The interaction between KIF21A and KANK1 regulates dendritic morphology and synapse plasticity in neurons
Bibliographic record
Abstract
JOURNAL/nrgr/04.03/01300535-202501000-00029/figure1/v/2024-05-14T021156Z/r/image-tiff Morphological alterations in dendritic spines have been linked to changes in functional communication between neurons that affect learning and memory. Kinesin-4 KIF21A helps organize the microtubule-actin network at the cell cortex by interacting with KANK1; however, whether KIF21A modulates dendritic structure and function in neurons remains unknown. In this study, we found that KIF21A was distributed in a subset of dendritic spines, and that these KIF21A-positive spines were larger and more structurally plastic than KIF21A-negative spines. Furthermore, the interaction between KIF21A and KANK1 was found to be critical for dendritic spine morphogenesis and synaptic plasticity. Knockdown of either KIF21A or KANK1 inhibited dendritic spine morphogenesis and dendritic branching, and these deficits were fully rescued by coexpressing full-length KIF21A or KANK1, but not by proteins with mutations disrupting direct binding between KIF21A and KANK1 or binding between KANK1 and talin1. Knocking down KIF21A in the hippocampus of rats inhibited the amplitudes of long-term potentiation induced by high-frequency stimulation and negatively impacted the animals' cognitive abilities. Taken together, our findings demonstrate the function of KIF21A in modulating spine morphology and provide insight into its role in synaptic 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".