COVID-19 Vaccine Development: Insights, Prospects and Challenges

This paper explores the trends, issues and challenges confronting the successful vaccine development for the novel Coronavirus disease (COVID-19). Right from the commencement of the COVID-19 pandemic, no drugs or vaccine has been developed nor approved for treating those down with COVID-19. This year, the scientific community and the vaccine industry have been asked to respond urgently to SARS-COVID-2 pandemic. Presently numerous vaccine development platforms are under process and DNA- and RNA-based platforms showing great potential followed by recombinant-subunit vaccines. Through explorative research, it was established that companies involved in COVID-19 vaccine development are facing big challenges in the scientific, economic and logistical perspectives. Amongst these challenges are distrust, misinformation, and about understanding the immune system interaction with the vaccine being developed, as well as with the pathogen itself. Adjudged as insurmountable may be too early a conclusion. The race is on and progresses are being made. Proper understanding of trends, metrics and dynamics revolving around COVID-19 vaccine development is crucial in expanding possibilities for positive results from ongoing vaccine research. In this review, we spotlight on the most recent developments in COVID-19 vaccine, including top 10 early candidates that may hit the market in next few months.

Differential of Antioxidant Ability, CD4+T Cells Count and Viral Load in HIV Infected Patients on cART in Yaounde, Cameroon

Background Decreased antioxidant ability is one of the worsening conditions in AIDS.We aimed to evaluate total antioxidant ability among others, and their variation in HIV infected patients following their CD4+T cells count and viral load, in a context of new ART scarcity in most LMICs. Material and Methods We conducted a cross sectional study on 167 individuals (76 controls, 33 treatments naïve and 58 HIV-1 infected patients on ART). We assessed their plasma total antioxidant ability (FRAP), malondialdehyde (MDA) and thiol (SH) groups using standard spectrophotometric methods, then we calculated lipid peroxidation index (LPI). Statistical analysis was performed using GraphPad Prism 6. Data were analyzed by two-tailed unpaired t-test for two groups’ comparison and ANOVA for more than two groups. Pearson correlation between CD4+T cells count, viral load and the above markers was determined; P ≤ 0.05 was considered statistically significant. Results The following controls/naïve/treated subjects’ values for FRAP(mM) (1.907±0.074/1.77±0.05/1.695±0.03); MDA(μΜ) (0.781±0.081/1.115±0.118/ 1.342±0.109); SH (μΜ) (2.747±0.130/1.582±0.197/1.498 ±0.140)and LPI (0.43±0.61/ 0.61±0.7/2.59±0.83) were all obtained with P ≤ 0.05. The FRAP increased only with 3TC+TDF+EFV and 3TC+ABC+NVP cART while MDA decrease significantly with the later(p=0.027). MDA and LPI significantly increased in heavily treated patients with p<0.0014 and p=0.0001 respectively. overall, the patients showed an increase of viral loads following a decrease of CD4+T cells (r= -0.803, p=0.016) but 3TC+TDF+EFV seem to better manage the both. The only significant correlation was established between SH groups and CD4+Tcells count (r=0.447; p=0.0006); Conclusion Our study showed that thiol groups may be protective againstCD4+Tcells count depletion and that the cART 3TC+TDF+EFV, 3TC+ABC+NVP may be helpful in fighting against free radical generation and particularly 3TC+TDF+EFV as controlling CD4+Tcells count and viral load in long term treated patients. The study particularly showed the implication of cART in increasing lipid peroxidation index following the treatment duration in heavily treated patients, which aggravated their conditions in an area where drug options are limited, calling for new drugs availability and personalized medicine.

Adaptive Artificial Passive Immunity as a Suggested Strategy for Treatment of COVID-19 Critical Cases

Currently, the emergence of a novel human corona virus, SARS-CoV-2, has become a global health concern causing severe respiratory tract infections in humans. Human-to-human transmissions have been described with incubation times between 2-14 days, facilitating its spread via droplets, contaminated hands or surfaces, resulting in high spread and death rates according to date, time and place of infection. We therefore reviewed the literature on all available information about the treatment of the cases, especially critical cases to decrease the mortality rate, the spread and incubation time of the virus by using the adaptive artificial passive immunity (anti-bodies from fully recovered patients with COVID-19).

