Bibliographic record
Abstract
Insulin-mediated signalling in the brain is critical for neuronal functioning. Insulin resistance is implicated in the development of some neurological diseases, although changes associated with absence epilepsy have not been established yet. Therefore, we examined the major components of PI3K/Akt-mediated insulin signalling in cortical, thalamic, and hippocampal tissues collected from Genetic Absence Epilepsy Rats from Strasbourg (GAERS) and Non-Epileptic Control (NEC) rats. Insulin levels were also measured in plasma and cerebrospinal fluid (CSF). For the brain samples, the nuclear fraction (NF) and total homogenate (TH) were isolated and investigated for insulin signalling markers including insulin receptor beta (IRβ), IR substrate-1 and 2 (IRS1 & 2), phosphatase and tensin homologue (PTEN), phosphoinositide 3-kinase phospho-85 alpha (PI3K p85α), phosphatidylinositol 4,5-bisphosphate, phosphatidylinositol (3,4,5)-trisphosphate, protein kinase B (PKB/Akt1/2/3), glucose transporter-1 and 4 (GLUT1 & 4) and glycogen synthase kinase-3β (GSK3β) using western blotting. A significant increase in PTEN and GSK3β levels and decreased PI3K p85α and pAkt1/2/3 levels were observed in NF of GAERS cortical and hippocampal tissues. IRβ, IRS1, GLUT1, and GLUT4 levels were significantly decreased in hippocampal TH of GAERS compared to NEC. A non-significant increase in insulin levels was observed in plasma and CSF of GAERS rats. An insulin sensitivity assay showed decreased p-Akt level in cortical and hippocampal tissues. Together, altered hippocampal insulin signalling was more prominent in NF and TH compared to cortical and thalamic regions in GAERS. Restoring insulin signalling may improve the pathophysiology displayed by GAERS, including the spike-and-wave discharges that relate to absence seizures in patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".