Dystroglycan and Kir4.1 coclustering in retinal Müller glia is regulated by laminin‐1 and requires the PDZ‐ligand domain of Kir4.1
Bibliographic record
Abstract
Inwardly rectifying potassium (Kir) channels in Müller glia play a critical role in the spatial buffering of potassium ions that accumulate during retinal activity. To this end, Kir channels show a polarized subcellular distribution with the predominant channel subunit in Müller glia, Kir4.1, clustered in the endfeet of these cells at the inner limiting membrane. However, the molecular mechanisms underlying their distribution have yet to be identified. Here, we show that laminin, agrin and alpha-dystroglycan (DG) codistribute with Kir4.1 at the inner limiting membrane in the retina and that laminin-1 induces the clustering of alpha-DG, syntrophin and Kir4.1 in Müller cell cultures. In addition, we found that alpha-DG clusters were enriched for agrin and sought to investigate the role of agrin in their formation using recombinant C-agrins. Both C-agrin 4,8 and C-agrin 0,0 failed to induce alpha-DG clustering and neither of them potentiated the alpha-DG clustering induced by laminin-1. Finally, our data reveal that deletion of the PDZ-ligand domain of Kir4.1 prevents their laminin-induced clustering. These findings indicate that both laminin-1 and alpha-DG are involved in the distribution of Kir4.1 to specific Müller cell membrane domains and that this process occurs via a PDZ-domain-mediated interaction. Thus, in the basal lamina laminin is an essential regulator involved in clearing excess potassium released during neuronal activity, thereby contributing to the maintenance of normal synaptic transmission in the retina.
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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".