Using Human Development Indices to Identify Indicators to Monitor the Corona Virus Pandemic

Introduction The Corona virus (CoVID-19) pandemic has hit the most developed countries and has thence spread to inflict other countries around the world. It is the first pandemic that appears in countries not linked to poverty and poor hygiene. Aim To study the relationship between human development and the pattern of the pandemic caused by the CoVID-19 and to identify development indicators that can be useful in monitoring the pandemic. Methods Data collected included confirmed cases of CoVID-19 by country, number of cases that recovered and cases that died and population density per million in this particular country. The data for this information was obtained from the online data on the daily reports on CoVID-19 from the different countries. Data for the Human Development index (HDI) and the ranking for each country were obtained from the most recent United Nations Development of Populations (UNDP) report for 2019. We analyzed data for 166 countries for which the HDI was available for the date of cases reported online on 27th March, 2020 at midnight. Findings There were significant differences by ANOVA for the confirmed cases of CoVID19 cases and total cases per one million population between the countries in the 4 tier group of Human Development. HDI was significantly correlated with confirmed cases, case density and cases that died from CoVID-19 (P<0.01) for all countries but the significance decreased by tier group. Country ranking was inversely correlated with confirmed cases of CoVID-19 (r-0.25 at P=0.001), CoVID-19 cases per million (r-0.4 at P=0.000) and cases that died from CoVID-19 (r-0.2 at P=0.03). Recovery was not inked to HDI or country ranking. The upper HDI tier groups (very high, high and medium) showed significant correlations with total cases per one million population P<0.05, but no correlation was found with confirmed cases or cases that died or recovered from CoVID-19 P>0.05. Conclusions Total cases of CoVID-19 per one million population seems to be a better indicator of the pandemic. The pattern of spread is closely linked to industry.

Quantitative Computational Prediction of the Consensus B-cell Epitopes of 2019-nCoV

The goal of this paper is to obtain the numerical consensus of B cell epitopes from the three-dimensional structure of the prefusion spike glycoprotein of the new betacoronavirus that could lead to the development of a vaccine to 2019-nCoV. In order to do that, we first calculated the B-cell epitopes that are predicted using fourteen different mathematical algorithms. Later, we obtained the consensus of B-cell epitopes according to the Similarity Index, and finally selecting the best candidates according to the results of a function called <F> which is evaluated for the glycoprotein. The best candidates that we obtained in order to design a vaccine are SSANNCT, PLQSYGFQPT, TESNKKFLP, NNSYEC, AENS, LPDPSK and YDPLQPE.

Recent New Results and Achievements of California South University (CSU) BioSpectroscopy Core Research Laboratory for COVID-19 or 2019-nCoV Treatment: Diagnosis and Treatment Methodologies of “Coronavirus”

Coronavirus nanoparticles show a strong peak of Plasmon absorption in ultraviolet–visible zone. A strong interaction exists between the surface of Coronavirus nanoparticles and Bcr–Abl tyrosine–kinase inhibitors (TKI) such as Imatinib (STI571), Nilotinib (AMN107), Dasatinib (BMS–345825), Bosutinib (SKI–606), Ponatinib (AP–24534) and Bafetinib (INNO–406). Bcr–Abl tyrosine–kinase inhibitors (TKI) such as Imatinib (STI571), Nilotinib (AMN107), Dasatinib (BMS–345825), Bosutinib (SKI–606), Ponatinib (AP–24534) and Bafetinib (INNO–406) cause to aggregation of Coronavirus nanoparticles linked to DNA/RNA and hence, lead to widening of peak Plasmon of Coronavirus nanoparticles surface at 550 (nm) and emerging a new peak at higher wavelength. In the current project, this optical characteristic of Coronavirus nanoparticles is used to time investigate of interaction between different Bcr–Abl tyrosine–kinase inhibitors (TKI) such as Imatinib (STI571), Nilotinib (AMN107), Dasatinib (BMS–345825), Bosutinib (SKI–606), Ponatinib (AP–24534) and Bafetinib (INNO–406) and Coronavirus nanoparticles. The results were shown that Bcr–Abl tyrosine–kinase inhibitors (TKI) such as Imatinib (STI571), Nilotinib (AMN107), Dasatinib (BMS–345825), Bosutinib (SKI–606), Ponatinib (AP–24534) and Bafetinib (INNO–406) with shorter chain length interact faster with Coronavirus nanoparticles. Therefore, a simple and fast method for identification of Bcr–Abl tyrosine–kinase inhibitors (TKI) such as Imatinib (STI571), Nilotinib (AMN107), Dasatinib (BMS–345825), Bosutinib (SKI–606), Ponatinib (AP–24534) and Bafetinib (INNO–406) with various chain length using red shift in surficial Plasmon absorption is presented.