MET receptor tyrosine kinase promotes the generation of functional synapses in adult cortical circuits
Bibliographic record
Abstract
JOURNAL/nrgr/04.03/01300535-202505000-00026/figure1/v/2024-07-28T173839Z/r/image-tiff Loss of synapse and functional connectivity in brain circuits is associated with aging and neurodegeneration, however, few molecular mechanisms are known to intrinsically promote synaptogenesis or enhance synapse function. We have previously shown that MET receptor tyrosine kinase in the developing cortical circuits promotes dendritic growth and dendritic spine morphogenesis. To investigate whether enhancing MET in adult cortex has synapse regenerating potential, we created a knockin mouse line, in which the human MET gene expression and signaling can be turned on in adult (10-12 months) cortical neurons through doxycycline-containing chow. We found that similar to the developing brain, turning on MET signaling in the adult cortex activates small GTPases and increases spine density in prefrontal projection neurons. These findings are further corroborated by increased synaptic activity and transient generation of immature silent synapses. Prolonged MET signaling resulted in an increased α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-D-aspartate (AMPA/NMDA) receptor current ratio, indicative of enhanced synaptic function and connectivity. Our data reveal that enhancing MET signaling could be an interventional approach to promote synaptogenesis and preserve functional connectivity in the adult brain. These findings may have implications for regenerative therapy in aging and neurodegeneration conditions.
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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) | 0.006 | 0.002 |
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".