Autoimmune Manifestations in the 3xTg-AD Model of Alzheimer's Disease
Bibliographic record
Abstract
BACKGROUND: Immune system activation is frequently reported in patients with Alzheimer's disease (AD). However, it remains unknown whether this is a cause, a consequence, or an epiphenomenon of brain degeneration. OBJECTIVE: The present study examines whether immunological abnormalities occur in a well-established murine AD model and if so, how they relate temporally to behavioral deficits and neuropathology. METHODS: A broad battery of tests was employed to assess behavioral performance and autoimmune/inflammatory markers in 3xTg-AD (AD) mice and wild type controls from 1.5 to 12 months of age. RESULTS: Aged AD mice displayed severe manifestations of systemic autoimmune/inflammatory dise6ase, as evidenced by splenomegaly, hepatomegaly, elevated serum levels of anti-nuclear/anti-dsDNA antibodies, low hematocrit, and increased number of double-negative T splenocytes. However, anxiety-related behavior and altered spleen function were evident as early as 2 months of age, thus preceding typical AD-like brain pathology. Moreover, AD mice showed altered olfaction and impaired "cognitive" flexibility in the first 6 months of life, suggesting mild cognitive impairment-like manifestations before general learning/memory impairments emerged at an older age. Interestingly, all of these features were present in 3xTg-AD mice prior to significant amyloid-β or tau pathology. CONCLUSION: The results indicate that behavioral deficits in AD mice develop in parallel with systemic autoimmune/inflammatory disease. These changes antedate AD-like neuropathology, thus supporting a causal link between autoimmunity and aberrant behavior. Consequently, 3xTg-AD mice may be a useful model in elucidating the role of immune system in the etiology 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) | 0.000 | 0.001 |
| 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 | 0.001 | 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".