Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model.

Air pollution has become a significant concern for human health, and its impact on influenza, has been increasingly recognized. This study aims to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza and to confirm a better method for infectious disease surveillance. Spearman correlation coefficient was used to evaluate the correlation between air pollution and the influenza case counts. VIF was used to test for collinearity among selected air pollutants. OLS regression, GWR, and STWR models were fitted to explore the potential spatiotemporal relationship between air pollution and influenza. The R2, the RSS and the AICc were used to evaluate and compare the models. In addition, the DTW and K-medoids algorithms were applied to cluster the county-level time-series coefficients. Compared with the OLS regression and GWR models, STWR model exhibits superior fit especially when the influenza outbreak changes rapidly and is able to more accurately capture the changes in different regions and time periods. We discovered that identical air pollutant factors may yield contrasting impacts on influenza within the same period in different areas of Fuzhou. NO2 and PM10 showed opposite impacts on influenza in the eastern and western areas of Fuzhou during all periods. Additionally, our investigation revealed that the relationship between air pollutant factors and influenza may exhibit temporal variations in certain regions. From 2013 to 2019, the influence coefficient of O3 on influenza epidemic intensity changed from negative to positive in the western region and from positive to negative in the eastern region. STWR model could be a useful method to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza in geospatial processes. The research findings emphasize the importance of considering spatiotemporal heterogeneity when studying the relationship between air pollution and influenza.

N-cystaminylbiguanide MC001 prevents neuron cell death and alleviates motor deficits in the MPTP-model of Parkinson's disease.

Parkinson's disease (PD) is a common neurodegenerative disease characterized by the progressive loss of dopaminergic (DA) neurons in the substantia nigra (SN), which is highly associated with oxidative stress. Antioxidants are therefore considered as potential therapies in PD treatment. In this study, we examined the neuroprotective effect of a cysteamine-based biguanide N-cystaminylbiguanide (MC001) in the MPTP mouse model of PD. The results showed that MC001 prevented neuron cell death and alleviated motor deficits in the MPTP mouse model of PD. Both in vitro and in vivo data indicated that MC001 may exert its neuroprotective effect by alleviating ROS production, suppressing neuroinflammation, and upregulating BDNF expression. Further mechanistic studies revealed that MC001 promoted GSH synthesis by inducing the expression of Glutamate-cysteine ligase catalytic subunit (Gclc) and enhancing the activity of Glutamate-cysteine ligase (Gcl). Our results suggest that MC001 warrants further investigation as a potential candidate for the treatment of PD.

Effect of docetaxel on mechanical properties of ovarian cancer cells.

Docetaxel could inhibit the proliferation of tumor cells by targeting microtubules. The extension of cellular microtubules plays an important role in the invasion and metastasis of tumor cells. This paper aims to study the distribution and mechanical properties of cytoskeletal proteins with low concentration of docetaxel. MTT assay was used to detect the minimum drug activity concentration of docetaxel on SKOV-3 cells, fluorescence staining was used to analyze the distribution of cytoskeleton proteins, scanning electron microscopy(SEM) was used to observe the morphology of single cells, and atomic force microscopy(AFM) was used to determine the microstructure and mechanical properties of cells. The results showed that the IC10 of docetaxel was 1 ng/ml. Docetaxel can effectively inhibit the formation of cell pseudopodia, hinder the indirectness between cells, reduce the cell extension area, and make the cells malformed. In addition, when AFM analyzes the effects of drugs on cell microstructure and mechanical properties, the average cell surface roughness and cell height are positively correlated with the concentration of docetaxel. Especially when the concentration was 100 ng/ml, the adhesion decreased by 37.04% and Young's modulus increased by 1.57 times compared with the control group. This may be because docetaxel leads to microtubule remodeling and membrane protein aggregation, which affects cell microstructure and increases cell strength, leading to significant changes in the mechanical properties of ovarian cells. This is of great significance to the study of the formation mechanism of tumor cell invasion and migration activities mediated by actin.

Computational Study and Modified Design of Selective Dopamine D3 Receptor Agonists.

Dopamine D3 receptor (D3 R) is considered as a potential target for the treatment of nervous system disorders, such as Parkinson's disease. Current research interests primarily focus on the discovery and design of potent D3 agonists. In this work, we selected 40 D3 R agonists as the research system. Comparative molecular field analysis (CoMFA) of three-dimensional quantitative structure-activity relationship (3D-QSAR), structure-selectivity relationship (3D-QSSR), and molecular docking was performed on D3 receptor agonists to obtain the details at atomic level. The results indicated that both the CoMFA model (r(2) = 0.982, q(2) = 0.503, rpred2 = 0.893, SEE = 0.057, F = 166.308) for structure-activity and (r(2) = 0.876, q(2) = 0.436, rpred2 = 0.828, F = 52.645) for structure-selectivity have good predictive capabilities. Furthermore, docking studies on three compounds binding to D3 receptor were performed to analyze the binding modes and interactions. The results elucidate that agonists formed hydrogen bond and hydrophobic interactions with key residues. Finally, we designed six molecules under the guidance of 3D-QSAR/QSSR models. The activity and selectivity of designed molecules have been improved, and ADMET properties demonstrate they have low probability of hepatotoxicity (<0.5). These results from 3D-QSAR/QSSR and docking studies have great significance for designing novel dopamine D3 selective agonists in the future.