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https://www.selleckchem.com/products/eeyarestatin-i.html Numerous studies have concentrated on high-dose radiation exposed accidentally or through therapy, and few involve low-dose occupational exposure, to investigate the correlation between low-dose ionizing radiation and changing hematological parameters among medical workers. Using a prospective cohort study design, we collected health examination reports and personal dose monitoring data from medical workers and used Poisson regression and restricted cubic spline models to assess the correlation between changing hematological parameters and cumulative radiation dose and determine the dose-response relationship. We observed that changing platelet of 1265 medical workers followed up was statistically different among the cumulative dose groups (P = 0.010). Although the linear trend tested was not statistically significant (P = 0.258), the non-linear trend tested was statistically significant (P = 0.007). Overall, there was a correlation between changing platelets and cumulative radiation dose (a change ation for a short period of time might have increased first and then decreased platelets, and there was a dose-response relationship between the cumulative radiation dose and platelets changing. Due to continued advances in sequencing technology, the limitation in understanding biological systems through an "-omics" lens is no longer the generation of data, but the ability to analyze it. Importantly, much of this rich -omics data is publicly available waiting to be further investigated. Although many code-based pipelines exist, there is a lack of user-friendly and accessible applications that enable rapid analysis or visualization of data. GECO (Gene Expression Clustering Optimization; http//www.theGECOapp.com ) is a minimalistic GUI app that utilizes non-linear reduction techniques to rapidly visualize expression trends in many types of biological data matrices (such as bulk RNA-seq or proteomics). The required inp

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