Examination of the Combined Effects of Chondroitinase ABC, Growth Factors and Locomotor Training following Compressive Spinal Cord Injury on Neuroanatomical Plasticity and Kinematics
Bibliographic record
Abstract
While several cellular and pharmacological treatments have been evaluated following spinal cord injury (SCI) in animal models, it is increasingly recognized that approaches to address the glial scar, including the use of chondroitinase ABC (ChABC), can facilitate neuroanatomical plasticity. Moreover, increasing evidence suggests that combinatorial strategies are key to unlocking the plasticity that is enabled by ChABC. Given this, we evaluated the anatomical and functional consequences of ChABC in a combinatorial approach that also included growth factor (EGF, FGF2 and PDGF-AA) treatments and daily treadmill training on the recovery of hindlimb locomotion in rats with mid thoracic clip compression SCI. Using quantitative neuroanatomical and kinematic assessments, we demonstrate that the combined therapy significantly enhanced the neuroanatomical plasticity of major descending spinal tracts such as corticospinal and serotonergic-spinal pathways. Additionally, the pharmacological treatment attenuated chronic astrogliosis and inflammation at and adjacent to the lesion with the modest synergistic effects of treadmill training. We also observed a trend for earlier recovery of locomotion accompanied by an improvement of the overall angular excursions in rats treated with ChABC and growth factors in the first 4 weeks after SCI. At the end of the 7-week recovery period, rats from all groups exhibited an impressive spontaneous recovery of the kinematic parameters during locomotion on treadmill. However, although the combinatorial treatment led to clear chronic neuroanatomical plasticity, these structural changes did not translate to an additional long-term improvement of locomotor parameters studied including hindlimb-forelimb coupling. These findings demonstrate the beneficial effects of combined ChABC, growth factors and locomotor training on the plasticity of the injured spinal cord and the potential to induce earlier neurobehavioral recovery. However, additional approaches such as stem cell therapies or a more adapted treadmill training protocol may be required to optimize this repair strategy in order to induce sustained functional locomotor improvement.
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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) | 0.001 | 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 | 0.001 |
| 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".