An Essential Role for the Integrin-Linked Kinase–Glycogen Synthase Kinase-3β Pathway during Dendrite Initiation and Growth
Bibliographic record
Abstract
Multiple cues, including growth factors and circuit activity, signal to regulate the initiation and growth of mammalian dendrites. In this study, we have asked how these environmental cues regulate dendrite formation, and in particular, whether dendrite initiation and growth requires integrin-linked kinase (ILK) or its downstream effector, glycogen synthase kinase-3beta (GSK-3beta). In cultured sympathetic neurons, NGF and neuronal depolarization activated ILK and promoted dendrite initiation and growth, and inhibition of ILK (either pharmacologically, with a dominant-negative form of ILK, or by genetic knockdown) reduced depolarization-induced dendrite formation. In sympathetic neurons, ILK phosphorylated and inhibited GSK-3beta, and inhibition of GSK-3beta (either pharmacologically, with dominant-negative GSK-3beta, or by genetic knockdown) caused robust dendrite initiation. GSK-3beta inhibition also caused dendrite initiation in cultured cortical neurons and growth of hippocampal neurons in slice cultures. GSK-3beta functioned downstream of ILK to regulate dendrite formation, because inhibition of GSK-3beta promoted dendrite initiation even when ILK was simultaneously inhibited. Moreover, GSK-3beta promoted dendrite formation in sympathetic neurons by regulating the activity of a key dendrite formation effector, the MAP (microtubule-associated protein) kinase kinase (MEK)-extracellular signal-regulated protein kinase (ERK) pathway. Specifically, inhibition of GSK-3beta led to increased ERK phosphorylation, and inhibition of MEK completely blocked the effects of GSK-3beta inhibition on dendrite initiation and growth. Thus, the ILK-GSK-3beta pathway plays a key role in regulating dendrite formation in developing mammalian neurons.
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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 | 0.000 |
| 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".