The Effects of Age on the Morphometry of the Cervical Spinal Cord and Spinal Column in Adult Rats: An <scp>MRI</scp>‐Based Study
Bibliographic record
Abstract
Rat models are commonly used to investigate the pathophysiological pathways and treatment outcomes after spinal cord injury (SCI). The high incidence of fall-induced SCI in older adults has created a need for aging models of SCI in rats to investigate potential age-related differences in SCI severity and outcomes. The aims of this study were to determine the influences of age and vertebral level on the geometries of the cervical spinal cord and spinal column in a rat model. Three young (3 months) and three aged (12 months) Fischer 344 rats were imaged in a high field (7 T) small-animal magnetic resonance imaging system. All spinal cord geometry variables (including depth, width, and axial cross-sectional area) and one spinal canal variable (depth) were significantly larger in the aged specimens by an average of 8.1%. There were main effects of vertebral level on all spinal cord variables and four spinal canal variables with values generally larger at C4 as compared to C6 (average increases ranged from 5.7% to 12.9% in spinal cord measures and 5.4% to 6.8% in spinal canal measures). High inter-rater reliability between two measurers was observed with a mean intraclass correlation of 0.921 and percent difference of 0.9% across all variables measured. This study clearly demonstrates that cervical spinal cord geometry changes between the ages of 3 and 12 months in Fischer 344 rats. This information can aid in the planning and interpretation of studies that use a rat model to investigate the influence of age on cervical SCI.
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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) | 0.000 | 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".