Conditional Deletion of α-CaMKII Impairs Integration of Adult-Generated Granule Cells into Dentate Gyrus Circuits and Hippocampus-Dependent Learning
Bibliographic record
Abstract
New granule cells are continuously integrated into hippocampal circuits throughout adulthood, and the fine-tuning of this process is likely important for efficient hippocampal function. During development, this integration process is critically regulated by the α-calcium/calmodulin-dependent protein kinase II (α-CaMKII), and here we ask whether this role is conserved in the adult brain. To do this, we developed a transgenic strategy to conditionally delete α-CaMKII from neural progenitor cells and their progeny in adult mice. First, we found that the selective deletion of α-CaMKII from newly generated dentate granule cells led to an increase in dendritic complexity. Second, α-CaMKII deletion led to a reduction in number of mature synapses and cell survival. Third, consistent with altered morphological and synaptic development, acquisition of one-trial contextual fear conditioning was impaired after deletion of α-CaMKII from newly generated dentate granule cells. Previous work in Xenopus identified α-CaMKII as playing a key role in the stabilization of dendritic and synaptic structure during development. The current study indicates that α-CaMKII plays a plays a similar, cell-autonomous role in the adult hippocampus and, in addition, reveals that the loss of α-CaMKII from adult-generated granule cells is associated with impaired hippocampus-dependent learning.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".