Hypothermia rescues hippocampal CA1 neurons and attenuates down-regulation of the AMPA receptor GluR2 subunit after forebrain ischemia
Bibliographic record
Abstract
Brief forebrain ischemia in rodents induces selective and delayed neuronal death, particularly of hippocampal CA1 pyramidal neurons. Neuronal death is preceded by down-regulation specific to CA1 of GluR2, the alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor subunit that limits Ca(2+) influx. This alteration is hypothesized to cause neurodegeneration by permitting a lethal influx of Ca(2+) and/or Zn(2+) through newly formed GluR2-lacking AMPA receptors. Two days of mild hypothermia induced 1 h after ischemia potently and lastingly protects against ischemic injury. We examined molecular mechanisms underlying hypothermia-induced neuroprotection. We report that hypothermia rescues most hippocampal CA1 neurons from ischemia-induced cell death and attenuates ischemia-induced down-regulation of mRNA encoding the AMPA receptor subunit GluR2. Ischemia induced a marked down-regulation of GluR2 mRNA and a small down-regulation of GluR1 mRNA in CA1 at 2 days, as assessed by quantitative in situ hybridization. The ischemia-induced changes in gene expression were cell-specific in that GluR2 was not significantly altered in CA3 or dentate gyrus. After ischemia treated by hypothermia GluR2 mRNA expression was modestly reduced at 2 days and exhibited complete recovery to control levels at 7 days. Hypothermia prevented ischemia induced changes in GluR1 mRNA expression. These findings suggest that intervention at the level of transcriptional regulation of the GluR2 gene may be a mechanism by which prolonged postischemic cooling rescues CA1 neurons otherwise "destined to die."
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) | 0.001 | 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".