MyD88-adaptor protein acts as a preventive mechanism for memory deficits in a mouse model of Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is an age-related neurodegenerative disorder associated with brain innate immune activation mainly mediated by microglia. These cells are known to be activated in the brain of AD patients and to produce inflammatory cytokines and neurotoxic molecules in response to Amyloid beta (Aβ). Activation of microglia can also promote Aβ clearance via Toll-like receptors (TLRs). Myeloid differentiation factor 88 (MyD88) is the adaptor molecule for most of these innate immune receptors, transducing the intracellular signal from TLRs to nucleus. RESULTS: Here, we report that more than 50% reduction in MyD88 expression in a mouse model of AD accelerated spatial learning and memory deficits. Brain of APPswe/PS1-MyD88+/- mice was characterized by a delay in accumulation of Aβ plaques and increased soluble levels of Aβ oligomers. Furthermore, inflammatory monocyte subset and brain IL-1β gene expression were significantly reduced in APPswe/PS1 mice with impaired MyD88 signaling. CONCLUSIONS: These data indicate that activation of MyD88 intracellular signaling pathway, likely by TLRs, acts as a natural innate immune mechanism to restrict disease progression of APPswe/PS1 mice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".