Upregulation of inflammatory mediators in the ventricular zone after cortical stroke
Bibliographic record
Abstract
PURPOSE: After cortical stroke, neural precursor cells (NPCs) in the distal ventricular zone (VZ) proliferate more rapidly and migrate toward the injured cortex. While evidence suggests this can enhance stroke recovery, the underlying molecular mechanisms initiating the response are poorly understood. Here we identified changes in protein expression in the ipsilateral VZ early (4 h) after stroke to gain insight into the initial mechanisms involved in NPC activation post-stroke. EXPERIMENTAL DESIGN: Four hours after photothrombotic stroke (or sham surgery control) in the sensorimotor cortex, adult mice (10 stroke, 10 sham) were subjected to cardiac perfusion with PBS, and ipsilateral and contralateral VZ tissue was microdissected. Two separate sets of ipsilateral and contralateral VZ tissues (from 5 pooled surgery or 5 pooled sham mice) were analyzed simultaneously using 8-plex iTRAQ. We used Western blotting and confocal microscopy to confirm changes in protein expression in the VZ ipsilateral to stroke in a separate cohort of mice. RESULTS: We identified nine proteins which exhibited a significant mean increase (by ≥ 2-fold) in stroke ipsilateral compared to sham ipsilateral. Many of these proteins were antiproteases or cytokine/growth factor binding proteins that are known to act as inflammatory responders or effectors and play roles in modulating tissue growth and remodeling. CONCLUSION AND CLINICAL RELEVANCE: These novel findings support a growing body of literature that inflammatory signaling is involved in the NPC response to brain injury and identifies novel potential targets that could be exploited to better understand and to optimize this regenerative response.
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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 | 0.000 |
| 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 | 0.000 | 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".