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Record W4206331989 · doi:10.1177/23978473211061428

Safety assessment of purine nucleosidase from <i>Aspergillus luchuensis</i>

2021· article· en· W4206331989 on OpenAlexaff
Trung D. Vo, Jwar Meetro, Seth Floyd, Barry Lynch, Shahrzad Tafazoli, A. Ichihara, Go Chikamatsu

Bibliographic record

VenueToxicology Research and Application · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsPurinePurine analogueChemistryPurine metabolismAmes testPharmacologyBiochemistryFood scienceBiologyEnzyme

Abstract

fetched live from OpenAlex

Purine nucleosidase (EC 3.2.2.1) catalyzes the N-riboside hydrolysis of purine nucleosides to D-ribose and a purine base. This enzyme may be used in the production of beer and other alcoholic beverages to reduce the purine content of these products. Purine nucleosidase was obtained from Aspergillus luchuensis naturally occurring in grain sources. The safety profile of purine nucleosidase is not well documented in the scientific literature, and a series of toxicological studies were undertaken to investigate the safety of its use in food production. Purine nucleosidase from A. luchuensis was non-mutagenic and non-clastogenic in a standard Ames test and in vitro mammalian chromosome aberration assay. Administration of purine nucleosidase in a 90-day subchronic toxicity study in Sprague-Dawley rats did not elicit adverse findings on any hematology, clinical chemistry, urinalysis, organ weight, or histopathological parameter at doses up to 1700 mg total organic solids (TOS)/kg body weight/day, the highest dose tested. The results suggest purine nucleosidase to lack systemic toxic effect. The no-observed-adverse-effect level was concluded to be 1700 mg TOS/kg body weight/day. The results of the toxicology studies support the safety of purine nucleosidase from a non-genetically modified strain of A. luchuensis when used in food production.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.040
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.020
GPT teacher head0.363
Teacher spread0.342 · 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.

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
Published2021
Admission routes1
Has abstractyes

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