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Record W3163107759 · doi:10.1038/s42003-021-02126-w

Super-resolution imaging reveals α-synuclein seeded aggregation in SH-SY5Y cells

2021· article· en· W3163107759 on OpenAlexfundno aff
Jason C. Sang, Eric Hidari, Georg Meisl, Rohan T. Ranasinghe, Maria Grazia Spillantini, David Klenerman

Bibliographic record

VenueCommunications Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersUK Dementia Research InstituteUniversity of TorontoMedical Research CouncilRoyal SocietyParkinson's UKAlzheimer's Society
KeywordsProtein aggregationBiophysicsSeedingChemistryFibrilSynucleinopathiesCell biologySH-SY5YAmyloid (mycology)Mechanism (biology)EndogenyNanoscopic scaleAlpha-synucleinCell cultureNanotechnologyBiologyBiochemistryParkinson's diseaseMaterials scienceDiseaseInternal medicineMedicine

Abstract

fetched live from OpenAlex

Aggregation of α-synuclein (α-syn) is closely linked to Parkinson's disease (PD) and the related synucleinopathies. Aggregates spread through the brain during the progression of PD, but the mechanism by which this occurs is still not known. One possibility is a self-propagating, templated-seeding mechanism, but this cannot be established without quantitative information about the efficiencies and rates of the key steps in the cellular process. To address this issue, we imaged the uptake and seeding of unlabeled exogenous α-syn fibrils by SH-SY5Y cells and the resulting secreted aggregates, using super-resolution microscopy. Externally-applied fibrils very inefficiently induced self-assembly of endogenous α-syn in a process accelerated by the proteasome. Seeding resulted in the increased secretion of nanoscopic aggregates (mean 35 nm diameter), of both α-syn and Aβ. Our results suggest that cells respond to seed-induced disruption of protein homeostasis predominantly by secreting nanoscopic aggregates; this mechanism may therefore be an important protective response by cells to protein aggregation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.319
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations49
Published2021
Admission routes1
Has abstractyes

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