Publications by authors named "R V Reshetnikov"

14 Publications

A simplified cluster model and a tool adapted for collaborative labeling of lung cancer CT scans.

Comput Methods Programs Biomed 2021 Jul 18;206:106111. Epub 2021 Apr 18.

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Petrovka str., 24, Moscow, 127051, Russia; Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Vavilova str., 44/2, Moscow, 119333, Russia. Electronic address:

Background And Objective: Lung cancer is the most common type of cancer with a high mortality rate. Early detection using medical imaging is critically important for the long-term survival of the patients. Computer-aided diagnosis (CAD) tools can potentially reduce the number of incorrect interpretations of medical image data by radiologists. Datasets with adequate sample size, annotation, and truth are the dominant factors in developing and training effective CAD algorithms. The objective of this study was to produce a practical approach and a tool for the creation of medical image datasets.

Methods: The proposed model uses the modified maximum transverse diameter approach to mark a putative lung nodule. The modification involves the possibility to use a set of overlapping spheres of appropriate size to approximate the shape of the nodule. The algorithm embedded in the model also groups the marks made by different readers for the same lesion. We used the data of 536 randomly selected patients of Moscow outpatient clinics to create a dataset of standard-dose chest computed tomography (CT) scans utilizing the double-reading approach with arbitration. Six volunteer radiologists independently produced a report for each scan using the proposed model with the main focus on the detection of lesions with sizes ranging from 3 to 30 mm. After this, an arbitrator reviewed their marks and annotations.

Results: The maximum transverse diameter approach outperformed the alternative methods (3D box, ellipsoid, and complete outline construction) in a study of 10,000 computer-generated tumor models of different shapes in terms of accuracy and speed of nodule shape approximation. The markup and annotation of the CTLungCa-500 dataset revealed 72 studies containing no lung nodules. The remaining 464 CT scans contained 3151 lesions marked by at least one radiologist: 56%, 14%, and 29% of the lesions were malignant, benign, and non-nodular, respectively. 2887 lesions have the target size of 3-30 mm. Only 70 nodules were uniformly identified by all the six readers. An increase in the number of independent readers providing CT scans interpretations led to an accuracy increase associated with a decrease in agreement. The dataset markup process took three working weeks.

Conclusions: The developed cluster model simplifies the collaborative and crowdsourced creation of image repositories and makes it time-efficient. Our proof-of-concept dataset provides a valuable source of annotated medical imaging data for training CAD algorithms aimed at early detection of lung nodules. The tool and the dataset are publicly available at https://github.com/Center-of-Diagnostics-and-Telemedicine/FAnTom.git and https://mosmed.ai/en/datasets/ct_lungcancer_500/, respectively.
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http://dx.doi.org/10.1016/j.cmpb.2021.106111DOI Listing
July 2021

Re: Controversy in coronaViral Imaging and Diagnostics (COVID).

Clin Radiol 2020 11 22;75(11):871-872. Epub 2020 Aug 22.

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow, Russia.

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http://dx.doi.org/10.1016/j.crad.2020.07.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442928PMC
November 2020

Interaction between thrombin and oligonucleotide RA36 is a two-stage process.

Biochem Biophys Res Commun 2020 02 6;522(4):1037-1040. Epub 2019 Dec 6.

Apto-Pharm Ltd, Kolomensky dr., 13A, 115564, Moscow, Russia; Sechenov First Moscow State Medical University, Institute of Molecular Medicine, Trubetskaya str. 8-2, 119048, Moscow, Russia.

Oligonucleotide RA36 contains two G-quadruplex modules with thrombin binding aptamer sequence GGTTGGTGTGGTTGG. Each of the modules potentially can bind thrombin while differing in functional activity. Despite that, previously published studies report a single dissociation constant for the thrombin:RA36 complex, which value varies widely. Here we address this discrepancy using electrophoretic mobility shift assay. Our results reveal that the interaction between RA36 and thrombin is a two-stage process. The two modules have different affinities for thrombin, which explains the discrepancy in the published data.
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http://dx.doi.org/10.1016/j.bbrc.2019.11.190DOI Listing
February 2020

PeptoGrid-Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries.

Molecules 2019 Jan 13;24(2). Epub 2019 Jan 13.

Faculty of Bioengineering, Lomonosov Moscow State University, Moscow 119234, Russia.

Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein's ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads.
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http://dx.doi.org/10.3390/molecules24020277DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359344PMC
January 2019

Advances in the Application of Modified Nucleotides in SELEX Technology.

Biochemistry (Mosc) 2018 Oct;83(10):1161-1172

Apto-Pharm Ltd., Moscow, 115564, Russia.

Aptamers are widely used as molecular recognition elements for detecting and blocking functional biological molecules. Since the common "alphabet" of DNA and RNA consists of only four letters, the chemical diversity of aptamers is less than the diversity of protein recognition elements built of 20 amino acids. Chemical modification of nucleotides enlarges the potential of DNA/RNA aptamers. This review describes the latest achievements in a variety of approaches to aptamers selection with an extended genetic alphabet.
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http://dx.doi.org/10.1134/S0006297918100024DOI Listing
October 2018
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