The Role of Neuroglial Metabotropic Glutamate Receptors in Alzheimer’sDisease
Bibliographic record
Abstract
Glutamate, the major excitatory neurotransmitter in the brain exerts its effects via both ionotropic glutamate receptors and metabotropic glutamate receptors (mGluRs). There are three subgroups of mGluRs, pre-synaptic Group II and Group III mGluRs and post-synaptic Group I mGluRs. mGluRs are ubiquitously expressed in the brain and their activation is poised upstream of a myriad of signaling pathways, resulting in their implication in the pathogenesis of various neurodegenerative diseases including, Alzheimer's Disease (AD). While the exact mechanism of AD etiology remains elusive, β-amyloid (Aβ) plaques and hyperphosphorylated tau tangles remain the histopathological hallmarks of AD. Though less electrically excitable, neuroglia are a major non-neuronal cell type in the brain and are composed of astrocytes, microglia, and oligodendrocytes. Astrocytes, microglia, and oligodendrocytes provide structural and metabolic support, active immune defence, and axonal support and sheathing, respectively. Interestingly, Aβ and hyperphosphorylated tau are known to disrupt the neuroglial homeostasis in the brain, pushing them towards a more neurotoxic state. In this review, we discuss what is currently known regarding the expression patterns of various mGluRs in neuroglia and how Aβ and tau alter the normal mGluR function in the neuroglia and contribute to the pathophysiology of AD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".