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Ochratoxin A from a toxicological perspective

2000· review· en· W2060360020 on OpenAlexaboutno aff
Petzinger, Ziegler

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2000
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsnot available
Fundersnot available
KeywordsOchratoxin AMycotoxinAspergillus ochraceusFood scienceOchratoxinAflatoxinCarcinogenToxicologyBiology

Abstract

fetched live from OpenAlex

Ochratoxin A (OTA) is a widespread mycotoxin which is produced mainly by the mould fungi Aspergillus ochraceus and Penicillum verrucosum during the storage of cereals, cereal products and other plant-derived products such as herbs, spices, grapes, etc. By carry over from mouldy fodder, ochratoxin A is also found in pork meat, offal and sausages containing pork blood. When ingested as a food contaminant, OTA is very persistent in human beings with a blood half-life of 35 days after a single oral dosage due to unfavourable elimination toxicokinetics. This renders the toxin among the most frequent mycotoxin contaminants in human blood in the EU, the US, Canada, and elsewhere, where it has been investigated. OTA is neither stored nor deposited in the body, but heterogeneous body distribution may impose serious damage to the kidneys. The toxin was classified a 2B cancer compound, being possibly carcinogenic for humans. It was among the strongest carcinogenic compounds in rats and mice. As the toxicological profile also includes teratogenesis, nephrotoxicity, and immunotoxicity, legislation authorities are currently discussing maximal residue levels (MRL) for OTA in various foodstuffs. In the present article arguments are presented which suggest an acceptable daily intake (ADI) of 1.5 ng OTA/kg body weight and a much lower MRL than 5 microgram OTA/kg cereals and cereal products as has been postulated by the EU commission.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.102
GPT teacher head0.376
Teacher spread0.273 · 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 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

Citations309
Published2000
Admission routes1
Has abstractyes

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