ArticleJournal of clinical microbiology2002
Experimental versus in silico fluorescent amplified fragment length polymorphism analysis of Mycobacterium tuberculosis: improved typing with an extended fragment range.
Article in Journal of clinical microbiology, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- Molecular Strain Typing of Mycobacterium tuberculosis: a Review of Frequently Used Methods.Journal of Korean medical science · 2016Review
- Methodological and Clinical Aspects of the Molecular Epidemiology of Mycobacterium tuberculosis and Other Mycobacteria.Clinical microbiology reviews · 2016Review
- Current methods in the molecular typing of Mycobacterium tuberculosis and other mycobacteria.BioMed research international · 2014Review
- From local surveys to global surveillance: three high-throughput genotyping methods for epidemiological monitoring of Xanthomonas citri pv. citri pathotypes.Applied and environmental microbiology · 2009Article
- Discriminatory power and reproducibility of novel DNA typing methods for Mycobacterium tuberculosis complex strains.Journal of clinical microbiology · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Whole-genome fingerprinting fluorescent amplified fragment length polymorphism (FAFLP) data were compared with in silico data for the sequenced strains of Mycobacterium tuberculosis (H37Rv and CDC1551). For this G+C-rich genome, many predicted fragments were not detected experimentally. For H37Rv, only 108 (66%) of the 163 predicted EcoRI-MseI fragments between 100 and 500 bp were visualized in vitro. FAFLP was also used to identify polymorphism in 10 clinical isolates of M. tuberculosis characterized previously by IS6110 typing, examining fragments of up to 1,000 bp in size rather than up to 500 bp as was done previously. Five isolates had unique IS6110 profiles and were not known to be epidemiologically related, two isolates were the same single-band IS6110 type but were not known to be epidemiologically related, and the remaining three isolates were epidemiologically related with identical IS6110 profiles. Analysis of fragments in the 500- to 1,000-bp range using nonselective primers differentiated better between strains than analysis of fragments in the 50- to 500-bp range using a set of four selective primers. Seventeen polymorphic fragments were identified between 500 and 1,000 bp in size compared with nine polymorphic fragments between 50 and 500 bp. Using the 500- to 1,000-bp analysis, a level of discrimination similar to that of IS6110 typing was achieved which, unlike the IS6110 typing, was able to differentiate the two M. tuberculosis strains, each of which had only a single copy of IS6110.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.