Assessment of Cystamine’s Radioprotective/Antioxidant Ability under High-Dose-Rate Irradiation: A Monte Carlo Multi-Track Chemistry Simulation Study
Bibliographic record
Abstract
(1) Background: cystamine and its reduced form cysteamine have radioprotective/antioxidant effects in vivo. In this study, we use an in vitro model system to examine the behavior of cystamine towards the reactive primary species produced during the radiolysis of the Fricke dosimeter under high dose-rate irradiation conditions. (2) Methods: our approach was to use the familiar radiolytic oxidation of ferrous to ferric ions as an indicator of the radioprotective/antioxidant capacity of cystamine. A Monte Carlo computer code was used to simulate the multi-track radiation-induced chemistry of aerated and deaerated Fricke-cystamine solutions as a function of dose rate while covering a large range of cystamine concentrations. (3) Results: our simulations revealed that cystamine provides better protection at pulsed dose rates compared to conventional, low-dose-rate irradiations. Furthermore, our simulations confirmed the radical-capturing ability of cystamine, clearly indicating the strong antioxidant profile of this compound. (4) Conclusion: assuming that these findings can be transposable to cells and tissues at physiological pH, it is suggested that combining cystamine with FLASH-RT could be a promising approach to further enhance the therapeutic ratio of cancer cure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".