mRNA stability and mA are major determinants of subcellular mRNA localization in neurons.

For cells to perform their biological functions, they need to adopt specific shapes and form functionally distinct subcellular compartments. This is achieved in part via an asymmetric distribution of mRNAs within cells. Currently, the main model of mRNA localization involves specific sequences called "zipcodes" that direct mRNAs to their proper locations.

Massively parallel identification of mRNA localization elements in primary cortical neurons.

Cells adopt highly polarized shapes and form distinct subcellular compartments in many cases due to the localization of many mRNAs to specific areas, where they are translated into proteins with local functions. This mRNA localization is mediated by specific cis-regulatory elements in mRNAs, commonly called 'zipcodes'. Although there are hundreds of localized mRNAs, only a few zipcodes have been characterized.

Multi-Omics Alleviates the Limitations of Panel Sequencing for Cancer Drug Response Prediction.

Comprehensive genomic profiling using cancer gene panels has been shown to improve treatment options for a variety of cancer types. However, genomic aberrations detected via such gene panels do not necessarily serve as strong predictors of drug sensitivity. In this study, using pharmacogenomics datasets of cell lines, patient-derived xenografts, and ex vivo treated fresh tumor specimens, we demonstrate that utilizing the transcriptome on top of gene panel features substantially improves drug response prediction performance in cancer.

Identifying tumor cells at the single-cell level using machine learning.

Tumors are complex tissues of cancerous cells surrounded by a heterogeneous cellular microenvironment with which they interact. Single-cell sequencing enables molecular characterization of single cells within the tumor. However, cell annotation-the assignment of cell type or cell state to each sequenced cell-is a challenge, especially identifying tumor cells within single-cell or spatial sequencing experiments.

European Registry on the management of Helicobacter pylori infection (Hp-EuReg): analysis of 2360 patients receiving first-line therapy in Russia.

Aim: European Registry on the management of Helicobacter pylori infection («Hp-EuReg») - a multicenter prospective observational study initiated by the European Helicobacter and Microbiota Study Group, conducted in 27 European countries in order to evaluate the real clinical practice of diagnosis and treatment of H. pylori and its comparison with international recommendations.

Materials And Methods: The analysis of 2360 patients entered in the register by the Russian centres of «Hp-EuReg» in 2013-2017, who were underwent 1st line eradication therapy.