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Record W4417196131 · doi:10.1080/19390211.2025.2597203

Bioavailability and Metabolism of N-Trans Caffeoyltyramine and N-Trans Feruloyltyramine – A Narrative Review

2025· review· en· W4417196131 on OpenAlexaff
Julie Shlisky, Swati Kalgaonkar, Clayton Bloszies, Jan-Willem van Kinken, Mário G. Ferruzzi

Bibliographic record

VenueJournal of Dietary Supplements · 2025
Typereview
Languageen
FieldMedicine
TopicCoffee research and impacts
Canadian institutionsNutrasource
Fundersnot available
KeywordsBioavailabilityNarrative reviewMetabolismMicrobial metabolismFermentationHuman studies

Abstract

fetched live from OpenAlex

and animal systems. However, the bioavailability of similar phenolics and phenolic amides from other sources has been experimentally determined. This concise review summarizes the current state of knowledge for phenolic amides with the goal of providing experimental guidance on the assessment of NCT and NFT from hemp ingredients in humans. Evidence from phenolic and avenanthramide (similar phenolic amides from oats) suggest that overall absorption of free phenolic amides would be limited in humans to <2% of native forms. Metabolites derived by both host (conjugated Phase II metabolites) and microbial fermentation products would likely represent the main compounds in circulation derived from NCT or NFT intake. This would be extensively influenced by the matrix provided including hemp-based ingredients with large portions of physically and chemically bound NCT and NFT forms that are not absorbable. Experimental designs to determine NCT and NFT response in humans would need to consider longer exposure and collection periods to adequately capture 24 and 48h urine and blood samples likely to have key NCT and NFT derived microbial and host metabolites present. Considering adaptation of the microbiota to these compounds it is likely that a robust design would also include a dimension of long-term exposure to enable detection of target metabolites derived from hemp NCT and NFT.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.841
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.409
Teacher spread0.356 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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