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Record W2604058676 · doi:10.1113/jp274036

α‐Linolenic acid and exercise training independently, and additively, decrease blood pressure and prevent diastolic dysfunction in obese Zucker rats

2017· article· en· W2604058676 on OpenAlexafffund
Pierre‐Andre Barbeau, Tanya M. Holloway, Jamie Whitfield, Brittany L. Baechler, Joe Quadrilatero, Luc J. C. van Loon, Adrian Chabowski, Graham P. Holloway

Bibliographic record

VenueThe Journal of Physiology · 2017
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of WaterlooUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineInternal medicineEndurance trainingBlood pressureEndocrinologyVasodilationDiastole

Abstract

fetched live from OpenAlex

KEY POINTS: α-linolenic acid (ALA) and exercise training both attenuate hyperlipidaemia-related cardiovascular derangements, however, there is a paucity of information pertaining to their mechanisms of action when combined. We investigated both the independent and combined effects of exercise training and ALA consumption in obese Zucker rats, aiming to determine the potential for additive improvements in cardiovascular function. ALA and exercise training independently improved cardiac output, end-diastolic volume, left ventricular fibrosis and mean blood pressure following a 4 week intervention. Combining ALA and endurance exercise yielded greater improvements in these parameters, independent of changes in markers of oxidative stress or endogenous anti-oxidants. We postulate that divergent mechanisms of action may explain these changes: ALA increases peripheral vasodilation, and exercise training stimulates angiogenesis. ABSTRACT: Although α-linolenic acid (ALA) and endurance exercise training independently attenuate hyperlipidaemia-related cardiovascular derangements, there is a paucity of information pertaining to their mechanisms of action and efficacy when combined as a preventative therapeutic approach. Therefore, we used obese Zucker rats to investigate the independent and combined effects of these interventions on cardiovascular disease. Specifically, animals were randomly assigned to one of the following groups: control diet-sedentary, ALA supplemented-sedentary, control diet-exercise trained or ALA supplemented-exercise trained. Following a 4 week intervention, although the independent and combined effects of ALA and exercise reduced (P < 0.05) the serum free/esterified cholesterol ratio, only the ALA supplemented-exercise trained animals displayed a reduction in the content of both serum free and esterified cholesterol. Moreover, although ALA and endurance training individually increased cardiac output, stroke volume and end-diastolic volume, as well as reduced left ventricle fibrosis, mean blood pressure and total peripheral resistance, these responses were all greater following the combined intervention (ALA supplemented-exercise trained). These effects occurred independent of changes in oxidative phosphorylation proteins, markers of oxidative stress or endogenous anti-oxidant capacity. We propose that the beneficial effects of a combined intervention occur as a result of divergent mechanisms of action elicited by ALA and endurance exercise because only exercise training increased the capillary content in the left ventricle and skeletal muscle, and tended to decrease protein carbonylation in the left ventricle (P = 0.06). Taken together, our data indicate that combining ALA and endurance exercise provides additional improvements in cardiovascular disease risk reduction compared to singular interventions in the obese Zucker rat.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.304
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2017
Admission routes2
Has abstractyes

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