy of broader promotion in clinical transfusion testing.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective To retrospectively analyze multicenter data from domestic sources, aiming to explore the link between intrahepatic cholangiocarcinoma (ICC) tumor size and prognosis, establishing a classification system based on tumor size. Methods Between December 2011 and September 2018, 280 ICC patients from 13 hospitals were included. The tumor size prognosis cutoff was identified by the minimum P-value method, and the classification's overall survival related effectiveness was assessed by Kaplan-Meier analysis. Results All 280 patients were divided into the group of tumor maximum diameter ≤4 cm and >4 cm. Tumor size was confirmed as an independent prognosis factor by multivariate COX regression analysis (HR=2.110, 95% CI: 1.358-3.280). Conclusions The tumor size dichotomy classification system based on the Chinese patient group can expediently predict ICC prognosis and offers an important basis for selecting post-operative individualized adjuvant therapy and follow up plans.

Space radiation is the most important environmental harmful factor in long-term manned spaceflight and deep space exploration, and it may produce deterministic and stochastic effects on tissues and organs. In-depth research into the biological effects, mechanisms, and protective measures of space radiation is essential and serves as an important foundation for exploring radiation biology and promoting major manned space projects. Firstly, this review introduces the spatiotemporal distribution characteristics of space radiation during low-earth orbit flights, manned lunar landings, and deep space exploration missions, as well as the health risks and challenges it posed to astronauts. Then, it discusses medical requirements and exposure limits, risk assessment, and protection technologies included in the space radiation protection system established internationally and over 30 years of Chinese manned spaceflight departments. Finally, it outlines the subsequent work and prospects for further research.

Objective To explore the distribution of common TCM syndromes and symptoms of insomnia;To prepare for the construction of the theoretical framework and item pool of syndrome diagnosis and efficacy evaluation scale.Methods TCM guideline standards of insomnia,textbooks and journals over the years were retrieved,the information of TCM syndromes,syndrome elements and symptoms was extracted,the guideline textbook and journal database were established,and descriptive statistics,association rules,systematic clustering,factor analysis,potential categories and implicit structure analysis were carried out.Results Totally 116 guide standards and textbooks over the years were included,and 454 articles of journals were included.The high-frequency symptoms accounted for≥3%of the guide textbooks and journal databases were 87 and 79 categories,respectively,and the cumulative proportion was 87.48%and 87.75%,respectively.According to the analysis results,five common TCM syndromes and their characteristic symptom classification of insomnia were finally deduced.According to the frequency/person time distribution,they were heart and spleen deficiency syndrome,yin deficiency and fire hyperactivity syndrome,liver fire disturbing heart syndrome,phlegm heat disturbing heart syndrome,heart and gallbladder qi deficiency syndrome.Conclusion There are five common TCM syndromes of insomnia,and the characteristic symptoms of each TCM syndrome provide a reference source for the theoretical framework of syndrome diagnosis and efficacy evaluation scale and the establishment of item pool.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

Allergen-specific immunotherapy（AIT） remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis（AR）. Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group（CRRCG） convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
Humans ; Allergens/immunology* ; China ; Consensus ; Desensitization, Immunologic ; Immunoglobulin E ; Quality of Life ; Rhinitis, Allergic/therapy* ; Treatment Outcome ; East Asian People

Buyang Huanwu Decoction(BYHWD), as one of the classic formulas in traditional Chinese medicine(TCM) for the treatment of cerebral ischemic stroke(CIS), has demonstrated definite effects in clinical practice. However, the material basis and mechanism of treatment have not been systematically elucidated. This study employed network pharmacology and molecular docking to analyze the potential targets and mechanisms of blood-and brain-penetrating active components of BYHWD in reducing cell apoptosis in CIS. Cell experiments were then carried out to validate the prediction results. In the experiments, five active components including hydroxysafflor yellow A( HSYA), tetramethylpyrazine( TMP), astragaloside Ⅳ( AS-Ⅳ), amygdalin( AMY), and paeoniflorin(PF) were selected to explore the pharmacological effects of BYHWD. HT22 cells were treated with BYHWD, and the cell counting kit-8(CCK-8) method was employed to examine the toxic and side effects of BYHWD. A cell model of oxygen-glucose deprivation/reoxygenation( OGD/R) was constructed, with apoptosis and pyroptosis as the main screening indicators. The levels of lactate dehydrogenase(LDH) and glutathione(GSH) were measured to assess the cell membrane integrity. Flow cytometry was employed to detect apoptosis, and the activities of caspase-3 and caspase-1 were measured to clarify the status of apoptosis and pyroptosis. ELISA was employed to determine the levels of interleukin(IL)-1β and IL-18 to confirm pyroptosis. HSYA and AMY were identified in this study as the active components regulating apoptosis and pyroptosis. TUNEL was employed to detect the apoptosis rate, and Western blot was employed to determine the expression levels of apoptosis-related proteins B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), and caspase-3, which confirmed that the anti-apoptotic effect of the combined component group was superior to that of the single component groups. The molecular docking results revealed strong binding affinity of HSYA and AMY with SDF-1α and CXCR4.AMD3100, a selective antagonist of CXCR4, was then used for intervention. The results of Western blot showed alterations in the expression levels of apoptosis-associated proteins, SDF-1α, and CXCR4. In conclusion, HSYA and AMY influence cellular apoptosis by modulating the SDF-1α/CXCR4 signaling cascade.
Drugs, Chinese Herbal/chemistry* ; Apoptosis/drug effects* ; Animals ; Neurons/cytology* ; Mice ; Molecular Docking Simulation ; Cell Line ; Glucose/metabolism* ; Humans ; Neuroprotective Agents/pharmacology*