pith:SNTL7X6Y
Voxel-aware oxygen kinetics resolves radiation-induced DNA damage retention across LET-oxygen conditions
Voxel-aware oxygen kinetics enables particle-specific modeling of DNA damage retention across LET and oxygen conditions at clinical planning speeds.
arxiv:2605.12558 v2 · 2026-05-11 · physics.med-ph
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Claims
VOxA is the first particle-specific OER model to reproduce Z-ordering analytically at clinical planning speed, validated on the largest OER calibration dataset for this model class.
The dual sigmoidal LET-OER transitions constrained to increase monotonically with atomic number Z, combined with Michaelis-Menten kinetics and a single calibrated particle-specific sensitivity parameter, sufficiently capture the underlying biology across the full range of LET and oxygen conditions.
VOxA achieves R²=0.719 on 233 OER observations across 10 particle types and outperforms clinical standards by 28.4% in survival OER MAE while running over 10^6 times faster than Monte Carlo.
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| First computed | 2026-05-18T03:10:02.020485Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9366bfdfd83dce52235bd060967ebbf0537162e732c22299a34ef65ec9ca4928
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/SNTL7X6YHXHFEI232BQJM7V36B \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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