Simple hemogram to support the decision-making of COVID-19 diagnosis using clusters analysis with self-organizing maps neural network.

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is related to new coronavirus disease (COVID-19) has mobilized several scientifics to explore clinical data using soft-computing approaches. In the context of machine learning, previous studies have explored supervised algorithms to predict and support diagnosis based on several clinical parameters from patients diagnosed with and without COVID-19. However, in most of them the decision is based on a "black-box" method, making it impossible to discover the variable relevance in decision making. Hence, in this study, we introduce a non-supervised clustering analysis with neural network self-organizing maps (SOM) as a strategy of decision-making. We propose to identify potential variables in routine blood tests that can support clinician decision-making during COVID-19 diagnosis at hospital admission, facilitating rapid medical intervention. Based on SOM features (visual relationships between clusters and identification of patterns and behaviors), and using linear discriminant analysis , it was possible to detect a group of units of the map with a discrimination power around 83% to SARS-CoV-2-positive patients. In addition, we identified some variables in admission blood tests (Leukocytes, Basophils, Eosinophils, and Red cell Distribution Width) that, in combination had strong influence in the clustering performance, which could assist a possible clinical decision. Thus, although with limitations, we believe that SOM can be used as a soft-computing approach to support clinician decision-making in the context of COVID-19.

Relation between red blood cell distribution width and acute kidney injury in patients with sepsis.

OBJECTIVE: The objective of the present study is to evaluate the association of red blood cell distribution width with acute kidney injury in sepsis. METHODS: This is a retrospective study of 849 critically ill patients with sepsis in intensive care unit. Demographic data, renal function, inflammation, complete blood count, and acid-base parameters were compared between acute kidney injury and non-acute kidney injury groups. Therefore, a multivariate analysis was performed to observe independent predictive factors. RESULTS: Comparatively, higher levels of C-reactive protein, lactate, red blood cell distribution width, and Simplified Acute Physiology Score 3 were found in the acute kidney injury group. The study showed a higher frequency of women, hemoglobin (Hgb) concentration, platelets, bicarbonate and PaO2/FiO2 ratio in the non-acute kidney injury group. In addition, there was an independent association of comorbidity-chronic kidney disease [OR 3.549, 95%CI: 1.627-7.743; p<0.001], urea [OR 1.047, 95%CI: 1.036-1.058; p<0.001] and RDW [OR 1.158, 95%CI: 1.045-1.283; p=0.005] with acute kidney injury in sepsis patients. CONCLUSION: As an elective risk factor, red blood cell distribution width was independently associated with sepsis-related acute kidney injury. Thus, red blood cell distribution width acts like a predictive factor for sepsis-induced acute kidney injury in intensive care unit admission.

Relation between red blood cell distribution width and acute kidney injury in patients with sepsis

ABSTRACT Objective The objective of the present study is to evaluate the association of red blood cell distribution width with acute kidney injury in sepsis. Methods This is a retrospective study of 849 critically ill patients with sepsis in intensive care unit. Demographic data, renal function, inflammation, complete blood count, and acid-base parameters were compared between acute kidney injury and non-acute kidney injury groups. Therefore, a multivariate analysis was performed to observe independent predictive factors. Results Comparatively, higher levels of C-reactive protein, lactate, red blood cell distribution width, and Simplified Acute Physiology Score 3 were found in the acute kidney injury group. The study showed a higher frequency of women, hemoglobin (Hgb) concentration, platelets, bicarbonate and PaO2/FiO2 ratio in the non-acute kidney injury group. In addition, there was an independent association of comorbidity-chronic kidney disease [OR 3.549, 95%CI: 1.627-7.743; p<0.001], urea [OR 1.047, 95%CI: 1.036-1.058; p<0.001] and RDW [OR 1.158, 95%CI: 1.045-1.283; p=0.005] with acute kidney injury in sepsis patients. Conclusion As an elective risk factor, red blood cell distribution width was independently associated with sepsis-related acute kidney injury. Thus, red blood cell distribution width acts like a predictive factor for sepsis-induced acute kidney injury in intensive care unit admission.

