Introduction Defects of platelet functional responses in COVID-19 were reported, but their origin and pathophysiological significance are unclear. The objective of this study was to characterize the thrombocytopathy in COVID-19. Materials and methods Analysis of platelet functional responses to activation by flow cytometry and aggregometry in 46 patients with confirmed COVID-19 of different severity (non-ICU, ICU, and ECMO) over the course of hospitalization alongside with plasma coagulation, inflammatory markers (CRP, fibrinogen, NETosis assays in smears) was performed. Results and conclusions All patients had increased baseline percentage of procoagulant platelets (healthy: 0.9 ± 0.5%; COVID-19: 1.7 ± 0.6%). Patients had decreased agonist-induced platelet GPIb shedding (1.8 ± 0.7 vs 1.25 ± 0.4), P-Selectin exposure (1.51 ± 0.21 vs 1.1 ± 0.3) and aggregation. The values of these parameters among the non-ICU and ICU cohorts differed modestly, while the ECMO cohort differed significantly. Only ECMO patients had pronounced thrombocytopenia. While inflammatory markers improved over time, the observed platelet functional responses changed only moderately. SARS-CoV-2 RNA was found in 8% of blood samples and it did not correlate with platelet counts or responses. All patients had increased NETosis that moderately correlated with platelet dysfunction. High cumulative dosages of LMWH (average > 12,000 IU/day over 5 days) resulted in an improvement in platelet parameters. The observed pattern of platelet refractoriness was reproduced by in vitro pre-treatment of washed platelets with subnanomolar thrombin or perfusion of blood through a collagen-covered flow chamber. We conclude that platelet dysfunction in COVID-19 is consistent with the intravascular-coagulation-induced refractoriness rather than with an inflammation-induced mechanism or a direct activation by the virus.

Over the past few years, Raman spectroscopy has become a powerful diagnostic tool in the life sciences. The present work is devoted to the application of Raman microspectroscopy for distinction of neutrophils transformed during NETosis and the quantitative determination of the level of their transformation based on the analysis of the neutrophil Raman spectra acquired from the samples of human blood at different levels of transformation. NETosis is a process of the programmed neutrophil cell death involved in the development of many diseases, including those associated with high mortality. Our goal was to search for possible spectral markers in neutrophil Raman spectra, caused precisely by NETotic transformation of neutrophils. The results of the work were (a) obtaining of neutrophil Raman spectra at different levels of cell transformation; (b) creation of spectral archetypes of neutrophils (as a "representative" Raman spectrum for spectra group) with a given level of cell transformation; (c) detection of statistically significant differences in the spectral archetypes of the neutrophil Raman spectra at different levels of transformation. K E Y W O R D S human blood neutrophils, NETosis, microRaman spectroscopy, spectra preprocessing, spectral marker 1 | INTRODUCTION Raman microspectroscopy is widely used in the studies of cell biology, microbiology, and medicine for optical analysis of biological objects at the cellular level. [1-6] Raman microspectroscopy allows exploring intracellular transformations and their features [7-12] and helps to understand the processes occurring in the cell when studying the properties of the selective interaction of reagents in the cell. [13-15] Recently, achievements in Raman microspectroscopy have opened up new prospects for the rapid and sensitive detection of bacteria of various types. [16-21] Neutrophils are the most common human blood leukocytes, which are the most important part of the innate immunity and carry out a fast response to microbial invasion. In 2004, a new type of programmed cell death of neutrophils, called NETosis, [22] was described. Currently,

Express-test by the method of coherent fluctuation nephelometry for urine contamination was carried out on two prototype instruments with standard polystyrene photometric cuvettes. We analyzed 209 and 119 urine samples. Due to high sensitivity of the method, up to 50% negative samples were detected within 10 min by initial opacity and 90% negative samples were detected during 3.5 h by registration of the bacterial growth curves.

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