Pannexin 1 Regulates Network Ensembles and Dendritic Spine Development in Cortical Neurons
Bibliographic record
Abstract
Dendritic spines are the postsynaptic targets of excitatory synaptic inputs that undergo extensive proliferation and maturation during the first postnatal month in mice. However, our understanding of the molecular mechanisms that regulate spines during this critical period is limited. Previous work has shown that pannexin 1 (Panx1) regulates neurite growth and synaptic plasticity. We therefore investigated the impact of global Panx1 KO on spontaneous cortical neuron activity using Ca2+imaging andin siliconetwork analysis. Panx1 KO increased both the number and size of spontaneous co-active cortical neuron network ensembles. To understand the basis for these findings, we investigated Panx1 expression in postnatal synaptosome preparations from early postnatal mouse cortex. Between 2 and 4 postnatal weeks, we observed a precipitous drop in cortical synaptosome protein levels of Panx1, suggesting it regulates synapse proliferation and/or maturation. At the same time points, we observed significant enrichment of the excitatory postsynaptic density proteins PSD-95, GluA1, and GluN2a in cortical synaptosomes from global Panx1 knock-out mice.Ex vivoanalysis of pyramidal neuron structure in somatosensory cortex revealed a consistent increase in dendritic spine densities in both male and female Panx1 KO mice. Similar findings were observed in an excitatory neuron-specific Panx1 KO line (Emx1-Cre driven; Panx1 cKOE) and in primary Panx1 KO cortical neurons culturedin vitro.Altogether, our study suggests that Panx1 negatively regulates cortical dendritic spine development.
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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) | 0.001 | 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".