Evidence map›Paper›PMID 33395447›Full record

ArticlePloS one2021

Evidence of vascular endothelial dysfunction in Wooden Breast disorder in chickens: Insights through gene expression analysis, ultra-structural evaluation and supervised machine learning methods.

Behnam Abasht, Michael B Papah, Jing Qiu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. 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
3.0field-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

13 citing papers in PubMed, 23 citations in OpenAlex.

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  6. Frontiers in physiology · 2023
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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

3 authors at 1 institution in 1 country.

Behnam AbashtDepartment of Animal and Food Sciences, University of Delaware, Newark, DE, United States of America.ORCID 0000-0003-2374-8145
Michael B PapahDepartment of Animal and Food Sciences, University of Delaware, Newark, DE, United States of America.ORCID 0000-0003-0306-7510
Jing QiuDepartment of Applied Economics and Statistics, University of Delaware, Newark, DE, United States of America.
University of Delaware · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several gene expression studies have been previously conducted to characterize molecular basis of Wooden Breast myopathy in commercial broiler chickens. These studies have generally used a limited sample size and relied on a binary disease outcome (unaffected or affected by Wooden Breast), which are appropriate for an initial investigation. However, to identify biomarkers of disease severity and development, it is necessary to use a large number of samples with a varying degree of disease severity. Therefore, in this study, we assayed a relatively large number of samples (n = 96) harvested from the pectoralis major muscle of unaffected (U), partially affected (P) and markedly affected (A) chickens. Gene expression analysis was conducted using the nCounter MAX Analysis System and data were analyzed using four different supervised machine-learning methods, including support vector machines (SVM), random forests (RF), elastic net logistic regression (ENET) and Lasso logistic regression (LASSO). The SVM method achieved the highest prediction accuracy for both three-class (U, P and A) and two-class (U and P+A) classifications with 94% prediction accuracy for two-class classification and 85% for three-class classification. The results also identified biomarkers of Wooden Breast severity and development. Additionally, gene expression analysis and ultrastructural evaluations provided evidence of vascular endothelial cell dysfunction in the early pathogenesis of Wooden Breast.

Indexed as

Gene Expression RegulationSupervised Machine LearningAnimalsBiomarkersBreast DiseasesChickensEndothelium, VascularLipid MetabolismLipoprotein LipaseLogistic ModelsMicroscopy, Electron, TransmissionMuscle ContractionPectoralis MusclesPoultry DiseasesBiomarkersLipoprotein Lipase

Identifiers

PMID33395447
PMCPMC7781381
OpenAlexW3119036229

What Socratic 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 Socratic graph.