ArticleJournal of clinical microbiology2015
Molecular identification of Mycobacterium avium subsp. silvaticum by duplex high-resolution melt analysis and subspecies-specific real-time PCR.
Article in Journal of clinical microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- High mortality in patients with Mycobacterium avium complex lung disease: a systematic review.BMC infectious diseases · 2018Pooled it
- First whole-genome sequence of Mycobacterium avium subsp. silvaticum isolated from a diseased Egyptian goose (Alopochen aegyptiaca).BMC genomics · 2025Article
- Mycobacteriosis in Various Pet and Wild Birds from Germany: Pathological Findings, Coinfections, and Characterization of Causative Mycobacteria.Microbiology spectrum · 2022Article
- Genetic Involvement ofInternational journal of molecular sciences · 2021Review
- Avian Mycobacteriosis and Molecular Identification ofAnimals : an open access journal from MDPI · 2021Article
- Practical Guidance for Clinical Microbiology Laboratories: Mycobacteria.Clinical microbiology reviews · 2018Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate identification of mycobacterial species and subspecies is essential to evaluate their significance and to perform epidemiological studies. The subspecies of Mycobacterium avium have different attributes but coincide in their zoonotic potential. Our knowledge about M. avium subsp. silvaticum is limited, since its identification is uncertain. Mycobacterium avium subsp. avium and M. avium subsp. silvaticum can be discriminated from each other based only on phenotypic characteristics, as they have almost identical genome sequences. Here we describe the development of a diagnostic method which enables the molecular identification of M. avium subsp. silvaticum and discrimination from M. avium subsp. avium based on genomic differences in a duplex high-resolution melt and M. avium subsp. silvaticum-specific mismatch real-time PCR. The developed assay was tested on reference strains and 199 field isolates, which were analyzed by phenotypic methods previously. This assay not only identified all 63 M. avium subsp. silvaticum and 138 M. avium subsp. avium strains correctly but also enabled the detection of mixed M. avium subsp. avium-M. avium subsp. silvaticum cultures. This is the first time that such a large panel of strains has been analyzed, and we also report the first isolation of M. avium subsp. silvaticum from red fox, red deer, wild boar, cattle, and badger. This assay is reliable, rapid, simple, inexpensive, and robust. It eliminates the long-existing problem of ambiguous phenotypic identification and opens up the possibility for detailed and comprehensive strain studies.
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.