Kallikrein 6 signals through <scp>PAR</scp>1 and <scp>PAR</scp>2 to promote neuron injury and exacerbate glutamate neurotoxicity
Bibliographic record
Abstract
Abstract CNS trauma generates a proteolytic imbalance contributing to secondary injury, including axonopathy and neuron degeneration. Kallikrein 6 (Klk6) is a serine protease implicated in neurodegeneration, and here we investigate the role of protease‐activated receptors 1 (PAR1) and PAR2 in mediating these effects. First, we demonstrate Klk6 and the prototypical activator of PAR1, thrombin, as well as PAR1 and PAR2, are each elevated in murine experimental traumatic spinal cord injury (SCI) at acute or subacute time points. Recombinant Klk6 triggered extracellular signal‐regulated kinase (ERK1/2) signaling in cerebellar granule neurons and in the NSC34 spinal cord motoneuron cell line, in a phosphoinositide 3‐kinase and MEK‐dependent fashion. Importantly, lipopeptide inhibitors of PAR1 or PAR2, and PAR1 genetic deletion, each reduced Klk6‐ERK1/2 activation. In addition, Klk6 and thrombin promoted degeneration of cerebellar neurons and exacerbated glutamate neurotoxicity. Moreover, genetic deletion of PAR1 blocked thrombin‐mediated cerebellar neurotoxicity and reduced the neurotoxic effects of Klk6. Klk6 also increased glutamate‐mediated Bim signaling, poly‐ADP‐ribose polymerase cleavage and lactate dehydrogenase release in NSC34 motoneurons and these effects were blocked by PAR1 and PAR2 lipopeptide inhibitors. Taken together, these data point to a novel Klk6‐signaling axis in CNS neurons that is mediated by PAR1 and PAR2 and is positioned to contribute to neurodegeneration. image Here, we show kallikrein 6 (Klk6) and thrombin contribute to the proteolytic imbalance that occurs in CNS injury. Activation of the G‐protein coupled receptor PAR1 was sufficient to mediate the neurotoxic effects of thrombin while KLK6 neurotoxicity involved activation of PAR1 and PAR2. In addition, both proteases exacerbated glutamate neurotoxicity. These data suggest Klk6, thrombin and PARs each represent new targets for the development of neuroprotective therapies.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".