Publications by authors named "K V Lepik"

PD-1 inhibitors have shown unconventional response patterns in classic Hodgkin lymphoma (cHL). These include the phenomenon of pseudoprogression, highlighting the need for specialized response criteria such as the LyRIC, which stringened definitions for disease progression with introduction of indeterminate response category. Despite their potential utility, these provisional criteria are currently underutilized and require further refinement through clinical practice data collection.

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Natural selection acts ubiquitously on complex human traits, predominantly constraining the occurrence of extreme phenotypes (stabilizing selection). These constraints propagate to DNA sequence variants associated with traits under selection. The genetic signatures of such evolutionary events can thus be detected via combining effect size estimates from genetic association studies and the corresponding allele frequencies.

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Motivation: Mendelian randomization (MR) is a widely used approach to estimate causal effect of variation in gene expression on complex traits. Among several MR-based algorithms, transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) enables the uses of multiple SNPs as instruments and multiple gene expression traits as exposures to facilitate causal inference in observational studies.

Results: Here we present a Python-based implementation of TWMR and revTWMR.

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Engineered calcium carbonate (CaCO) particles are extensively used as drug delivery systems due to their availability, biological compatibility, biodegradability, and cost-effective production. The synthesis procedure of CaCO particles, however, suffers from poor reproducibility. Furthermore, reducing the size of CaCO particles to <100 nm requires the use of additives in the reaction, which increases the total reaction time.

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Article Synopsis
  • - The study explores the relationship between genetic variations (both common and rare) and their impact on plasma proteins, analyzing data from up to 500 individuals.
  • - Researchers identified a significant number of genetic signals (184 cis and 94 trans) affecting 157 protein traits, with a detailed analysis yielding credible sets for 101 cis and 87 trans signals.
  • - The findings highlight the influence of rare genetic variations and copy number variants (CNVs) on specific protein levels, including their role in inflammatory responses, offering valuable insights into the genetic factors affecting plasma proteins.
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