Control of Excitatory Synaptic Transmission by C-terminal Src Kinase
Bibliographic record
Abstract
The induction of long-term potentiation at CA3-CA1 synapses is caused by an N-methyl-d-aspartate (NMDA) receptordependent accumulation of intracellular Ca(2+), followed by Src family kinase activation and a positive feedback enhancement of NMDA receptors (NMDARs). Nevertheless, the amplitude of baseline transmission remains remarkably constant even though low frequency stimulation is also associated with an NMDAR-dependent influx of Ca(2+) into dendritic spines. We show here that an interaction between C-terminal Src kinase (Csk) and NMDARs controls the Src-dependent regulation of NMDAR activity. Csk associates with the NMDAR signaling complex in the adult brain, inhibiting the Src-dependent potentiation of NMDARs in CA1 neurons and attenuating the Src-dependent induction of long-term potentiation. Csk associates directly with Src-phosphorylated NR2 subunits in vitro. An inhibitory antibody for Csk disrupts this physical association, potentiates NMDAR mediated excitatory postsynaptic currents, and induces long-term potentiation at CA3-CA1 synapses. Thus, Csk serves to maintain the constancy of baseline excitatory synaptic transmission by inhibiting Src kinase-dependent synaptic plasticity in the hippocampus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".