Region-specific changes in<i>Mus musculus</i>brain size and cell composition under chronic nutrient restriction
Bibliographic record
Abstract
Nutrition is one of the most influential environmental factors affecting the development of different tissues and organs. It is suggested that under nutrient restriction the growth of the brain is spared as a result of the differential allocation of resources from other organs. However, it is not clear whether this sparing occurs brain-wide. Here, we analyzed morphological changes and cell composition in different regions of the offspring mouse brain after maternal exposure to nutrient restriction during pregnancy and lactation. Using high-resolution magnetic resonance imaging, we found that brain regions were differentially sensitive to maternal protein restriction and exhibited particular patterns of volume reduction. The cerebellum was reduced in absolute and relative volume, while cortex volume was relatively preserved. Alterations in cell composition (examined by the isotropic fractionator method) and organization of white matter (measured by diffusor tensor images) were also region specific. These changes were not related to the metabolic rate of the regions and were only partially explained by their specific growth trajectories. This study is a first step towards understanding the mechanisms of regional brain sparing at microstructural and macrostructural levels resulting from undernutrition.
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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 | 0.000 |
| 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".