Kallikrein Cascades in Traumatic Spinal Cord Injury: In Vitro Evidence for Roles in Axonopathy and Neuron Degeneration
Bibliographic record
Abstract
Kallikreins (KLKs) are a family of 15 secreted serine proteases with emerging roles in neurologic diseases. To illuminate their contributions to the pathophysiology of spinal cord injury (SCI), we evaluated acute through chronic changes in the immunohistochemical appearance of 6 KLKs (KLK1, KLK5, KLK6, KLK7, KLK8, and KLK9) in postmortem human traumatic SCI cases, quantified their RNA expression levels in experimental murine SCI, and assessed the impact of recombinant forms of each enzyme toward murine cortical neurons in vitro. Temporally and spatially distinct changes in KLK expression were observed with partially overlapping patterns between human and murine SCI, including peak elevations (or reductions) during the acute and subacute periods. Kallikrein 9 showed the most marked changes and remained chronically elevated. Importantly, a subset of KLKs (KLK1, KLK5, KLK6, KLK7, and KLK9) were neurotoxic toward primary neurons in vitro. Kallikrein immunoreactivity was also observed in association with swollen axons and retraction bulbs in the human SCI cases examined. Together, these findings demonstrate that elevated levels of a significant subset of KLKs are positioned to contribute to neurodegenerative changes in cases of CNS trauma and disease and, therefore, represent new potential targets for the development of neuroprotective strategies.
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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 | 0.000 |
| 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".