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Record W4309729732 · doi:10.3390/foods11233761

Uptake of Flaxseed Dietary Linusorbs Modulates Regulatory Genes Including Induction of Heat Shock Proteins and Apoptosis

2022· article· en· W4309729732 on OpenAlexaff
Youn Young Shim, Timothy J. Tse, AkalRachna K. Saini, Young Jun Kim, Martin J. T. Reaney

Bibliographic record

VenueFoods · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsGenome PrairieUniversity of Saskatchewan
FundersMinistry of Science and ICT, South Korea
KeywordsApoptosisHeat shock proteinBiologyCell biologyCell growthGene expressionCancer cellCell cultureHeat shockProgrammed cell deathCellGeneBiochemistryCancerGenetics

Abstract

fetched live from OpenAlex

L.) is gaining popularity as a superfood due to its health-promoting properties. Mature flax grain includes an array of biologically active cyclic peptides or linusorbs (LOs, also known as cyclolinopeptides) that are synthesized from three or more ribosome-derived precursors. Two flaxseed orbitides, [1-9-NαC]-linusorb B3 and [1-9-NαC]-linusorb B2, suppress immunity, induce apoptosis in a cell line derived from human epithelial cancer cells (Calu-3), and inhibit T-cell proliferation, but the mechanism of LO action is unknown. LO-induced changes in gene expression in both nematode cultures and human cancer cell lines indicate that LOs promoted apoptosis. Specific evidence of LO bioactivity included: (1) distribution of LOs throughout the organism after flaxseed consumption; (2) induction of heat shock protein (HSP) 70A, an indicator of stress; (3) induction of apoptosis in Calu-3 cells; and (4) modulation of regulatory genes (determined by microarray analysis). In specific cancer cells, LOs induced apoptosis as well as HSPs in nematodes. The uptake of LOs from dietary sources indicates that these compounds might be suitable as delivery platforms for a variety of biologically active molecules for cancer therapy.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.024
GPT teacher head0.250
Teacher spread0.226 · 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 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

Citations7
Published2022
Admission routes1
Has abstractyes

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