Objective To establish a method for simultaneous determination of four high-molecular-weight thiol derivatives (TDs) in workplace air by gas chromatography. Methods The four kinds of vapor-phase macromolecular TDs (1-pentanethiol, 1-hexanethiol, 1-benzyl mercaptan, and n-octanethiol) in the workplace air were collected using the GDH-1 air sampling tubes, desorbed with anhydrous ethanol, separated on a DB-FFAP capillary column, and determined by flame ionization detector. Results The quantitation range of the four TDs was 0.30-207.37 mg/L, with the correlation coefficients greater than 0.999 00. The minimum detection mass concentrations and minimum quantitation mass concentrations were 0.18-0.32 and 0.60-1.05 mg/m³, respectively (both calculated based on the 1.5 L sample and 3.0 mL desorption solvent). The mean desorption efficiencies ranged from 87.07% to 103.59%. The within-run and between-run relative standard deviations were 1.92%-8.22% and 1.89%-8.45%, respectively. The samples can be stored at room temperature or 4 ℃ for three days and up to 7 days at -18 ℃. Conclusion This method is suitable for the simultaneous determination of four vapor-phase TDs in workplace air.

Objective To analyze the trend of global cellulitis disease burden from 1990 to 2019, and to provide a theoretical basis for the prevention and control of cellulitis disease. Methods The Global Burden of Disease 2021 (GBD2021) data were collected, and data on the incidence, mortality, and disability-adjusted life year (DALY) of cellulitis were analyzed for each country worldwide. The estimated annual percentage change (EAPC) and age-standardized rate (ASR) were used to estimate the trend change of cellulitis from 1990 to 2021. Results The global burden of cellulitis increased significantly in 2021, with 55.96 million cases, 28.9 million deaths and 876.1 million DALYs, respectively. Incidence and mortality rates were generally higher in males than in females. The incidence and DALYs were higher in high SDI regions, with the highest burden observed in South Asia. In contrast, East Asia exhibited the lowest burden and demonstrated a declining trend. There were significant differences between countries, with India having the highest prevalence, the United States having the highest incidence, and Bahrain having the fastest growing rate.In 2021, China had the lowest age-standardised incidence of cellulitis in the world and the fastest declining age-standardised incidence and age-standardised DALYs. Conclusion The global disease burden of cellulitis is increasing from 1990-2021, and cellulitis remains an an important global public health problem. Targeted preventive meausres should be taken in areas with different economical levels. Men, middle-aged and elderly people, and newborns are the key groups in need of attention and health education.

OBJECTIVE: This study aims to elucidate the therapeutic potential of osthole for the treatment of atopic dermatitis (AD), focusing on its ability to alleviate chronic pruritus (CP) and the underlying molecular mechanisms. METHODS: In this study, we investigated the anti-inflammatory effects of osthole in both a 2,4-dichloronitrobenzene (DNCB)-induced AD mouse model and tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) stimulated huma immortalized epidermal (HaCaT) cells. The anti-itch effect of osthole was specifically assessed in the AD mouse model. Using methods such as hematoxylin and eosin (HE) staining, enzyme-linked immunosorbent assay (ELISA), western blot (WB), quantitative real-time PCR (qRT-PCR), and immunofluorescence staining. RESULTS: Osthole improved skin damage and clinical dermatitis scores, reduced scratching bouts, and decreased epidermal thickness AD-like mice. It also reduced the levels of interleukin (IL)-31 and IL-31 receptor A (IL-31 RA) in both skin tissues and HaCaT cells. Furthermore, Osthole suppressed the protein expression levels of phosphor-p65 (p-p65) and phosphor-inhibitor of nuclear factor kappa-Bα (p-IκBα). Meanwhile, it increased the protein expression levels of peroxisome proliferator-activated receptor α (PPARα) and PPARγ in HaCaT cells. CONCLUSION These findings indicated that osthole effectively inhibited CP in AD by activating PPARα, PPARγ, repressing the NF-κB signaling pathway, as well as the expression of IL-31 and IL-31 RA.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.

