Brain region-specific dopamine receptor changes and astrocyte activation influence tau pathology through CDK5 in Alzheimer's disease models
Bibliographic record
Abstract
Background The abnormal extracellular accumulation of amyloid-β (Aβ) plaques and intracellular tau inclusions are hallmarks of early events in the pathogenesis of Alzheimer's disease (AD). Although growing evidence implicates neurotransmitter dysregulation in AD-associated neurodegeneration, the influence of these pathological hallmarks on dopaminergic signaling remains poorly understood. This study reports changes in dopamine receptor (DR), Aβ, and astrocyte distribution in the cortex and hippocampus of 5XFAD mice. Objective To investigate how Aβ pathology alters dopamine receptor subtype expression in the AD brain and neuronal models, and whether this contributes to tau phosphorylation and CDK5 activation. Methods We examined DR1-DR5 expression and localization in the cortex and hippocampus of 5XFAD mice using immunohistochemistry, qPCR, and western blot. SH-SY5Y cells were differentiated with retinoic acid and treated with Aβ 1−42 ; MC-65 cells produced endogenous Aβ via tetracycline withdrawal. DR1, DR2, and DR3 agonists were used to assess effects on cAMP, CDK5, and tau phosphorylation. Results In AD brains, Gs-coupled DR1 and DR5 were upregulated, while Gi-coupled DR2, DR3, and DR4 were downregulated at mRNA and protein levels. SH-SY5Y and MC-65 cells recapitulated these subtype-specific changes following Aβ exposure. In the cortex, receptor alterations were implicated in increased CDK5 and tau phosphorylation. DR activation modulated cAMP and kinase pathways in a receptor- and cell-specific manner. The cortex showed greater vulnerability to Aβ-associated degeneration, whereas the hippocampus was more susceptible to inflammation and tau pathology. Conclusions These findings reveal a role for DR subtypes in regulating tau phosphorylation and CDK5, with implications for AD-related cognitive dysfunction.
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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 | 0.001 | 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".