Evidence map›Paper›PMID 33937870›Full record

ArticleCurrent research in food science2021

Characterising the efficacy and bioavailability of bioactive peptides identified for attenuating muscle atrophy within a

Alberto R Corrochano, Roi Cal, Kathy Kennedy, Audrey Wall, Niall Murphy, Sanja Trajkovic, Sean O'Callaghan, Alessandro Adelfio, Nora Khaldi

Open access · goldAbstract read
In one paragraph

Article in Current research in food science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

12 citing papers in PubMed, 29 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Production of Multifunctional Hydrolysates from theBiotech (Basel (Switzerland)) · 2025
    Article
  6. Quantification of Peptides in Food Hydrolysate fromFoods (Basel, Switzerland) · 2025
    Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
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

9 authors at 1 institution in 1 country.

Alberto R CorrochanoNuritas Ltd., D02 RY95, Dublin, Ireland.
Roi CalNuritas Ltd., D02 RY95, Dublin, Ireland.
Kathy KennedyNuritas Ltd., D02 RY95, Dublin, Ireland.
Audrey WallNuritas Ltd., D02 RY95, Dublin, Ireland.
Niall MurphyNuritas Ltd., D02 RY95, Dublin, Ireland.
Sanja TrajkovicNuritas Ltd., D02 RY95, Dublin, Ireland.
Sean O'CallaghanNuritas Ltd., D02 RY95, Dublin, Ireland.
Alessandro AdelfioNuritas Ltd., D02 RY95, Dublin, Ireland.
Nora KhaldiNuritas Ltd., D02 RY95, Dublin, Ireland.
Nuritas (Ireland) · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterising key components within functional ingredients as well as assessing efficacy and bioavailability is an important step in validating nutritional interventions. Machine learning can assess large and complex data sets, such as proteomic data from plants sources, and so offers a prime opportunity to predict key bioactive components within a larger matrix. Using machine learning, we identified two potentially bioactive peptides within a

Indexed as

Anti-inflammatoryBioactive peptideIntestinal absorptionMachine learningProtein synthesisSimulated gastrointestinal digestion

Identifiers

PMID33937870
PMCPMC8079236
OpenAlexW3145281922

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.