Objective To develop a solvent desorption-gas chromatography method for quantifying malononitrile in workplace air. Methods Malononitrile in workplace air was collected using a silica gel tube and desorbed with methanol. Separation was performed using DB-FFAP capillary column, and detection was performed by hydrogen flame ionization detector. Results The linear ranges of malononitrile were 4.00-600.00 mg/L, with the correlation coefficient of 0.999 92. The detection limit was 0.54 mg/L. The minimum detection concentration was 0.36 mg/m³ (based on a collected air volume of 1.5 L). The average desorption efficiency was 95.0%-101.0%. The within-run and between-run relative standard deviations were 0.9%-5.3% and 1.0%-6.8%, respectively. The sampling efficiency was 100.0%. The samples were stable at 4 ℃ for at least 14 days. Conclusion The solvent desorption-gas chromatography method established in this study for the determination of malononitrile in workplace air is simple to use, with high accuracy and good precision, and is suitable for the determination of malononitrile in workplace air.

Computational analysis can accurately detect drug-gene interactions(DGIs)cost-effectively.However,transductive learning models are the hotspot to reveal the promising performance for unknown DGIs(both drugs and genes are present in the training model),without special attention to the unseen DGIs(both drugs and genes are absent in the training model).In view of this,this study,for the first time,proposed an inductive learning-based model for the precise identification of unseen DGIs.In our study,by integrating disease nodes to avoid data sparsity,a multi-relational drug-disease-gene(DDG)graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions.Following the extraction of graph features by utilizing graph embedding algorithms,our next step was the retrieval of the attributes of individual gene and drug nodes.In this way,a hybrid feature charac-terization was represented by integrating graph features and node attributes.Machine learning(ML)models were built,enabling the fulfillment of transductive predictions of unknown DGIs.To realize inductive learning,this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights,enabling inductive predictions for the unseen DGIs.Consequently,the final model was superior to existing models,with significant improvement in predicting both external unknown and unseen DGIs.The practical feasibility of our model was further confirmed through case study and molecular docking.In summary,this study establishes an efficient data-driven approach through the proposed modeling,suggesting its value as a promising tool for accelerating drug discovery and repurposing.

BACKGROUND:Kidney deficiency is the main pathogenesis of osteoporosis.To study the relationship between the two major syndrome types of kidney deficiency,Kidney-Yang deficiency and Kidney-Yin deficiency,is beneficial for the development of clinical diagnosis and treatments based on the combination of disease and syndrome. OBJECTIVE:To evaluate the biomechanical differences of the rat femurs with Kidney-Yang deficiency and Kidney-Yin deficiency caused by Yougui pills,and to demonstrate the scientific efficacy of medication based on the combination of disease and syndrome in osteoporosis from a biomechanical perspective. METHODS:The bilateral ovaries of 60 female Sprague-Dawley rats were surgically removed to establish an ovariectomized osteoporosis model.At 10 weeks after modeling,all the rats were randomly divided into a Kidney-Yang deficiency group(n=30)and a Kidney-Yin deficiency group(n=30).Rats with Kidney-Yang deficiency were given gluteal intramuscular injection of hydrocortisone,while rats with Kidney-Yin deficiency were orally administered with thyroid tablet suspension,once a day,for 14 consecutive days.After successful modeling,20 rats in each group were given a suspension of Yougui pills by gavage once a day for 12 consecutive weeks and the remaining 10 rats were used as the control group without intervention.After gavage,the microstructural parameters of the bone were measured using Micro-CT scanning.Three-point bending,finite element simulation,femoral head compression,and surface indentation distribution experiments of the femurs were performed on a mechanical testing machine. RESULTS AND CONCLUSION:Micro-CT revealed that the femoral bone density,bone volume fraction,bone surface density,trabecular number,and trabecular separation were improved in the Kidney-Yin deficiency+Yougui pills group compared with the Kidney-Yin deficiency group(P＜0.05);the femoral bone volume fraction,bone surface density,trabecular number,and trabecular thickness were improved in the Kidney-Yang deficiency+Yougui pills group compared with the Kidney-Yang deficiency group(P＜0.05).The three-point bending experiment showed that the femur elastic modulus,maximum bending strength and bending fracture strength were decreased(P＜0.05)and toughness was increased(P＜0.05)in the Kidney-Yang deficiency+Yougui pills group compared with the Kidney-Yang deficiency group.Finite element simulation showed that Yougui pills could significantly improve the bending resistance of the femurs in the Kidney-Yang deficiency group,but had no significant effect on the Kidney-Yin deficiency group.The femoral head compression experiments showed that Yougui pills could enhance the ability of the femoral head to resist deformation in the Kidney-Yang deficiency group,but there was no significant difference in the effect of Yougui pills on the surface properties of the femoral head in the Kidney-Yin deficiency group and the Kidney-Yang deficiency group.To conclude,Yougui pills can significantly enhance the biomechanical properties of the osteoporotic bones with Kidney-Yang deficiency,but have no significant effect on the osteoporotic bone with Kidney-Yin deficiency.

