Evidence map›Paper›PMID 34138928›Full record

ArticlePloS one2021

Visible colorimetric growth indicators of Neisseria gonorrhoeae for low-cost diagnostic applications.

Taylor Mae Oeschger, David Carl Erickson

Abstract read
In one paragraph

Article in PloS one, 2021. 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
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

2 authors.

Taylor Mae OeschgerMeinig School of Biomedical Engineering, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0001-8544-9656
David Carl EricksonSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, United States of America.ORCID 0000-0002-1624-9711

Funding

FeverPhone: Point of Care Diagnosis of Acute Febrile Illness using a Mobile DeviceR01EB021331 · NIBIB · CORNELL UNIVERSITY · PI ERICKSON, DAVID CARL, MEHTA, SAURABH · 2016 to 2020
$3.0M
NIBIB NIH HHS R01 EB021331
6 · The paper itself

Abstract

N. gonorrhoeae is one of the most pressing antibiotic resistant threats of our time and low-cost diagnostics that can easily identify antibiotic resistance are desperately needed. However, N. gonorrhoeae responds so uniquely to growth conditions that it cannot be assumed gonorrhea will respond to common microbiological methods used for other pathogenic organisms. In this paper, we explore visual colorimetric indicators of N. gonorrhoeae growth that can be seen without a microscope or spectrophotometer. We evaluate growth media, pH indicators, resazurin-based dyes, and tetrazolium-based dyes for their use in simple colorimetric system. Overall, we identified Graver Wade media as the best at supporting robust gonococcal growth while also providing the least background when analyzing results of colorimetric tests. XTT, a tetrazolium-based dye, proved to show to brightest color change over time and not negatively impact the natural growth of N. gonorrhoeae. However, other dyes including PrestoBlue, MTT, and NBT are less expensive than XTT and work well when added after bacterial growth has already occurred. By identifying the specific use cases of these dyes, this research lays the groundwork for future development of a color-based antibiotic susceptibility low-cost test for N. gonorrhoeae.

Indexed as

Bacteriological TechniquesColorimetryCulture MediaEarly DiagnosisGonorrheaHumansHydrogen-Ion ConcentrationNeisseria gonorrhoeaeOxazinesSensitivity and SpecificityTetrazolium SaltsXanthenesCulture MediaOxazinesresazurinTetrazolium SaltsXanthenes

Identifiers

PMID34138928
PMCPMC8211239

What OpenQuestion holds

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LicenceCC BY
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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.