The effectiveness of the anti-CD11d treatment is reduced in rat models of spinal cord injury that produce significant levels of intraspinal hemorrhage
Bibliographic record
Abstract
We have previously reported that administration of a CD11d monoclonal antibody (mAb) improves recovery in a clip-compression model of SCI. In this model the CD11d mAb reduces the infiltration of activated leukocytes into the injured spinal cord (as indicated by reduced intraspinal MPO). However not all anti-inflammatory strategies have reported beneficial results, suggesting that success of the CD11d mAb treatment may depend on the type or severity of the injury. We therefore tested the CD11d mAb treatment in a rat hemi-contusion model of cervical SCI. In contrast to its effects in the clip-compression model, the CD11d mAb treatment did not improve forelimb function nor did it significantly reduce MPO levels in the hemi-contused cord. To determine if the disparate results using the CD11d mAb were due to the biomechanical nature of the cord injury (compression SCI versus contusion SCI) or to the spinal level of the injury (12th thoracic level versus cervical) we further evaluated the CD11d mAb treatment after a T12 contusion SCI. In contrast to the T12 clip compression SCI, the CD11d mAb treatment did not improve locomotor recovery or significantly reduce MPO levels after T12 contusion SCI. Lesion analyses revealed increased levels of hemorrhage after contusion SCI compared to clip-compression SCI. SCI that is accompanied by increased intraspinal hemorrhage would be predicted to be refractory to the CD11d mAb therapy as this approach targets leukocyte diapedesis through the intact vasculature. These results suggest that the disparate results of the anti-CD11d treatment in contusion and clip-compression models of SCI are due to the different pathophysiological mechanisms that dominate these two types of spinal cord injuries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".