TORC1 selectively regulates synaptic maturation and input convergence in the developing visual system
Bibliographic record
Abstract
Newly synthesized proteins support the development of functional neural circuits and previous work has suggested that dysregulated translation mediates certain forms of autism spectrum disorder (ASD). Here, we investigated the role of Target of Rapamycin Complex 1 (TORC1) in synaptic and dendritic development in vivo in the retinotectal system of Xenopus laevis tadpoles. We found that TORC1 signaling regulates dendritic growth and branching and that acute over-activation of TORC1 by Rheb overexpression drove enhanced maturation of excitatory synapses by recruiting AMPA receptors. Interestingly, TORC1 over-activation did not affect inhibitory transmission, resulting in a significant imbalance in the excitatory-to-inhibitory ratio. Rheb overexpression also enlarged excitatory visual input fields in tectal neurons, consistent with dysregulation of retinotopic input refinement and integration of the cell into the circuit. In contrast to other reports that mainly found impairments in synaptic inhibition using broad systemic deletion or mutation of TORC1 regulatory proteins, our findings from acute, local manipulation of TORC1 reveal its critical role in selectively regulating the number and maturity of excitatory, but not inhibitory, synapses in the developing brain.
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 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".