A Mechanism for Ca <sup>2+</sup> /Calmodulin-Dependent Protein Kinase II Clustering at Synaptic and Nonsynaptic Sites Based on Self-Association
Bibliographic record
Abstract
The activity of Ca2+/calmodulin-dependent protein kinase II (CaMKII) plays an integral role in regulating synaptic development and plasticity. We designed a live-cell-imaging approach to monitor an activity-dependent clustering of green fluorescent protein (GFP)-CaMKII holoenzymes, termed self-association, a process that we hypothesize contributes to the translocation of CaMKII to synaptic and nonsynaptic sites in activated neurons. We show that GFP-CaMKII self-association in human embryonic kidney 293 (HEK293) cells requires a catalytic domain and multimeric structure, requires Ca2+ stimulation and a functional Ca2+/CaM-binding domain, is regulated by cellular pH and Thr286 autophosphorylation, and has variable rates of dissociation depending on Ca2+ levels. Furthermore, we show that the same rules that govern CaMKII self-association in HEK293 cells apply for extrasynaptic and postsynaptic translocation of GFP-CaMKII in hippocampal neurons. Our data support a novel mechanism for targeting CaMKII to postsynaptic sites after neuronal activation. As such, CaMKII may form a scaffold that, in combination with other synaptic proteins, recruits and localizes additional proteins to the postsynaptic density. We discuss the potential function of CaMKII self-association as a tag of synaptic activity.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".