Evidence map›Paper›PMID 20686082›Full record

ArticleJournal of clinical microbiology2010

Biochip system for rapid and accurate identification of mycobacterial species from isolates and sputum.

Lingxiang Zhu, Guanglu Jiang, Shengfen Wang, Can Wang, Qiang Li, Hao Yu, Yang Zhou, Bing Zhao, Hairong Huang, Wanli Xing and 4 more

Open access · bronzeAbstract readComparative StudyEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

26 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
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  4. Biochip-Based Identification of Mycobacterial Species in Russia.International journal of molecular sciences · 2024
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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

14 authors at 1 institution in 1 country.

Lingxiang ZhuNational Engineering Research Center for Beijing Biochip Technology, Changping District, Beijing, China.
Guanglu Jiang
Shengfen Wang
Can Wang
Qiang Li
Hao Yu
Yang Zhou
Bing Zhao
Hairong Huang
Wanli Xing
Keith Mitchelson
Jing Cheng
Yanlin Zhao
Yong Guo
Tsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate detection of mycobacterial species from isolates and clinical samples is important for pathogenic diagnosis and treatment and for disease control. There is an urgent need for the development of a rapid, simple, and accurate detection method. We established a biochip assay system, including a biochip, sample preparation apparatus, hybridization instrument, chip washing machine, and laser confocal scanner equipped with interpretation software for automatic diagnosis. The biochip simultaneously identified 17 common mycobacterial species by targeting the differences in the 16S rRNA. The system was assessed with 64 reference strains and 296 Mycobacterium tuberculosis and 243 nontuberculous mycobacterial isolates, as well as 138 other bacteria and 195 sputum samples, and then compared to DNA sequencing. The entire biochip assay took 6 h. The concordance rate between the biochip assay and the DNA sequencing results was 100%. In conclusion, the biochip system provides a simple, rapid, reliable, and highly accurate clinical assay for determination of mycobacterial species in a 6-h procedure, from either culture isolates or sputum samples, allowing earlier pathogen-adapted antimicrobial therapy in patients.

Indexed as

Bacteriological TechniquesHumansMycobacterium tuberculosisOligonucleotide Array Sequence AnalysisRNA, BacterialRNA, Ribosomal, 16SSputumTime FactorsTuberculosisRNA, BacterialRNA, Ribosomal, 16S

Identifiers

PMID20686082
PMCPMC2953089
OpenAlexW2053525361

What OpenQuestion holds

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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.