P3‐428: Minocycline corrects early, pre‐plaque neuroinflammation and inhibits BACE in a transgenic model of Alzheimer's‐like amyloid pathology
Bibliographic record
Abstract
Epidemiological data indicate that chronic use of NSAIDs can protect from the development of Alzheimer's disease (AD), suggesting a crucial role for inflammation in early, pre-clinical stages of the pathology. We have previously demonstrated that intracellular accumulation of amyloid beta peptide (Aß) and Aß oligomers is associated with a pro-inflammatory reaction in the hippocampus of young transgenic (Tg) McGill-Thy1-App mice, in the absence of amyloid plaques. To establish the role of such pro-inflammatory process in the progression of the amyloid pathology, we administered minocycline, a tetra-cyclic derivative with anti-inflammatory and neuroprotective properties, to young, pre-plaque Tg mice for one month via i.p. injections (50mg/Kg/day). Western blotting was used to assess brain levels of inflammatory and cell-signaling markers in hippocampal and cortical homogenates. Beta-amyloid cleaving enzyme (BACE) activity was measured with a commercially available Fluor metric assay. The results were compared with Non Tg age-matched littermates. Minocycline was able to significantly reverse the up-regulation of the inflammatory markers i-NOS and COX-2 observed in young Tg mice (p < 0.01). Furthermore, down-regulation of inflammatory markers correlated with a strong (70%) reduction of a 12KDa 6E10-immunoreactive band which we interpreted as C99 and-or Aß trimers. BACE activity was found to be significantly increased in Tg placebo (p < 0.01), and was restored to normal levels following minocycline treatment (p < 0.05). The anti-inflammatory and BACE effects could be explained by the inhibition of the NF-kB pathway, as minocycline corrected the up-regulation of NF-kB levels observed in Tg animals. While the inter play between inflammation and amyloid pathology remains to be elucidated, our study suggests that pharmacological modulation of neuroinflammation and NF-kB blockade might represent a promising approach for preventing AD onset.
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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 | 0.001 | 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) | 0.002 | 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".