In vitro evaluation of percutaneous diffusion of uranyl nitrate through intact or excoriated skin of rat and pig
Bibliographic record
Abstract
At the present time, the International Commission on Radiological Protection (ICRP) has not published any model concerning internal radioactive contamination by uptake from wounds. The aims of our work were to determine the time available to treat contamination of intact or wounded skin before a significant uptake of uranium occurred and to evaluate the consequences of incomplete decontamination on uranium uptake. The kinetics of percutaneous diffusion of uranium through intact or excoriated skin and its distribution in skin layers were evaluated using an in vitro technique. Our data demonstrated a dramatic increase of uranium percutaneous diffusion through excoriated skin compared with intact skin. Significant uptake of uranium through excoriated skin occurred in only 30 min, indicating that there is only a short interval available to treat a contaminated wound effectively. Moreover, in the case of an incompletely decontaminated superficial wound, viable epidermis behaved as a reservoir for uranium that remained bioavailable. At the present time, potential uptake of uranium and perhaps other radionuclides through intact or wounded skin is not adequately taken into account by radiological protection agencies. Our results emphasize the need for further study and modeling of uptake of radionuclides through intact or wounded skin.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".