The Systemic Inflammatory Response after Spinal Cord Injury in the Rat Is Decreased by α4β1 Integrin Blockade
Bibliographic record
Abstract
Abstract The systemic inflammatory response syndrome (SIRS) follows spinal cord injury (SCI) and causes damage to the lungs, kidney, and liver due to an influx of inflammatory cells from the circulation. After SCI in rats, the SIRS develops within 12 h and is sustained for at least 3 days. We have previously shown that blockade of CD11d/CD18 integrin reduces inflammation-driven secondary damage to the spinal cord. This treatment reduces the SIRS after SCI. In another study we found that blockade of α4β1 integrin limited secondary cord damage more effectively than blockade of CD11d/CD18. Therefore we considered it important to assess the effects of anti-α4β1 treatment on the SIRS in the lung, kidney, and liver after SCI. An anti-α4 antibody was given IV at 2 h after SCI at the fourth thoracic segment and the effects on the organs were evaluated at 24 h post-injury. The migration of neutrophils into the lungs and liver was markedly reduced and all three organs contained fewer macrophages. In the lungs and liver, the activation of the oxidative enzymes myeloperoxidase (MPO), inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and gp91(phox), the production of free radicals, lipid peroxidation, and cell death were substantially and similarly reduced. Treatment effects were less robust in the kidney. Overall, the efficacy of the anti-α4β1 treatment did not differ greatly from that of the anti-CD11d antibody, although details of the results differed. The SIRS after SCI impedes recovery, and attenuation of the SIRS with an anti-integrin treatment is an important, clinically-relevant finding.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".