Glial Activation in A?PP/PS1 Mice is Associated with Infiltration of IFN?-Producing Cells.
Bibliographic record
Abstract
Whereas the classical histological hallmarks of Alzheimer's disease (AD) are deposition of amyloid-containing plaques and development of neurofibrillary tangles, there is also clear evidence of inflammatory changes accompanied by the presence of activated microglia and astrocytosis.However, at this time it remains uncertain whether inflammatory changes contribute to pathogenesis of the disease or if they are secondary to deposition of amyloid-β or other pathological changes.A greater understanding of the sequence of events would clearly improve development of strategies to delay progression of the disease.There is a realistic expectation that advances in imaging technology may provide the key to uncovering this sequence.In this study, we employed non-invasive imaging techniques to examine changes in tissue state in hippocampus and cortex of transgenic mice which overexpress amyloid precursor protein and presenilin 1 and show that the observed increase in T 1 relaxation time was associated with astrogliosis while the decrease in T 2 relaxation time was associated with microglial activation.We explored the possibility that interferon-γ might trigger glial activation and demonstrate a genotyperelated infiltration of macrophages and natural killer cells, which release interferon-γ.The evidence suggests that IFNγ triggers glial activation and expression of proinflammatory cytokines, and these changes, in turn, contribute to the decrease in long-term potentiation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".