Altered brain morphology after focal radiation reveals impact of off-target effects: implications for white matter development and neurogenesis
Bibliographic record
Abstract
Background: Children with brain tumors treated with cranial radiation therapy (RT) often exhibit cognitive late effects, commonly associated with reduced white matter (WM) volume and decreased neurogenesis. The impact of radiation damage in particular regions or tissues on brain development as a whole has not been elucidated. Methods: We delivered whole-brain or focal radiation (8 Gy single dose) to infant mice. Focal treatments targeted white matter (anterior commissure), neuronal (olfactory bulbs), or neurogenic (subventricular zone) regions. High-resolution ex vivo MRI was used to assess radiation-induced volume differences. Immunohistochemistry for myelin basic protein and doublecortin was performed to assess associated cellular changes within white matter and related to neurogenesis, respectively. Results: Both whole-brain and focal RT in infancy resulted in volume deficits in young adulthood, with whole-brain RT resulting in the largest deficits. RT of the anterior commissure, surprisingly, showed no impact on its volume or on brain development as a whole. In contrast, RT of the olfactory bulbs resulted in off-target volume reduction in the anterior commissure and decreased subventricular zone neurogenesis. RT of the subventricular zone likewise produced volume deficits in both the olfactory bulbs and the anterior commissure. Similar off-target effects were found in the corpus callosum and parietal cortex. Conclusions: Our results demonstrate that radiation damage locally can have important off-target consequences for brain development. These data suggest that WM may be less radiosensitive than volume change alone would indicate and have implications for region-sparing radiation treatments aimed at reducing cognitive late effects.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".