Extracellular vesicles isolated from mesenchymal stromal cells modulate CD4+ T lymphocytes toward a regulatory profile

Mesenchymal stromal cells (MSCs) can generate immunological tolerance due to their regulatory activity in many immune cells. Extracellular vesicles (EVs) release is a pivotal mechanism by which MSCs exert their actions. In this study, we evaluate whether mesenchymal stromal cell extracellular vesicles (MSC-EVs) can modulate T cell response. MSCs were expanded and EVs were obtained by differential ultracentrifugation of the supernatant. The incorporation of MSC-EVs by T cells was detected by confocal microscopy. Expression of surface markers was detected by flow cytometry or CytoFLEX and cytokines were detected by RT-PCR, FACS and confocal microscopy and a miRNA PCR array was performed. We demonstrated that MSC-EVs were incorporated by lymphocytes in vitro and decreased T cell proliferation and Th1 differentiation. Interestingly, in Th1 polarization, MSC-EVs increased Foxp3 expression and generated a subpopulation of IFN-gama+/Foxp3+T cells with suppressive capacity. A differential expression profile of miRNAs in MSC-EVs-treated Th1 cells was seen, and also a modulation of one of their target genes, TGFbR2. MSC-EVs altered the metabolism of Th1-differentiated T cells, suggesting the involvement of the TGF-ß pathway in this metabolic modulation. The addition of MSC-EVs in vivo, in an OVA immunization model, generated cells Foxp3+. Thus, our findings suggest that MSC-EVs are able to specifically modulate activated T cells at an alternative regulatory profile by miRNAs and metabolism shifting

Extracellular Vesicles isolated from mesenchymal stromal cells modulate CD4+ T lymphocytes toward a regulatory profile

Mesenchymal stromal cells (MSCs) can generate immunological tolerance due to their regulatory activity in many immune cells. Extracellular vesicles (EVs) release is a pivotal mechanism by which MSCs exert their actions. In this study, we evaluate whether mesenchymal stromal cell extracellular vesicles (MSC-EVs) can modulate T cell response. MSCs were expanded and EVs were obtained by differential ultracentrifugation of the supernatant. The incorporation of MSC-EVs by T cells was detected by confocal microscopy. Expression of surface markers was detected by flow cytometry or CytoFLEX and cytokines were detected by RT-PCR, FACS and confocal microscopy and a miRNA PCR array was performed. We demonstrated that MSC-EVs were incorporated by lymphocytes in vitro and decreased T cell proliferation and Th1 differentiation. Interestingly, in Th1 polarization, MSC-EVs increased Foxp3 expression and generated a subpopulation of IFN-gama+/Foxp3+T cells with suppressive capacity. A differential expression profile of miRNAs in MSC-EVs-treated Th1 cells was seen, and also a modulation of one of their target genes, TGFbR2. MSC-EVs altered the metabolism of Th1-differentiated T cells, suggesting the involvement of the TGF-ß pathway in this metabolic modulation. The addition of MSC-EVs in vivo, in an OVA immunization model, generated cells Foxp3+. Thus, our findings suggest that MSC-EVs are able to specifically modulate activated T cells at an alternative regulatory profile by miRNAs and metabolism shifting

A regulatory miRNA-mRNA network is associated with tissue repair induced by mesenchymal stromal cells in acute kidney injury

Mesenchymal stromal cells (MSCs) orchestrate tissue repair by releasing cell-derived microvesicles (MVs), which, presumably by small RNA species, modulate global gene expression. The knowledge of miRNA/mRNA signatures linked to a reparative status may elucidate some of the molecular events associated with MSC protection. Here, we used a model of cisplatin-induced kidney injury (acute kidney injury) to assess how MSCs or MVs could restore tissue function. MSCs and MVs presented similar protective effects, which were evidenced in vivo and in vitro by modulating apoptosis, inflammation, oxidative stress, and a set of prosurvival molecules. In addition, we observed that miRNAs (i.e., miR-880, miR-141, miR-377, and miR-21) were modulated, thereby showing active participation on regenerative process. Subsequently, we identified that MSC regulates a particular miRNA subset which mRNA targets are associated with Wnt/TGF-beta fibrosis, and epithelial-mesenchymal transition signaling pathways. Our results suggest that MSCs release MVs that transcriptionally reprogram injured cells, thereby modulating a specific miRNA-mRNA network.