Algorithms for predicting COVID outcome using ready-to-use laboratorial and clinical data.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging crisis affecting the public health system. The clinical features of COVID-19 can range from an asymptomatic state to acute respiratory syndrome and multiple organ dysfunction. Although some hematological and biochemical parameters are altered during moderate and severe COVID-19, there is still a lack of tools to combine these parameters to predict the clinical outcome of a patient with COVID-19. Thus, this study aimed at employing hematological and biochemical parameters of patients diagnosed with COVID-19 in order to build machine learning algorithms for predicting COVID mortality or survival. Patients included in the study had a diagnosis of SARS-CoV-2 infection confirmed by RT-PCR and biochemical and hematological measurements were performed in three different time points upon hospital admission. Among the parameters evaluated, the ones that stand out the most are the important features of the T1 time point (urea, lymphocytes, glucose, basophils and age), which could be possible biomarkers for the severity of COVID-19 patients. This study shows that urea is the parameter that best classifies patient severity and rises over time, making it a crucial analyte to be used in machine learning algorithms to predict patient outcome. In this study optimal and medically interpretable machine learning algorithms for outcome prediction are presented for each time point. It was found that urea is the most paramount variable for outcome prediction over all three time points. However, the order of importance of other variables changes for each time point, demonstrating the importance of a dynamic approach for an effective patient's outcome prediction. All in all, the use of machine learning algorithms can be a defining tool for laboratory monitoring and clinical outcome prediction, which may bring benefits to public health in future pandemics with newly emerging and reemerging SARS-CoV-2 variants of concern.

Single-Response Electronic Tongue and Machine Learning Enable the Multidetermination of Extracellular Vesicle Biomarkers for Cancer Diagnostics Without Recognition Elements.

Platforms based on impedimetric electronic tongue (nonselective sensor) and machine learning are promising to bring disease screening biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point-of-care, thus contributing to rationalize and decentralize laboratory tests with social and economic impacts being achieved. By combining a low-cost and scalable electronic tongue with machine learning, in this chapter, we describe the simultaneous determination of two extracellular vesicle (EV) biomarkers, i.e., the concentrations of EV and carried proteins, in mice blood with Ehrlich tumor from a single impedance spectrum without using biorecognizing elements. This tumor shows primary features of mammary tumor cells. Pencil HB core electrodes are integrated into polydimethylsiloxane (PDMS) microfluidic chip. The platform shows the highest throughput in comparison with the methods addressed in the literature to determine EV biomarkers.

Photobiomodulation Reduces the Cytokine Storm Syndrome Associated with COVID-19 in the Zebrafish Model.

Although the exact mechanism of the pathogenesis of coronavirus SARS-CoV-2 (COVID-19) is not fully understood, oxidative stress and the release of pro-inflammatory cytokines have been highlighted as playing a vital role in the pathogenesis of the disease. In this sense, alternative treatments are needed to reduce the level of inflammation caused by COVID-19. Therefore, this study aimed to investigate the potential effect of red photobiomodulation (PBM) as an attractive therapy to downregulate the cytokine storm caused by COVID-19 in a zebrafish model. RT-qPCR analyses and protein-protein interaction prediction among SARS-CoV-2 and Danio rerio proteins showed that recombinant Spike protein (rSpike) was responsible for generating systemic inflammatory processes with significantly increased levels of pro-inflammatory (il1b, il6, tnfa, and nfkbiab), oxidative stress (romo1) and energy metabolism (slc2a1a and coa1) mRNA markers, with a pattern similar to those observed in COVID-19 cases in humans. On the other hand, PBM treatment was able to decrease the mRNA levels of these pro-inflammatory and oxidative stress markers compared with rSpike in various tissues, promoting an anti-inflammatory response. Conversely, PBM promotes cellular and tissue repair of injured tissues and significantly increases the survival rate of rSpike-inoculated individuals. Additionally, metabolomics analysis showed that the most-impacted metabolic pathways between PBM and the rSpike treated groups were related to steroid metabolism, immune system, and lipid metabolism. Together, our findings suggest that the inflammatory process is an incisive feature of COVID-19 and red PBM can be used as a novel therapeutic agent for COVID-19 by regulating the inflammatory response. Nevertheless, the need for more clinical trials remains, and there is a significant gap to overcome before clinical trials can commence.

Taming the SARS-CoV-2-mediated proinflammatory response with BromAc®.

