Evidence map›Paper›PMID 37025416›Full record

ArticleFood chemistry: X2023

Proteomics and metabolomics profiling of meat exudate to determine the impact of postmortem aging on oxidative stability of beef muscles.

Derico Setyabrata, Danyi Ma, Shaojun Xie, Jyothi Thimmapuram, Bruce R Cooper, Uma K Aryal, Yuan H Brad Kim

Open access · goldAbstract read
In one paragraph

Article in Food chemistry: X, 2023. 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
6.0field-weighted citation impact, top 3% 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, 32 citations in OpenAlex.

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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 1 institution in 1 country.

Derico SetyabrataMeat Science and Muscle Biology Lab, Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.
Danyi MaMeat Science and Muscle Biology Lab, Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.
Shaojun XieBioinformatics Core, Purdue University, West Lafayette, IN, USA.
Jyothi ThimmapuramBioinformatics Core, Purdue University, West Lafayette, IN, USA.
Bruce R CooperMetabolites Profiling Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN, USA.
Uma K AryalPurdue Proteomics Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN, USA.
Yuan H Brad KimMeat Science and Muscle Biology Lab, Department of Animal Sciences, Purdue University, West Lafayette, IN, USA.
Purdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to characterize the major proteomes and metabolites in beef exudate and determine their relationship to color and oxidative quality of beef muscles. Beef loin (LD) and tenderloin (PM) muscles were cut into sections, individually vacuum-packaged, and aged for 9, 16 and 23 days at 2 °C. Following aging, beef exudates were collected and analyzed for both proteomics and metabolomics profiles. Proteome analysis indicated clustering by muscle types, while metabolomics profiling further clustered the samples based on the aging periods. The PM exudate had a greater concentration of oxidative enzymes, while the LD exudate contained more glycolytic enzymes. Greater lipid, nucleotide, carnitine and glucoside metabolites were observed in LD and 23d exudates. HSP70 and laminin proteins, together with glucosides metabolites, were correlated to muscle oxidative stability. The results indicated that meat exudate could be a viable analytical matrix to determine changes in quality attributes of meat with aging.

Identifiers

PMID37025416
PMCPMC10070507
OpenAlexW4360603335

What OpenQuestion holds

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Registered trials

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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.