Evidence map›Paper›PMID 29642414›Full record

ArticleNutrients2018

Proteomic Profiles of Adipose and Liver Tissues from an Animal Model of Metabolic Syndrome Fed Purple Vegetables.

Hala M Ayoub, Mary Ruth McDonald, James Alan Sullivan, Rong Tsao, Kelly A Meckling

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Loss of GlycineInternational journal of molecular sciences · 2019
    Article
  6. Review
  7. 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

5 authors at 2 institutions in 1 country.

Hala M AyoubDepartment of Human Health and Nutrition Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada. hayoub@uoguelph.ca.
Mary Ruth McDonaldDepartment of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada. mrmcdona@uoguelph.ca.
James Alan SullivanDepartment of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada. asulliva@uoguelph.ca.
Rong TsaoGuelph Research & Development Centre, Agriculture and Agri-Food Canada, Guelph, ON N1G 5C9, Canada. Rong.Cao@agr.gc.ca.
Kelly A MecklingDepartment of Human Health and Nutrition Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada. kmecklin@uoguelph.ca.
University of Guelph · CAAgriculture and Agri-Food Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic Syndrome (MetS) is a complex disorder that predisposes an individual to Cardiovascular Diseases and type 2 Diabetes Mellitus. Proteomics and bioinformatics have proven to be an effective tool to study complex diseases and mechanisms of action of nutrients. We previously showed that substitution of the majority of carbohydrate in a high fat diet by purple potatoes (PP) or purple carrots (PC) improved insulin sensitivity and hypertension in an animal model of MetS (obese Zucker rats) compared to a control sucrose-rich diet. In the current study, we used TMT 10plex mass tag combined with LC-MS/MS technique to study proteomic modulation in the liver (

Indexed as

Animal FeedEnergy MetabolismAdipose TissueAnimalsCholesterolChromatography, LiquidColorDaucus carotaDisease Models, AnimalEsterificationFatty Acids, NonesterifiedLipogenesisLiverMetabolic SyndromeOxidative StressPlant RootsCholesterolFatty Acids, NonesterifiedProteinscarrotshigh fat diethypertensioninsulin resistanceobesitypotatoesproteomic analyses

Identifiers

PMID29642414
PMCPMC5946241
OpenAlexW2795633020

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.