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Developmental Validation of a Novel Lateral Flow Strip Test for Rapid Identification of Human Blood (Rapid Stain Identification TM-Blood)

NCJ Number
223116
Journal
Forensic Science International: Genetics Volume: 2 Issue: 3 Dated: June 2008 Pages: 243-247
Author(s)
Brett A. Schweers; Jennifer Old; P. W. Boonlayangoor; Karl A. Reich
Date Published
June 2008
Length
5 pages
Annotation
This article describes the developmental validation of a new blood identification test, Rapid Stain Identification TM-Blood (RSID TM-Blood).
Abstract
The study determined that the test is accurate, reproducible, easy to use, and highly specific for human blood. It is able to detect as little as 0.05 ml of human blood. Further, the test does not cross-react with ferret, skunk, or primate blood. In addition, the test can detect blood from a variety of forensic exhibits prior to processing for DNA-STR analysis. The high-dose hook effect that is responsible for false negative results with hemoglobin-based blood detection tests was not observed with RSID TM-Blood. The authors conclude that RSID TM-Blood is effective and useful for the detection of human blood on forensic exhibits and offers an improved means for blood detection compared to other methods currently used, since many of these methods are presumptive and prone to false positive results. RSID TM-Blood uses two anti-glycophorin A (red blood cell membrane specific protein) monoclonal antibodies in a lateral flow strip test format in detecting human blood. Each RSID TM-Blood kit contains 25 lateral flow strip tests, 25 ml of extraction buffer, 10 ml of running buffer, a technical information sheet, and a protocol sheet. The extraction buffer has been formulated to promote efficient extraction of the glycophorin A antigen from evidence samples, and the running buffer promotes consistent test flow rates and eliminates background signal. Buffers are compatible with downstream DNA analysis procedures, which allows users to employ single tube stain identification and DNA extraction approaches that optimize evidence sample conservation. 4 figures and 12 references