A Detailed Viscoelastic Characterization of the P17 and Adult Rat Brain
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Bibliographic record
Abstract
Brain is a morphologically and mechanically heterogeneous organ. Although rat brain is commonly used as an experimental neurophysiological model for various in vivo biomechanical studies, little is known about its regional viscoelastic properties. To address this issue, we have generated viscoelastic mechanical property data for specific anatomical regions of the P17 and adult rat brain. These ages are commonly used in rat experimental models. We measured mechanical properties of both white and gray matter regions in coronal slices with a custom-designed microindentation device performing stress-relaxation indentations to 10% effective strain. Shear moduli calculated for short (100?ms), intermediate (1?sec), and long (20?sec) time points, ranged from ?1?kPa for short term moduli to ?0.4?kPa for long term moduli. Both age and anatomic region were significant factors affecting the time-dependent shear modulus. White matter regions and regions of the cerebellum were much more compliant than those of the hippocampus, cortex, and thalamus. Linear viscoelastic models (Prony series, continuous phase lag, and a power law model) were fit to the time-dependent shear modulus data. All models fit the data equally with no significant differences between them (F-test; p>0.05). The F-test was also used to statistically determine that a Prony series with three time-dependent parameters accurately fit the data with no added benefit from additional terms. The age- and region-dependent rat brain viscoelastic properties presented here will help inform future biomechanical models of the rat brain with specific and accurate regional mechanical property data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it