Ciprofibrate increases plasma concentration of platelet-derived growth factor AB in patients with advanced atherosclerosis and hyperlipidemia independently of its hypolipidemic effects

Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning

Background

Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. Discovering platelet-related biomarkers, developing diagnostic models, and screening antiplatelet drugs are crucial for IS diagnosis and treatment.

Methods and results

Combining and normalizing GSE16561 and GSE22255 datasets identified 1,753 upregulated and 1,187 downregulated genes. Fifty-one genes in the platelet-related module were isolated using weighted gene co-expression network analysis (WGCNA) and other analyses, including 50 upregulated and one downregulated gene. Subsequent enrichment and network analyses resulted in 25 platelet-associated genes and six diagnostic markers for a risk assessment model. This model's area under the ROC curve outperformed single genes, and in the peripheral blood of the high-risk group, immune infiltration indicated a higher proportion of CD4, resting CD4 memory, and activated CD4 memory T cells, along with a lower proportion of CD8 T cells in comparison to the low-risk group. Utilizing the gene expression matrix and the CMap database, we identified two potential drugs for IS. Finally, a rat MACO/R model was used to validate the diagnostic markers' expression and the drugs' predicted anticoagulant effects.

Conclusion

We identified six IS platelet-related biomarkers (APP, THBS1, F13A1, SRC, PPBP, and VCL) for a robust diagnostic model. The drugs alpha-linolenic acid and ciprofibrate have potential antiplatelet effects in IS. This study advances early IS diagnosis and treatment.

Aptamer-modified gold nanoparticles for colorimetric determination of platelet-derived growth factors and their receptors

We have developed a highly specific sensing system for platelet-derived growth factors (PDGFs) and platelet-derived growth factor receptors (PDGFR) that uses gold nanoparticles (GNPs). We synthesized GNPs modified with an aptamer (Apt-GNPs) that is specific to PDGFs and used them to detect PDGFs by monitoring the changes in the color and extinction of the Apt-GNPs that occur as a result of aggregation. The color of the Apt-GNPs changes from red to purple at low concentrations (<400 nM), but changes only slightly at higher concentrations (>400 nM). We found that the sensitivity of the Apt-GNPs for the three PDGFs is highly salt-dependent, with an optimum condition of 200 mM NaCl. We obtained biphasic curves when plotting of the ratios of the extinction coefficients of the Apt-GNPs at 650 and 530 nm against the concentrations of PDGF-AA at various concentrations of Apt-GNPs. The linear ranges of the increases and decreases in this extinction ratio are 2.5-10 and 10-20 nM, respectively, for 0.42 nM Apt-GNPs and 25-75 and 75-200 nM, respectively, for 8.4 nM Apt-GNPs. When using 8.4 nM Apt-GNPs, the corresponding linear ranges of the increases and decreases in this extinction ratio are 15-100 and 100-400 nM, respectively, for PDGF-AB and 35-150 and 150-400 nM, respectively, for PDGF-BB. In addition, we have developed a homogeneous assay to detect the PDGF receptor-beta (PDGFR-beta) at concentrations as low as 3.2 nM, on the basis of the competition between the Apt-GNPs and PDGFR-beta for PDGF-BB. The results we present in this paper imply that there are practical applications of Apt-GNPs in protein analysis and cancer diagnosis.