Suppr超能文献

Advances in the automated detection of metaphase chromosomes labeled with fluorescence dyes.

作者信息

Mascio L N, Yuen B K, Kegelmeyer W P, Matsumoto K, Briner J, Wyrobek A J

机构信息

Defense Sciences Engineering Division, Lawrence Livermore National Laboratory, Livermore, California 94551, USA.

出版信息

Cytometry. 1998 Sep 1;33(1):10-8.

PMID:9725554
Abstract

Applications of fluorescence in situ hybridization (FISH) for translocation studies and biological dosimetry would benefit substantially from reliable and efficient automatic detection of metaphase chromosomes labeled with fluorescent dyes. We replicated and evaluated a fluorescence metaphase finder previously developed at the Medical Research Council (MRC), Human Genetics Unit (Scotland) and at Lawrence Berkeley Laboratory (LBL; California). The MRC/LBL system seemed to detect nearly all of the metaphases on the test slides, but it presented an unacceptable number of false positives (about five false positives per one true positive). Furthermore, we determined that the system actually overcalled true detections by counting certain metaphase spreads twice (duplicates). Through modifications of the MRC/LBL system, we developed the Lawrence Livermore National Laboratory (LLNL) system, which minimizes the detection of duplicates, incorporates new detection features, uses a binary decision tree (BDT) for classification, and provides functionalities to improve scanning accuracy and improve the post-detection review. To test the new system, DAPI-stained preparations of metaphase chromosomes from blood lymphocytes of four unrelated donors were placed on slides in drops ranging from 7 mm to 20 mm in diameter. Drops contained between 5 and 200 scorable metaphases each. The LLNL system achieved approximately 90% detection of non-duplicated metaphases as verified by an expert cytogeneticist, with typically less than one false positive per every one true positive detected.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验