Development of a recombinant Newcastle disease virus-vectored vaccine for infectious bronchitis virus variant strains circulating in Egypt

Infectious bronchitis virus (IBV) causes a major disease problem for the poultry industry worldwide. The currently used live-attenuated vaccines have the tendency to mutate and/or recombine with circulating field strains resulting in the emergence of vaccine-derived variant viruses. In order to circumvent these issues, and to develop a vaccine that is more relevant to Egypt and its neighboring countries, a recombinant avirulent Newcastle disease virus (rNDV) strain LaSota was constructed to express the codon-optimized S glycoprotein of the Egyptian IBV variant strain IBV/Ck/EG/CU/4/2014 belonging to GI-23 lineage, that is prevalent in Egypt and in the Middle East. A wild type and two modified versions of the IBV S protein were expressed individually by rNDV. A high level of S protein expression was detected in vitro by Western blot and immunofluorescence analyses. All rNDV-vectored IBV vaccine candidates were genetically stable, slightly attenuated and showed growth patterns comparable to that of parental rLaSota virus. Single-dose vaccination of 1-day-old SPF White Leghorn chicks with the rNDVs expressing IBV S protein provided significant protection against clinical disease after IBV challenge but did not show reduction in tracheal viral shedding. Single-dose vaccination also provided complete protection against virulent NDV challenge. However, prime-boost vaccination using rNDV expressing the wild type IBV S protein provided better protection, after IBV challenge, against clinical signs and significantly reduced tracheal viral shedding. These results indicate that the NDV-vectored IBV vaccines are promising bivalent vaccine candidates to control both infectious bronchitis and Newcastle disease in Egypt.https://doi.org/10.1186/s13567-019-0631-

Spectroscopic, crystal structural, theoretical and biological studies of phenylacetohydrazide Schiff base derivatives and their copper complexes

Two phenylacetohydrazide Schiff base derivatives: N’-(1-(2-hydroxyphenyl)ethylidene)-2-phenylacetohydrazide, HL1, and N’-((1-hydroxynaphthalen-2-yl)methylene)-2-phenylacetohydrazide, HL2, were synthesized. HL1 dimerizes in presence of HCl, probably via radical mechanism to give (2,2’-((1E)-hydrazine-1,2-diylidenebis(ethan-1-yl-1-ylidene))diphenol (DIM). Thermal reactions of Cu(II) ions with the two Schiff base ligands resulted in formation of the binuclear complexes [(CuL1)2] and [(CuL2)2]. The stoichiometry and structures of the reported compounds were investigated by several spectroscopic and analytical techniques. The structure of the HL1 ligand and its complex [(CuL1)2] as well as the DIM derivative were analyzed by single crystal X-ray analysis. The X-ray analysis revealed the binuclear coordination of the copper complex with the formation of five- and six-membered rings with every ligand. The molecular geometries of the ligands and their copper complexes were investigated using the DFT‐B3LYP/GENECP level of theory. The optimized structures of the studied complexes are consistent with the finding of the X-ray analysis. The quantum, non-quantum global reactivity descriptors and the non-linear optical properties were calculated. Biological studies including, antimicrobial and antioxidant activities of the complexes along with fluorescence quenching studies and viscosity measurements are carried out. The molecular docking of the two ligands and [(CuL2)2] complex is also reported. The different biological studies as well as molecular docking are correlated to each other and supported the fact that the complexes can bind to DNA via intercalative mode and showed a various DNA binding potency.peerReviewe

Spatio Prediction of Soil Capability Modeled with Modified RVFL Using Aptenodytes Forsteri Optimization and Digital Soil Assessment Technique

