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Record W4401345796 · doi:10.3389/fnins.2024.1436262

“Prion-like” seeding and propagation of oligomeric protein assemblies in neurodegenerative disorders

2024· review· en· W4401345796 on OpenAlexafffund
Silvia Zampar, Sonja E. Di Gregorio, Gustavo Grimmer, Joel C. Watts, Martin Ingelsson

Bibliographic record

VenueFrontiers in Neuroscience · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsOntario Brain InstituteOccupational Cancer Research CentreUniversity of TorontoUniversity Health Network
FundersKrembil Foundation
KeywordsPrion proteinNeuroscienceSeedingBiologyChemistryMedicineDiseasePathology

Abstract

fetched live from OpenAlex

Intra- or extracellular aggregates of proteins are central pathogenic features in most neurodegenerative disorders. The accumulation of such proteins in diseased brains is believed to be the end-stage of a stepwise aggregation of misfolded monomers to insoluble cross-β fibrils via a series of differently sized soluble oligomers/protofibrils. Several studies have shown how α-synuclein, amyloid-β, tau and other amyloidogenic proteins can act as nucleating particles and thereby share properties with misfolded forms, or strains, of the prion protein. Although the roles of different protein assemblies in the respective aggregation cascades remain unclear, oligomers/protofibrils are considered key pathogenic species. Numerous observations have demonstrated their neurotoxic effects and a growing number of studies have indicated that they also possess seeding properties, enabling their propagation within cellular networks in the nervous system. The seeding behavior of oligomers differs between the proteins and is also affected by various factors, such as size, shape and epitope presentation. Here, we are providing an overview of the current state of knowledge with respect to the "prion-like" behavior of soluble oligomers for several of the amyloidogenic proteins involved in neurodegenerative diseases. In addition to providing new insight into pathogenic mechanisms, research in this field is leading to novel diagnostic and therapeutic opportunities for neurodegenerative diseases.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.018
GPT teacher head0.299
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2024
Admission routes2
Has abstractyes

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