Glycolysis Prevents Anoxia-Induced Synaptic Transmission Damage in Rat Hippocampal Slices
Bibliographic record
Abstract
Prolonged anoxia can cause permanent damage to synaptic transmission in the mammalian CNS. We tested the hypothesis that lack of glucose is the major cause of irreversible anoxic transmission damage, and that anoxic synaptic transmission damage could be prevented by glycolysis in rat hippocampal slices. The evoked population spike (PS) was extracellularly recorded in the CA1 pyramidal cell layer after stimulation of the Schaffer collaterals. When the slice was superfused with artificial cerebrospinal fluid (ACSF) containing 4 mM glucose, following 10 min anoxia, the evoked PS did not recover at all after 60 min reoxygenation. When superfusion ACSF contained 10 mM glucose with or without 0.5 mM alpha-cyano-4-hydroxycinnate (4-CIN), after 60 min reoxygenation the evoked PS completely recovered following 10 min anoxia. When superfusion ACSF contained 20 mM glucose with or without 1 mM sodium cyanide (NaCN), after 60 min reoxygenation the evoked PS completely recovered even following 120 min anoxia. In contrast, when superfusion ACSF contained 4 mM glucose, following 10 min 1 mM NaCN chemical anoxia alone, without anoxic anoxia, the evoked PS displayed no recovery after 60 min reoxygenation. Moreover, when 16 mM mannitol and 16 sodium L-lactate were added into 4 mM glucose ACSF, following 10 min anoxia the evoked PS failed to recover at all after 60 min reoxygenation. The results indicate that elevated glucose concentration powerfully protected the synaptic transmission against anoxic damage, and the powerful protection is due to anaerobic metabolism of glucose and not a result of the higher osmolality in higher glucose ACSF. We conclude that lack of glucose is the major cause of anoxia-induced synaptic transmission damage, and that if sufficient glucose is supplied, glycolysis could prevent this damage in vitro.
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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) | 0.000 | 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 | 0.000 |
| 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".