To meet the needs of Egypt’s rising population, more land must be cultivated. Land evaluation is vital to achieving sustainable agricultural production. To determine the soil capability in the northeast Nile Delta region of Egypt, the present study introduces a new form of integration between the Agriculture Land Evaluation System (ALES Arid) model and the machine learning (ML) approach. The soil capability indicators required for the ALES Arid model were determined for the 47 collected soil profiles covering the study area. These indicators include soil pH, soil salinity, the sodium adsorption ratio (SAR), the exchangeable sodium percentage (ESP), the organic matter (OM) content, the calcium carbonate (CaCO3) content, the gypsum content, the clay percentage, and the slope. The ALES Arid model was run using these indicators, and soil capability indexes were obtained. Using GIS, these indexes helped to classify the study area into four capability classes, ranging from good to very poor soils. To predict the soil capability, three machine learning algorithms named traditional RVFL, sine cosine algorithm (SCA), and AFO were also applied to the same soil criteria. The developed ML method aims to enhance the prediction of soil capability. This method depends on improving the performance of Random Vector Functional Link (RVFL) using an optimization technique named Aptenodytes Forsteri Optimization (AFO). The operators of AFO were used to determine the best parameters of RVFL since traditional RVFL is sensitive to parameters. To assess the performance of the developed AFO-RVFL method, a set of real collected data was used. The experimental results illustrate the high efficacy of AFO-RVFL in the spatial prediction of soil capability. The correlations found in this study are critical for understanding the overall techniques for predicting soil capability

Spatio Prediction of Soil Capability Modeled with Modified RVFL Using Aptenodytes Forsteri Optimization and Digital Soil Assessment Technique

To meet the needs of Egypt’s rising population, more land must be cultivated. Land evaluation is vital to achieving sustainable agricultural production. To determine the soil capability in the northeast Nile Delta region of Egypt, the present study introduces a new form of integration between the Agriculture Land Evaluation System (ALES Arid) model and the machine learning (ML) approach. The soil capability indicators required for the ALES Arid model were determined for the 47 collected soil profiles covering the study area. These indicators include soil pH, soil salinity, the sodium adsorption ratio (SAR), the exchangeable sodium percentage (ESP), the organic matter (OM) content, the calcium carbonate (CaCO3) content, the gypsum content, the clay percentage, and the slope. The ALES Arid model was run using these indicators, and soil capability indexes were obtained. Using GIS, these indexes helped to classify the study area into four capability classes, ranging from good to very poor soils. To predict the soil capability, three machine learning algorithms named traditional RVFL, sine cosine algorithm (SCA), and AFO were also applied to the same soil criteria. The developed ML method aims to enhance the prediction of soil capability. This method depends on improving the performance of Random Vector Functional Link (RVFL) using an optimization technique named Aptenodytes Forsteri Optimization (AFO). The operators of AFO were used to determine the best parameters of RVFL since traditional RVFL is sensitive to parameters. To assess the performance of the developed AFO-RVFL method, a set of real collected data was used. The experimental results illustrate the high efficacy of AFO-RVFL in the spatial prediction of soil capability. The correlations found in this study are critical for understanding the overall techniques for predicting soil capability

Comparison of genomic and antigenic properties of Newcastle Disease virus genotypes II, XXI and VII from Egypt do not point to antigenic drift as selection marker

Newcastle disease (ND), caused by avian orthoavulavirus type-1 (NDV), is endemic in poultry in many regions of the world and causes continuing outbreaks in poultry populations. In the Middle East, genotype XXI, used to be present in poultry in Egypt but has been replaced by genotype VII. We investigated whether virus evolution contributed to superseding and focussed on the antigenic sites within the hemagglutinin-neuraminidase (HN) spike protein. Full-length sequences of an NDV genotype VII isolate currently circulating in Egypt was compared to a genotype XXI isolate that was present as co-infection with vaccine-type viruses (II) in a historical virus isolated in 2011. Amino acid differences in the HN glycoprotein for both XXI and VII viruses amounted to 11.7% and 11.9%, respectively, compared to the La Sota vaccine type. However, mutations within the globular head (aa 126-570), bearing relevant antigenic sites, were underrepresented (a divergence of 8.8% and 8.1% compared to 22.4% and 25.6% within the protein domains encompassing cytoplasmic tail, transmembrane part and stalk regions (aa 1-125) for genotypes XXI and VII, respectively). Nevertheless, reaction patterns of HN-specific monoclonal antibodies inhibiting receptor binding revealed differences between vaccine-type viruses and genotype XXI and VII viruses for epitopes located in the head domain. Accordingly, compared to Egyptian vaccine-type isolates and the La Sota vaccine reference strain, single aa substitutions in 6 of 10 described neutralizing epitopes of HN were found. However, the same alterations in neutralization sensitive epitopes were present in old genotype XXI as well as in newly emerged genotype VII isolates. In addition, isolates were indistinguishable by polyclonal chicken sera raised against different genotypes including vaccine viruses. These findings suggest that factors other than antigenic differences within the HN protein account for facilitating the spread of genotype VII versus genotype XXI viruses in Egypt

