A role for Numb in Protein kinase M (PKM)‐mediated increase in surface AMPA receptors during facilitation in <i>Aplysia</i>
Bibliographic record
Abstract
There is considerable evidence from both vertebrates and invertebrates that persistently active protein kinases maintain changes in synaptic strength that underlie memory. In the hermaphrodite marine mollusk, Aplysia californica, truncated forms of protein kinase C (PKC) termed protein kinase Ms have been implicated in both intermediate- and long-term facilitation, an increase in synaptic strength between sensory neurons and motor neurons thought to underlie behavioural sensitization in the animal. However, few substrates have been identified as candidates that could mediate this increase in synaptic strength. PKMs have been proposed to maintain synaptic strength through preventing endocytosis of AMPA receptors. Numb is a conserved regulator of endocytosis that is modulated by phosphorylation. We have identified and cloned Aplysia Numb (ApNumb). ApNumb contains three conserved PKC phosphorylation sites and PKMs generated from classical and atypical Aplysia PKCs can phosphorylate ApNumb in vitro and in cells. Over-expression of ApNumb that lacks the conserved PKC phosphorylation sites blocks increases in surface levels of a pHluorin-tagged Aplysia glutamate receptor measured using live imaging after intermediate- or long-term facilitation. Over-expression of this form of ApNumb did not block increases in synaptic strength seen during intermediate-term facilitation, but did block increases in synaptic strength seen during long-term facilitation. There was no effect of over-expression of this form of ApNumb on other putative Numb targets as measured using increases in calcium downstream of neurotrophins or agonists of metabotropic glutamate receptors. These results suggest that in Aplysia neurons, Numb specifically regulates AMPA receptor trafficking and is an attractive candidate for a target of PKMs in long-term maintenance of synaptic strength. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/. Open Science: This manuscript was awarded with the Open Materials Badge For more information see: https://cos.io/our-services/open-science-badges/.
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".