QOL-23. POTENTIAL MYELIN REPAIR AFTER IRRADIATED PEDIATRIC BRAIN TUMOR: A MAGNETIZATION TRANSFER IMAGING ANALYSIS
Bibliographic record
Abstract
Abstract BACKGROUND Exercise training and metformin treatment may improve cognition after cranial irradiation in pediatric brain tumors (PBT), but the neuronal mechanisms underlying the effect of these interventions remains unknown. Magnetization transfer imaging (MTI) is an imaging technique that may be sensitive to white matter microstructure – including myelin. METHODS In this work, we analyzed changes in magnetization transfer ratio (MTR) over a 12-week period in irradiated PBT survivors who participated in pilot clinical trials entailing 12 weeks of exercise training (exercise group, n=17), or metformin treatment (n=12). Pre- and post-intervention assessment included MRI scanning and neurocognitive tests. A no intervention control group, (n=7) was also included and seen before and after a 12 week period of time. We used a longitudinal Tract-Based Spatial Statistics (TBSS) approach to analyze differences in MTR across the 12 weeks in the three groups, using as covariates: age at baseline, sex, handedness, age at diagnosis and delay from diagnosis. Then we performed correlations between mean MTR changes and behavioral outcomes. RESULTS Clusters of significant increase in MTR were observed in the right temporal lobe in the exercise group after intervention and in the right minor forceps in the metformin group after treatment. These changes respectively correlated with higher performance in free recall score in exercise group and with higher performances in inhibitory control and attention in metformin group. There was no difference in MTR changes between groups nor within the control group. DISCUSSION This exploratory work suggests either a 12-week period of exercise training or metformin may promote myelination in PBT survivors in brain regions. These changes appear to be associated with improved memory and executive function, two core domains of neurocognitive deficit in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".