Evidence map›Paper›PMID 27540322›Full record

ArticleThe Malaysian journal of medical sciences : MJMS2016

Genotypic Detection of rpoB and katG Gene Mutations Associated with Rifampicin and Isoniazid Resistance in Mycobacterium Tuberculosis Isolates: A Local Scenario (Kelantan).

Nurul-Ain Ismail, Mohd Fazli Ismail, Siti Suraiya Md Noor, Siti Nazrina Camalxaman

Open access · greenAbstract read
In one paragraph

Article in The Malaysian journal of medical sciences : MJMS, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 78% 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

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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

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Nurul-Ain IsmailDepartment of Medical Laboratory Technology, Faculty of Health Sciences, Universiti Teknologi MARA, 42300, Bandar Puncak Alam, Selangor, Malaysia.
Mohd Fazli IsmailDepartment of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
Siti Suraiya Md NoorDepartment of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
Siti Nazrina CamalxamanDepartment of Medical Laboratory Technology, Faculty of Health Sciences, Universiti Teknologi MARA, 42300, Bandar Puncak Alam, Selangor, Malaysia.
Universiti Sains Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug resistant tuberculosis (DR-TB) remains a public health issue that is of major concern on a global scale. The characterisation of clinical isolates may provide key information regarding the underlying mechanisms of drug resistance, and helps to augment therapeutic options. This study aims to evaluate the frequency of gene mutations associated with Rifampicin (RIF) and Isoniazid (INH) resistance among nine clinical isolates.

methodsA total of nine drug resistant Mycobacterium tuberculosis clinical isolates were screened for genetic mutations in rpoB and katusing polymerase chain reaction (PCR) amplification and DNA sequencing. Genotypic analysis was performed to detect the mutations in the sequence of the target genes.

resultsOur findings reveal that 80% of the isolates possess mutations at codon 119 (His119Tyr) and 135 (Arg135Trp and Ser135Leu) within the rpoB gene; and 70% possess mutations in the katG gene at codon 238 with amino acid change (Leu238Arg).

conclusionFindings from this study provide an overview of the current situation of RIF and INH resistance in a hospital Universiti Sains Malaysia (HUSM) located in Kelantan, Malaysia, which could facilitate molecular-based detection methods of drug-resistant strains. Further information regarding the molecular mechanisms involved in resistance in RR-/MDR-TB should be addressed in the near future.

Indexed as

isoniazidkatGM. tuberculosismutationrifampicinrpoB

Identifiers

PMID27540322
PMCPMC4975585
OpenAlexW2992547268

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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.