Evidence map›Paper›PMID 33367346›Full record

ArticleThe Analyst2021

The cyanobacterial lectin, microvirin-N, enhances the specificity and sensitivity of lipoarabinomannan-based TB diagnostic tests.

Megan van der Horst, Leshern Karamchand, Westley S Bauer, Andrew J M Nel, Jonathan M Blackburn, David W Wright

Open access · hybridAbstract read
In one paragraph

Article in The Analyst, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. 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

6 authors at 2 institutions in 2 countries.

Megan van der HorstDepartment of Chemistry, Vanderbilt University, Station B 351822, Nashville, TN 37235, USA. david.wright@vanderbilt.edu.
Leshern Karamchand
Westley S Bauer
Andrew J M Nel
Jonathan M Blackburn
David W Wright
University of Cape Town · ZAVanderbilt University · US

Funding

A 100-fold more sensitive TB diagnostic based on magnetic concentration and "coffee ring" formationR01AI135937 · NIAID · VANDERBILT UNIVERSITY · PI BLACKBURN, JONATHAN MICHAEL, HASELTON, FREDERICK R · 2017 to 2021
$1.7M
NIAID NIH HHS R01 AI135937
6 · The paper itself

Abstract

Tuberculosis (TB) is one of the top ten causes of death globally, despite being treatable. The eradication of TB disease requires, amongst others, diagnostic tests with high specificity and sensitivity that will work at the point of care (POC) in low-resource settings. The TB surface glycolipid antigen, mannose-capped lipoarabinomannan (ManLAM) currently serves as the only POC molecular diagnostic biomarker suitable for use in low cost immunoassays. Here, we demonstrate the high affinity and exceptional specificity of microvirin-N (MVN), a 14.3 kDa cyanobacterial lectin, toward H37Rv TB ManLAM and utilize it to develop a novel on-bead ELISA. MVN binds to ManLAM with sub-picomolar binding affinity, but does not bind to other variants of LAM expressed by non-pathogenic mycobacteria - a level of binding specificity and affinity that current commercially available anti-LAM antibodies cannot achieve. An on-bead ELISA was subsequently developed using MVN-functionalized magnetic beads which allows for the specific capture of ManLAM from human urine with a limit of detection (LOD) of 1.14 ng mL

Indexed as

Mycobacterium tuberculosisTuberculosisDiagnostic Tests, RoutineHumansLectinsLipopolysaccharidesSensitivity and SpecificityLectinslipoarabinomannanLipopolysaccharides

Identifiers

PMID33367346
PMCPMC8374243
OpenAlexW3113850794

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.