Brucellosis is one of the most important worldwide zoonoses of many countries including Egypt. Camel brucellosis has not gained much attention in Egypt yet. This study is focused on the three governorates with the highest camel populations and the largest camel markets in the country to determine the disease seroprevalence and identify the Brucella species in local camel holdings. In total, 381 serum samples were collected from male and female camels from Giza, Aswan, and Al-Bahr Al-Ahmar (the Red Sea) governorates. Samples were serologically examined using the Rose–Bengal plate test (RBPT), indirect ELISA (i-ELISA), competitive ELISA (c-ELISA) and complement fixation test (CFT). Brucella antibodies were detected in 59 (15.5%), 87 (22.8%), 77 (20.2%) and 118 (31.0%) of sera by RBPT, i-ELISA, c-ELISA and CFT, respectively. Using real-time PCR, Brucella DNA was amplified in 32 (8.4%) seropositive samples including Brucella abortus (25/32), Brucella suis (5/32) and Brucella melitensis (2/32), defining a complex epidemiological status. To the best of our knowledge, this is the first study reporting Brucella suis DNA in camel serum. The risk-associated factors including age, sex, breed and geographical distribution were statistically analyzed, showing non-significant association with seroprevalence. The results of this study will raise awareness for camel brucellosis and help develop effective control strategies.

Brucellosis is a highly contagious zoonosis that occurs worldwide. Whole-genome sequencing (WGS) has become a widely accepted molecular typing method for outbreak tracing and genomic epidemiology of brucellosis. Twenty-nine Brucella spp. (eight B. abortus biovar 1 and 21 B. melitensis biovar 3) were isolated from lymph nodes, milk, and fetal abomasal contents of infected cattle, buffaloes, sheep, and goats originating from nine districts in Egypt. The isolates were identified by microbiological methods and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Differentiation and genotyping were confirmed using multiplex PCR. Illumina MiSeq® was used to sequence the 29 Brucella isolates. Using MLST typing, ST11 and ST1 were identified among B. melitensis and B. abortus, respectively. Brucella abortus and B. melitensis isolates were divided into two main clusters (clusters 1 and 2) containing two and nine distinct genotypes by core-genome SNP analysis, respectively. The genotypes were irregularly distributed over time and space in the study area. Both Egyptian B. abortus and B. melitensis isolates proved to be genomically unique upon comparison with publicly available sequencing from strains of neighboring Mediterranean, African, and Asian countries. The antimicrobial resistance mechanism caused by mutations in rpoB, gyrA, and gyrB genes associated with rifampicin and ciprofloxacin resistance were identified. To the best of our knowledge, this is the first study investigating the epidemiology of Brucella isolates from livestock belonging to different localities in Egypt based on whole genome analysis.

Bovine brucellosis is a global zoonosis of public health importance. It is an endemic disease in many developing countries including Pakistan. This study aimed to estimate the seroprevalence and molecular detection of bovine brucellosis and to assess the association of potential risk factors with test results. A total of 176 milk and 402 serum samples were collected from cattle and buffaloes in three districts of upper Punjab, Pakistan. Milk samples were investigated using milk ring test (MRT), while sera were tested by Rose–Bengal plate agglutination test (RBPT) and indirect enzyme-linked immunosorbent assay (i-ELISA). Real-time PCR was used for detection of Brucella DNA in investigated samples. Anti-Brucella antibodies were detected in 37 (21.02%) bovine milk samples using MRT and in 66 (16.4%) and 71 (17.7%) bovine sera using RBPT and i-ELISA, respectively. Real-time PCR detected Brucella DNA in 31 (7.71%) from a total of 402 bovine sera and identified as Brucella abortus. Seroprevalence and molecular identification of bovine brucellosis varied in some regions in Pakistan. With the use of machine learning, the association of test results with risk factors including age, animal species/type, herd size, history of abortion, pregnancy status, lactation status, and geographical location was analyzed. Machine learning confirmed a real observation that lactation status was found to be the highest significant factor, while abortion, age, and pregnancy came second in terms of significance. To the authors' best knowledge, this is the first time to use machine learning to assess brucellosis in Pakistan; this is a model that can be applied for other developing countries in the future. The development of control strategies for bovine brucellosis through the implementation of uninterrupted surveillance and interactive extension programs in Pakistan is highly recommended.

