Mikhail A. Makarkin

Dr. Mikhail A. Makarkin

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
Verified
Journal Article
Open access
PDF file
DVDenis V. Voronin
Denis V. Voronin
AKAnastasiia Kozlova
Anastasiia Kozlova
RVRoman Verkhovskii
Roman Verkhovskii
Alexey V. ErmakovAlexey V. Ermakov
Alexey V. Ermakov
MMMikhail A. Makarkin
Mikhail A. Makarkin
DBDaniil Bratashov
Daniil Bratashov
Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, various microorganisms and parasites in the blood during acute blood infections. All of these rare diagnostic objects can be detected and identified very rapidly to save a patient’s life. This review outlines the main techniques of visualization of rare objects in the blood flow, methods for extraction of such objects from the blood flow for further investigations and new approaches to identify the objects automatically with the modern deep learning methods.

14 December 2021 in Micromachines
Verified
Journal Article
Open access
PDF file
MMMikhail A. Makarkin
Mikhail A. Makarkin
DBDaniil Bratashov
Daniil Bratashov
In modern digital microscopy, deconvolution methods are widely used to eliminate a number of image defects and increase resolution. In this review, we have divided these methods into classical, deep learning-based, and optimization-based methods. The review describes the major architectures of neural networks, such as convolutional and generative adversarial networks, autoencoders, various forms of recurrent networks, and the attention mechanism used for the deconvolution problem. Special attention is paid to deep learning as the most powerful and flexible modern approach. The review describes the major architectures of neural networks used for the deconvolution problem. We describe the difficulties in their application, such as the discrepancy between the standard loss functions and the visual content and the heterogeneity of the images. Next, we examine how to deal with this by introducing new loss functions, multiscale learning, and prior knowledge of visual content. In conclusion, a review of promising directions and further development of deconvolution methods in microscopy is given.

14 December 2021 in Pharmaceutics
Verified
Journal Article
Open access
PDF file
RVRoman Verkhovskii
Roman Verkhovskii
Alexey V. ErmakovAlexey V. Ermakov
Alexey V. Ermakov
Olga SindeevaOlga Sindeeva
Olga Sindeeva
EPEkaterina Prikhozhdenko
Ekaterina Prikhozhdenko
AKAnastasiia Kozlova
Anastasiia Kozlova
DBDaniil Bratashov
Daniil Bratashov
Drug carriers based on polyelectrolyte microcapsules remotely controlled with an external magnetic field are a promising drug delivery system. However, the influence of capsule parameters on microcapsules’ behavior in vivo is still ambiguous and requires additional study. Here, we discuss how the processes occurring in the blood flow influence the circulation time of magnetic polyelectrolyte microcapsules in mouse blood after injection into the blood circulatory system and their interaction with different blood components, such as WBCs and RBCs. The investigation of microcapsules ranging in diameter 1–5.5 μm allowed us to reveal the dynamics of their filtration by vital organs, cytotoxicity, and hemotoxicity, which is dependent on their size, alongside the efficiency of their interaction with the magnetic field. Our results show that small capsules have a long circulation time and do not affect blood cells. In contrast, the injection of large 5.5 μm microcapsules leads to fast filtration from the blood flow, induces the inhibition of macrophage cell line proliferation after 48 h, and causes an increase in hemolysis, depending on the carrier concentration. The obtained results reveal the possible directions of fine-tuning microcapsule parameters, maximizing capsule payload without the side effects for the blood flow or the blood cells.

17 September 2022 in Molecules
Verified
Journal Article
Open access
PDF file
RVRoman Verkhovskii
Roman Verkhovskii
Alexey V. ErmakovAlexey V. Ermakov
Alexey V. Ermakov
OGOleg Grishin
Oleg Grishin
MMMikhail A. Makarkin
Mikhail A. Makarkin
ИКИлья Кожевников
Илья Кожевников
DBDaniil Bratashov
Daniil Bratashov
A promising approach to targeted drug delivery is the remote control of magnetically sensitive objects using an external magnetic field source. This method can assist in the accumulation of magnetic carriers in the affected area for local drug delivery, thus providing magnetic nanoparticles for MRI contrast and magnetic hyperthermia, as well as the magnetic separation of objects of interest from the bloodstream and liquid biopsy samples. The possibility of magnetic objects’ capture in the flow is determined by the ratio of the magnetic field strength and the force of viscous resistance. Thus, the capturing ability is limited by the objects’ magnetic properties, size, and flow rate. Despite the importance of a thorough investigation of this process to prove the concept of magnetically controlled drug delivery, it has not been sufficiently investigated. Here, we studied the efficiency of polyelectrolyte capsules’ capture by the external magnetic field source depending on their size, the magnetic nanoparticle payload, and the suspension’s flow rate. Additionally, we estimated the possibility of magnetically trapping cells containing magnetic capsules in flow and evaluated cells’ membrane integrity after that. These results are required to prove the possibility of the magnetically controlled delivery of the encapsulated medicine to the affected area with its subsequent retention, as well as the capability to capture magnetically labeled cells in flow.