Brain volume and microglial density changes are correlated in a juvenile mouse model of cranial radiation and CSF1R inhibitor treatment
Bibliographic record
Abstract
Microglia have been shown to proliferate and become activated following cranial radiotherapy (CRT), resulting in a chronic inflammatory response. We investigated the role of microglia in contributing to widespread volume losses observed in the brain following CRT in juvenile mice. To manipulate microglia, we used low-dose treatment with a highly selective CSF1R inhibitor called PLX5622 (PLX). We hypothesized that alteration of the post-CRT microglia population would lead to changes in brain development outcomes, as evaluated by structural MRI. Wild-type C57BL/6J mice were provided with daily intraperitoneal injections of PLX (25 mg/kg) or vehicle from postnatal day (P)14 to P19. Mice also received whole-brain irradiation (7 Gy) or sham irradiation (0 Gy) at 16 days of age. In one cohort of mice, immunohistochemical assessment in tissue sections was conducted to assess the impact of the selected PLX and CRT doses as well as their combination. In a separate cohort, mice were imaged using MRI at P14 (pretreatment), P19, P23, P42 and P63 in order to assess induced volume changes, which were measured based on structures from a predefined atlas. We observed that PLX and radiation treatments led to sex-specific changes in the microglial cell population. Across treatment groups, MRI-detected anatomical volumes at P19 and P63 were associated with microglia and proliferating microglia densities, respectively. Overall, our study demonstrates that low-dose PLX treatment produces a sex-dependent response in juvenile mice, that manipulation of microglia alters CRT-induced volume changes and that microglia density and MRI-derived volume changes are correlated in this model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".