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Record W2916380333 · doi:10.1055/s-0039-1678691

Importance of Flaxseed and its Components in the Management of Hypertension

2019· review· en· W2916380333 on OpenAlexaff
Kailash Prasad

Bibliographic record

VenueInternational Journal of Angiology · 2019
Typereview
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineAngiologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract This review paper describes the effects of flaxseed and its components (flax oil, secoisolariciresinol diglucoside [SDG], flax lignan complex [FLC], and flaxseed protein hydrolysate [FPH]) on blood pressure (BP) in Sprague Dawley rats (SDR), spontaneously hypertensive rats (SHR), and humans. Flaxseed, flax oil, and FLC had variable effects on BP in humans, while SDG and FPH significantly reduced the BP in SDR and SHR. The effect of SDG was dose-dependent and long lasting. The lowering of BP is mediated through inhibition of soluble epoxide by α-linolenic acid in flax oil, stimulation of guanylate cyclase and inhibition of angiotensin converting enzyme (ACE) by SDG, and inhibition of renin and ACE activity by FPH. Flaxseed, flax oil, and FLC have variable effects on BP (none, slight, and significant). They are effective in lowering BP in individuals with hypertension and metabolic syndrome but ineffective in healthy individuals' ineffectiveness of flaxseed and its compounds in lowering BP may be due to their low doses, long interval of dosing, short duration of consumption, and patient status. In conclusion, the data at present suggest that flaxseed, flax oil, and FLC cannot serve as therapeutic agents for the treatment of hypertension. However, they can be used as an adjunct in the treatment of hypertension. A clinical trial should be conducted of these agents with higher doses which would be given twice daily for long duration. Pure SDG and FPS may serve as therapeutic agents for the treatment of hypertension but they have not been tried in humans.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.129
GPT teacher head0.370
Teacher spread0.241 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations14
Published2019
Admission routes1
Has abstractyes

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