35 research outputs found

    Bioinformatics analysis of the potential mechanisms of Alzheimer’s disease induced by exposure to combined triazine herbicides

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    The development of Alzheimer’s disease (AD) is promoted by a combination of genetic and environmental factors. Notably, combined exposure to triazine herbicides atrazine (ATR), simazine (SIM), and propazine (PRO) may promote the development of AD, but the mechanism is unknown. To study the molecular mechanism of AD induced by triazine herbicides. Differentially expressed genes (DEGs) of AD patients and controls were identified. The intersectional targets of ATR, SIM, and PRO for possible associations with AD were screened through network pharmacology and used for gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis. The binding potentials between the core targets and herbicides were validated by molecular docking and molecular dynamics. A total of 1,062 DEGs were screened between the AD patients and controls, which identified 148 intersectional targets of herbicides causing AD that were screened by network pharmacology analysis. GO and KEGG enrichment analysis revealed that cell cycling and cellular senescence were important signalling pathways. Finally, the core targets EGFR, FN1, and TYMS were screened and validated by molecular docking and molecular dynamics. Our results suggest that combined exposure to triazine herbicides might promote the development of AD, thereby providing new insights for the prevention of AD.</p

    Relative combined effect of NHV and recovery over time (a) and individual effects of NHV-E and NHV-L and recovery over time (b).

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    <p>Relative combined effect of NHV and recovery over time (a) and individual effects of NHV-E and NHV-L and recovery over time (b).</p

    Baseline characteristics of the NHV study groups.

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    <p>SD = Standard Deviation; BI = Barthel Index. <sup>‡</sup>F–test for metric; Chi–square for categorical variables. *Significant difference between NHV-E and Controls only, according to post hoc tests (Scheffé), <sup>†</sup>T-test.</p

    Sensitivity analysis: estimated change in NHV rehabilitation effect based on different dropout imputation scenarios.

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    <p>Legend: Scenario A  =  no dropouts incurred any change in Barthel Index; Scenario B  =  all dropouts decreased by ten points in Barthel Index at follow up; Scenario C  =  dropouts from the intervention groups did not change between baseline and follow up, while dropouts from the control group increased by ten points in Barthel Index; Complete cases  =  model estimation with valid cases only (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053995#pone-0053995-t002" target="_blank">Table 2</a>). Error bars represent 95% confidence intervals.</p

    Parameter estimates for Barthel Index (BI) based on the three-level Tobit model.

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    <p>Log Likelihood: −3415.094; Bayesian Information Criterion (BIC): 6947.956.</p><p>SE = standard error, z = standardized coefficient; EQ = earthquake; MP = point of measurement; cov = covariance *p<0.05, **p<0.01, *** p<0.001.</p

    Marginal predictions of Barthel Index mean scores for the NHV study groups at time points based on the three-level Tobit model.

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    <p>Marginal predictions of Barthel Index mean scores for the NHV study groups at time points based on the three-level Tobit model.</p

    Preoperative and postoperative audiograms.

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    <p>(<b>a</b>) ANCI_01, preoperative and 10 months postoperative; (<b>b</b>) ANCI_04, preoperative and 7 months postoperative; (<b>c</b>) ANCI_05, preoperative and 48 months postoperative; (<b>d</b>) ANCI_09, preoperative and 11 months postoperative; (<b>e</b>) ANCI_10 preoperative and 12 months postoperative.</p
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