Disruption of NMDAR–CRMP-2 signaling protects against focal cerebral ischemic damage in the rat middle cerebral artery occlusion model
Bibliographic record
Abstract
Collapsin response mediator protein 2 (CRMP-2), traditionally viewed as an axon/dendrite specification and axonal growth protein, has emerged as nidus in regulation of both pre- and post-synaptic Ca ( 2+) channels. Building on our discovery of the interaction and regulation of Ca ( 2+) channels by CRMP-2, we recently identified a short sequence in CRMP-2 which, when appended to the transduction domain of HIV TAT protein, suppressed acute, inflammatory and neuropathic pain in vivo by functionally uncoupling CRMP-2 from the Ca ( 2+) channel. Remarkably, we also found that this region attenuated Ca ( 2+) influx via N-methylD-Aspartate receptors (NMDARs) and reduced neuronal death in a moderate controlled cortical impact model of traumatic brain injury (TBI). Here, we sought to extend these findings by examining additional neuroprotective effects of this peptide (TAT-CBD3) and exploring the biochemical mechanisms by which TAT-CBD3 targets NMDARs. We observed that an intraperitoneal injection of TAT-CBD3 peptide significantly reduced infarct volume in an animal model of focal cerebral ischemia. Neuroprotection was observed when TAT-CBD3 peptide was given either prior to or after occlusion but just prior to reperfusion. Surprisingly, a direct biochemical complex was not resolvable between the NMDAR subunit NR2B and CRMP-2. Intracellular application of TAT-CBD3 failed to inhibit NMDAR current. NR2B interactions with the post synaptic density protein 95 (PSD-95) remained intact and were not disrupted by TAT-CBD3. Peptide tiling of intracellular regions of NR2B revealed two 15-mer sequences, in the carboxyl-terminus of NR2B, that may confer binding between NR2B and CRMP-2 which supports CRMP-2's role in excitotoxicity and neuroprotection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".