Real-time imaging of glutamate clearance reveals normal striatal uptake in Huntington disease mouse models
Bibliographic record
Abstract
It has become well accepted that Huntington disease (HD) is associated with impaired glutamate uptake, resulting in a prolonged time-course of extracellular glutamate that contributes to excitotoxicity. However, the data supporting this view come largely from work in synaptosomes, which may overrepresent nerve-terminal uptake over astrocytic uptake. Here, we quantify real-time glutamate dynamics in HD mouse models by high-speed imaging of an intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) and electrophysiological recordings of synaptically activated transporter currents in astrocytes. These techniques reveal a disconnect between the results obtained in synaptosomes and those in situ. Exogenous glutamate uptake is impaired in synaptosomes, whereas real-time measures of glutamate clearance in the HD striatum are normal or even accelerated, particularly in the aggressive R6/2 model. Our results highlight the importance of quantifying glutamate dynamics under endogenous release conditions, and suggest that the widely cited uptake impairment in HD does not contribute to pathogenesis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".