Bibliographic record
Abstract
BACKGROUND: Activity through NMDA type glutamate receptors sculpts connectivity in the developing nervous system. This topic is typically studied in the visual system in vivo, where activity of inputs can be differentially regulated, but in which individual synapses are difficult to visualize and mechanisms governing synaptic competition can be difficult to ascertain. Here, we develop a model of NMDA-receptor dependent synaptic competition in dissociated cultured hippocampal neurons. METHODOLOGY/PRINCIPAL FINDINGS: GluN1 -/- (KO) mouse hippocampal neurons lacking the essential NMDA receptor subunit were cultured alone or cultured in defined ratios with wild type (WT) neurons. The absence of functional NMDA receptors did not alter neuron survival. Synapse development was assessed by immunofluorescence for postsynaptic PSD-95 family scaffold and apposed presynaptic vesicular glutamate transporter VGlut1. Synapse density was specifically enhanced onto minority wild type neurons co-cultured with a majority of GluN1 -/- neighbour neurons, both relative to the GluN1 -/- neighbours and relative to sister pure wild type cultures. This form of synaptic competition was dependent on NMDA receptor activity and not conferred by the mere physical presence of GluN1. In contrast to these results in 10% WT and 90% KO co-cultures, synapse density did not differ by genotype in 50% WT and 50% KO co-cultures or in 90% WT and 10% KO co-cultures. CONCLUSIONS/SIGNIFICANCE: The enhanced synaptic density onto NMDA receptor-competent neurons in minority coculture with GluN1 -/- neurons represents a cell culture paradigm for studying synaptic competition. Mechanisms involved may include a retrograde 'reward' signal generated by WT neurons, although in this paradigm there was no 'punishment' signal against GluN1 -/- neurons. Cell culture assays involving such defined circuits may help uncover the rules and mechanisms of activity-dependent synaptic competition in the developing nervous system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".