Multiple types of GABAA responses identified from zebrafish Mauthner cells
Bibliographic record
Abstract
γ-Aminobutyric acid (GABA) binds to ionotropic GABAA receptors to mediate fast inhibitory synaptic transmission in the central nervous system (CNS). GABAA receptors are pentameric structures composed of receptor subunits (α1-6, β1-3, γ1-3, δ, ε, θ, π, ρ1-3) with various stoichiometries. They play important roles in the control of neural networks and are the pharmacological targets for the treatment of diseases such as epilepsy, autism, and schizophrenia. Thus far, there has been no report on GABA synaptic transmission in developing zebrafish. Here we used whole-cell patch-clamp electrophysiology to record GABAA-mediated miniature postsynaptic currents from the Mauthner cells of embryonic zebrafish. Spontaneous GABAA currents occurred infrequently and were low in amplitude (27.2 ± 0.9 pA). Analysis of their kinetics suggested the existence of three main types of events: the first (group I) is mediated by a single type of receptor with decay kinetics of 54 ± 1.6 ms; the second (group II) is also mediated by a single receptor type, but exhibits significantly longer decay kinetics (151 ± 7.2 ms); and the third type of synapse (group III) contains multiple receptor types with fast (τ1=28.7 ± 2.5 ms) and slow (τ2=153 ± 11 ms) kinetics. Thus, for the first time, we report the properties of GABA synaptic currents associated with the Mauthner cells of zebrafish.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".