Evidence map›Paper›PMID 27610043›Full record

ArticleTropical medicine and health2016

Detection of Mycobacterium ulcerans by real-time PCR with improved primers.

Noriko Shinoda, Hajime Nakamura, Mineo Watanabe

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 35% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Noriko ShinodaGraduate School of Infection Control Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641 Japan.
Hajime NakamuraResearch Institute of Tuberculosis, Japan Anti-Tuberculosis Association, 3-1-24 Matsuyama, Kiyose, Tokyo 204-8533 Japan.
Mineo WatanabeGraduate School of Infection Control Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641 Japan ; Kitasato Institute for Life Sciences, Kitasato University, 5-9-1 Shirokane, Minato-ku, Tokyo 108-8641 Japan.ORCID 0000-0003-4259-3353
Kitasato Institute Hospital · JPJapan Anti Tuberculosis Association · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBuruli ulcer is a severe skin disease caused by Mycobacterium ulcerans. Real-time PCR targeting the IS2404 sequence has been used as a reliable and rapid method for the diagnosis of Buruli ulcer and detection of M. ulcerans in the environment. The genome of M. ulcerans contains hundreds of IS2404 copies, which have variability in certain sequences. Therefore, the design of new primers specific to conserved IS2404 regions may potentially improve the sensitivity of M. ulcerans detection and, consequently, the diagnosis of Buruli ulcer, thus ensuring timely treatment of the disease.

resultsIn silico analysis indicates that DNA sequences of the IS2404 elements are highly variable within a single strain. As the binding sites of conventional IS2404-specific primers used for M. ulcerans detection contain polymorphic sequences, we designed new primers, which enabled the detection of M. ulcerans by real-time PCR with higher sensitivity and similar specificity with respect to that of conventional primers. However, the increase in sensitivity with the new primers depended on the M. ulcerans strain.

conclusionsThe results suggest that real-time PCR based on the new primers could improve Buruli ulcer diagnosis and M. ulcerans detection in environmental samples.

Indexed as

Buruli ulcerDiagnosisMycobacterium ulceransReal-time PCR

Identifiers

PMID27610043
PMCPMC5009631
OpenAlexW2519330161

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Registered trials

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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.