Evidence map›Paper›PMID 14605126›Full record

ArticleJournal of clinical microbiology2003

Novel enzyme-linked minisequence assay for genotypic analysis of human immunodeficiency virus type 1 drug resistance.

Wataru Sugiura, Kazunori Shimada, Masakazu Matsuda, Tomoko Chiba, Lay Myint, Aiko Okano, Kaneo Yamada

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Genotypic resistance testing in HIV by arrayed primer extension.Analytical and bioanalytical chemistry · 2008
    Article
  4. Article
  5. 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

7 authors.

Wataru SugiuraAIDS Research Center, National Institute of Infectious Diseases, Tokyo 2080011, Japan. wsugiura@nih.go.jp
Kazunori Shimada
Masakazu Matsuda
Tomoko Chiba
Lay Myint
Aiko Okano
Kaneo Yamada

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We constructed a novel tool for genotypic analysis of human immunodeficiency virus type 1 (HIV-1) drug resistance by using an enzyme-linked minisequence assay (ELMA). ELMA is a combination of hybridization and a 1-base extension reaction, and we designed the assay to detect five mutations conferring nucleoside analogue resistance (M41L, D67N, K70R, T215Y, and M184V) and six mutations conferring protease inhibitor resistance (D30N, M46I, G48V, V82A, I84V, and L90M). At all detection points, ELMA demonstrated high sensitivity and specificity, sufficient for clinical use. Compared to that obtained by direct sequencing, the genotypic information obtained by ELMA is limited to the targeted loci for which it was designed. However, ELMA proves advantageous in several respects. The assay does not require expensive equipment, such as an autosequencer, and can be performed in regular clinical diagnostic laboratories. Therefore ELMA can be a candidate for a drug resistance monitoring assay to be introduced in developing countries. In addition, ELMA demonstrated higher sensitivity in the detection of minor resistant populations. We successfully detected a minor virus population (10%) by the assay. The high sensitivity and specificity of the assay recommend it as a first screening assay for drug resistance surveillance.

Indexed as

Base SequenceDNA PrimersDrug Resistance, ViralEnzyme-Linked Immunosorbent AssayGenotypeHIV-1HIV Protease InhibitorsHumansMutationOligonucleotide ProbesPolymerase Chain ReactionReverse Transcriptase InhibitorsDNA PrimersHIV Protease InhibitorsOligonucleotide ProbesReverse Transcriptase Inhibitors

Identifiers

PMID14605126
PMCPMC262484

What OpenQuestion holds

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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.