Expression of human equilibrative nucleoside transporter 1 in mouse neurons regulates adenosine levels in physiological and hypoxic‐ischemic conditions
Bibliographic record
Abstract
Activation of adenosine A(1) receptors inhibits excitatory synaptic transmission. Equilibrative nucleoside transporters (ENTs) regulate extracellular adenosine levels; however, the role of neuronal ENTs in adenosine influx and efflux during cerebral ischemia has not been determined. We used mice with neuronal expression of human ENT type 1 and wild type (Wt) littermates to compare responses to in vitro hypoxic or ischemic conditions. Extracellular recordings in the CA1 region of hippocampal slices from transgenic (Tg) mice revealed increased basal synaptic transmission, relative to Wt slices, and an absence of 8-cyclopentyl-1,3-dipropyl-xanthine mediated augmentation of excitatory neurotransmission. Adenosine (10-100 μM) had a reduced potency for inhibiting synaptic transmission in slices from Tg mice; inhibitory concentration 50% values were approximately 25 and 50 μM in Wt and Tg slices, respectively. Potency of the A(1) receptor agonist N(6) -cyclopentyladenosine (1 nM-1 μM) was unchanged. Transient hypoxia or oxygen-glucose deprivation produced greater inhibition of excitatory neurotransmission in slices from Wt than Tg, mice. The ENT1 inhibitor S-(4-nitrobenzyl)-6-thioinosine abolished these differences. Taken together, our data provide evidence that neuronal ENTs reduce hypoxia- and ischemia-induced increases in extracellular adenosine levels and suggest that inhibition of neuronal adenosine transporters may be a target for the treatment of cerebral ischemia.
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 | 0.000 |
| 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) | 0.002 | 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".