Adaptations in the Walking Pattern of Spinal Cord Injured Rats
Bibliographic record
Abstract
Walking ability is a measure of recovery used in many studies that test experimental strategies to treat injuries or diseases of the central nervous system (CNS) in animal models. A common measure in the rat animal model of thoracic spinal cord injury (SCI) is visual inspection and scoring of hind limb activity, which allows the documentation of movements associated with the recovery of locomotor function. In this study, we expand on previously documented visible changes in the locomotor pattern following SCI. The spontaneous recovery of locomotion in rats with thoracic SCIs of variable extent was evaluated using electromyographic (EMG) and kinematic analysis while rats walked on an elevated runway. Comparisons with pre-lesion walking sequences revealed changes in the kinematics and in the muscle activation pattern of various muscles, including enhanced fore limb extensor activity, possibly reflecting an increased contribution to propulsion, altered recruitment of back muscles inserting into the hip (possibly to support stepping movements), and elevated posture during stance, which may compensate for deficits in weight support. These changes were noted in spinal cord injured rats with varying degrees of impairment, including animals with no visually detectable deficit in open-field walking. In summary, the presented results demonstrate that spinal cord injured rats develop alternative locomotor patterns following SCI that cannot be discriminated by the use of qualitative visually based analysis, thus urging the use of quantitative outcome measures in assessing motor function after 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) | 0.002 | 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".