Does Hypofractionated Radiotherapy Regimens Increase the Vulnerability to SARS-COV-2 by Influencing ACE-2 Activity?

In the context of the novel Coronavirus pandemic due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the management of patients with cancer constitutes a real challenge. These patients are more likely to be immunocompromised due to the underlying malignancy or anticancer treatments. As a consequence, they are more at risk of contracting this virus and tend to show a higher rate of fatal cases. In order to reduce the risk of this pandemic among patients and health care professionals, oncologists are currently proposing hypofractionated radiotherapy regimens using higher doses per fraction, thus shortening treatment courses and saving treatment visits. Since higher doses of radiation may also increase the ACE/ACE2 activity, which has been identified as a key SARS-CoV-2 receptor, this paper raises the question of whether hypofractionated radiotherapy regimens further increase the infectivity of these already vulnerable patients.Copyright © 2021 Bentham Science Publishers.

Efficient Coronavirus Herd Immunity Optimizer for the UAV Base Stations Placement Problem

This paper proposes an improved version of the Coronavirus Herd Immunity Optimizer (CHIO) algorithm, called RFDB-CHIO, for solving the Unmanned Aerial vehicle carried Base Stations (UAV-BSs) placement problem in 5G networks. The proposed RFDB-CHIO is based on the integration of the Roulette Fitness Distance Balance (RFDB) selection mechanism into the original CHIO algorithm. RFDB-CHIO is validated in terms of user coverage and mean coverage radius under 16 scenarios with different numbers of drones and users. The simulation results demonstrated that RFDB-CHIO obtained better results than CHIO, Whale optimization algorithm (WOA), and Grey Wolf Optimization (GWO) algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Solving the Mesh Router Nodes Placement in Wireless Mesh Networks Using Coyote Optimization Algorithm

Wireless Mesh Networks (WMNs) have rapid real developments during the last decade due to their simple implementation at low cost, easy network maintenance, and reliable service coverage. Despite these properties, the nodes placement of such networks imposes an important research issue for network operators and influences strongly the WMNs performance. This challenging issue is known to be an NP-hard problem, and solving it using approximate optimization algorithms (i.e. heuristic and meta-heuristic) is essential. This motivates our attempts to present an application of the Coyote Optimization Algorithm (COA) to solve the mesh routers placement problem in WMNs in this work. Experiments are conducted on several scenarios under different settings, taking into account two important metrics such as network connectivity and user coverage. Simulation results demonstrate the effectiveness and merits of COA in finding optimal mesh routers locations when compared to other optimization algorithms such as Firefly Algorithm (FA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), Bat Algorithm (BA), African Vulture Optimization Algorithm (AVOA), Aquila Optimizer (AO), Bald Eagle Search optimization (BES), Coronavirus herd immunity optimizer (CHIO), and Salp Swarm Algorithm (SSA).

Development of an in-house COVID-19 serology ELISA Test

Background: COVID-19 pandemic created an unprecedented demand for reagents and diagnostic tools to confirm COVID-19 cases. Thus, the development of a robust in-house diagnostic test is considered of high importance. Within a few days after exposure, the human body produces specific antibodies that recognize the surface proteins of the invading SARS-CoV-2 virus1. Therefore, virus specific immunoglobulins are neutralizing antibodies and their appearance in the blood is a good sign of immunity2. The aim of this study was to develop an in-house COVID-19 serology ELISA test to quantify induced antibody responses. This test can help identify convalescent plasma donors with high antibody titers that can be used to treat other patients. Methods: Spike protein antigen is highly expressed in SARS-CoV-23. Recombinant protein corresponding to the spike receptor-binding domain (RBD), which binds to specific antibodies circulating in COVID-19 patients' blood was used as the antigen in this colorimetric ELISA test. Briefly, a 96-microtiter well plate was coated with RBD protein, where serum dilutions were added. Antibody titers were detected using an anti-human IgG- peroxidase labelled antibody and the substrate o-phenylenediamine dihydrochloride;measured at optical density (OD) of 450 nm (Figure 1). Results: The in-house quantitative serology test was validated using serum samples collected from severe COVID-19 patients (n=282) admitted to the intensive care unit at Hamad General Hospital. Serum samples from non-COVID-19 (n=10) were used as a negative control. We detected high antibody titers in ∼90% of COVID-19 sera. In contrast, no SARS-CoV-2 specific antibodies were detected in the serum of non-infected subjects (n=6), pooled human serum collected before 2019, or Middle East Respiratory Syndrome (MERS) infected subjects (n=3) confirming the specificity and the sensitivity of this in-house serology test. Conclusion: This in-house quantitative serology test is sensitive, specific, and inexpensive. The test can address the rising issue of COVID-19 supply chain globally and foster the capacity-building efforts envisioned by Qatar University.

Delaying admission to inpatient rehabilitation worsens outcome for stroke patients: Detrimental impact of COVID-19 on stroke survivors

Introduction: Inpatient rehabilitation (IPR) is crucial to recovery after stroke. COVID-19, however, has led to delays in post-stroke admission to IPR due to transmission concerns. Objective: We evaluated the effect of time from stroke onset to IPR admission on post-stroke recovery Design: A retrospective analysis of 680 patients with acute stroke or intracerebral hemorrhage (ICH), admitted to IPR between APR-2017 and AUG-2019. Association between time from stroke onset to IPR and discharge FIM-Motor Total and FIM-Motor Total with transfers scores was studied, after adjusting for sex, age at onset, stroke severity and type. Multiple linear regression models were conducted for outcomes discharge: (FIM-Motor Total) and (FIM-Motor Total with transfers) (Table 1). Square transformations were used to satisfy model assumptions. Ordinal logistic regression models were run for outcomes discharge FIM subset scores categorized as independent (6-7), needs supervision (5), and needs assistance (1-4, reference). The primary variable of interest was days onset to IPR, adjusted for stroke severity (admit FIM subset scores), sex, stroke type and age. (Table 2). The proportional odds assumption was verified using Brant test. Results: An inverse relationship was observed between days from onset to IPR and discharge FIMMotor with and without transfers. Time from stroke onset to IPR admission was associated with decreased discharge FIM-Motor and FIM-Motor with transfers, after adjusting for other covariates. Among FIM subset discharges, an additional day also resulted in a 2-5% decrease in the odds of being more independent. Conclusion: Delays to IPR admission result in decreased motor function gains and lower chance of independence. In addition to current community education practices, acute care hospitals and IPR facilities must review their processes to remove delays. These processes include requirements for COVID disease testing and IPR acceptance policies.