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 determine the causative agent, clinical manifestations and risk factors for infection during a September 2023 outbreak of acute haemorrhagic conjunctivitis (AHC) in Pak Touch village, Ratanakiri province, Cambodia. Methods: A retrospective case-control study was conducted. Cases were age-matched to controls (1:1), who were randomly selected from the village population. Twenty-one conjunctival samples were analysed using real-time reverse transcription–polymerase chain reaction (RT–PCR). RNA sequencing was additionally performed to identify the causative agent of the outbreak. Logistic regression models were used to identify significant risk factors. Results: A total of 73 cases and 73 controls were included in the analysis. Cases had a median age of 20 years (range: 1–70, mean and standard deviation: 27.7 ± 20.0), and 46.6% (34/73) were male. The overall attack rate was 12.3% (73 cases/594 residents). Clinical presentations included conjunctival hyperaemia (100%), subconjunctival haemorrhage (82.2%, 60), pain and discharge (64.4%, 47 each), eyelid swelling (57.5%, 42) and tearing (54.8%, 40). RT–PCR identified enterovirus in 52.4% (11/21) of conjunctival swabs, with RNA sequencing confirming the coxsackievirus A24 variant as the causative agent in five swabs. Statistical analysis identified significant risk factors, including physical contact with patients with acute haemorrhagic conjunctivitis (adjusted odds ratio [aOR]: 4.42, 95% confidence interval [CI]: 1.90–10.10), frequent eye rubbing (aOR: 4.56, 95% CI: 2.00–10.37) and poor hand hygiene (aOR: 3.70, 95% CI: 1.64–8.43). Discussion: The outbreak of acute haemorrhagic conjunctivitis in Pak Touch village was primarily caused by coxsackievirus A24. Significant risk factors included physical contact with infected individuals, frequent eye rubbing and poor hand hygiene. Effective hygiene measures are crucial to prevent the spread of AHC.

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*

OBJECTIVE: To reveal the molecular basis of knee osteoarthritis (KOA) with Yang deficiency and blood stasis syndrome by analyzing the gene expression profiles in synovial fluid and blood of KOA patients with this syndrome. METHODS: A total of 80 KOA patients were recruited from October 2022 to June 2024, including 40 cases in the non-Yang deficiency and blood stasis group (27 males and 13 females), with an average age of (61.75±3.45) years old;and 40 cases in the Yang deficiency and blood stasis group (22 males and 18 females), with an average age of (62.00±2.76) years old. The levels of body mass index (BMI), high-density lipoprotein (HDL), low-density lipoprotein (LDL), fibrinogen, total cholesterol, and D-dimer were recorded and summarized. Blood and synovial fluid samples from patients were collected for gene expression profile microarray sequencing, and then PCR and immunohistochemistry were used for clinical verification on the patients' synovial fluid and cartilage samples. RESULTS: Logistic regression analysis showed that compared with KOA patients with non-Yang deficiency and blood stasis syndrome, those with Yang deficiency and blood stasis syndrome had increased BMI, LDL, fibrinogen, total cholesterol, and D-dimer, and decreased HDL, with a clear correlation between the two groups. There were 562 differential genes in the blood, among which 322 were up-regulated and 240 were down-regulated;755 differential genes were found in the synovial fluid, with 350 up-regulated and 405 down-regulated. KEGG signaling pathway analysis of synovial fluid revealed changes in lipid metabolism-related pathways, including cholesterol metabolism, fatty acid metabolism, and PPARG signaling pathway. Analysis of the involved differential genes identified 6 genes in synovial fluid that were closely related to lipid metabolism, namely LRP1, LPL, ACOT6, TM6SF2, DGKK, and PPARG. Subsequently, PCR and immunohistochemical verification were performed using synovial fluid and cartilage samples, and the results were consistent with those of microarray sequencing. CONCLUSION This study explores the clinical and genomic correlation between traditional Chinese medicine syndromes and knee osteoarthritis from the perspective of lipid metabolism, and proves that abnormal lipid metabolism is closely related to KOA with Yang deficiency and blood stasis syndrome from both clinical and basic aspects.
Humans ; Male ; Female ; Middle Aged ; Synovial Fluid/metabolism* ; Osteoarthritis, Knee/metabolism* ; Yang Deficiency/complications* ; Aged

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.

Transmembrane protein 33(TMEM33)is up-regulated in the majority of cancers.To change the expression of TMEM33 can significantly affect the proliferation,migration,and invasion of renal and cervical cancer cells.Its mechanisms of action may involve four aspects:1)participation in lipid metabolism;2)regu-lation of endoplasmic reticulum;3)regulation of intracellular calcium homeostasis;4)participation in angio-genesis.

