Compensatory Locomotor Adjustments of Rats with Cervical or Thoracic Spinal Cord Hemisections
Bibliographic record
Abstract
The accurate measurement of behavioral compensation after CNS trauma, such as spinal cord injury, is important when assessing the functional effects of injury and treatment in animal models. We investigated the locomotor abilities of rats with unilateral thoracic or cervical spinal cord injuries using a locomotor rating (BBB) scale, reflex tests, and quantitative kinetic measurements. The BBB rating scale indicated that thoracic spinal hemisected (TH) rats had more severely affected hindlimbs compared to cervical spinal hemisected (CH) and sham-operated animals. Kinetic measurements revealed that CH and TH animals moved with different ground reaction force patterns, which nevertheless shared some similarities with each other and with the gait patterns of rats with different unilateral CNS lesions. Uninjured rats typically had an equal distribution of their body weight over the forelimbs and hind limbs, and used their forelimbs predominantly for braking while using their hind limbs mostly for propulsion. CH rats bore more weight on their hind limbs than their forelimbs, while TH animals bore more weight on their forelimbs than their hind limbs. Neither CH nor TH rats used the forelimb ipsilateral to the spinal hemisection for net braking or propulsion. The hindlimb contralateral to the hemisection was placed on the ground prematurely during the stride cycle for both CH and TH animals. The altered kinetics of the locomotor pattern in hemisected animals resulted in changes in the oscillations of total body potential and kinetic energies. These two forms of energy oscillate synchronously in intact locomoting rats, but were asynchronous during parts of the stride cycle in spinal hemisected animals. We conclude that rats develop a general compensatory response for unilateral CNS lesions, which may help stabilize the animal during locomotion.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".