Distributions of vesicular glutamate transporters 1 and 2 in the visual thalamus and associated areas of the cat
Bibliographic record
Abstract
Glutamate is packaged in vesicles via two main vesicular transporter (VGLUT) proteins, VGLUT1 and VGLUT2, which regulate its storage and release from synapses of excitatory neurons. Studies in rodents, primates, ferrets, and tree shrews suggest that these transporters may identify distinct subsets of excitatory projections in visual structures, particularly in thalamocortical pathways where they tend to correlate with modulatory and driver projections, respectively. Despite being a well-studied model of thalamocortical connectivity, little is known about their expression pattern in the cat visual system. To expand current knowledge on their distribution and how they correlated with known driver and modulator projecting sites, we examined the protein expression patterns of VGLUT1 and VGLUT2 in the visual thalamus of the cat (lateral geniculate nucleus and the pulvinar complex). We also studied their expression pattern in relevant visual structures projecting to or receiving significant thalamic projections, such as the primary visual cortex and the superior colliculus. Our results indicate that both VGLUTs are consistently present throughout the cat visual system and show laminar or nuclei specificity in their distribution, which suggests, as in other species, that VGLUT1 and VGLUT2 represent distinct populations of glutamatergic projections.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".