Objective To understand the status quo of job embeddedness and turnover intention of hospital nurses,and to explore their correlation.Methods Using convenient sampling method,we selected 538 nursing workers from 8 tertiary hospi-tals in Guangzhou,and conducted an electronic questionnaire survey with job embeddedness Scale and Turnover Intention Scale.Results The total average score of job embeddedness was(3.41±1.26),and the total average score of turnover intention was(2.66±0.94).There was a negative correlation between job embeddedness and turnover intention(r =-0.060,P＞0.05).Conclusion The scores of job embeddedness and turnover intention of hospital nurses are at the middle level,and job embed-dedness is negatively correlated with the total average score of turnover intention.It is suggested that the management mode of hospital nurses should be standardized,the legitimate rights and interests of nurses should be guaranteed,the construction of pro-fessional certification system should be promoted,the nurses'positive job embeddedness should be promoted,the hospital nurs-ing staff should be stabilized,and the satisfaction of nursing service should be improved.

AIM To investigate the protective effects and the mechanism of corosolic acid on doxorubicin-induced cardiotoxicity in H9c2 cardiomyocytes.METHODS To screen and determine the effective concentration of corosolic acid,the injury models of H9c2 cardiomyocytes established by 1 μmol/L doxorubicin were exposed to 24 h different concentrations of corosolic acid,followed by detections of their cell activity by MTT method;their cell apoptosis morphology by Hoechst 33342 staining method;their cell apoptosis rate by Annexin V-FITC/PI double staining method;their intracellular ROS level by DCFH-DA probe;their intracellular iron level by iron ion colorimetry;and their protein expressions of Bax,Bcl-2,cleaved-caspase3,Nrf2,GPX4 and Ptgs2 by Western blot.RESULTS Upon the doxorubicin-induced injury models of H9c2 cardiomyocytes,corosolic acid improved their viability and survival rate(P<0.05),decreased their levels of ROS and Fe2+ and the apoptosis rate(P<0.05),up-regulated the protein expressions of Bcl-2,Nrf2 and GPX4(P<0.05),and down-regulated the protein expressions of Bax,cleved-caspase 3 and Ptgs2(P<0.05).CONCLUSION Corosolic acid can inhibit the ROS level and apoptosis of doxorubicin-induced injury models of H9c2 cardiomyocytes,and the iron death as well via activating Nrf2/GPX4 pathway.

Biotoxins, which include bacterial, fungal, marine, plant, and animal toxins, are widespread in living and occupational environments, posing potential threats to human health. Rapid detection of biotoxins in blood is crucial for preventing health hazards and enabling timely disease diagnosis and treatment. Biosensors and immunoassay technologies have critical advantages in the rapid detection of biotoxins in blood. Common biosensors, such as surface plasmon resonance biosensors and fluorescent biosensors, enhance sensitivity and reduce detection limits through signal amplification. Common immunoassay methods, such as colloidal gold immunochromatography, fluorescence immunochromatography, and chemiluminescence immunoassay, improve detection efficacy and sensitivity through specific antibody-antigen binding and nanotechnology. However, current rapid detection technologies of bitoxins in blood face challenges such as matrix interference and insufficient specificity, and they fall short in high-throughput detection of multiple toxins simultaneously. Future developments should focus on improving sample pretreatment, innovating signal amplification methods, enhancing specificity on recognition of elements, and designing portable detection devices and high-throughput platforms for simultaneous toxin analysis. These advancements aim to improve the sensitivity and reliability of detection methods, providing more accurate and convenient solutions for biotoxin detection in blood.