Robust acidic pH and digestive enzyme stability of anti-SarsCov2 IgY antibodies: Implications for treatment of viral transmission thru gastrointestinal, ocular, nasal and skin tissues (preprint)

There are many paths for the transmission of SarsCov2 virus. The main routes are nasal and oral and the droplets carrying the virus can also be transmitted thru ocular and skin tissues. The gastrointestinal (small intestine), nasal, ocular and skin tissues all present an acidic pH milieu and therefore any treatment with antibodies thru these routes has to have the antibodies remain active at acid pH as well as be resistant to typical protease digestion. To this end we profiled our anti-SarasCov2 receptor binding domain IgY antibodies for retention of activity at acidic and basic pHs and trypsin digestion. We find that the IgY are strongly resistant to denaturation at acid pH as well as not digested by trypsin. Our data strongly support the use of these IgY in treatment of viral transmission thru the GI, nasal, ocular and skin all tissues where the pH is acidic. We also provide an enabling platform to rapidly asses the suitability of any antibody or protein therapeutic for use at acidic pH.

Metformin an anti-diabetic drug, possess ACE-2 receptor-SARS- Cov-2 RBD binding antagonist activity, anti-inflammatory and cytokine inhibitory properties suitable for treatment of COVID-19 (preprint)

Metformin is a widely used and is a safe anti-diabetic drug. It has also been shown to have anti-inflammatory and anti-viral activities in humans and animal models. Specifically we explored its activity in SARS-CoV-2 initiated COVID19 disease. Here we show that metformin 1. blocks the binding of SARS-CoV-2 spike protein receptor binding domain RBD to human ACE2 receptor 2. We also show that it has anti-inflammatory effects and reduces cytokine secretion as well as blocks the recruitment of monocytes to endothelial cells 3. Finally we show its activity in a hamster in vivo model of SARS-CoV-2 infection as a nasal formulation. Based on the safety and the therapeutic properties relevant to COVID-19 it is feasible to propose a nasal spray of metformin that can be used in treatment of this disease. A nasal spray would deliver the drug to the target organ lung and spare other organs which get exposed upon oral dosing.

Differential Activity of Repurposed Drugs as Receptor Binding Domain Antagonists for Omicron and Native Strains of SarsCov2 (preprint)

Omicron strain is the latest variant of concern of SarsCov2 virus. The mutations in this strain in the S protein Receptor Binding domain (RBD) enable it to be more transmissible as well as escape neutralizing activity by antibodies in response to vaccine. Thus, Omicron specific strategies are need to counter infection by this strain. We investigated a collection of approved drugs shown to antagonize the binding of native strain RBD to human ACE2, for their ability to antagonize binding to Omicron strain RBD. While most of the drugs the drugs that antagonize binding to native RBD are also active for Omicron RBD but some were inactive, namely drugs that contain iodine are completely inactive against Omicron RBD. Our data strongly indicate that presence of a single iodine molecule in the drug renders it inactive against Omicron strain. Thus, there is molecular specificity of drugs for antagonizing Omicron strain RBD versus native strain RBD of this virus. Such information will pave way for specific drugs for Omicron. A pragmatic message from our data is that the often-used iodine containing mouth wash and rises may be ineffective in antagonizing receptor binding of Omicron strain.

A scrutiny on covid-19 detection using convolutional neural network and image processing

The world is facing pandemics as Coronavirus is spreading wide far and wide every country rapidly since late 2019, that infect not alone human but put in concert animals. Associate outsize type of people area unit affected at intervals several aeon from the first detail and it remainexpanding everylocationover the world. The factors rather like the speed of infection and spreading area unit very high. it's calculable that in Asian nation the speed of spreading is 1:14, which means the virus unfold from one covid patient to 14 others returning involved with him/her. The services offered by most post-covid-19 clinics at intervals the govt. sector embrace checking the vital parameters and body mass index, ECG, blood test, CT scan, supermolecule testing, etc. The foremost drawback is that the testing a private with of those services to sight covid-19 may be a protracted technique, and if the results once that check go positive then the patient should be in quarantine for 2 weeks/14 days or further. A clinical Investigation of CORONA VIRUS contaminatedcase has exposed that these sorts of sufferers area unit mainly sick with internal organ infection once getting exposed to the COVID. This study is geared toward making economical deep learning models, skilled with upper body X-ray pictures, intended forquicktransmission of COVID sufferers. We have a tendency to used publically out there upper body X ray pictures of grown-up COVID sufferers for the event of computing primarily groundcategorization models for CORONA VIRUS and different significantmicrobes. To extend the dataset amount and enlargewidespread models, we have a tendency to performed twenty five differing types of augmentations on the first pictures. More-over, we have a tendency to utilised the transfer learning move toward for the coaching and examining of the categorization models. The fusion of 2 finest acting models exhibited the best calculationcorrectness for traditional, CORONA, non CORONA, pneumonia, and TB pictures.Artificial Intelligence primarily based categorization models learnedfrom side to side with the transfer learning advance will with efficiency categorize the upper body X ray pictures representing premeditatedmalady. This technique is a lot of economical than antecedently revealed strategies. it's single step in front towards the accomplishment of AI primarily grounded strategies for categorization issues in medical specialty picturing associated with CORONA.The majoraspire of the project be sight the virusin the company of the chest X-ray of the patients. Artificial Intelligent, Deep Learning, Machine Learning, data Science area unit variety of the modern technologies that have a super scope at intervals this state takes location.Deep learning provides a useful analysis to review chest x-ray flick for screening covid-19. A Convolutional neural network may be a DL model, most commonly applied to analyzing a plain image. Flick of the covid patient, disease infected patient, and healthy person X-rays square measure progressing to be the information for work and testing the model.Detection coronavirus with the model can facilitate in getting the results previous graphical record and thereby helps in stop the unfold, designation of the illness, medicine& antigen detection, management and plenty of further. © 2021 Universitatea de Vest Vasile Goldis din Arad. All rights reserved.