Evidence map›Paper›PMID 28149262›Full record

ArticleEJIFCC2016

Mass Spectrometry Applications for Toxicology.

Michael M Mbughuni, Paul J Jannetto, Loralie J Langman

Open access · greenAbstract read
In one paragraph

Article in EJIFCC, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Comparison of liquid chromatography-high-resolution tandem mass spectrometry (MSJournal of mass spectrometry and advances in the clinical lab · 2023
    Article
  7. Article
  8. Bridging the gap: The critical role of laboratory developed tests in clinical toxicology.Journal of mass spectrometry and advances in the clinical lab · 2023
    Review
  9. Review
  10. Zebrafish as a Model for Anticancer Nanomedicine Studies.Pharmaceuticals (Basel, Switzerland) · 2021
    Review
  11. Article
  12. Review
  13. Article
  14. 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

3 authors at 1 institution in 1 country.

Michael M MbughuniDepartment of Laboratory Medicine, Mayo Clinic , Rochester, MN, USA.
Paul J JannettoDepartment of Laboratory Medicine, Mayo Clinic , Rochester, MN, USA.
Loralie J LangmanDepartment of Laboratory Medicine, Mayo Clinic , Rochester, MN, USA.
Mayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxicology is a multidisciplinary study of poisons, aimed to correlate the quantitative and qualitative relationships between poisons and their physiological and behavioural effects in living systems. Other key aspects of toxicology focus on elucidation of the mechanisms of action of poisons and development of remedies and treatment plans for associated toxic effects. In these endeavours, Mass spectrometry (MS) has become a powerful analytical technique with a wide range of application used in the Toxicological analysis of drugs, poisons, and metabolites of both. To date, MS applications have permeated all fields of toxicology which include; environmental, clinical, and forensic toxicology. While many different analytical applications are used in these fields, MS and its hyphenated applications such as; gas chromatography MS (GC-MS), liquid chromatography MS (LC-MS), inductively coupled plasma ionization MS (ICP-MS), tandem mass spectrometry (MS/MS and MS

Indexed as

clinical toxicologyEnvironmental toxicologyforensic toxicologymass spectrometry technologies

Identifiers

PMID28149262
PMCPMC5282913
OpenAlexW2586833259

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.