We have used the polymerase chain reaction (PCR) to obtain sensitive detection and identification of poliovirus RNA genomes. Primer pairs were designed to permit identification of each Sabin poliovaccine strain by the electrophoretic mobilities of the amplified DNA products (Sabin 1: 97 bp; Sabin 2: 71 bp; Sabin 3: 44 bp). The compositions of samples containing mixtures of vaccine strains could be readily determined by PCR. When the amplified products were visualized by ethidium bromide fluorescence, as few as 250 genomic copies in the original sample could be detected. When PCR was used in combination with strain-specific 32P-labeled oligonucleotide probes, the limit of detection was less than or equal to 2.5 poliovirus genomes, exceeding the sensitivity of poliovirus isolation in cell culture by at least 100-fold. PCR amplifications may be performed on virion RNAs extracted directly from clinical specimens, potentially eliminating the requirement for virus isolation in routine identifications while yielding reliable results within 8 h.

Download full-text PDF

Source
http://dx.doi.org/10.1016/0168-1702(91)90107-7DOI Listing

Publication Analysis

Top Keywords

detection identification
8
polymerase chain
8
chain reaction
8
sabin sabin
8
identification vaccine-related
4
vaccine-related polioviruses
4
polioviruses polymerase
4
reaction polymerase
4
pcr
4
reaction pcr
4

Similar Publications

A dedicated caller for DUX4 rearrangements from whole-genome sequencing data.

BMC Med Genomics

January 2025

Illumina Cambridge Ltd., Granta Park, Great Abington, Cambridge, UK.

Rearrangements involving the DUX4 gene (DUX4-r) define a subtype of paediatric and adult acute lymphoblastic leukaemia (ALL) with a favourable outcome. Currently, there is no 'standard of care' diagnostic method for their confident identification. Here, we present an open-source software tool designed to detect DUX4-r from short-read, whole-genome sequencing (WGS) data.

View Article and Find Full Text PDF

Identification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study.

BMC Cancer

January 2025

Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, 1 Xueyuan Road, Fujian, 350108, China.

Objective: This study aims to identify potential lipid biomarkers and metabolic pathways associated with oral cancer (OC). Then to establish and evaluate disease classification models capable of distinguishing OC patients from healthy controls.

Methods: A total of 41 OC patients and 41 controls were recruited from a hospital in Southeast China to examine the serum lipidomics by Ultra-high Performance Liquid Chromatography Q Exactive Mass Spectrometry (UHPLC-QE-MS).

View Article and Find Full Text PDF

Fetal cardiac function in pregnancy affected by congenital heart disease: protocol for a multicentre prospective cohort study.

BMC Pregnancy Childbirth

January 2025

Royal Hospital for Women and UNSW, School of Clinical Medicine, Level 0, Royal Hospital for Women, Barker Street (Locked Bag 2000), Sydney, NSW, 2031, Australia.

Background: Congenital heart disease (CHD) is the most common fetal malformation, and it can result first in cardiac remodeling and dysfunction and later in cardiac failure and hydrops. A limited number of studies have evaluated cardiac function in fetuses affected by CHD. Functional parameters could potentially identify fetuses at risk of cardiac failure before its development.

View Article and Find Full Text PDF

Optimized convolutional neural network using African vulture optimization algorithm for the detection of exons.

Sci Rep

January 2025

Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.

The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still required to increase the identification accuracy of exons.

View Article and Find Full Text PDF

Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!