Abstract. The present work reports our attempt in developing an EnglishArabic bi-directional Machine Translation (MT) tool in the agriculture domain. It aims to achieve automated translation of expert systems. In particular, we describe the translation of knowledge base, including, prompts, responses, explanation text, and advices. In the central laboratory for agricultural expert systems, this tool is found to be essential in developing bi-directional (EnglishArabic) expert systems because both English and Arabic versions are needed for development, deployment, and usage purpose. The tool follows the rulebased transfer MT approach. A major design goal of this tool is that it can be used as a stand-alone tool and can be very well integrated with a general (English-Arabic) MT system for Arabic scientific text. The paper also discusses our experience with the developed MT system and reports on results of its application on real agricultural expert systems.

Staphylococcus aureus is a commensal resident of the skin and nasal cavities of humans and can cause various infections. Some toxigenic strains can contaminate food matrices and cause foodborne intoxications. The present study aimed to provide relevant information (clonal complex lineages, agr types, virulence and antimicrobial resistance-associated genes) based on DNA microarray analyses as well as the origins and dissemination of several circulating clones of 60 Staphylococcus aureus isolated from food matrices (n = 24), clinical samples (n = 20), and nasal carriers (n = 16) in northern Algeria. Staphylococcus aureus were genotyped into 14 different clonal complexes. Out of 60 S. aureus, 13 and 10 isolates belonged to CC1-MSSA and CC97-MSSA, respectively. The CC 80-MRSA-IV was the predominant S. aureus strain in clinical isolates. The accessory gene regulator allele agr group III was mainly found among clinical isolates (70.4%). Panton–Valentine leukocidin genes lukF/lukS-PV were detected in 13.3% of isolates that all belonged to CC80-MRSA. The lukF/S-hlg, hlgA, and hla genes encoding for hemolysins and leucocidin components were detected in all Staphylococcusaureus isolates. Clinical and food isolates harbored more often the antibiotic resistance genes markers. Seventeen (28.3%) methicillin-resistant Staphylococcus aureus carrying the mecA gene localized on a SCCmec type IV element were identified. The penicillinase operon (blaZ/I/R) was found in 71.7% (43/60) of isolates. Food isolates belonging to CC97-MSSA carried several antibiotic resistance genes (blaZ, ermB, aphA3, sat, tetM, and tetK). The results of this study showed that all clones were found in their typical host, but interestingly, some nasal carriers had isolates assigned to CC705 thought to be absent in humans. The detection of MRSA strains among food isolates should be considered as a potential public health risk. Therefore, controlling the antibiotics prescription for a rational use in human and animal infections is mandatory.

Neurexin1 (NRXN1) gene is playing an important role in synaptic formation, plasticity and maturity. Studies have reported non-synonymous SNPs in NRXN1 in patient with mental disorders. The current work is applying computational tools on recoded NRXN1 SNPs in mental disorder patients. The aim of the work is to identify deleterious SNPs, determine damaged protein features (function, stability) and recognise potential protein regions for future research. The effect on protein function is predicted by PROVEAN, SIFT and PolyPhen-2 while protein stability is predicted by MUpro and I-Mutant2.0. Prediction results have identified 2 SNPs to be deleterious by all tools. Higher deleterious results in the stability tools with the percentages of 72%, 78% than the function tools with 25%, 41% and 47%. Agreement percentage of deleterious prediction between stability tools was 56% while 12.5% in the function tools. The identified regions of NRXN1 for future research are SP and LNS4.

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Neurexin1 gene is essential for formulating synaptic cell adhesion to establish synapses. In a previous work, 38 SNPs in Neurexin1 recoded in mental disorder patients have been collected. Five computational prediction tools have been used to predict the effect of SNPs on protein function and stability. Only four SNPs in Neurexin1α have deleterious prediction results from at least four tools. The current work aims to use molecular dynamic simulation (MD) to study the effects of the four mutations on Neurexin1α both on the whole protein as well as identifying affected domains by mutations. A protein model that consists of five domains out of six domains in the real protein was used; missing residues were added, and model was tested for quality. The MD experiment has last for 1.5 μs where four parameters have been used for studying the whole protein in addition to three more parameters for the domain analysis. The whole protein study has shown that two mutations E427I for Autism and R525C for non-syndromic intellectual disability (NSID) have distinctive behavior across the four used parameters. Domain study has confirmed the previous results where the five domains of R525C have acted differently from wild type (WT), while E427I has acted differently for four domains from wild type. The other two mutations D104H and G379E have three domains that only acted differently from wild type. The fourth domain of all mutations has an obvious distinctive behavior from wild type. Further study of E427I and R525C mutations can lead to better understanding of autism and NSID.