Pannexin 1 Differentially Affects Neural Precursor Cell Maintenance in the Ventricular Zone and Peri-Infarct Cortex
Bibliographic record
Abstract
We demonstrated previously that Pannexin 1 (Panx1), an ion and metabolite channel, promotes the growth and proliferation of ventricular zone (VZ) neural precursor cells (NPCs) in vitro. To investigate its role in vivo, we used floxed Panx1 mice in combination with viruses to delete Panx1 in VZ NPCs and to track numbers of Panx1-null and Panx1-expressing VZ NPCs over time. Two days after virus injection, Panx1-null cells were less abundant than Panx1-expressing cells, suggesting that Panx1 is required for the maintenance of VZ NPCs. We also investigated the effect of Panx1 deletion in VZ NPCs after focal cortical stroke via photothrombosis. Panx1 is essential for maintaining elevated VZ NPC numbers after stroke. In contrast, Panx1-null NPCs were more abundant than Panx1-expressing NPCs in the peri-infarct cortex. Together, these findings suggest that Panx1 plays an important role in NPC maintenance in the VZ niche in the naive and stroke brain and could be a key target for improving NPC survival in the peri-infarct cortex. SIGNIFICANCE STATEMENT: Here, we demonstrate that Pannexin 1 (Panx1) maintains a consistent population size of neural precursor cells in the ventricular zone, both in the healthy brain and in the context of stroke. In contrast, Panx1 appears to be detrimental to the survival of neural precursor cells that surround damaged cortical tissue in the stroke brain. This suggests that targeting Panx1 in the peri-infarct cortex, in combination with other therapies, could improve cell survival around the injury site.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".