Objective This study aimed to explore the expression pattern of transmembrane protein 33(TMEM33)in lung adenocarcinoma and its correlation with clinical pathological features.Methods Bioinformatics tools and public databases(e.g.,TCGA and GEO)were used to analyze TMEM33 expression data in lung cancer.Then,immunoblotting and real-time quantitative PCR were performed to detect TMEM33 protein and mRNA levels in four cell lines.Immunofluorescence and immunohistochemistry were also used to assess TMEM33 expression and localization in lung adenocarcinoma and normal lung tissue samples.Results Bioinformatics analysis revealed higher TMEM33 expression in lung adenocarcinoma than in normal lung tissue(P＜0.05)and a significant correlation between TMEM33 and SLC30A9 expression(P＜0.0001).Logistic regression analysis indicated an association between TMEM33 expression and tumor T stage(OR=0.48,P=0.044).Experimental results showed higher TMEM33 protein(P＜0.01)and mRNA(P＜0.001)levels in lung adenocarcinoma cell lines than in normal lung epithelial cells.Similarly,TMEM33 protein(P＜0.05)and mRNA(P＜0.01)levels were higher in lung adenocarcinoma tissues than in adjacent tissues.Immunohistochemistry confirmed high TMEM33 expression in lung adenocarcinoma tissues.Conclusion TMEM33 is highly expressed in lung adenocarcinoma,associated with malignancy and T stage,and may be a potential prognostic and therapeutic target.

Objective:To prepare the anti-programmed death-ligand 1 (PD-L1) nanoantibody P3C8-C3Fab by ligating with C3Fab and to investigate its role in plasma half-life.Methods:The C3Fab peptide derived from protein G was molecularly fused with the nanobody P3C8 by DNA recombination technology. The nanoantibody P3C8-C3Fab was inducibly expressed and purified in the E. coli BL21 strain, and the binding of it to PD-L1 protein, mouse IgG, and PD-L1-expressing tumor cells was detected by enzyme-linked immunosorbent assay (ELISA). The residual P3C8-C3Fab was detected in mouse serum at different times using double-antibody sandwich ELISA to assess the prolongation of the plasma half-life of PD-L1 nanobodies by C3Fab. Results:The nanoantibody P3C8-C3Fab was successfully constructed, and it could efficiently express itself in soluble form in BL21. The purified NbP3C8-C3Fab protein was obtained with a mass fraction of about 90% at a yield of 7.18 mg/L. The affinity of P3C8-C3Fab for PD-L1 protein and mouse IgG gradually increased with increasing mass concentration and showed a concentration correlation. The binding of P3C8-C3Fab to lung cancer A549 cells showed a concentration correlation. The concentration standard curve of P3C8-C3Fab in mouse serum showed a typical S-shape with a concentration correlation. The plasma half-life of P3C8 was only 0.44 h, while the plasma half-life of P3C8-C3Fab was 21.27-fold higher, up to 9.36 h.Conclusions:The linkage of C3Fab to the nanobodies of P3C8 can significantly prolong the plasma half-life of P3C8, which is valuable for the improvement of in vivo nanobody effects.

Background ¹³⁷Cs in atmospheric aerosol is the product of past nuclear weapon tests and nuclear accidents. When ¹³⁷Cs is released into the atmosphere, it will deposit in dry land and marine environment, causing pollution of soil surface, water, agricultural products, and animal byproducts, and affecting public health. Objective To identify the variation pattern of ¹³⁷Cs activity concentration in aerosol and its correlation with dust concentration in Beijing area from 2017 to 2020. Methods A total of 958 aerosol samples were collected from November 1, 2017 to June 30, 2020 in Beijing with a high volume air sampler at a sampling flow rate about 600 m³·h⁻¹ and a collection time for each sample about 24 h. The activity concentration of ¹³⁷Cs in the aerosol samples was determined with a low-background high-purity germanium γ spectrometer. The dust concentration was calculated using the difference in the mass of the aerosol filter before and after sampling. The detection rate of ¹³⁷Cs and dust concentration in different seasons were compared. Spearman rank correlation test was used to analyze the correlation between ¹³⁷Cs activity concentration and dust concentration. Results From 2017 to 2020, the ¹³⁷Cs activity concentrations of 33 from 958 aerosol samples in Beijing were above the minimum detectable activityconcentration, the overall detection rate of ¹³⁷Cs was 3.4%, and the activity concentration ranged from 1.86 to 45.53 μBq·m⁻³, with a median value of 4.85 μBq·m⁻³. The detection rate of ¹³⁷Cs was highest in spring, followed by autumn, and lowest in winter and summer (8.4%, 3.0%, 1.1%, and 0.5%, respectively). The dust concentration ranged from 0.03 to 1.55 mg·m⁻³, with an average value of 0.18 mg·m⁻³. There was a statistically significant difference in the dust concentrations in spring, summer, autumn, and winter (F=45.51, P<0.05), and the highest value was 0.24 mg·m⁻³ in spring (P<0.05). The ¹³⁷Cs activity concentration was positively correlated with the dust concentration (P<0.05). Conclusion The ¹³⁷Cs activity concentration in aerosol in Beijing from 2017 to 2020 fluctuates within the range of background level, and its activity concentration is highest in spring, followed autumn, and lowest in summer and winter.