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Record W4310461146 · doi:10.1080/10408398.2022.2148627

A review of flaxseed lignan and the extraction and refinement of secoisolariciresinol diglucoside

2022· review· en· W4310461146 on OpenAlexafffund
Yingxue Hu, Timothy J. Tse, Youn Young Shim, Sarah K. Purdy, Young Jun Kim, Venkatesh Meda, Martin J. T. Reaney

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2022
Typereview
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of Saskatchewan
FundersMitacs
KeywordsLignanPhenylpropanoidChemistryFood scienceIngredientBiotechnologyBiochemistryOrganic chemistryBiologyEnzyme

Abstract

fetched live from OpenAlex

Lignan is a class of diphenolic compounds that arise from the condensation of two phenylpropanoid moieties. Oilseed and cereal crops (e.g., flaxseed, sesame seed, wheat, barley, oats, rye, etc.) are major sources of plant lignan. Methods for commercial isolation of the lignan secoisolariciresinol diglucoside (SDG) are not well reported, as most publications describing the detection, extraction, and enrichment of SDG use methods that have not been optimized for commercial scale lignan recovery. Simply scaling up laboratory methods would require expensive infrastructure to achieve a marketable yield and reproducible product quality. Therefore, establishing standard protocols to produce SDG and its derivatives on an industrial scale is critical to decrease lignan cost and increase market opportunities. This review summarizes the human health benefits of flaxseed lignan consumption, lignan physicochemical properties, and mammalian lignan metabolism, and describes methods for detecting, extracting, and enriching flaxseed lignan. Refining and optimization of these methods could lead to the development of inexpensive lignan sources for application as an ingredient in medicines, dietary supplements, and other healthy ingredients.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.736
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.112
GPT teacher head0.445
Teacher spread0.333 · 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 designNot applicable
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

Citations21
Published2022
Admission routes2
Has abstractyes

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