Differential NMDA‐dependent activation of glial cells in mouse hippocampus
Bibliographic record
Abstract
In the hippocampus, the NMDA receptor is thought to be an important glutamate receptor involved in synaptic plasticity and in memory processes. Until recently, NMDA receptors have been considered solely as neuronal components, but some evidence suggests that glial cells in the hippocampus, and in particular astrocytes, also could be activated by NMDA applications. On the basis of their shape and electrophysiological properties (linear and rectified I/V curve), we describe two different populations of glial cells from GFAP-GFP transgenic mice that are activated differentially by NMDA. We found that linear glial cells were depolarized by NMDA that was not dependent on Ca2+ rise but partially involved a Ca2+ entry. Additionally, NMDA-induced depolarization of linear glial cells involved both a TTX-independent pathway likely through a direct activation, and a TTX-dependent pathway that required neuronal activity. The NMDA-induced depolarization in these cells was in part due to the activation of glutamate transporters and GABA B receptors. Furthermore, TTX-dependent NMDA-induced activation regulates the level of gap junction coupling between linear glial cells. In contrast, NMDA-induced depolarization in outward rectifying cells do not require a Ca2+ rise but are mediated directly by Ca2+ entry and are independent of glutamate transporters, GABA B and GABA A receptors. Our findings reveal that NMDA differentially activates hippocampal glial cells and the glial network through heterogeneous mechanisms in a cell-type specific manner.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".