Protective Effect of High Glucose Against Ischemia-Induced Synaptic Transmission Damage in Rat Hippocampal Slices
Bibliographic record
Abstract
Cerebral ischemic damage is an important cause of morbidity and mortality. However, there is conflicting evidence regarding the effect of the extracellular glucose concentration in focal and global ischemic injury. This study was designed to investigate this effect in ischemia-induced synaptic transmission damage in rat hippocampal slices. Slices were superfused with artificial cerebrospinal fluid (ACSF) containing various concentrations of glucose before and after ischemia. The evoked somatic postsynaptic population spike (PS) and dendritic field excitatory postsynaptic potential (fEPSP) were extracellularly recorded in the CA1 stratum pyramidal cell layer and s. radiatum after stimulation of the Schaeffer collaterals, respectively. The glucose concentration in ACSF before and after ischemia determined the duration of ischemia tolerated by synaptic transmission as demonstrated by complete recovery of the somatic PS and dendritic fEPSP. Specifically, the somatic PS and dendritic fEPSP completely recovered following 3, 4, and 5 min of ischemia only when slices were superfused with ACSF containing 4, 10, and 20 mM glucose before and after ischemia, respectively. The latencies of the somatic and dendritic ischemic depolarization (ID) occurrence in the CA1 s. pyramidal cell layer and s. radiatum were significantly longer with 10 than 4 mM glucose in ACSF before ischemia and significantly longer with 20 than 10 mM glucose in ACSF before ischemia. Regardless of the glucose concentration in ACSF before and after ischemia, the somatic PS and dendritic fEPSP only partially recovered when ischemia was terminated at the occurrence of ID. These results indicate that high glucose in ACSF during the period before and after ischemia significantly protects CA1 synaptic transmission against in vitro ischemia-induced damage through postponing the occurrence of ID.
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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) | 0.001 | 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".