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1.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-318926

ABSTRACT

COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at identifying automatically lung parenchyma and lobes. Next, we combined such segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the obtained classification results with those obtained by three expert radiologists on a dataset consisting of 162 CT scans. Results showed a sensitivity of 90\% and a specificity of 93.5% for COVID-19 detection, outperforming those yielded by the expert radiologists, and an average lesion categorization accuracy of over 84%. Results also show that a significant role is played by prior lung and lobe segmentation that allowed us to enhance performance by over 20 percent points. The interpretation of the trained AI models, moreover, reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai.

2.
Pathogens ; 11(2)2022 Feb 08.
Article in English | MEDLINE | ID: covidwho-1674750

ABSTRACT

Indoor air sanitizers contrast airborne diseases and particularly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/Coronavirus disease 2019 (COVID-19). The commercial air sanitizer Zefero (Cf7 S.r.l., San Giovanni La Punta, Italy) works alternatively using a set of integrated disinfecting technologies (namely Photocatalysis/UV mode) or by generating ozone (Ozone mode). Here we evaluated the virucidal efficacy of Zefero setup modes against human Betacoronavirus OC43 and SARS-CoV-2. For this purpose, we designed a laboratory test system in which each virus, as aerosol, was treated with Photocatalysis/UV or Ozone mode and returned into a recirculation plexiglass chamber. Aerosol samples were collected after different times of exposure, corresponding to different volumes of air treated. The viral RNA concentration was determined by qRT-PCR. In Photocatalysis/UV mode, viral RNA of OC43 or SARS-CoV-2 was not detected after 120 or 90 min treatment, respectively, whereas in Ozone mode, viruses were eliminated after 30 or 45 min, respectively. Our results indicated that the integrated technologies used in the air sanitizer Zefero are effective in eliminating both viruses. As a reliable experimental system, the recirculation chamber developed in this study represents a suitable apparatus for effectively comparing the disinfection capacity of different air sanitizers.

3.
Int J Mol Sci ; 22(21)2021 Oct 21.
Article in English | MEDLINE | ID: covidwho-1480798

ABSTRACT

Disseminated intravascular coagulation (DIC) is a severe condition characterized by the systemic formation of microthrombi complicated with bleeding tendency and organ dysfunction. In the last years, it represents one of the most frequent consequences of coronavirus disease 2019 (COVID-19). The pathogenesis of DIC is complex, with cross-talk between the coagulant and inflammatory pathways. The objective of this study is to investigate the anti-inflammatory action of ultramicronized palmitoylethanolamide (um-PEA) in a lipopolysaccharide (LPS)-induced DIC model in rats. Experimental DIC was induced by continual infusion of LPS (30 mg/kg) for 4 h through the tail vein. Um-PEA (30 mg/kg) was given orally 30 min before and 1 h after the start of intravenous infusion of LPS. Results showed that um-PEA reduced alteration of coagulation markers, as well as proinflammatory cytokine release in plasma and lung samples, induced by LPS infusion. Furthermore, um-PEA also has the effect of preventing the formation of fibrin deposition and lung damage. Moreover, um-PEA was able to reduce the number of mast cells (MCs) and the release of its serine proteases, which are also necessary for SARS-CoV-2 infection. These results suggest that um-PEA could be considered as a potential therapeutic approach in the management of DIC and in clinical implications associated to coagulopathy and lung dysfunction, such as COVID-19.


Subject(s)
Amides/therapeutic use , Blood Coagulation Disorders/drug therapy , Disseminated Intravascular Coagulation/drug therapy , Ethanolamines/therapeutic use , Palmitic Acids/therapeutic use , Sepsis/complications , Amides/chemistry , Amides/pharmacology , Animals , Blood Coagulation Disorders/etiology , COVID-19/pathology , COVID-19/virology , Cytokines/blood , Cytokines/metabolism , Disease Models, Animal , Disseminated Intravascular Coagulation/etiology , Ethanolamines/chemistry , Ethanolamines/pharmacology , Fibrin Fibrinogen Degradation Products/metabolism , Lipopolysaccharides/toxicity , Lung/metabolism , Lung/pathology , Male , Mast Cells/cytology , Mast Cells/drug effects , Mast Cells/metabolism , Palmitic Acids/chemistry , Palmitic Acids/pharmacology , Partial Thromboplastin Time , Prothrombin Time , Rats , Rats, Sprague-Dawley , SARS-CoV-2/isolation & purification , Sepsis/pathology , Serine Proteases/metabolism
4.
Int J Mol Sci ; 22(11)2021 May 24.
Article in English | MEDLINE | ID: covidwho-1273453

ABSTRACT

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are common and devastating clinical disorders with high mortality and no specific therapy. Lipopolysaccharide (LPS) is usually used intratracheally to induce ALI in mice. The aim of this study was to examine the effects of an ultramicronized preparation of palmitoylethanolamide (um-PEA) in mice subjected to LPS-induced ALI. Histopathological analysis reveals that um-PEA reduced alteration in lung after LPS intratracheal administration. Besides, um-PEA decreased wet/dry weight ratio and myeloperoxidase, a marker of neutrophils infiltration, macrophages and total immune cells number and mast cells degranulation in lung. Moreover, um-PEA could also decrease cytokines release of interleukin (IL)-6, interleukin (IL)-1ß, tumor necrosis factor (TNF)-α and interleukin (IL)-18. Furthermore, um-PEA significantly inhibited the phosphorylation of nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IκBα) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation in ALI, and at the same time decreased extracellular signal-regulated kinase 1/2 (ERK1/2), c-Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (p38/MAPK) expression, that was increased after LPS administration. Our study suggested that um-PEA contrasted LPS-induced ALI, exerting its potential role as an adjuvant anti-inflammatory therapeutic for treating lung injury, maybe also by p38/NF-κB pathway.


