An appraisal of the published literature on the safety and toxicity of food-related nanomaterials
Bibliographic record
Abstract
Nanotechnology is poised to impact the food and food-related industries through improvements in areas as diverse as production, packaging, shelf life, and bioavailability of food and beverage components. An evaluation was undertaken to characterize the published literature pertaining to the safety of oral exposure to food-related nanomaterials and to identify research needs in this area. Thirty publications were identified in which a toxicological endpoint was assessed following in vivo (oral) or in vitro exposure to food-related nanomaterials. These publications were evaluated for overall quality using a two-step method that determined the reliability of the study design and the extent of nanomaterial characterization within each study. Of the 21 in vivo studies evaluated, 20 used mice or rats, 15 were lacking in some critical component of study design (e.g., oral gavage dose volume was not reported), none was longer than 90 days in duration, and only seven reported more than five physicochemical parameters for the nanomaterial(s) being evaluated. Of the nine in vitro studies evaluated, seven focused on cytotoxicity, two evaluated genotoxicity, only five reported more than five physicochemical parameters for the nanomaterial(s) being evaluated, and none discussed the potential interference by the nanomaterial(s) of the experimental assays that were employed. The results of this evaluation indicate that there is currently insufficient reliable data to allow clear assessment of the safety of oral exposure to food-related nanomaterials. Significant investment must be made to generate studies of sufficient quality and duration and that report comprehensive nanomaterial characterization such that results can be judged reliable and interpretable. Failure to do so will result in the perpetuation of the publication of studies that are inadequate for use in risk characterization.
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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.034 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".