Evidence map›Paper›PMID 33003560›Full record

ArticleAntibiotics (Basel, Switzerland)2020

Aptamer-Based Detection of Ampicillin in Urine Samples.

Matthew D Simmons, Lisa M Miller, Malin O Sundström, Steven Johnson

Open access · goldAbstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2020. 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
1.4field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
  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

4 authors at 1 institution in 1 country.

Matthew D SimmonsDepartment of Electronic Engineering, University of York, Heslington, York, North Yorkshire YO10 5DD, UK.ORCID 0000-0001-7598-7266
Lisa M MillerDepartment of Chemistry, University of York, Heslington, York, North Yorkshire YO10 5DD, UK.ORCID 0000-0003-3667-3840
Malin O SundströmDepartment of Electronic Engineering, University of York, Heslington, York, North Yorkshire YO10 5DD, UK.
Steven JohnsonDepartment of Electronic Engineering, University of York, Heslington, York, North Yorkshire YO10 5DD, UK.
University of York · GB

Funding

Biological Physical Sciences Interdisciplinary Network (BPSInet) 2019Engineering and Physical Sciences Research Council EP/P02324X/1
6 · The paper itself

Abstract

The misuse of antibiotics in health care has led to increasing levels of drug resistant infections (DRI's) occurring in the general population. Most technologies developed for the detection of DRI's typically focus on phenotyping or genotyping bacterial resistance rather than on the underlying cause and spread of DRI's; namely the misuse of antibiotics. An aptameric based assay has been developed for the monitoring of ampicillin in urine samples, for use in determining optimal antibiotic dosage and monitoring patient compliance with treatment. The fluorescently labelled aptamers were shown to perform optimally at pH 7, ideal for buffered clinical urine samples, with limits of detection as low as 20.6 nM, allowing for determination of ampicillin in urine in the clinically relevant range of concentrations (100 nM to 100 µM). As the assay requires incubation for only 1 h with a small sample volume, 50 to 150 µL, the test would fit within current healthcare pathways, simplifying the adoption of the technology.

Indexed as

ampicillinantimicrobial resistanceaptamerbeta-lactambeta-lactamasediagnosticsdrug-resistant-infectionsfluorescencegold nanoparticlesurine analysis

Identifiers

PMID33003560
PMCPMC7601551
OpenAlexW3090098390

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.