GABA and glutamate receptors have different effects on excitability and are differentially regulated by calcium in spider mechanosensory neurons
Bibliographic record
Abstract
GABA and glutamate receptors belonging to the ligand-gated chloride-channel family are primary targets of insecticides and antiparasitics, so their molecular structure, pharmacology and biophysical properties have attracted significant attention. However, little is known about the physiological roles of these channels or how they regulate neuronal excitability and animal behavior. Mechanosensory neurons of VS-3 slit sensilla in the patella of the tropical wandering spider, Cupiennius salei, react to the GABA(A)-receptor agonists, GABA and muscimol, with depolarization and an increase in intracellular [Ca(2+)] and, during random noise stimulation, with a mixed inhibitory-excitatory response. We established that the GABA(A)-receptors in all VS-3 neurons are identical, but there are at least two types of glutamate receptors and some neurons do not respond to glutamate at all. Immunohistochemistry with antibodies against Drosophila inhibitory glutamate receptor (GluCls) α-subunit suggests that in addition to VS-3 neurons, these receptors may also be present in the efferent neurons surrounding the sensory neurons. Most VS-3 neurons were inhibited but not depolarized by glutamate during random stimulation, but some depolarized and had a similar excitatory-inhibitory response to glutamate as to muscimol. The membrane-permeable Ca(2+)-chelator BAPTA-AM abolished muscimol effects but potentiated glutamate effects, indicating that GABA and glutamate receptors are differentially modulated by Ca(2+), leading to diverse regulation of neuronal excitability. We hypothesize that this could be achieved by different Ca(2+)-triggered phosphorylation processes at each receptor type. These findings are important for understanding the significance of Ca(2+)-mediated regulation of transmitter receptor molecules and its role in controlling excitability.
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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) | 0.000 | 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".