A CD11d Monoclonal Antibody Treatment Reduces Tissue Injury and Improves Neurological Outcome after Fluid Percussion Brain Injury in Rats
Bibliographic record
Abstract
Traumatic brain injury (TBI) is an international health concern often resulting in chronic neurological abnormalities, including cognitive deficits, emotional disturbances, and motor impairments. An anti-CD11d monoclonal antibody that blocks the CD11d/CD18 integrin and vascular cell adhesion molecule (VCAM)-1 interaction following experimental spinal cord injury improves functional recovery, while reducing the intraspinal number of neutrophils and macrophages, oxidative activity, and tissue damage. Since the mechanisms of secondary injury in the brain and spinal cord are similar, we designed a study to evaluate fully the effects of anti-CD11d treatment after a moderate lateral fluid percussion TBI in the rat. Rats were treated at 2 h after TBI with either the anti-CD11d antibody or an isotype-matched control antibody 1B7, and both short (24- to 72-h) and long (4-week) recovery periods were examined. The anti-CD11d integrin treatment reduced neutrophil and macrophage levels in the injured brain, with concomitant reductions in lipid peroxidation, astrocyte activation, amyloid precursor protein accumulation, and neuronal loss. The reduced neuroinflammation seen in anti-CD11d-treated rats correlated with improved performance on a number of behavioral tests. At 24 h, the anti-CD11d group performed significantly better than the 1B7 controls on several water maze measures of spatial cognition. At 4 weeks post-injury the anti-CD11d-treated rats had better sensorimotor function as assessed by the beam task, and reduced anxiety-like behaviors, as evidenced by elevated-plus maze testing, compared to 1B7 controls. These findings suggest that neuroinflammation is associated with behavioral deficits after TBI, and that anti-CD11d antibody treatment is a viable strategy to improve neurological outcomes after TBI.
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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) | 0.000 | 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) | 0.000 | 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".