The Glycolysis Inhibitor 2-Deoxy-d-Glucose Exerts Different Neuronal Effects at Circuit and Cellular Levels, Partially Reverses Behavioral Alterations and does not Prevent NADPH Diaphorase Activity Reduction in the Intrahippocampal Kainic Acid Model of Temporal Lobe Epilepsy
Bibliographic record
Abstract
Temporal lobe epilepsy is the most drug-resistant type with the highest incidence among the other focal epilepsies. Metabolic manipulations are of great interest among others, glycolysis inhibitors like 2-deoxy d -glucose (2-DG) being the most promising intervention. Here, we sought to investigate the effects of 2-DG treatment on cellular and circuit level electrophysiological properties using patch-clamp and local field potentials recordings and behavioral alterations such as depression and anxiety behaviors, and changes in nitric oxide signaling in the intrahippocampal kainic acid model. We found that epileptic animals were less anxious, more depressed, with more locomotion activity. Interestingly, by masking the effect of increased locomotor activity on the parameters of the zero-maze test, no altered anxiety behavior was noted in epileptic animals. However, 2-DG could partially reverse the behavioral changes induced by kainic acid. The findings also showed that 2-DG treatment partially suppresses cellular level alterations while failing to reverse circuit-level changes resulting from kainic acid injection. Analysis of NADPH-diaphorase positive neurons in the CA1 area of the hippocampus revealed that the number of positive neurons was significantly reduced in dorsal CA1 of the epileptic animals and 2-DG treatment did not affect the diminishing effect of kainic acid on NADPH-d + neurons in the CA1 area. In the control group receiving 2-DG, however, an augmented NADPH-d + cell number was noted. These data suggest that 2-DG cannot suppress epileptiform activity at the circuit-level in this model of epilepsy and therefore, may fail to control the seizures in temporal lobe epilepsy cases.
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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 | 0.001 |
| 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".