Fish diseases can be caused by a variety of diverse organisms, including bacteria, fungi, viruses and protozoa, and pose a universal threat to the ornamental fish industry and aquaculture. The lack of rapid, accurate and reliable means by which fish pathogens can be detected and identified has been one of the main limitations in fish pathogen diagnosis and fish disease management and has consequently stimulated the search for alternative diagnostic techniques. Here, we describe a method based on multiplex and broad-range PCR amplification combined with DNA array hybridization for the simultaneous detection and identification of all cyprinid herpesviruses (CyHV-1, CyHV-2 and CyHV-3) and some of the most important fish pathogenic Flavobacterium species, including F. branchiophilum, F. columnare and F. psychrophilum. For virus identification, the DNA polymerase and helicase genes were targeted. For bacterial identification, the ribosomal RNA gene was used. The developed methodology permitted 100% specificity for the identification of the target species. Detection sensitivity was equivalent to 10 viral genomes or less than a picogram of bacterial DNA. The utility and power of the array for sensitive pathogen detection and identification in complex samples such as infected tissue is demonstrated in this study.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/j.1365-2761.2011.01304.x | DOI Listing |
J Med Internet Res
January 2025
Department of Radiation Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Background: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. Therefore, early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life.
View Article and Find Full Text PDFAm J Public Health
January 2025
Melanie S. Askari is with the Epidemic Intelligence Service at the Centers for Disease Control and Prevention (CDC) and the New York City Health Department, Long Island City, NY. Robert J. Arciuolo, Olivia Matalka, Krishika A. Graham, Beth M. Isaac, Ramona Lall, Antonine Jean, and Jennifer B. Rosen are with the New York City Health Department, Bureau of Immunization, Long Island City.
To determine utility of syndromic surveillance in improving varicella case detection during an outbreak among recent immigrants to New York City (NYC). During March through August 2023, the NYC Health Department received varicella reports from routine sources and syndromic surveillance from emergency department visits with varicella as a chief complaint or discharge diagnosis. Reports were reviewed to determine if individuals met criteria for confirmed or probable varicella cases and if cases were outbreak-associated.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
February 2025
Department of Construction Sciences, Lund University, Lund SE-22100, Sweden.
Preemptive identification of potential failure under loading of engineering structures is a critical challenge. Our study presents an innovative approach to design built-in prefailure indicators within multiscale structural designs with optimized load carrying capabilities utilizing the design freedom of topology optimization. The indicators are engineered to visibly signal load conditions approaching the global critical buckling load at predefined locations.
View Article and Find Full Text PDFPLoS Negl Trop Dis
January 2025
Infectious Diseases Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
Background: During the 2023-dengue outbreak in Bangladesh, a diagnostic evaluation study was conducted to investigate concurrent Zika virus (ZIKV) and dengue virus (DENV) transmission in Dhaka in 2023.
Aims: The study explored to simultaneously detect the presence of ZIKV, DENV, and/or CHIKV while considering relevant clinical and epidemiological risk factors, using a real-time multiplex RT-PCR system. Following this, it was planned to sequence the selected samples to identify genetic variations of the ZIKV infections within the population.
Detecting low birth weight is crucial for early identification of at-risk pregnancies which are associated with significant neonatal and maternal morbidity and mortality risks. This study presents an efficient and interpretable framework for unsupervised detection of low, very low, and extreme birth weights. While traditional approaches to managing class imbalance require labeled data, our study explores the use of unsupervised learning to detect anomalies indicative of low birth weight scenarios.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!