GSK-3β-induced Tau pathology drives hippocampal neuronal cell death in Huntington’s disease: involvement of astrocyte–neuron interactions
Bibliographic record
Abstract
Glycogen synthase kinase-3β (GSK-3β) has emerged as a critical factor in several pathways involved in hippocampal neuronal maintenance and function. In Huntington's disease (HD), there are early hippocampal deficits both in patients and transgenic mouse models, which prompted us to investigate whether disease-specific changes in GSK-3β expression may underlie these abnormalities. Thirty-three postmortem hippocampal samples from HD patients (neuropathological grades 2-4) and age- and sex-matched normal control cases were analyzed using real-time quantitative reverse transcription PCRs (qPCRs) and immunohistochemistry. In vitro and in vivo studies looking at hippocampal pathology and GSK-3β were also undertaken in transgenic R6/2 and wild-type mice. We identified a disease and stage-dependent upregulation of GSK-3β mRNA and protein levels in the HD hippocampus, with the active isoform pGSK-3β-Tyr(216) being strongly expressed in dentate gyrus (DG) neurons and astrocytes at a time when phosphorylation of Tau at the AT8 epitope was also present in these same neurons. This upregulation of pGSK-3β-Tyr(216) was also found in the R6/2 hippocampus in vivo and linked to the increased vulnerability of primary hippocampal neurons in vitro. In addition, the increased expression of GSK-3β in the astrocytes of R6/2 mice appeared to be the main driver of Tau phosphorylation and caspase3 activation-induced neuronal death, at least in part via an exacerbated production of major proinflammatory mediators. This stage-dependent overactivation of GSK-3β in HD-affected hippocampal neurons and astrocytes therefore points to GSK-3β as being a critical factor in the pathological development of this condition. As such, therapeutic targeting of this pathway may help ameliorate neuronal dysfunction in HD.
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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".