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Record W4387537408 · doi:10.1101/2023.10.10.560427

Quinoa as Functional Food? Urinary elimination of ecdysterone after consumption of quinoa alone and in combination with spinach

2023· preprint· en· W4387537408 on OpenAlexfundno aff
Eduard Isenmann, Tasha Yuliandra, Konstantina Touvleliou, Matthias Broekmann, Xavier de la Torre, Francesco Botrè, Patrick Diel, Maria Kristina Parr

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsEcdysteroneSpinachUrineChemistryUrinary systemFood scienceBiologyBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

Abstract The phytosteroid ecdysterone is included on the monitoring list of the World Anti-Doping Agency. Therefore, the consumption of food rich in ecdysterone is the focus of a lively debate. Thus, urinary excretion of ecdysterone and its metabolites in humans was investigated following quinoa consumption alone and in combination with spinach. After intake of both preparations, ecdysterone and two metabolites were excreted in urine. Maximum concentrations of ecdysterone ranged from 0.44–5.50µg/mL after quinoa and 0.34– 4.09µg/mL after quinoa with spinach. The total urinary excreted amount as parent drug plus metabolites was 2.60(1.09)% following quinoa and 1.71(0.86)% after combination. Significant differences were found in total urinary excreted amounts of ecdysterone, 14-deoxy-ecdysterone, and 14-deoxy-poststerone. In conclusion, only small proportions of ecdysterone from quinoa and the combination with spinach were excreted in urine. The results indicate that both, quinoa and spinach, are poor sources of ecdysterone.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.027
GPT teacher head0.246
Teacher spread0.219 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

Explore more

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