Targeted Deletion of Vesicular GABA Transporter from Retinal Horizontal Cells Eliminates Feedback Modulation of Photoreceptor Calcium Channels
Bibliographic record
Abstract
The cellular mechanisms underlying feedback signaling from horizontal cells to photoreceptors, which are important for the formation of receptive field surrounds of early visual neurons, remain unsettled. Mammalian horizontal cells express a complement of synaptic proteins that are necessary and sufficient for calcium-dependent exocytosis of inhibitory neurotransmitters at their contacts with photoreceptor terminals, suggesting that they are capable of releasing GABA via vesicular release. To test whether horizontal cell vesicular release is involved in feedback signaling, we perturbed inhibitory neurotransmission in these cells by targeted deletion of the vesicular GABA transporter (VGAT), the protein responsible for the uptake of inhibitory transmitter by synaptic vesicles. To manipulate horizontal cells selectively, an iCre mouse line with Cre recombinase expression controlled by connexin57 (Cx57) regulatory elements was generated. In Cx57-iCre mouse retina, only horizontal cells expressed Cre protein, and its expression occurred in all retinal regions. After crossing with a VGAT(flox/flox) mouse line, VGAT was selectively eliminated from horizontal cells, which was confirmed immunohistochemically. Voltage-gated ion channel currents in horizontal cells of Cx57-VGAT(-/-) mice were the same as Cx57-VGAT(+/+) controls, as were the cell responses to the ionotropic glutamate receptor agonist kainate, but the response to the GABAA receptor agonist muscimol in Cx57-VGAT(-/-) mice was larger. In contrast, the feedback inhibition of photoreceptor calcium channels, which in control animals is induced by horizontal cell depolarization, was completely absent in Cx57-VGAT(-/-) mice. The results suggest that vesicular release of GABA from horizontal cells is required for feedback inhibition of photoreceptors.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".