Subject(s)
Acute Lung Injury/drug therapy , Amides/pharmacology , Cytokines/metabolism , Ethanolamines/pharmacology , MAP Kinase Signaling System/drug effects , Palmitic Acids/pharmacology , Acute Lung Injury/metabolism , Acute Lung Injury/pathology , Amides/therapeutic use , Animals , Ethanolamines/therapeutic use , Immunohistochemistry , Inflammation/metabolism , Interleukin-18/metabolism , Interleukin-1beta/metabolism , Interleukin-6/metabolism , JNK Mitogen-Activated Protein Kinases/metabolism , Lipopolysaccharides/administration & dosage , Lipopolysaccharides/toxicity , Macrophages/drug effects , Macrophages/immunology , Male , Mast Cells/drug effects , Mast Cells/pathology , Mice , Mitogen-Activated Protein Kinase 1/metabolism , Mitogen-Activated Protein Kinase 3/metabolism , NF-KappaB Inhibitor alpha/metabolism , NF-kappa B/metabolism , Neutrophils/drug effects , Neutrophils/immunology , Palmitic Acids/therapeutic use , Peroxidase/metabolism , Tumor Necrosis Factor-alpha/metabolism , p38 Mitogen-Activated Protein Kinases/metabolism
5.
Artif Intell Med ; 118: 102114, 2021 08.
Article in English | MEDLINE | ID: covidwho-1240193

ABSTRACT

COVID-19 infection caused by SARS-CoV-2 pathogen has been a catastrophic pandemic outbreak all over the world, with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at automatically identifying lung parenchyma and lobes. Next, we combine the segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the model's classification results with those obtained by three expert radiologists on a dataset of 166 CT scans. Results showed a sensitivity of 90.3% and a specificity of 93.5% for COVID-19 detection, at least on par with those yielded by the expert radiologists, and an average lesion categorization accuracy of about 84%. Moreover, a significant role is played by prior lung and lobe segmentation, that allowed us to enhance classification performance by over 6 percent points. The interpretation of the trained AI models reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai. The whole AI system is unique since, to the best of our knowledge, it is the first AI-based software, publicly available, that attempts to explain to radiologists what information is used by AI methods for making decisions and that proactively involves them in the decision loop to further improve the COVID-19 understanding.


Subject(s)
COVID-19 , Artificial Intelligence , Humans , Lung/diagnostic imaging , SARS-CoV-2 , Tomography, X-Ray Computed
6.
Int J Mol Sci ; 21(14)2020 Jul 21.
Article in English | MEDLINE | ID: covidwho-671084

ABSTRACT

Some coronavirus disease 2019 (COVID-19) patients develop acute pneumonia which can result in a cytokine storm syndrome in response to Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection. The most effective anti-inflammatory drugs employed so far in severe COVID-19 belong to the cytokine-directed biological agents, widely used in the management of many autoimmune diseases. In this paper we analyze the efficacy of epigallocatechin 3-gallate (EGCG), the most abundant ingredient in green tea leaves and a well-known antioxidant, in counteracting autoimmune diseases, which are dominated by a massive cytokines production. Indeed, many studies registered that EGCG inhibits signal transducer and activator of transcription (STAT)1/3 and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription factors, whose activities are crucial in a multiplicity of downstream pro-inflammatory signaling pathways. Importantly, the safety of EGCG/green tea extract supplementation is well documented in many clinical trials, as discussed in this review. Since EGCG can restore the natural immunological homeostasis in many different autoimmune diseases, we propose here a supplementation therapy with EGCG in COVID-19 patients. Besides some antiviral and anti-sepsis actions, the major EGCG benefits lie in its anti-fibrotic effect and in the ability to simultaneously downregulate expression and signaling of many inflammatory mediators. In conclusion, EGCG can be considered a potential safe natural supplement to counteract hyper-inflammation growing in COVID-19.


Subject(s)
Anti-Inflammatory Agents/therapeutic use , Catechin/analogs & derivatives , Coronavirus Infections/drug therapy , Cytokine Release Syndrome/drug therapy , Pneumonia, Viral/drug therapy , Antioxidants/therapeutic use , Autoimmune Diseases/drug therapy , Betacoronavirus/drug effects , Betacoronavirus/immunology , COVID-19 , Catechin/therapeutic use , Coronavirus Infections/immunology , Coronavirus Infections/pathology , Cytokine Release Syndrome/pathology , Humans , NF-kappa B/antagonists & inhibitors , Pandemics , Plant Extracts/therapeutic use , Pneumonia, Viral/immunology , Pneumonia, Viral/pathology , Pulmonary Fibrosis/drug therapy , Pulmonary Fibrosis/prevention & control , SARS-CoV-2 , STAT1 Transcription Factor/antagonists & inhibitors , STAT3 Transcription Factor/antagonists & inhibitors , Signal Transduction/drug effects
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