δ-Opioid receptor antagonism induces NMDA receptor-dependent excitotoxicity in anoxic turtle cortex
Bibliographic record
Abstract
delta-Opioid receptor (DOR) activation is neuroprotective against short-term anoxic insults in the mammalian brain. This protection may be conferred by inhibition of N-methyl-d-aspartate receptors (NMDARs), whose over-activation during anoxia otherwise leads to a deleterious accumulation of cytosolic calcium ([Ca(2+)](c)), severe membrane potential (E(m)) depolarization and excitotoxic cell death (ECD). Conversely, NMDAR activity is decreased by approximately 50% with anoxia in the cortex of the painted turtle, and large elevations in [Ca(2+)](c), severe E(m) depolarization and ECD are avoided. DORs are expressed in high quantity throughout the turtle brain relative to the mammalian brain; however, the role of DORs in anoxic NMDAR regulation has not been investigated in turtles. We examined the effect of DOR blockade with naltrindole (1-10 micromol l(-1)) on E(m), NMDAR activity and [Ca(2+)](c) homeostasis in turtle cortical neurons during normoxia and the transition to anoxia. Naltrindole potentiated normoxic NMDAR currents by 78+/-5% and increased [Ca(2+)](c) by 13+/-4%. Anoxic neurons treated with naltrindole were strongly depolarized, NMDAR currents were potentiated by 70+/-15%, and [Ca(2+)](c) increased 5-fold compared with anoxic controls. Following naltrindole washout, E(m) remained depolarized and [Ca(2+)](c) became further elevated in all neurons. The naltrindole-mediated depolarization and increased [Ca(2+)](c) were prevented by NMDAR antagonism or by perfusion of the G(i) protein agonist mastoparan-7, which also reversed the naltrindole-mediated potentiation of NMDAR currents. Together, these data suggest that DORs mediate NMDAR activity in a G(i)-dependent manner and prevent deleterious NMDAR-mediated [Ca(2+)](c) influx during anoxic insults in the turtle cortex.
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) | 0.001 | 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".