Repair and Neurorehabilitation Strategies for Spinal Cord Injury
Bibliographic record
Abstract
The failure of axons in the central nervous system (CNS) to regenerate has been considered the main factor limiting recovery from spinal cord injury (SCI). Impressive gains in identification of growth-inhibitory molecules in the CNS led to expectations that their neutralization would lead to functional regeneration. However, results of therapeutic approaches based on this assumption have been mixed. Recent data suggest that neurons differ in their ability to regenerate through similar extracellular environments, and moreover, they undergo a developmental loss of intrinsic regenerative ability. Factors mediating these intrinsic regenerative abilities include expression of (1) receptors for inhibitory molecules such as the myelin-associated growth inhibitors and developmental guidance molecules, (2) surface molecules that permit axon adhesion to cells in the path of growth, (3) cytoskeletal proteins that mediate the mechanics of axon growth, and (4) molecules in the intracellular signaling cascades that mediate responses to chemoattractive and chemorepulsive cues. In contrast to axon development, regeneration might involve internal protrusive forces generated by microtubules, either through their own elongation or by transporting other cytoskeletal elements such as neurofilaments into the axon tip. Because of the complexity of the regenerative program, one approach will probably be insufficient to achieve functional restoration of neuronal circuits. Combination treatments will be increasingly prominent. SCI is a debilitating and costly condition that compromises pursuit of activities usually associated with an independent and productive lifestyle. This article discusses recent advances in neurorehabilitation that can improve the life quality of individuals with 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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".