Cellular distribution of the neutral amino acid transporter subtype ASCT2 in mouse brain
Bibliographic record
Abstract
ASCT2 is an ASC (alanine-, serine-, cysteine-preferring) neutral amino acid exchanger that may regulate CNS function by transporting amino acid substrates including L-serine, L-cysteine, L-glutamine, L-glutamate and D-serine. Despite the potentially important role of ASCT2 in influencing metabolic and signaling functions of these amino acids in brain, there has been little description of its distribution in brain tissue. We employed a commercially available human ASCT2 antibody in immunohistochemistry studies in adult mouse brain and found a wide regional distribution for ASCT2 that was limited to dendrites labeled by anti-microtubule-associated protein-2 in cortex, hippocampus and striatum. No ASCT2 immunoreactivity was observed in areas labeled by antibodies against a neuronal cell body marker (NeuN), or either of the astrocyte markers, glial fibrillary acidic protein or S100beta. In cerebellum both Purkinje cell bodies and dendrites were positive for ASCT2 immunoreactivity. In support of a dendritic localization for ASCT2 in cortex, low affinity (K(T) > 1 mM), Na(+)-dependent D-serine and L-glutamine uptake characteristic of ASCT2-mediated transport was observed in P2 synaptosomal preparations. These results suggest that ASCT2 may be an important neuronal neutral amino acid transporter and highlight a discrepancy between findings of astrocyte ASCT2 function in tissue culture and brain in situ.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".