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Record W179573588 · doi:10.1038/npre.2009.2867.1

Evolutionary descent of prion genes from a ZIP metal ion transport ancestor

2009· preprint· en· W179573588 on OpenAlexaff
Gerold Schmitt‐Ulms, Sepehr Ehsani, Joel C. Watts, David Westaway, Holger Wille

Bibliographic record

VenueNature Precedings · 2009
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of AlbertaUniversity of Toronto
Fundersnot available
KeywordsPhylogenetic treeBiologyPrion proteinGenePrion ProteinsFungal prionFunction (biology)GeneticsPhylogeneticsTransmembrane domainComputational biologyTransmembrane proteinInteractomePhenotypeDisease

Abstract

fetched live from OpenAlex

Abstract In the more than 20 years since its discovery, both the phylogenetic origin and cellular function of the prion protein (PrP) have remained enigmatic. Insights into the function of PrP may be obtained through a characterization of its molecular neighborhood. Quantitative interactome data revealed the spatial proximity of a subset of metal ion transporters of the ZIP family to mammalian prion proteins. A subsequent bioinformatic analysis revealed the presence of a prion-like protein sequence within the N-terminal, extracellular domain of a phylogenetic branch of ZIPs. Additional structural threading and ortholog sequence alignment analyses consolidated the conclusion that the prion protein gene family is phylogenetically derived from a ZIP-like ancestor molecule. Our data explain structural and functional features found within mammalian prion proteins as elements of an ancient involvement in the transmembrane transport of divalent cations. The connection to ZIP proteins is expected to open new avenues to elucidate the biology of the prion protein in health and disease.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.259
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2009
Admission routes1
Has abstractyes

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