The Effect of Obesity on Pregnancy and its Outcome in the Population of Oman, Seeb Province

Objectives: The World Health Organization estimated that in 2011 worldwide 1.6 billion adults were overweight, and 400 million were obese. The obesity epidemic is a documented phenomenon and Oman is no exception. The aim of this study was to determine the effect of obesity on pregnancy and its prenatal and neonatal outcomes. Methods: A prospective cohort study was carried out among pregnant Omani women attending antenatal clinics in their first trimester in the Seeb province of Muscat, Oman. Results: A total of 700 pregnant women were enrolled in the study and were categorized according to their body mass index: 245 (35%) were normal weight, 217 (31%) were overweight, and 238 (34%) were obese. The relative risk (RR) of cesarean section among obese women compared to women of normal weight was 2.1 (95% confidence interval (CI) 1.2–3.2) and of overweight women was 1.4 (95% CI 0.9–2.3). The risk of elective cesarean section increased to 7.5 (95% CI 1.7–32.8) in obese women and was statistically significant in the obese group. In this study, 100 women (15.7%) developed gestational diabetes (11.8% of normal weight women, 17.8% of overweight women, and 17.9% of obese women). Miscarriages were more common among obese women 11.9% (n = 27) compared to the normal weight and overweight groups (6.7% and 9.4%, respectively). There was a weak yet statistically significant correlation between birth weight and body mass index. The risk of macrosomia was significantly higher in obese women compared to normal weight women. To evaluate the sensitivity of the oral glucose challenge test (OGCT), the oral glucose tolerance test (OGTT) was measured in 203 participants (29%) who had a normal OGCT result. It was found that 14.5% of overweight women and 13.5% of normal weight women had an abnormal OGTT result even when their OGCT result was normal.  Conclusions: Obesity is associated with an increased risk of cesarean section (especially elective cesarean), gestational hypertension, macrosomia, and miscarriage. It also increases the risk of gestational diabetes

Comparison of SARS-Cov-2 omicron variant with the previously identified SARS-Cov-2 variants in Egypt, 2020–2022: insight into SARS-Cov-2 genome evolution and its impact on epidemiology, clinical picture, disease severity, and mortality

Abstract Background The o severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic has killed millions of people and caused widespread concern around the world. Multiple genetic variants of SARS-CoV-2 have been identified as the pandemic continues. Concerns have been raised about high transmissibility and lower vaccine efficacy against omicron. There is an urgent need to better describe how omicron will impact clinical presentation and vaccine efficacy. This study aims at comparing the epidemiologic, clinical, and genomic characteristics of the omicron variant prevalent during the fifth wave with those of other VOCs between May 2020 and April 2022. Methods Epidemiological data were obtained from the National Electronic Diseases Surveillance System. Secondary data analysis was performed on all confirmed COVID-19 patients. Descriptive data analysis was performed for demographics and patient outcome and the incidence of COVID-19 was calculated as the proportion of SARS-CoV-2 confirmed patients out of the total population of Egypt. Incidence and characteristics of the omicron cohort from January- April 2022, were compared to those confirmed from May 2020-December 2021. We performed the whole-genome sequencing of SARS-CoV-2 on 1590 specimens using Illumina sequencing to describe the circulation of the virus lineages in Egypt. Results A total of 502,629 patients enrolled, including 60,665 (12.1%) reported in the fifth wave. The incidence rate of omicron was significantly lower than the mean of incidences in the previous subperiod (60.1 vs. 86.3/100,000 population, p < 0.001). Symptoms were reported less often in the omicron cohort than in patients with other variants, with omicron having a lower hospitalization rate and overall case fatality rate as well. The omicron cohort tended to stay fewer days at the hospital than did those with other variants. We analyzed sequences of 2433 (1590 in this study and 843 were obtained from GISAID platform) Egyptian SARS-CoV-2 full genomes. The first wave that occurred before the emergence of global variants of concern belonged to the B.1 clade. The second and third waves were associated with C.36. Waves 4 and 5 included B.1.617.2 and BA.1 clades, respectively. Conclusions The study indicated that Omicron-infected patients had milder symptoms and were less likely to be hospitalized; however, patients hospitalized with omicron had a more severe course and higher fatality rates than those hospitalized with other variants. Our findings demonstrate the importance of combining epidemiological data and genomic analysis to generate actionable information for public health decision-making