Convergence of adenosine and GABA signaling for synapse stabilization during development
Bibliographic record
Abstract
Synapse stabilization Early in brain development, neurons connect to each other enthusiastically. With development, an overabundance of synapses is winnowed down to refine efficiently connected circuits. Inactive synapses are prime targets for elimination, whereas active synapses tend to be retained. Gomez-Castro et al . took a closer look at how those choices are made (see the Perspective by Blum and Lopes). When postsynaptic adenosine receptors are muted or do not find enough extracellular adenosine, synapses get eliminated. Neurotransmitter-dependent signaling pathways drive protein kinase A to phosphorylate the postsynaptic scaffolding molecule gephyrin. Together with a partner synaptogenic membrane protein, gephyrin is required for the stabilization of γ-aminobutyric acid receptors. Adenosine receptors thus detect synaptic activity and in turn drive the stabilization of synapses that produce such activity. —PJH
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".