Generation of ultrafast, transient, highly acidic pH spikes in the radiolysis of water at very high dose rates: relevance for FLASH radiotherapy
Bibliographic record
Abstract
Monte Carlo multi-track chemistry simulations were carried out to study the effects of high dose rates on the transient yields of hydronium ions (H3O+) formed during low linear energy transfer (LET) radiolysis of both pure, deaerated and aerated liquid water at 25 °C, in the interval ∼1 ps – 10 μs. Our simulation model consisted of randomly irradiating water with N interactive tracks of 300-MeV incident protons (LET ∼ 0.3 keV/µm), which simultaneously impact perpendicularly on the water within a circular surface. The effect of the dose rate was studied by varying N. Our calculations showed that the radiolytic formation of H3O+ causes the entire irradiated volume to temporarily become very acidic. The magnitude and duration of this abrupt “acid-spike” response depend on the value of N. It is most intense at times less than ∼10–100 ns, equal to ∼3.4 and 2.8 for N = 500 and 2000 (i.e., for dose rates of ∼1.9 × 109 and 8.7 × 109 Gy/s, respectively). At longer times, the pH gradually increases for all N values and eventually returns to the neutral value of seven, which corresponds to the non-radiolytic, pre-irradiation concentration of H3O+. It is worth noting that these early acidic pH responses are very little dependent on the presence or absence of oxygen. Finally, given the importance of pH for many cellular functions, this study suggests that these acidic pH spikes may contribute to the normal tissue-sparing effect of FLASH radiotherapy.
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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) | 0.000 | 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 | 0.001 | 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".