The role of platelets and neutrophil extracellular traps (NETs) in sepsis: A comprehensive literature review

Sepsis is defined as "an organic dysfunction secondary to the dysregulated response of the patient to an infection." This concept only reveals the tip of the iceberg, the clinical expression of organic failures, without understanding their basis, which is currently explained by cellular and molecular phenomena. Neutrophils are crucial pillars of early innate immune responses, and their fundamental function is phagocytosis. Additionally, neutrophils can degranulate upon activation, releasing various antimicrobial enzymes and pro-inflammatory cytokines, and form neutrophil extracellular traps (NETs), whose purpose is to trap pathogens by releasing their "sticky" nuclear content; the presence of activated platelets amplifies this phenomenon. NETosis is a beneficial process; however, deregulated, it can be detrimental, inducing "immunothrombosis" and compromising the microcirculation, thereby increasing the clinical severity of sepsis. The purpose of this review is to clearly describe the pathophysiological role therapeutic target of NETs, their interaction with platelets in sepsis, and their potential as therapeutic targets, since it has been shown that a therapeutic approach aimed at curbing NETs would be beneficial

In silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19

Background: There is pressing urgency to identify therapeutic targets and drugs that allow treating COVID-19 patients effectively.Methods: We performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19.Results: We screened 1,584 high-confidence immune system proteins in ACE2 and TMPRSS2 co-expressing cells, finding 25 potential therapeutic targets significantly overexpressed in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs, obtaining several approved drugs, compounds under investigation, and experimental compounds with the highest area under the receiver operating characteristics.Conclusion: After being effectively analyzed in clinical trials, these drugs can be considered for treatment of severe COVID-19 patients. Scripts can be downloaded at

Role of Uremic Toxins in Early Vascular Ageing and Calcification

In patients with advanced chronic kidney disease (CKD), the accumulation of uremic toxins, caused by a combination of decreased excretion secondary to reduced kidney function and increased generation secondary to aberrant expression of metabolite genes, interferes with different biological functions of cells and organs, contributing to a state of chronic inflammation and other adverse biologic effects that may cause tissue damage. Several uremic toxins have been implicated in severe vascular smooth muscle cells (VSMCs) changes and other alterations leading to vascular calcification (VC) and early vascular ageing (EVA). The above mentioned are predominant clinical features of patients with CKD, contributing to their exceptionally high cardiovascular mortality. Herein, we present an update on pathophysiological processes and mediators underlying VC and EVA induced by uremic toxins. Moreover, we discuss their clinical impact, and possible therapeutic targets aiming at preventing or ameliorating the harmful effects of uremic toxins on the vasculature

Development of a fast and sensitive RT-qPCR assay based on SYBR® green for diagnostic and quantification of Avian Nephritis Virus (ANV) in chickens affected with enteric disease

Abstract Background Enteric viruses are among the most prominent etiological agents of Runting-Stunting Syndrome (RSS). The Avian Nephritis Virus (ANV) is an astrovirus associated with enteric diseases in poultry, whose early diagnosis is essential for maintaining a good poultry breeding environment. ANV is an RNA virus that rapidly mutates, except for some conserved regions such as ORF1b. Therefore, the approach of a diagnostic method based on fast-RT-qPCR using SYBR® Green that focuses on the amplification of a fragment of ORF1b is presented as a feasible alternative for the diagnosis of this viral agent. In this study, the proposed assay showed a standard curve with an efficiency of 103.8% and a LoD and LoQ of 1 gene viral copies. The assay was specific to amplify the ORF 1b gene, and no amplification was shown from other viral genomes or in the negative controls. 200 enteric (feces) samples from chickens (broilers) and laying hens with signs of RSS from Ecuadorian poultry flocks were examined to validate the proposed method. Results Using our method, 164 positive results were obtained out of the total number of samples run, while the presence of viral RNA was detected in samples collected from one day to 44 weeks old in both avian lines. Conclusions Our study presents a novel, rapid, robust, and sensitive molecular assay capable of detecting and quantifying even low copy numbers of the ANV in commercial birds, therefore introducing a handy tool in the early diagnosis of ANV in enteric disease outbreaks in poultry

Modulatory effect of Andean blackberry polyphenols on genes related to antioxidant and inflammatory responses, the NLRP3 inflammasome, and autophagy

BACKGROUND: The Andean blackberry (Rubus glaucus Benth) is one of Ecuador’s most iconic Andean berries for which a high anthocyanin content has been described. OBJECTIVE: The aim of the present study was to determine the chemical composition and anti-inflammatory potential of the Andean blackberry from Ecuador, with an emphasis on its effects on NLRP3 inflammasome activation and autophagy processes. RESULTS: Andean blackberry extracts were rich in hydroxycinnamates (coumaric acid and derivates), in addition to quercetin and kaempferol as principal flavonols. Cyanidin and its glycosides were identified as the main anthocyanins present. Andean blackberry extracts efficiently reduced oxidative stress markers in the lipopolysaccharide-stimulated RAW 264.7 cells. The extracts also caused a moderate decrease in the expression of the pro-inflammatory and antioxidant genes NFκB1, TNF, IL-1β, IL-6, and NOS2 expression, while they significantly increased the mRNA levels of both SOD1 and NFE2L2 genes. Andean blackberry extracts significantly decreased the activation of the NLRP3 inflammasome complex, as well as p62 levels, and the LC3I/LC3II ratio increased, suggesting a direct action of Andean blackberry compounds on the inflammatory response and restoration of the autophagy process. CONCLUSIONS: These results suggest that Andean blackberries potentially have an anti-inflammatory effect through their ability to regulate genes related to the inflammatory and antioxidant response, as well as modulate the activation of the NLRP3 inflammasome complex and autophagy processes

European families reveal MHC class I and II associations with autoimmune-mediated congenital heart block

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In Silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19

There is pressing urgency to better understand the immunological underpinnings of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) in order to identify potential therapeutic targets and drugs that allow treating patients effectively. To fill in this gap, we performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19. As results, the high-confidence protein interactome network was conformed by 1,588 nodes between immune system proteins and human proteins physically associated with SARS-CoV-2. Subsequently, we screened all these nodes in ACE2 and TMPRSS2 co-expressing cells according to the Alexandria Project, finding 75 potential therapeutic targets significantly overexpressed (Z score > 2) in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs for 25 of the 75 aforementioned proteins. On one hand, we obtained 45 approved drugs, 16 compounds under investigation, and 35 experimental compounds with the highest area under the receiver operating characteristic (AUROCs) for 15 immune system proteins. On the other hand, we obtained 4 approved drugs, 9 compounds under investigation, and 16 experimental compounds with the highest multi-target affinities for 9 immune system proteins. In conclusion, computational structure-based drug discovery focused on immune system proteins is imperative to select potential drugs that, after being effectively analyzed in cell lines and clinical trials, these can be considered for treatment of complex symptoms of COVID-19 patients, and for co-therapies with drugs directly targeting SARS-CoV-2