The rapid spread of novel coronavirus disease
(COVID19) throughout the world without available
specific treatment or vaccine necessitates alternative
options to contain the disease. Historically, children
and pregnant women were considered high-risk
population of infectious diseases but rarely have been
spotlighted nowadays in the regular COVID-19
updates, may be due to low global rates of incidence,
morbidity, and mortality. However, complications did
occur in these subjects affected by COVID-19. We
aimed to explore the latest updates of
immunotherapeutic perspectives of COVID-19
patients in general population and some added details
regarding pediatric and obstetrical practice.
Immune system boosting strategy is one of the
recently emerging issues allowing the body defense
mechanism to produce virus-neutralizing antibodies to
counteract the viral impacts on multiple organ
damage. Measles vaccination (which is universally
used for children in many countries, but
contraindicated during pregnancy) could urge the
body to produce these antibodies which may apply
their effects through cross-reactivity of measles
vaccine and COVID-19 antigenic proteins. In
addition, intravenous immunoglobulin and
convalescent plasma could have such neutralizing
antibody effect leading to clinical improvement and
viral elimination. Pediatric and obstetrical experience
has appeared in previous publications.
Human monoclonal antibodies are the future
promising approach to treat and prevent COVID-19
with the use of tocilizumab in recent studies. Pediatric
data are still in progress while no pregnancy ongoing
trials are planned up to date.
The better understanding of the host antiviral response
may pave the way to develop immunotherapeutic
plans against COVID-19 in the near upcoming days.
The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from
... Show MoreThe purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.
The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.
The qualified subjects for this study included 33 patients with benign and malignant oral tumors aged 15-75 years and 31 matched age and gender healthy subjects used as control. Proteins measurements included total protein, albumin, globulines in sera and saliva samples, and immunoglobulins (IgG, IgM, IgA) in sera samples of control and patients. Meanwhile, polyacrylamide gel electrophoresis (PAGE) was used to differentiate between protein patterns in both serum and saliva samples among the studied groups. The gel was also stained for glycoprotein to evaluate as well the changes in glycoprotein contents. For total protein, the results revealed a signifigant increase (P?0.01) in both samples (serum and saliva) of patient group. Albumin conce
... Show MoreSince the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave.
This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected
Profound maternal hemodynamic changes occur in order to satisfy the demands of a growing foetus. Early in pregnancy, peripheral vascular resistance (PVR) lowers, generating a considerable rise in cardiac output. Many parameters are employed for measuring the LV systolic function with different echocardiographic modalities including: M-Mode echocardiography, two-dimensional echocardiography, three-dimensional echocardiography, tissue doppler imaging.
In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.
... Show MoreThe emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA
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