Mathematical model explains differences in Omicron and Delta SARS-CoV-2 dynamics in Caco-2 and Calu-3 cells.

Within-host infection dynamics of Omicron dramatically differs from previous variants of SARS-CoV-2. However, little is still known about which parameters of virus-cell interplay contribute to the observed attenuated replication and pathogenicity of Omicron. Mathematical models, often expressed as systems of differential equations, are frequently employed to study the infection dynamics of various viruses.

Development of a novel mathematical model that explains SARS-CoV-2 infection dynamics in Caco-2 cells.

Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for data, which are less noisy and more reproducible.

Alterations in SARS-CoV-2 Omicron and Delta peptides presentation by HLA molecules.

The T-cell immune response is a major determinant of effective SARS-CoV-2 clearance. Here, using the recently developed T-CoV bioinformatics pipeline (https://t-cov.hse.

ExhauFS: exhaustive search-based feature selection for classification and survival regression.

Feature selection is one of the main techniques used to prevent overfitting in machine learning applications. The most straightforward approach for feature selection is an exhaustive search: one can go over all possible feature combinations and pick up the model with the highest accuracy. This method together with its optimizations were actively used in biomedical research, however, publicly available implementation is missing.

Low expression of CD24 is associated with poor survival in colorectal cancer.

In this study we analyzed expression of CD24 in a cohort of colorectal cancer patients using immunohistochemistry staining of CD24. We found a significant association between absence or low expression of CD24 (10% of membranous and 55% of cytoplasmic staining) and shortened patient survival. Protein localization played a crucial role in the prognosis: membranous form was the major and prognostic one in primary tumors, while cytoplasmic expression was elevated in liver metastases compared to the primary tumors and contained prognostic information.

Hypoxia-Induced miR-148a Downregulation Contributes to Poor Survival in Colorectal Cancer.

Hypoxia is an extensively investigated condition due to its contribution to various pathophysiological processes including cancer progression and metastasis formation. MicroRNAs (miRNAs) are well-known post-transcriptional gene expression regulators. However, their contribution to molecular response to hypoxia is highly dependent on cell/tissue types and causes of hypoxia.

miRGTF-net: Integrative miRNA-gene-TF network analysis reveals key drivers of breast cancer recurrence.

Analysis of regulatory networks is a powerful framework for identification and quantification of intracellular interactions. We introduce miRGTF-net, a novel tool for construction of miRNA-gene-TF networks. We consider multiple transcriptional and post-transcriptional interaction types, including regulation of gene and miRNA expression by transcription factors, gene silencing by miRNAs, and co-expression of host genes with their intronic miRNAs.

Association of HLA Class I Genotypes With Severity of Coronavirus Disease-19.

Human leukocyte antigen (HLA) class I molecules play a crucial role in the development of a specific immune response to viral infections by presenting viral peptides at the cell surface where they will be further recognized by T cells. In the present manuscript, we explored whether HLA class I genotypes can be associated with the critical course of Coronavirus Disease-19 by searching possible connections between genotypes of deceased patients and their age at death. HLA-A, HLA-B, and HLA-C genotypes of = 111 deceased patients with COVID-19 (Moscow, Russia) and = 428 volunteers were identified with next-generation sequencing.

Cumulative prognostic power of laminin genes in colorectal cancer.

Background: Laminins are a major family of extracellular matrix proteins and the main component of basement membranes. Laminins are involved in many if not all stages of cancer progression, and expression of laminin genes has prognostic value in various types of cancer, including colorectal. Only single laminin genes or components of a single laminin trimer with significant differential expression have been regarded as potential biomarkers to date.

Comprehensive network of miRNA-induced intergenic interactions and a biological role of its core in cancer.

MicroRNAs (miRNAs) are a family of short noncoding RNAs that posttranscriptionally regulate gene expression and play an important role in multiple cellular processes. A significant percentage of miRNAs are intragenic, which is often functionally related to their host genes playing either antagonistic or synergistic roles. In this study, we constructed and analyzed the entire network of intergenic interactions induced by intragenic miRNAs.

Plasma Level of hsa-miR-619-5p microRNA Is Associated with Prostatic Cancer Dissemination beyond the Capsule.

Profiles of circulating microRNA in the plasma of patients with prostate cancer with pathomorphological stages pT2, pT3, and pT4 are analyzed. The level of circulating microRNA hsa-miR-619-5p is elevated in patients with extracapsular spreading of the tumor, increasing significantly from stage pT2 to stage pT4.

Changes in the Level of Circulating hsa-miR-297 and hsa-miR-19b-3p miRNA Are Associated with Generalization of Prostate Cancer.

We performed diagnostic classification of plasma specimens from patients with non-metastatic and metastatic prostate cancer based on pairs of miRNA that have no individual diagnostic significance. Of 230 miRNA detected in plasma specimens, 3 pairs were diagnostically significant. The miRNA pair hsa-miR-19b-3p and hsa-miR-297 demonstrated highest sensitivity and specificity.

Instrumental tactile diagnostics in robot-assisted surgery.

Background: Robotic surgery has gained wide acceptance due to minimizing trauma in patients. However, the lack of tactile feedback is an essential limiting factor for the further expansion. In robotic surgery, feedback related to touch is currently kinesthetic, and it is mainly aimed at the minimization of force applied to tissues and organs.

Automated Detection of Heterogeneity in Medical Tactile Images.

Artificial tactile sensing is a capability important for many applications and, in particular, for endoscopic surgery. A recently developed Medical Tactile Endosurgical Complex (MTEC) that is a certified and commercially available product is an efficient tool that provides such a capability. Currently the analysis of intraoperative tactile images that are registered and visualized by MTEC is performed manually by a surgeon.

Highly informative marker sets consisting of genes with low individual degree of differential expression.

Genes with significant differential expression are traditionally used to reveal the genetic background underlying phenotypic differences between cancer cells. We hypothesized that informative marker sets can be obtained by combining genes with a relatively low degree of individual differential expression. We developed a method for construction of highly informative gene combinations aimed at the maximization of the cumulative informative power and identified sets of 2-5 genes efficiently predicting recurrence for ER-positive breast cancer patients.