Evidence map›Paper›PMID 23493089›Full record

ArticleIranian journal of basic medical sciences2012

Molecular Identification of Rare Clinical Mycobacteria by Application of 16S-23S Spacer Region Sequencing.

Hasan Shojaei, Hashemi Abodolrazagh, Parvin Heidarieh, Fazel Pourahmad, Daei Naser Daei Naser

Abstract read
In one paragraph

Article in Iranian journal of basic medical sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Hasan ShojaeiDepartment of Microbiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Hashemi Abodolrazagh
Parvin Heidarieh
Fazel Pourahmad
Daei Naser Daei Naser

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn addition to several molecular methods and in particular 16S rDNA analysis, the application of a more discriminatory genetic marker, i.e., 16S-23S internal transcribed spacer gene sequence has had a great impact on identification and classification of mycobacteria. In the current study we aimed to apply this sequencing power to conclusive identification of some Iranian clinical strains of mycobacteria. MATERIALS AND

methodsThe test strains consisted of nineteen mycobacterial isolates which were initially identified by the use of conventional phenotypic techniques and molecular methods and subjected to further definitive identification using the 16S-23S internal transcribed spacer gene sequencing.

resultsOut of 19 studied strains, 7 isolates were found to be rapidly growing and 12 isolates as slowly growing mycobacteria. With the exception of one isolate, i.e., the isolate HNTM87, which yielded a distinct ITS sequence incomparable with all previously identified mycobacteria, the remaining isolates produced the sequences similar to the established mycobacteria and were clearly identified and differentiated from closely related taxa. A phylogenetic tree based on maximum parsimony analysis of 16S-23S internal transcribed spacer gene sequences constructed showing the relatedness of Iranian clinical isolates with the closely related type species of mycobacteria.

conclusionThis study showed that the 16S-23S internal transcribed spacer gene of the genus Mycobacterium exhibits a high variation which is of value for discriminating closely related taxa and could be used independently or in combination with 16S rDNA sequencing to delineate the true identity of rare mycobacterial species.

Indexed as

Internal Transcribed SpacerMycobacteriumSequence Analysis

Identifiers

PMID23493089
PMCPMC3586870

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.