Anti-CD11d Integrin Antibody Treatment Restores Normal Serotonergic Projections to the Dorsal, Intermediate, and Ventral Horns of the Injured Spinal Cord
Bibliographic record
Abstract
Spinal serotonergic pathways provide inhibitory and excitatory modulation of sensory, autonomic, and motor processing. After spinal cord injury (SCI), the acute inflammatory response is one process that damages descending pathways. Increases in serotonergic fiber density in spinal segments rostral and decreases caudal to the lesion have been observed previously and may contribute to neuropathic pain and motor dysfunction associated with SCI. We investigated the effect of an acute anti-inflammatory treatment on the density of serotonergic fibers rostral and caudal to a thoracic SCI lesion. This treatment, a monoclonal antibody to the CD11d subunit of the leukocyte CD11d/CD18 integrin, limits the trafficking of neutrophils and macrophages into the SCI site. In the dorsal horn, after treatment, the typically increased serotonin immunoreactivity rostral to injury was reduced, whereas that caudal to the lesion increased toward normal. Coincidently, mechanical allodynia in the dorsal trunk and hindpaws was significantly reduced. Increased serotonergic fiber density below the lesion also occurred in the intermediolateral cell column and ventral horn of treated rats, relative to controls. Improved locomotor recovery paralleled this increased serotonin. The treatment increased compact myelin in and near the lesion epicenter and increased serotonergic fiber bundles coursing around part of the lesion but had no consistent effect on the number of raphe-spinal neurons retrogradely labeled by tracer injection below the injury. In conclusion, this anti-CD11d integrin antibody treatment is neuroprotective after SCI, corresponding with improved patterns of intraspinal serotonergic innervation. The improvement in serotonergic fiber projections paralleled reduced mechanical allodynia and enhanced locomotor recovery.
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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 | 0.000 | 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".