Engineered nanomaterials and human health: Part 2. Applications and nanotoxicology (IUPAC Technical Report)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Research on engineered nanomaterials (ENM) has progressed rapidly from the very early stages of studying their unique, size-dependent physicochemical properties and commercial exploration to the development of products that influence our everyday lives. We have previously reviewed various methods for synthesis, surface functionalization, and analytical characterization of ENM in a publication titled ‘Engineered Nanomaterials: Preparation, Functionalization and Characterization’. In this second, inter-linked document, we first provide an overview of important applications of ENM in products relevant to human healthcare and consumer goods, such as food, textiles, and cosmetics. We then highlight the challenges for the design and development of new ENM for bio-applications, particularly in the rapidly developing nanomedicine sector. The second part of this document is dedicated to nanotoxicology studies of ENM in consumer products. We describe the various biological targets where toxicity may occur, summarize the four nanotoxicology principles, and discuss the need for careful consideration of the biodistribution, degradation, and elimination routes of nanosized materials before they can be safely used. Finally, we review expert opinions on the risk, regulation, and ethical aspects of using engineered nanomaterials in applications that may have direct or indirect impact on human health or our environment.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 it