ER-resident STIM1/2 couples Ca <sup>2+</sup> entry by NMDA receptors to pannexin-1 activation
Bibliographic record
Abstract
Pannexin-1 (Panx1) is a large-pore ion and solute permeable channel highly expressed in the nervous system, where it subserves diverse processes, including neurite outgrowth, dendritic spine formation, and N-methyl D-aspartate (NMDA) receptor (NMDAR)-dependent plasticity. Moreover, Panx1 dysregulation contributes to neurological disorders, including neuropathic pain, epilepsy, and excitotoxicity. Despite progress in understanding physiological and pathological functions of Panx1, the mechanisms that regulate its activity, including its ion and solute permeability, remain poorly understood. In this study, we identify endoplasmic reticulum (ER)-resident stromal interaction molecules (STIM1/2), which are Ca 2+ sensors that communicate events within the ER to plasma membrane channels, as binding and signaling partners of Panx1. We demonstrate that Panx1 is activated to its large-pore configuration in response to stimuli that recruit STIM1/2 and map the interaction interface to a hydrophobic region within the N terminus of Panx1. We further characterize a Panx1 N terminus–recognizing antibody as a function-blocking tool able to prevent large-pore Panx1 activation by STIM1/2. Using either the function-blocking antibody or re-expression of Panx1 deletion mutants in Panx1 knockout (KO) neurons, we show that STIM recruitment couples Ca 2+ entry via NMDARs to Panx1 activation, thereby identifying a model of NMDAR-STIM-Panx1 signaling in neurons. Our study highlights a previously unrecognized and important role of the Panx1 N terminus in regulating channel activation and membrane localization. Considering past work demonstrating an intimate functional relation between NMDARs and Panx1, our study opens avenues for understanding activation modality and context-specific functions of Panx1, including functions linked to diverse STIM-regulated cellular responses.
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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".