Pulmonary biocompatibility assessment of helical rosette nanotubes
Bibliographic record
Abstract
Helical rosette nanotubes are a class of organic nanotubes synthesized through the self‐assembly of individual rosettes. These compounds have potential for custom drug delivery platforms. We have chosen to evaluate the pulmonary in vivo biocompatibility of a specific lysine rosette nanotube (G0). Male C57/BL6 mice were dosed intratracheally with 50μl of G0 at a dose of 5, 25 or 50μg (n=5 each). Control mice were treated with 50μl of nanopure water (N=5) or 50μg lysine (N=5) in 50μl nanopure water. No mortality was observed in any of the animals before their euthanasia at 24h post‐treatment. Bronchoalvealoar lavage (BAL) fluid analysis revealed no significant difference in total cell count between the control mice or those treated with either lysine or G0 (5μg). However, BAL from mice treated with 25μg or 50μg G0 showed more total cells as well as more neutrophils compared to other three groups (P<0.05). Peripheral blood cell counts remained unchanged following any of the treatments. Histological examination showed no pathology in lung tissues from mice treated with saline or lysine or 5μg G0. But the lungs from mice administered 25μg or 50μg of G0 demonstrated congestion and thickening of alveolar septa from influx of inflammatory cells. We conclude that doses of 25μg or 50μg of lysine‐conjugated nanotubes induces an acute pulmonary response but a dose of 5μg is well tolerated by the mice. (Funding: NSERC, CIHR)
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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) | 0.000 | 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 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".