Evaluation of the radiation-sensitizer/protector and/or antioxidant efficiencies using Fricke and PAG dosimeters
Bibliographic record
Abstract
In this study, our aim is to assess the potential of Fricke and polyacrylamide gel (PAG) dosimeters to quantitatively evaluate the efficiency of potential radiation sensitizers/protectors and antioxidants. These compounds are of importance in radiotherapy as well as in disease prevention and promotion of health. The basic principle of the Fricke dosimeter is the radiation-induced oxidation of Fe 2+ to Fe 3+ in an aerated aqueous 0.4 M H 2 SO 4 . The production of ferric ions is most sensitive to the radical species produced in the radiolysis of water. Using this method, we observed that cystamine (one of the best of the known radioprotectors) can prevent oxydation of Fe 2+ from reactive radiolysis species. However, one obvious disadvantage of the Fricke dosimeter is that it operates under highly acidic conditions (pH 0.46), which may degrade biological compounds. In contrast, the pH of the polyacrylamide gel (PAG) dosimeter is almost neutral, such that degradation of compounds is less probable. A change in R 2 -dose sensitivity was observed in the presence of radiosensitizers/radioprotectors and antioxidants. The protective effect of Trolox (a well-known antioxidant) and thiourea (a radioprotector) was readily observed using the PAG dosimeter. Incorporation of iodinated radiation sensitizers such as NaI and an iodine contrast agent led to a quantifiable sensitizer enhancement ratio. These studies suggest that the Fricke and the PAG dosimeters have the potential to evaluate the efficiency of radiation sensitizers/protectors and antioxidants.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".