' Candidatus Liberibacter asiaticus' (Las) is the most prevalent bacterium associated with huanglongbing, which is one of the most destructive diseases of citrus. In this paper, an extremely rapid and simple method for field detection of Las from leaf samples, based on recombinase polymerase amplification (RPA), is described. Three RPA primer pairs were designed and evaluated. RPA amplification was optimized so that it could be accomplished within 10 min. In combination with DNA crude extraction by a 50-fold dilution after 1 min of grinding in 0.5 M sodium hydroxide and visual detection via fluorescent DNA dye (positive samples display obvious green fluorescence while negative samples remain colorless), the whole detection process can be accomplished within 15 min. The sensitivity and specificity of this RPA-based method were evaluated and were proven to be equal to those of real-time PCR. The reliability of this method was also verified by analyzing field samples.
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http://dx.doi.org/10.1021/acs.jafc.8b01015 | DOI Listing |
One Health Outlook
January 2025
Medical Virology Unit, Faculty of Basic Medical and Applied Sciences, Lead City University and Primary Health Care Board, Ibadan, Oyo State, Nigeria.
Background: Dengue fever (DF) poses a growing global threat, necessitating a comprehensive one-health approach to address its complex interplay between human, animal, and environmental factors. In Oyo State, Nigeria, the true burden of DF remains unknown due to underdiagnosis and misdiagnosis as malaria, exacerbated by poor health-seeking behavior, weak surveillance systems, and inadequate health infrastructure. Adopting a one-health approach is crucial to understanding the dynamics of DF transmission.
View Article and Find Full Text PDFBMC Microbiol
January 2025
Department of Infectious Disease Epidemiology, Robert Koch Institute (RKI), Berlin, Germany.
Background: Carbapenem-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA) are among WHO's priority pathogens with antimicrobial resistance (AMR). Studies suggest potential impacts of the COVID-19-pandemic on AMR. We described changes in AMR incidence and epidemiology in Germany during the COVID-19-pandemic.
View Article and Find Full Text PDFJ Expo Sci Environ Epidemiol
January 2025
Division of Field Studies and Engineering, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA.
Sci Rep
January 2025
Rashpetco Company, Cairo, Egypt.
This study presents a comprehensive workflow to detect low seismic amplitude gas fields in hydrocarbon exploration projects, focusing on the West Delta Deep Marine (WDDM) concession, offshore Egypt. The workflow integrates seismic spectral decomposition and machine learning algorithms to identify subtle anomalies, including low seismic amplitude gas sand and background amplitude water sand. Spectral decomposition helps delineate the fairway boundaries and structural features, while Amplitude Versus Offset (AVO) analysis is used to validate gas sand anomalies.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
In the field of medical imaging, particularly MRI-based brain tumor classification, we propose an advanced convolutional neural network (CNN) leveraging the DenseNet-121 architecture, enhanced with dilated convolutional layers and Squeeze-and-Excitation (SE) networks' attention mechanisms. This novel approach aims to improve upon state-of-the-art methods of tumor identification. Our model, trained and evaluated on a comprehensive Kaggle brain tumor dataset, demonstrated superior performance over established convolution-based and transformer-based models: ResNet-101, VGG-19, original DenseNet-121, MobileNet-V2, ViT-L/16, and Swin-B across key metrics: F1-score, accuracy, precision, and recall.
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