Prion protein expression level alters regional copper, iron and zinc content in the mouse brain
Bibliographic record
Abstract
The central role of the prion protein (PrP) in a family of fatal neurodegenerate diseases has garnered considerable research interest over the past two decades. Moreover, the role of PrP in neuronal development, as well as its apparent role in metal homeostasis, is increasingly of interest. The host-encoded form of the prion protein (PrP(C)) binds multiple copper atoms via its N-terminal domain and can influence brain copper and iron levels. The importance of PrP(C) to the regulation of brain metal homeostasis and metal distribution, however, is not fully understood. We therefore employed synchrotron-based X-ray fluorescence imaging to map the level and distributions of several key metals in the brains of mice that express different levels of PrP(C). Brain sections from wild-type, prion gene knockout (Prnp(-/-)) and PrP(C) over-expressing mice revealed striking variation in the levels of iron, copper, and even zinc in specific brain regions as a function of PrP(C) expression. Our results indicate that one important function of PrP(C) may be to regulate the amount and distribution of specific metals within the central nervous system. This raises the possibility that PrP(C) levels, or its activity, might regulate the progression of diseases in which altered metal homeostasis is thought to play a pathogenic role such as Alzheimer's, Parkinson's and Wilson's diseases and disorders such as hemochromatosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".