Receptor protein tyrosine phosphatase sigma regulates synapse structure, function and plasticity
Bibliographic record
Abstract
The mechanisms that regulate synapse formation and maintenance are incompletely understood. In particular, relatively few inhibitors of synapse formation have been identified. Receptor protein tyrosine phosphatase σ (RPTPσ), a transmembrane tyrosine phosphatase, is widely expressed by neurons in developing and mature mammalian brain, and functions as a receptor for chondroitin sulfate proteoglycans that inhibits axon regeneration following injury. In this study, we address RPTPσ function in the mature brain. We demonstrate increased axon collateral branching in the hippocampus of RPTPσ null mice during normal aging or following chemically induced seizure, indicating that RPTPσ maintains neural circuitry by inhibiting axonal branching. Previous studies demonstrated a role for pre-synaptic RPTPσ promoting synaptic differentiation during development; however, subcellular fractionation revealed enrichment of RPTPσ in post-synaptic densities. We report that neurons lacking RPTPσ have an increased density of pre-synaptic varicosities in vitro and increased dendritic spine density and length in vivo. RPTPσ knockouts exhibit an increased frequency of miniature excitatory post-synaptic currents, and greater paired-pulse facilitation, consistent with increased synapse density but reduced synaptic efficiency. Furthermore, RPTPσ nulls exhibit reduced long-term potentiation and enhanced novel object recognition memory. We conclude that RPTPσ limits synapse number and regulates synapse structure and function in the mature CNS.
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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 | 0.000 |
| 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 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".