p21-Activated Kinases 1 and 3 Control Brain Size through Coordinating Neuronal Complexity and Synaptic Properties
Bibliographic record
Abstract
The molecular mechanisms that coordinate postnatal brain enlargement, synaptic properties, and cognition remain an enigma. Here, we demonstrate that neuronal complexity controlled by p21-activated kinases (PAKs) is a key determinant for postnatal brain enlargement and synaptic properties. We showed that double-knockout (DK) mice lacking both PAK1 and PAK3 were born healthy, with normal brain size and structure, but severely impaired in postnatal brain growth, resulting in a dramatic reduction in brain volume. Remarkably, the reduced brain size was accompanied by minimal changes in total cell count, due to a significant increase in cell density. However, the DK neurons have smaller soma, markedly simplified dendritic arbors/axons, and reduced synapse density. Surprisingly, the DK mice had elevated basal synaptic responses due to enhanced individual synaptic potency but were severely impaired in bidirectional synaptic plasticity. The actions of PAK1 and PAK3 are possibly mediated by cofilin-dependent actin regulation, because the activity of cofilin and the properties of actin filaments were altered in the DK mice. These results reveal an essential in vivo role of PAK1 and PAK3 in coordinating neuronal complexity and synaptic properties and highlight the critical importance of dendrite/axon growth in dictating postnatal brain growth and attainment of normal brain size and function.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".