Pten regulates endocytic trafficking of cell adhesion and Wnt signaling molecules to pattern the retina
Bibliographic record
Abstract
The retina is exquisitely patterned, with neuronal somata positioned at regular intervals to completely sample the visual field. Here, we show that phosphatase and tensin homolog ( P ten ) controls starburst amacrine cell spacing by modulating vesicular trafficking of cell adhesion molecules and Wnt proteins. Single-cell transcriptomics and double-mutant analyses revealed that Pten and Down syndrome cell adhesion molecule Dscam ) are co-expressed and function additively to pattern starburst amacrine cell mosaics. Mechanistically, Pten loss accelerates the endocytic trafficking of DSCAM, FAT3, and MEGF10 off the cell membrane and into endocytic vesicles in amacrine cells. Accordingly, the vesicular proteome, a molecular signature of the cell of origin, is enriched in exocytosis, vesicle-mediated transport, and receptor internalization proteins in Pten conditional knockout ( Pten cKO ) retinas. Wnt signaling molecules are also enriched in Pten cKO retinal vesicles, and the genetic or pharmacological disruption of Wnt signaling phenocopies amacrine cell patterning defects. Pten thus controls vesicular trafficking of cell adhesion and signaling molecules to establish retinal amacrine cell mosaics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".