Our findings indicated the expression profile analysis of CD4+ FoxP3+ CD25+ T cells could be a potential marker for the assessment of severity of COVID-19 patients.
  The present study aimed to identify human protein-host protein interactions of SARS-CoV-2 infection in the small intestine to discern the potential mechanisms and gain insights into the associated biomarkers and treatment strategies.
 
  Deciphering the tissue and organ interactions of the SARS-CoV-2 infection can be important to discern the potential underlying mechanisms. In the present study, we investigated the human protein-host protein interactions in the small intestine.
 
  Public databases and published works were used to collect data related to small intestine tissue and SARS-CoV-2 infection. We constructed a human protein-protein interaction (PPI) network and showed interactions of host proteins in the small intestine. Associated modules, biological processes, functional pathways, regulatory transcription factors, disease ontology categories, and possible drug candidates for therapeutic targets were identified.
 
  Thirteen primary protein neighbors were found for the SARS-CoV-2 receptor ACE2. ACE2 and and inflammation. The results suggest that antiviral targeting of these interactions may improve the condition of COVID-19 patients.
  Introducing possible diagnostic and therapeutic biomarker candidates via the identification of chief dysregulated proteins in COVID-19 patients is the aim of this study.
 
  Molecular studies, especially proteomics, can be considered as suitable approaches for discovering the hidden aspect of the disease.
 
  Differentially expressed proteins (DEPs) of three patients with demonstrated severe condition (S-COVID-19) were compared to healthy cases by a proteomics study. Cytoscape software and STRING database were used to construct the protein-protein interaction (PPI) network. The central DEPs were identified through topological analysis of the network. ClueGO+CluePedia were applied to find the biological processes related to the central nodes. MCODE molecular complex detection (MCODE) was used to discover protein complexes.
 
  A total of 242 DEPs from among 256 query ones were included in the network. Centrality analysis of the network assigned 16 hub-bottlenecks, nine of which were presented in the highest-scored protein complex. Ten protein complexes were determined. APOA1 was identified as the protein complex seed, and APP, EGF, and C3 were the top hub-bottlenecks of the network. The results specify that up-regulation of C3 and down-regulation of APOA1 in urine play a role in the stiffness in respiration and, accordingly, the severity of COVID-19. Moreover, dysregulation of APP and APOA1 could both contribute to the possible adverse effects of COVID-19 on the nervous system.
 
  The introduced central proteins of the S-COVID-19 interaction network, particularly APOA1, can be considered as diagnostic and therapeutic targets related to the coronavirus disease after being approved with complementary studies.
 The introduced central proteins of the S-COVID-19 interaction network, particularly APOA1, can be considered as diagnostic and therapeutic targets related to the coronavirus disease after being approved with complementary studies.
  This research aimed to investigate neutrophil-to-lymphocyte ratio (NLR) with C-reactive protein to identify potential clinical predictors and analyze differences among severe and non-severe COVID-19 patients.
 
  NLR and CRP are established markers that reflect systemic inflammatory, and these parameters alter in patients with novel coronavirus (SARS-CoV-2) pneumonia (COVID-19).
 
  A population of patients with COVID-19 referred to Loghman Hospital in Tehran was analyzed.  https://www.selleckchem.com/products/ipi-549.html  The baseline data of laboratory examinations, including NLR and CRP levels, was collected. Pearson analysis was used to assess the independent relationship between the NLR with disease severity and CRP levels.
 
  COVID-19 cases comprised 14 (20%) patients with severe disease and 56 (80%) with non-severe infection. The mean values of WBC, NEU, LYM, and NLR of the severe patients were significantly higher than those of the non-severe patients. Forty-six patients (65.7%) had NLR >1, and the remaining patients had NLR <1. Plasma CRP levels were higher in severe cases than in non-severe cases, and this difference was significant. The results showed that NLR was positively correlated with CRP levels (R=0.23) and negatively correlated with WBC (R=-0.38). CRP (AUC = 0.97, 95% CI 0.95-0.99) and NLR (AUC = 0.87, 95% CI 0.81-0.93) had very good accuracy in predicting the severity of COVID-19 disease.
 
  The findings of this study indicated that the integration of NLR and CRP may lead to improved predictions and is recommended as a valuable early marker to assess prognosis and evaluate the severity of clinical symptoms in COVID-19 patients.
 The findings of this study indicated that the integration of NLR and CRP may lead to improved predictions and is recommended as a valuable early marker to assess prognosis and evaluate the severity of clinical symptoms in COVID-19 patients.
  This study demonstrated potent inhibitors against COVID-19 using the molecular docking approach of FDA approved viral antiprotease drugs.
 
  COVID-19 has now spread throughout world. There is a serious need to find potential therapeutic agents. The 3C-like protease (Mpro/6LU7) is an attractive molecular target for rational anti-CoV drugs.
 
  The tertiary structure of COVID-19 Mpro was obtained from a protein data bank repository, and molecular docking screening was performed by Molegro Virtual Docker, ver. 6, with a grid resolution of 0.30 Å. Docking scores (DOS) are representative of calculated ligand-receptor (protein) interaction energy; therefore, more negative scores mean better binding tendency. Another docking study was then applied on each of the selected drugs with the best ligands separately and using a more accurate RMSD algorithm.
 
  The docking of COVID-19 major protease (6LU7) with 17 selected drugs resulted in four FDA approved viral antiprotease drugs (Temoporfin, Simeprevir, Cobicistat, Ritonavir) showing the best docking scores.