Regulation of actin dynamics during structural plasticity of dendritic spines: Signaling messengers and actin-binding proteins
Bibliographic record
Abstract
Activity-dependent plasticity of synaptic structure and function plays an essential role in neuronal development and in cognitive functions including learning and memory. The formation, maintenance and modulation of dendritic spines are mainly controlled by the dynamics of actin filaments (F-actin) through interaction with various actin-binding proteins (ABPs) and postsynaptic signaling messengers. Induction of long-term potentiation (LTP) triggers a cascade of events involving Ca2+ signaling, intracellular pathways such as cAMP and cGMP, and regulation of ABPs such as CaMKII, Cofilin, Aip1, Arp2/3, α-actinin, Profilin and Drebrin. We review here how these ABPs modulate the rate of assembly, disassembly, stabilization and bundling of F-actin during LTP induction. We highlight the crucial role that CaMKII exerts in both functional and structural plasticity by directly coupling Ca2+ signaling with F-actin dynamics through the β subunit. Moreover, we show how cAMP and cGMP second messengers regulate postsynaptic structural potentiation. Brain disorders such as Alzheimer's disease, schizophrenia or autism, are associated with alterations in the regulation of F-actin dynamics by these ABPs and signaling messengers. Thus, a better understanding of the molecular mechanisms controlling actin cytoskeleton can provide cues for the treatment of these disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".