Evidence map›Paper›PMID 30012760›Full record

ArticleAntimicrobial agents and chemotherapy2018

Screening of Preselected Libraries Targeting Mycobacterium abscessus for Drug Discovery.

Adrian Richter, Angelika Strauch, Joseph Chao, Mary Ko, Yossef Av-Gay

Open access · bronzeAbstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. The diversity of clinicalJournal of medical microbiology · 2024
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  11. Broad-Spectrum In Vitro Activity ofAntibiotics (Basel, Switzerland) · 2024
    Article
  12. Article
  13. Exploring antibiotic resistance mechanisms inFrontiers in microbiology · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Microbiology spectrum · 2022
    Article
  18. Article
  19. Article
  20. Mycobacterium abscessus drug discovery using machine learning.Tuberculosis (Edinburgh, Scotland) · 2022
    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 at 1 institution in 1 country.

Adrian RichterDivision of Infectious Diseases, Department of Medicine, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Angelika StrauchDivision of Infectious Diseases, Department of Medicine, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Joseph ChaoDivision of Infectious Diseases, Department of Medicine, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Mary KoDivision of Infectious Diseases, Department of Medicine, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada.
Yossef Av-GayDivision of Infectious Diseases, Department of Medicine, Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada yossi@mail.ubc.ca.
University of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Anti-Bacterial AgentsDrug DiscoveryHumansMicrobial Sensitivity TestsMycobacterium abscessusMycobacterium Infections, NontuberculousAnti-Bacterial Agentsfluorescence assaysin vitro screeningMycobacterium abscessus

Identifiers

PMID30012760
PMCPMC6125491
OpenAlexW2884594177

What OpenQuestion holds

Textmetadata
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.