Whey protein consumption exacerbates beta-amyloid pathology in AppNL-G-F mice with subclinical milk allergy 3724
Bibliographic record
Abstract
Abstract Description Alzheimer’s disease (AD) pathology is characterized by the accumulation of β-amyloid (Aβ) plaques in the brain and neuroinflammation, which can be reproduced in transgenic AppNL-G-F knock-in mice. We previously reported that C57BL/6J mice that were sensitized but tolerant to a bovine milk allergen, β-lactoglobulin (BLG; Bos d 5), showed lasting neuroinflammation after feeding on a whey-protein-containing diet (WP). Based on this finding, we hypothesized that chronic inflammation due to prolonged allergen consumption by subclinically sensitized individuals would exacerbate the development of genetically predisposed AD-related pathologies. To test this hypothesis, male and female AppNL-G-F mice were sensitized to BLG, and Aβ plaque load in the brain was examined after WP diet consumption for 3 or 6 months. Despite the development of allergen tolerance, evident from decreased BLG-specific IgE levels with the WP diet, increased Aβ levels were found in sensitized mice of both sexes after 6 months, indicating that sensitization alone was sufficient to exacerbate Aβ pathology. Importantly, the WP diet further elevated the Aβ levels. These results suggest that continued allergen consumption, as in oral immunotherapy, may have unexpected outcomes on the progression of AD in genetically predisposed individuals. Further characterization of neuroimmune responses may help define the mechanisms resulting in observed Aβ-related changes. Funding Sources Supported by NIH/NIA 1R21AG070412 to KNC; Histological services were provided by the UND Histology Core Facility supported by NIH/HIGMS awards P20GM113123, U54GM128729, and UND School of Medicine & Health Sciences Topic Categories Neuroimmunology (NEUR)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".