Reduced NMDA receptor tyrosine phosphorylation in PTPα‐deficient mouse synaptosomes is accompanied by inhibition of four src family kinases and Pyk2: an upstream role for PTPα in NMDA receptor regulation
Bibliographic record
Abstract
Mice lacking protein tyrosine phosphatase alpha (PTPalpha) exhibited defects in NMDA receptor (NMDAR)-associated processes such as learning and memory, hippocampal neuron migration, and CA1 hippocampal long-term potentiation (LTP). In vivo molecular effectors linking PTPalpha and the NMDAR have not been reported. Thus the involvement of PTPalpha as an upstream regulator of NMDAR tyrosine phosphorylation was investigated in synaptosomes of wild-type and PTPalpha-null mice. Tyrosine phosphorylation of the NMDAR NR2A and NR2B subunits was reduced upon PTPalpha ablation, indicating a positive effect of this phosphatase on NMDAR phosphorylation via intermediate molecules. The NMDAR is a substrate of src family tyrosine kinases, and reduced activity of src, fyn, yes and lck, but not lyn, was apparent in the absence of PTPalpha. In addition, autophosphorylation of proline-rich tyrosine kinase 2 (Pyk2), a tyrosine kinase linked to NMDAR signaling, was also reduced in PTPalpha-deficient synaptosomes. Altered protein tyrosine phosphorylation was not accompanied by altered expression of the NMDAR or the above tyrosine kinases at any stage of PTPalpha-null mouse development examined. In a human embryonic kidney (HEK) 293 cell expression system, PTPalpha enhanced fyn-mediated NR2A and NR2B tyrosine phosphorylation by several-fold. Together, these findings provide evidence that aberrant NMDAR-associated functions in PTPalpha-null mice are due to impaired NMDAR tyrosine phosphorylation resulting from the reduced activity of probably more than one of the src family kinases src, fyn, yes and lck. Defective NMDAR activity in these mice may also be linked to the loss of PTPalpha as an upstream regulator of Pyk2.
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".