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Record W4238071912 · doi:10.22215/etd/2013-09918

The antioxidant and anti-inflammatory activities of alkylresorcinols from rye bran

2013· dissertation· en· W4238071912 on OpenAlexaff
Julia Gliwa

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsCarleton UniversityAgriculture and Agri-Food Canada
Fundersnot available
KeywordsOxygen radical absorbance capacityAntioxidantBranChemistryFood scienceNitric oxideIn vivoGlutathioneSuperoxide dismutaseBiochemistryEnzymeAntioxidant capacityBiologyBiotechnology

Abstract

fetched live from OpenAlex

Alkylresorcinols (ARs) are phenolic lipids, found in the bran layer of cereals such as rye.They are natural antioxidants that confer many health benefits.In this study, ARs were extracted from Hazlet rye bran and analyzed for their in vitro antioxidant and antiinflammatory activities and in vivo antiobesity and antioxidant activities.In vitro studies showed that rye bran ARs have higher antioxidant activity than those from wheat and oat bran.ARs also exhibited anti-inflammatory activity by inhibiting the inflammatory mediator nitric oxide (NO), and gene expression of iNOS and COX-2.ARs did not exhibit antiobesity activity in CF-1 mice fed a 60% high fat (HF) diet but showed in vivo antioxidant activity in the liver using the oxygen radical absorbance capacity (ORAC) assay.In heart tissue, ARs exhibited higher antioxidant activity than the HF control diet, using the ORAC, superoxide dismutase (SOD), and glutathione assays, but results were not significant.v 2.4.6Effect of rye bran ARs on the protein expression of iNOS and COX-2 ........... 2.4.7 Effect of rye bran ARs on the mRNA expression of iNOS and COX-2........... 2.5 Discussion ..........

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.234
Teacher spread0.223 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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