Intraparenchymal Microdialysis after Acute Spinal Cord Injury Reveals Differential Metabolic Responses to Contusive versus Compressive Mechanisms of Injury
Bibliographic record
Abstract
In animal models, spinal cord injury (SCI) is typically imparted by contusion alone (e.g., weight drop) or by compression alone (e.g., clip compression). In humans, however, the cord is typically injured by a combination of violent contusion followed by varying degrees of ongoing mechanical compression. Understanding how the combination of contusion and compression influences the early pathophysiology of SCI is important for the pre-clinical development of neuroprotective therapies that are applicable to the human condition. Disturbances in the metabolism of energy-related substrates such as lactate, pyruvate, and glucose are important aspects of secondary damage. In this study, we used a porcine model of traumatic SCI to determine the extent to which these metabolites were influenced by contusion followed by sustained compression, using the microdialysis technique. Following contusion injury, lactate and pyruvate levels near the epicenter both increased, while glucose remained quite stable. When the contusion injury was followed by sustained compression, we observed a transient rise in lactate, while pyruvate and glucose levels dropped rapidly, which may reflect decreased regional spinal cord blood flow. Furthermore, contusion with sustained compression produced a prolonged and dramatic increase in the lactate-pyruvate (L/P) ratio as a marker of tissue hypoxia, whereas after contusion injury alone, a transient and less significant elevation of the L/P ratio was observed. In this study, we demonstrate that disturbances in energy metabolism within the injured spinal cord vary greatly depending upon the biomechanical nature of the injury. Such differences are likely to be relevant to the applicability of novel therapies targeting specific aspects of the early secondary injury cascade after acute human SCI.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".