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Coumarin and Safrole Content in Cinnamon-Flavored Food Products on the Syrian Market

2017· article· en· W2735429114 on OpenAlexvenueno aff
Raw'aa Solaiman, Joumaa Al-Zehouri

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSafroleCoumarinCassiaCinnamomumCinnamaldehydeFood scienceNutmegChemistryTraditional medicineCarcinogenToxicologyMedicineOrganic chemistryBiologyChromatography

Abstract

fetched live from OpenAlex

Some plants that are processed into foods often contain natural substances that may be hazardous to human health. One example is coumarin, which is known to cause liver and kidney damage in rats, mice and probably humans. Coumarin is found in different Cinnamomum species such as Cinnamomum cassia, Cinnamomum loureiroi, and Cinnamomum burmannii; all commonly referred to as cassia. Another hazardous substance is Safrole. Safrole is reasonably anticipated to be a human carcinogen based on sufficient evidence of carcinogenicity from studies in experimental animals; and is mainly present in cinnamon leaf oil and could be a possible contaminant in cinnamon powder. European Council’s Directive on food flavourings 88/388/EEC limits safrole in foodstuffs to 1ppm. The content of coumarin is regulated in the European Regulation (EC) No 1334/2008. In the present study, coumarin and safrole levels were analyzed in locally bought cinnamon samples and cinnamon-flavored food products using a validated HPLC method with diode array detector (DAD). Appreciable amounts of coumarin were found in bakery products with concentrations up to 39.466 mg/kg in certain kinds of cookies, whereas safrole was undetectable. Our exposure data on coumarin in bakery products show that there is still a need for a continued regulation of coumarin in foods. A toxicological re-evaluation of coumarin with the aim to derive scientifically founded maximum limits should be conducted with priority.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.084
GPT teacher head0.334
Teacher spread0.250 · 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
Published2017
Admission routes1
Has abstractyes

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