Safety evaluation of arabinase (arabinan endo‐1,5‐α‐L‐arabinanase) from <i>Aspergillus tubingensis</i>
Bibliographic record
Abstract
Abstract Arabinase is an enzyme recognized for its ability to degrade arabinan, a plant cell wall constituent. It has been applied in the food industry most commonly for juice processing. One commercial source of arabinase is Aspergillus tubingensis (A. tubingensis), a black Aspergillus species. Given the intended use in food for human consumption, and noting its potential presence at trace levels in finished products, a series of safety studies including in vitro Ames and chromosome aberration assays, in vivo mammalian erythrocyte micronucleus and alkaline comet assays, and a 90‐day rat oral toxicity study were conducted. No test article‐related mutagenic activity was observed in the Ames assay. Although positive activity was observed in the chromosome aberration assay, this was not replicated in the in vivo genotoxicity assays including in preabsorptive cells. In the subchronic toxicity study, no test article‐related adverse effects were observed following oral administration of arabinase at doses of 15.3, 153, or 1,530 mg total organic solids (TOS)/kg body weight/day to Sprague Dawley rats. The no‐observed‐adverse‐effect level was considered to be the highest dose tested (1,530 mg TOS/kg body weight/day). The results of the genotoxicity studies and the subchronic toxicity study support the safe use of arabinase from A. tubingensis in food production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".