<i>Pten</i> regulates endocytic trafficking of cell adhesion and signaling molecules to pattern the retina
Bibliographic record
Abstract
SUMMARY The retina is an exquisitely patterned tissue, with neuronal somata positioned at regular intervals to completely sample the visual field. Cholinergic amacrine cells are spectacular exemplars of precision, distributing in two radial layers and tangentially, forming regular mosaics. Here, we investigated how the intracellular phosphatase Pten and the cell adhesion molecule Dscam cooperate to regulate amacrine cell patterning. Using double mutants to test epistasis, we found that Pten and Dscam function in parallel pathways to regulate amacrine cell positioning. Mechanistically, Pten regulates endocytic remodeling of cell adhesion molecules (Dscam, Megf10, Fat3), which are aberrantly redistributed in Pten conditional-knock-out (cKO) amacrine cells. Furthermore, extracellular vesicles derived from multivesicular endosomes have altered proteomes in Pten cKO retinas. Consequently, Wnt signaling is elevated in Pten cKO retinal amacrine cells, the pharmacological disruption of which phenocopies Pten cKO patterning defects. Pten thus controls endocytic trafficking of critical cell adhesion/signaling molecules to control amacrine cell spacing. HIGHLIGHTS Pten and Dscam act in parallel pathways to regulate amacrine cell spacing Endocytic remodeling of cell adhesion molecules is perturbed in Pten cKO retinas Extracellular vesicle content is altered in Pten cKO retinas Perturbation of Wnt signaling phenocopies defects in amacrine cell positioning eTOC BLURB Patterns in nature range from stereotyped distributions of colored patches on butterfly wings to precise neuronal spacing in the nervous system. Waddington proposed that built-in constraints canalize developmental patterns. Touahri et al . identified Pten -mediated endocytic trafficking of cell adhesion/signaling molecules as a novel constraint measure controlling retinal amacrine cell patterning.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".