Small-Molecule Protein Tyrosine Phosphatase Inhibition as a Neuroprotective Treatment after Spinal Cord Injury in Adult Rats
Bibliographic record
Abstract
Spinal cord injury causes progressive secondary tissue degeneration, leaving many injured people with neurological disabilities. There are no satisfactory neuroprotective treatments. Protein tyrosine phosphatases inactivate neurotrophic factor receptors and downstream intracellular signaling molecules. Thus, we tested whether the peroxovanadium compound potassium bisperoxo(1,10-phenanthroline)oxovanadate (V) [bpV(phen)], a stable, potent and selective protein tyrosine phosphatase inhibitor, would be neuroprotective after a thoracic spinal cord contusion in adult rats. Intrathecal bpV(phen) infusions through a lumbar puncture rescued dorsal column sensory axons innervating the nucleus gracilis and white matter at the injury epicenter. At the most effective dose, essentially all of these axons and most of the white matter at the epicenter were spared (vs approximately 60% with control infusions). bpV(phen) treatments started 4 h after contusion were fully effective. This treatment greatly improved and normalized sensorimotor function in a grid-walking test and provided complete axonal protection over 6 weeks. The treatment rescued sensory-evoked potentials that disappeared after dorsal column transection. bpV(phen) affected early degenerative mechanisms, because the main effects were seen at 7 d and lasted beyond the treatment period. The neuroprotection appeared to be mediated by rescue of blood vessels. bpV(phen) reduced apoptosis of cultured endothelial cells. These results show that a small molecule, used in a clinically relevant manner, reduces loss of long-projecting axons, myelin, blood vessels, and function in a model relevant to the most common type of spinal cord injury in humans. They reveal a novel mechanism of spinal cord degeneration involving protein tyrosine phosphatases that can be targeted with therapeutic drugs.
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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 | 0.000 |
| 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".