High-LET-Radiation-Induced Persistent DNA Damage Response Signaling and Gastrointestinal Cancer Development
Bibliographic record
Abstract
Ionizing radiation (IR) dose, dose rate, and linear energy transfer (LET) determine cellular DNA damage quality and quantity. High-LET heavy ions are prevalent in the deep space environment and can deposit a much greater fraction of total energy in a shorter distance within a cell, causing extensive DNA damage relative to the same dose of low-LET photon radiation. Based on the DNA damage tolerance of a cell, cellular responses are initiated for recovery, cell death, senescence, or proliferation, which are determined through a concerted action of signaling networks classified as DNA damage response (DDR) signaling. The IR-induced DDR initiates cell cycle arrest to repair damaged DNA. When DNA damage is beyond the cellular repair capacity, the DDR for cell death is initiated. An alternative DDR-associated anti-proliferative pathway is the onset of cellular senescence with persistent cell cycle arrest, which is primarily a defense mechanism against oncogenesis. Ongoing DNA damage accumulation below the cell death threshold but above the senescence threshold, along with persistent SASP signaling after chronic exposure to space radiation, pose an increased risk of tumorigenesis in the proliferative gastrointestinal (GI) epithelium, where a subset of IR-induced senescent cells can acquire a senescence-associated secretory phenotype (SASP) and potentially drive oncogenic signaling in nearby bystander cells. Moreover, DDR alterations could result in both somatic gene mutations as well as activation of the pro-inflammatory, pro-oncogenic SASP signaling known to accelerate adenoma-to-carcinoma progression during radiation-induced GI cancer development. In this review, we describe the complex interplay between persistent DNA damage, DDR, cellular senescence, and SASP-associated pro-inflammatory oncogenic signaling in the context of GI carcinogenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".