Introduction: In the present study, the impact of BromAc®, a specific combination of bromelain and acetylcysteine, on the SARS-CoV-2-specific inflammatory response was evaluated. Methods: An in vitro stimulation system was standardized using blood samples from 9 healthy donors, luminex assays and flow cytometry were performed. Results and discussion: BromAc® demonstrated robust anti-inflammatory activity in human peripheral blood cells upon SARS-CoV-2 viral stimuli, reducing the cytokine storm, composed of chemokines, growth factors, and proinflammatory and regulatory cytokines produced after short-term in vitro culture with the inactivated virus (iSARS-CoV-2). A combined reduction in vascular endothelial growth factor (VEGF) induced by SARS-CoV-2, in addition to steady-state levels of platelet recruitment-associated growth factor-PDGFbb, was observed, indicating that BromAc® may be important to reduce thromboembolism in COVID-19. The immunophenotypic analysis of the impact of BromAc® on leukocytes upon viral stimuli showed that BromAc® was able to downmodulate the populations of CD16+ neutrophils and CD14+ monocytes observed after stimulation with iSARS-CoV-2. Conversely, BromAc® treatment increased steady-state HLA-DR expression in CD14+ monocytes and preserved this activation marker in this subset upon iSARS-CoV-2 stimuli, indicating improved monocyte activation upon BromAc® treatment. Additionally, BromAc® downmodulated the iSARS-CoV-2-induced production of TNF-a by the CD19+ B-cells. System biology approaches, utilizing comprehensive correlation matrices and networks, showed distinct patterns of connectivity in groups treated with BromAc®, suggesting loss of connections promoted by the compound and by iSARS-CoV-2 stimuli. Negative correlations amongst proinflammatory axis and other soluble and cellular factors were observed in the iSARS-CoV-2 group treated with BromAc® as compared to the untreated group, demonstrating that BromAc® disengages proinflammatory responses and their interactions with other soluble factors and the axis orchestrated by SARS-CoV-2. Conclusion: These results give new insights into the mechanisms for the robust anti-inflammatory effect of BromAc® in the steady state and SARS-CoV-2-specific immune leukocyte responses, indicating its potential as a therapeutic strategy for COVID-19.

Proteomics in Veterinary Medicine and Animal Science: Neglected Scientific Opportunities with Immediate Impact.

Animal/veterinary proteomics is an evolving field which holds a great promise not only for fundamental and applied discoveries regarding biology and pathology of domestic species, but can also be implemented in comparative applications of human diseases research. Experimental proteomics in domestic animals have advantages over use of rodents, such as multiple sampling in time series and availability of biological samples in sufficient volume for multiple analyses, such that both experimental and natural disease processes can be investigated. While there are certain technical limitations in the expansion of the field, they can currently be circumvented and in the future mastered with a greater participation of proteomic experts, which will in turn drive the accessibility of species-specific reagents, data volume expansion in bioinformatic databases, and increased funding. This Viewpoint highlights some comparative proteomics studies addressing important issues and encourages readers to expand their horizons of domestic animal proteomics research. It will hopefully inspire new fruitful collaborations between veterinary and animal scientists and proteomic specialists for research in these areas that can have immediate and direct impact on health, society, and the economy.

Who has anaphylaxis in Brazil? Validation of a questionnaire for population studies.

BACKGROUND: The incidence of anaphylaxis is increasing in several parts of the world; thus, determining the prevalence of the disease in a given region is important to understand the factors involved and to promote measures to avoid this type of allergic reaction. Aiming this objective, we validated an instrument for a population-basedstudy that assesses the prevalence of anaphylaxis in the Brazilian population. METHODS: A questionnaire was generated in two variants - one for subjects seven years old or above (Group A) and another for children who were up to six years, 11 months and 29 days (Group B). The instrument was administered to patients with and without anaphylaxis. By allocating points, a score was calculated to differentiate subjects with and without the disease. After validation, the questionnaire was applied in the city of Botucatu (São Paulo state, Brazil), by randomly selecting houses and inviting residents to answer the questionnaire. RESULTS: The questionnaire was reliable for identifying subjects with and without anaphylaxis in both groups, with a specificity and sensitivity above 90%. The prevalence of anaphylaxis in the pilot survey was 6.2% in Group A, however the evaluation was compromised in Group B by the low number of children below seven years of age due to random sampling of residences. DISCUSSION: The prevalence of anaphylaxis in our pilot test (6.2%) was similar to major epidemiological surveys from several parts of the world, showing that anaphylaxis is not a rare disease. The instrument of the present work was suitable for this epidemiological survey and might be a good option for studying anaphylaxis in other populations. CONCLUSION: This instrument might be of particular value in places where researchers cannot access medical records to conduct similar epidemiological studies.