Post-Stroke Recovery in Relation to Parvalbumin-Positive Interneurons and Perineuronal Nets
Bibliographic record
Abstract
BACKGROUND: There is a critical time window of post-stroke neuroplasticity when spontaneous behavioral recovery occurs. Potential factors responsible for this heightened plasticity are the reduction of parvalbumin-immunoreactive (PV+) interneuron inhibitory signaling and the disappearance of extracellular matrix synaptic stabilizers called perineuronal net(s; PNN/PNNs). OBJECTIVE: This study investigated whether behavioral recovery during this critical period following stroke is associated with changes in densities of PV+ interneurons and PNNs.MethodsMale, Sprague-Dawley rats received forelimb motor cortex stroke (n = 43) using endothelin-1, or vehicle injections (n = 44). Cohorts of rats underwent a battery of motor tests and were sacrificed within the post-stroke critical window on day 1, and 1, 2, 4, and 6 weeks. Using immunofluorescent labeling, PNNs (wisteria floribunda agglutinin; WFA+ cells), PV+ interneurons, and cells expressing both PV and PNNs were quantified in contra- and ipsilesional cortices to elucidate their spatial-temporal profiles following stroke.ResultsPV+ interneuron density decreased significantly at 1-day post-stroke in the lateral ipsilesional cortex, while the density of PNNs was significantly lower up to 4 weeks post-stroke in the lateral ipsilesional cortex and at 1 and 2 weeks post-stroke in the medial ipsilesional cortex. Reduction of combined PV+/PNN signaling coincided with spontaneous behavioral recovery.ConclusionsThese results suggest that post-stroke behavioral recovery corresponds to an early reduction in PV+/PNN co-labeled cells in conjunction with an early temporally-dependent reduction in PV+ interneuron signaling and chronic disappearance of PNNs. Interventions targeting PNNs or PV+ interneuron signaling have significant potential for extending the critical window of recovery following stroke.
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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".