Transient Blockade of the CD11d/CD18 Integrin Reduces Secondary Damage after Spinal Cord Injury, Improving Sensory, Autonomic, and Motor Function
Bibliographic record
Abstract
The early inflammatory response to spinal cord injury (SCI) causes significant secondary damage. Strategies that nonselectively suppress inflammation have not improved outcomes after SCI, perhaps because inflammation has both adverse and beneficial effects after SCI. We have shown that the selective, time-limited action of a monoclonal antibody (mAb) to the CD11d subunit of the CD11d/CD18 integrin, delivered intravenously during the first 48 hr after SCI in rats, markedly decreases the infiltration of neutrophils and delays the entry of hematogenous monocyte-macrophages into the injured cord. We hypothesized that this targeted strategy would lead to neuroprotection and improved neurological outcomes. In this study the development of chronic pain was detected in rats by assessing mechanical allodynia on the trunk and hindpaws 2 weeks to 3 months after a clinically relevant clip-compression SCI at the twelfth thoracic segment. The anti-CD11d mAb treatment reduced this pain by half. Motor performance also improved as rats were able to plantar-place their hindpaws and use them for weight support instead of sweeping movements only. Improved cardiovascular outcome was shown after SCI at the fourth thoracic segment by significant decreases in autonomic dysreflexia. Locomotor performance was also improved. These functional changes correlated with significantly greater amounts and increased organization of myelin and neurofilament near the lesion. The improved neurological recovery after the specific reduction of early inflammation after SCI demonstrates that this selective strategy increases tissue at the injury site and improves its functional capacity. This early neuroprotective treatment would be an ideal foundation for building later cell-based therapies.
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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".