O1–06–08: Activation of microglia by nasal vaccination with a proteosome based adjuvant and glatiramer acetate clears a–beta in an antibody independent fashion in a mouse model of Alzheimer's disease
Bibliographic record
Abstract
Immune therapy in Alzheimer's Disease (AD) models by Ab immunization or administration of anti–Ab antibodies reduces Ab levels and reverses behavioral impairment. A human trial of Ab immunization led to meningoencephalitis in some patients and was discontinued. We tested whether a nasal vaccination strategy that did not involve immunization with amyloid or depend on anti– Ab antibodies and was designed to activate microglia could clear Ab when given as prevention to young mice. Age– and sex–matched littermates (APP–J20 mice) received a weekly nasal treatment with Protollin (a proteosome–based adjuvant used in human influenza vaccination) 1ug/treatment, plus glatiramer acetate (GA, an approved drug for multiple sclerosis) 25ug/treatment, beginning at age 5 months for a duration of 8 months. We found a significant reduction in the level of amyloid fibril (∼80%) in the brains of GA+Protollin treated mice versus controls (P < 0.001). Furthermore, the reduction of amyloid load involved the reduction of both (50%) soluble Ab and (49%) insoluble form of Ab (p<0.02) as measured by ELISA and was associated with elevation of total serum Ab levels. The treated animalsexhibited no toxicity as measured by body weight, eating habits, tail tone, or mobility. Clearance of Ab was also observed with nasal Protollin alone and direct intrahippocampal injection of Protollin activated microglia and reduced Ab plaques. We also found reduction in astrocytosis following nasal vaccination with GA+Protollin or Protollin alone. We previously found that nasal vaccination with GA+Protollin, decreased Ab plaques in 14 month old APP Tg mice; vaccinated animals developed activated microglia (CD11b+ cells) that co–localized with Ab fibrils, and the extent of microglial activation correlated with the decrease in Ab fibrils (JCI: 115:2423, 2005). In this study, after chronic treatment for 8 months we observed no difference in microglial activation, suggesting that once Ab is cleared there is downregulation of microglial activation. Our results demonstrate an antibody–independent therapeutic approach for the treatment of AD which targets microglial cells and is also effective, without toxicity, when given chronically to young mice as prevention.
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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 | 0.000 | 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".