In silico and in vitro safety assessment of a fungal biomass from Rhizomucor pusillus for use as a novel food ingredient
Bibliographic record
Abstract
To address the growing world population and reduce the impact of environmental changes on the global food supply, ingredients are being produced using microorganisms to yield sustainable and innovative products. Food ingredients manufactured using modern biotechnology must be produced by non-toxigenic and nonpathogenic production organisms that do not harbor antimicrobial resistance (AMR). Several fungal species represent attractive targets as sources of alternative food products. One such product is a fungal biomass obtained from the fermentation of Rhizomucor pusillus strain CBS 143028. The whole genome sequence of this strain was annotated and subjected to sequence homology searches and in silico phenotype prediction tools to identify genetic elements encoding for protein toxins active via oral consumption, virulence factors associated with pathogenicity, and determinants of AMR. The in silico investigation revealed no genetic elements sharing significant sequence homology with putative virulence factors, protein toxins, or AMR determinants, including the absence of mucoricin, an essential toxin in the pathogenesis of mucormycosis. These in silico findings were corroborated in vitro based on the absence of clinically relevant mycotoxin or antibacterial secondary metabolites. Consequently, it is unlikely that R. pusillis strain CBS 143028 would pose a safety concern for use in food for human consumption.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".