P2‐239: Rapid transmission of exogenous beta‐amyloid peptides from blood to the brain
Bibliographic record
Abstract
Blood transfusion is associated with high risks of transmitting emerging infectious pathogens from donors to recipients. Like prion diseases, Alzheimer's disease (AD) is believed to result from abnormally refolded fibrils and aggregated plaques of Aβ peptides in the brain. Intracerebral infusion of Aβ peptides extracted from human Alzheimer's brain was showed to initiate and catalyze Aβ fibril/plaque formation or amyloidosis, a characteristic of Alzheimer's pathology, in APP-transgenic mice. Aβ peptides can be transported from brain to circulation. However, little is known whether Aβ peptides in donors' bloods can be transported into the brains of recipients. Exogenous Cy5.5-labeled Aβ1-40 peptides or scrambled Aβ40-1 peptides or Cy5.5 free-dye were injected intravenously into mice. The mice were scanned alive at 15min, 2h, 4h, 6h and 8h post-injection with an optical imager for fluorescent intensity and concentration. Mouse brains were collected for scanning and immunohistochemistry. Exogenous Aβ1-40 peptides injected into circulation can quickly get into mouse brains as compared to Cy5.5 free-dye and scrambled Aβ40-1 peptides. Immunohistochemistry confirms the presence and accumulation of Aβ peptides in the brains of the mice injected with Aβ peptides, but not in the mice injected with Cy5.5 free-dye or scrambled Aβ40-1 peptides. The results suggest that transfusion may have a risk of transmitting exogenous Aβ peptides in circulation (from donor) to the brains of the recipients. Since AD has a long latent pathogenic period, it is necessary to distinguish the donors with a family history of AD or early signs of AD and to minimize the risk of transmitting Aβ peptides from blood donors to recipients.
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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 | 0.000 |
| 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) | 0.004 | 0.002 |
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".