Mechanical Properties of the Developing Brain in a Model of Fetal Alcohol Spectrum Disorders and Relationships to Perineuronal Net Integrity
Bibliographic record
Abstract
Neuroimaging is a useful tool for examining altered neurodevelopmental trajectories in fetal alcohol spectrum disorders (FASD). FASD affects 1 in 20 infants in the United States with higher prevalence in specific regions across the globe. Advanced neuroimaging methods, such as volumetric morphometry and diffusion-weighted imaging, are critical for determining the effectiveness of interventions that support neurodevelopment in FASD. In this study, we introduce the use of magnetic resonance elastography (MRE), a cutting-edge neuroimaging technique used to measure the mechanical properties of brain tissue, to assess the impact of alcohol exposure and combined exercise and environmental complexity intervention on neurodevelopment in a rat model of FASD. Our results indicate that brain stiffness is reduced in juvenile alcohol-exposed rats which is recovered to baseline by adulthood, and damping ratio increases in all rats with age. Additionally, we quantified cortical perineuronal net (PNN) density which follows similar trends to shear stiffness and damping ratio, suggesting MRE may be an effective method for noninvasively monitoring FASD progression related to extracellular matrix integrity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".