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Improvements in arterial stiffness due to bean and pea consumption are determined by metabolic state

2017· article· en· W2911464464 on OpenAlexaffabout
Peter Zahradka, Danielle Perera, Angela Wilson, Matthew Wiecek, Rhonda C. Bell, Carla G. Taylor

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsUniversity of AlbertaUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsArterial stiffnessMedicineBlood pressureCholesterolPulse wave velocityBody mass indexCardiologyInternal medicineCohortEndocrinology

Abstract

fetched live from OpenAlex

Background Higher consumption of pulses (dried beans, peas, lentils, chickpeas) is associated with lower risk of cardiovascular disease due to declines in circulating LDL‐cholesterol levels and reduced blood pressure. These studies have focused on individuals who were healthy or had mild metabolic dysfunction. Furthermore, most studies have monitored cardiovascular risk factors and not vascular function directly. Objective To determine in a randomized clinical trial if metabolic disease parameters affect the response to bean and pea consumption with respect to vascular function assessed by pulse wave analysis. Methods Participants with mild hypercholesterolemia but not taking any cholesterol‐ or glucose‐lowering medications consumed a selection of 5 study foods containing 120 g beans or peas or rice per serving, five times per week for 6 weeks as part of their usual diet. At the Winnipeg site, vascular function was assessed non‐invasively at baseline and 6 weeks to determine arterial stiffness (augmentation index normalized to a heart rate of 75 beats per minute). The effect of body mass index, glycemia, lipidemia and blood pressure on the vascular response to beans or peas was determined by covariate analysis. Results No changes in augmentation index were detected without taking metabolic parameters into account. Interestingly, arterial stiffness (lower augmentation index) was improved in persons who had consumed beans or peas, but not rice, and had levels of LDL‐cholesterol or total cholesterol above the median (3.7 mmol/L and 5.7 mmol/L, respectively) within the cohort. Lower arterial stiffness was also seen in persons consuming beans or peas and having a BMI below the median (27.5 kg/m 2 ). Subgroup analysis also showed that insulin or triglycerides influenced augmentation index in persons consuming beans or peas, but the improvement occurred regardless of whether these values were above or below the median (53 pmol/L and 1.4 mmol/L, respectively). Metabolic factors associated with glycemia, including fasting glucose and HbA1c, were not associated with arterial stiffness. Conclusions This study has shown for the first time that augmentation index, a key parameter of arterial stiffness, can be influenced by several metabolic factors. Although contrary to expectations, participants with higher total and LDL‐cholesterol levels showed improvements in arterial stiffness in response to bean or pea consumption, while those with lower levels did not. In contrast, lower body mass index was associated with a reduction in arterial stiffness in persons eating beans or peas. These are the first data to indicate that the individual response of blood vessel elasticity to diet may depend upon the underlying metabolic characteristics of that individual even in the absence of overt disease. Support or Funding Information Alberta Innovates BioSolutions and Alberta Pulse Growers

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.296
Teacher spread0.269 · 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 designObservational
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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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