Taurine Activates Strychnine-Sensitive Glycine Receptors in Neurons Freshly Isolated From Nucleus Accumbens of Young Rats
Bibliographic record
Abstract
Although functional glycine receptors (GlyRs) are present in the mature nucleus accumbens (NAcc), an important area of the mesolimbic dopamine system involved in drug addiction, their role has been unclear because the NAcc contains little glycine. However, taurine, an agonist of GlyRs, is abundant throughout the brain, especially during early development. In the present study on freshly dissociated NAcc neurons from young Sprague-Dawley rats (12- to 21-day old), we found that both glycine and taurine can strongly depolarize NAcc neurons and modulate their excitability. In voltage-clamped NAcc neurons, glycine and taurine elicited chloride currents (IGly and ITau) with an EC50 of 0.12 and 1.25 mM, respectively. The reversal potential of IGly or ITau was 0 mV in conventional whole cell mode and -30 mV in gramicidin-perforated mode. At concentrations <1 mM, both glycine and taurine were very effectively antagonized by strychnine and by picrotoxin (with an IC50 of 60 nM and 36.5 microM for IGly, and 40 nM and 42.2 microM for ITau) but were insensitive to 10 microM bicuculline. The currents elicited by taurine (< or =1 mM) showed complete cross-desensitization with IGly, but none with gamma-aminobutyric acid (GABA)-induced currents (IGABA). However, ITau elicited by very concentrated taurine (10 mM) showed partial cross-desensitization with IGABA, and it was substantially antagonized by 10 microM bicuculline. These results indicate that taurine binds mainly to GlyRs in NAcc, but it could be a partial agonist of GABAA receptors. By activating GlyRs, taurine may play an important physiological role in the control of NAcc function, especially during development.
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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) | 0.001 | 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 | 0.001 |
| 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".