Extracellular Matrix and Oxidative Stress Following Traumatic Spinal Cord Injury: Physiological and Pathophysiological Roles and Opportunities for Therapeutic Intervention
Bibliographic record
Abstract
Significance: Traumatic spinal cord injury (SCI) causes significant disruption to neuronal, glial, vascular, and extracellular elements. The spinal cord extracellular matrix (ECM) comprises structural and communication proteins that are involved in reparative and regenerative processes after SCI. In the healthy spinal cord, the ECM helps maintain spinal cord homeostasis. After SCI, the damaged ECM limits plasticity and contributes to inflammation through the expression of damage-associated molecules such as proteoglycans. Recent Advances: Considerable insights have been gained by characterizing the origins of the gliotic and fibrotic scars, which not only reduce the spread of injury but also limit neuroregeneration. These properties likely limit the success of therapies used to treat patients with SCI. The ECM, which is a major contributor to the scars and normal physiological functions of the spinal cord, represents an exciting therapeutic target to enhance recovery post-SCI. Critical Issue: Various ECM-based preclinical therapies have been developed. These include disrupting scar components, inhibiting activity of ECM metalloproteinases, and maintaining iron homeostasis. Biomaterials have also been explored. However, the majority of these treatments have not experienced successful clinical translation. This could be due to the ECM and scars' polarizing roles. Future Directions: This review surveys the complexity involved in spinal ECM modifications, discusses new ECM-based combinatorial strategies, and explores the biomaterials evaluated in clinical trials, which hope to introduce new treatments that enhance recovery after SCI. These topics will incorporate oxidative species, which are both beneficial and harmful in reparative and regenerative processes after SCI, and not often assessed in pertinent literature. Antioxid. Redox Signal . 37, 184–207.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".