Evidence map›Paper›PMID 35282613›Full record

ArticleChemical science2022

LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics.

Cristian Piras, Oliver J Hale, Christopher K Reynolds, A K Barney Jones, Nick Taylor, Michael Morris, Rainer Cramer

Open access · diamondAbstract read
In one paragraph

Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Article
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  4. Article
  5. Review
  6. Exogenous prostaglandin DFrontiers in veterinary science · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Machine learning-empoweredChemical science · 2023
    Article
  13. 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 at 3 institutions in 2 countries.

Cristian PirasDepartment of Chemistry, University of Reading Whiteknights Reading RG6 6DX UK r.k.cramer@reading.ac.uk +44 (0)118 378 4550.
Oliver J HaleDepartment of Chemistry, University of Reading Whiteknights Reading RG6 6DX UK r.k.cramer@reading.ac.uk +44 (0)118 378 4550.
Christopher K ReynoldsSchool of Agriculture, Policy and Development, University of Reading Whiteknights Reading RG6 6EU UK.
A K Barney JonesSchool of Agriculture, Policy and Development, University of Reading Whiteknights Reading RG6 6EU UK.
Nick TaylorVeterinary Epidemiology and Economics Research Unit (VEERU), PAN Livestock Services Ltd, School of Agriculture, Policy and Development, University of Reading Whiteknights Reading RG6 6EU UK.
Michael MorrisWaters Corporation Stamford Avenue, Wilmslow SK9 4AX UK.
Rainer CramerDepartment of Chemistry, University of Reading Whiteknights Reading RG6 6DX UK r.k.cramer@reading.ac.uk +44 (0)118 378 4550.ORCID https://orcid.org/0000-0002-8037-2511
University of Reading · GBMagna Graecia University · ITWaters (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale population screening for early and accurate detection of disease is a key objective for future diagnostics. Ideally, diagnostic tests that achieve this goal are also cost-effective, fast and easily adaptable to new diseases with the potential of multiplexing. Mass spectrometry (MS), particularly MALDI MS profiling, has been explored for many years in disease diagnostics, most successfully in clinical microbiology but less in early detection of diseases. Here, we present liquid atmospheric pressure (LAP)-MALDI MS profiling as a rapid, large-scale and cost-effective platform for disease analysis. Using this new platform, two different types of tests exemplify its potential in early disease diagnosis and response to therapy. First, it is shown that LAP-MALDI MS profiling detects bovine mastitis two days before its clinical manifestation with a sensitivity of up to 70% and a specificity of up to 100%. This highly accurate, pre-symptomatic detection is demonstrated by using a large set of milk samples collected weekly over six months from approximately 500 dairy cows. Second, the potential of LAP-MALDI MS in antimicrobial resistance (AMR) detection is shown by employing the same mass spectrometric setup and similarly simple sample preparation as for the early detection of mastitis.

Identifiers

PMID35282613
PMCPMC8826629
OpenAlexW4206062997

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.