The current study was carried out to evaluate the phenotypic and genotypic characterization of avian pathogenic recovered from Riyadh, Saudi Arabia. During the period of 10th February-30th May 2015, 70 strains were isolated from chicken farms located in Riyadh, Saudi Arabia. All strains were tested phenotypically by standard microbiological techniques, serotyped and the virulence genes of such strains were detected by polymerase chain reaction (PCR). Most of the recovered strains from chickens belonged to serotype O111:K58 25 strains (35.7%), followed by serotype O157:H7 13 strains (18.57%), followed by serotype O114:K90 10 strains (14.29%), then serotype O126:K71 9 strains (12.9%), serotype O78:K80 8 strains (11.43%) and in lower percentage serotype O114:K90 and O119:K69 5 strains (7.14%). The virulence genotyping of isolates recovered from broilers revealed the presence of the gene in all the field isolates (6 serovars) examined in an incidence of 100%, as well as the gene was also present in all field isolates (6 serovars), while the gene and the gene were detected in 5 out of 6 field serovars in an incidence of 81.43% and 64.29%, respectively. Phenotypical examination of the other virulence factors revealed that 65 isolates were hemolytic (92.9%), as well as 15 isolates (21.42%) were positive for enterotoxin production. Meanwhile, 21 isolates (30%) were positive for verotoxin production, 58 isolates (82.86%) for the invasiveness and 31 isolates (44.29%) for Congo red binding activities of the examined serotypes.
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http://dx.doi.org/10.1016/j.sjbs.2015.11.011 | DOI Listing |
BMC Plant Biol
January 2025
Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, P.O. Box 15551, Al Ain, Abu Dhabi, United Arab Emirates.
This study investigated the effects of non-thermal atmospheric plasma (NTAP) treatment on the growth, chemical composition, and biological activity of geranium (Pelargonium graveolens L'Herit) leaves. NTAP was applied at a frequency of 13.56 MHz, exposure time of 15 s, discharge temperature of 25 °C, and power levels (T1 = 50, T2 = 80, and T3 = 120 W).
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January 2025
Department of Wildlife Fisheries and Aquaculture, College of Forest Resources, Mississippi State University, Mississippi State, MS, 39762-9690, USA.
This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies.
View Article and Find Full Text PDFEur Arch Otorhinolaryngol
January 2025
Department of Otolaryngology-Head and Neck Surgery, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Objective: This study aims to compare the outcomes of balloon-assisted rib graft placement with traditional graft placement in Endoscopic Posterior Cricoid Split with Rib Graft Placement (EPCS/RG).
Methods: We conducted a retrospective analysis of 23 patients who underwent EPCS/RG by a single senior surgeon at King Saud University Medical City from 2017 to 2024. Data were collected on demographics, surgical approach, and operative time.
Sci Rep
January 2025
Department of Biochemistry, College of Science, King Saud University, P.O.Box 2455, Riyadh, 11451, Saudi Arabia.
Nano-biochar considers a versatile and valuable sorbent to enhance plant productivity by improving soil environment and emerged as a novel solution for environmental remediation and sustainable agriculture in modern era. In this study, roles of foliar applied nanobiochar colloidal solution (NBS) on salt stressed tomato plants were investigated. For this purpose, NBS was applied (0%, 1% 3% and 5%) on two groups of plants (control 0 mM and salt stress 60 mM).
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January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
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