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Record W2584455684 · doi:10.1139/bcb-2016-0236

Modulation of amyloid assembly by glycosaminoglycans: from mechanism to biological significance

2017· review· en· W2584455684 on OpenAlexafffundvenue
Noé Quittot, Mathew Sebastiao, Steve Bourgault

Bibliographic record

VenueBiochemistry and Cell Biology · 2017
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité du Québec à Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsGlycosaminoglycanMechanism (biology)Amyloid (mycology)Modulation (music)ChemistryBiophysicsBiochemistryCell biologyNeuroscienceBiologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Glycosaminoglycans (GAGs) are long and unbranched polysaccharides that are abundant in the extracellular matrix and basement membrane of multicellular organisms. These linear polyanionic macromolecules are involved in many physiological functions from cell adhesion to cellular signaling. Interestingly, amyloid fibrils extracted from patients afflicted with protein misfolding diseases are virtually always associated with GAGs. Amyloid fibrils are highly organized nanostructures that have been historically associated with pathological states, such as Alzheimer's disease and systemic amyloidoses. However, recent studies have identified functional amyloids that accomplish crucial physiological roles in almost all living organisms, from bacteria to insects and mammals. Over the last 2 decades, numerous reports have revealed that sulfated GAGs accelerate and (or) promote the self-assembly of a large diversity of proteins, both inherently amyloidogenic and non-aggregation prone. Despite the fact that many studies have investigated the molecular mechanism(s) by which GAGs induce amyloid assembly, the mechanistic elucidation of GAG-mediated amyloidogenesis still remains the subject of active research. In this review, we expose the contribution of GAGs in amyloid assembly, and we discuss the pathophysiological and functional significance of GAG-mediated fibrillization. Finally, we propose mechanistic models of the unique and potent ability of sulfated GAGs to hasten amyloid fibril formation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.078
GPT teacher head0.362
Teacher spread0.284 · 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.

Study designOther design
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

Citations35
Published2017
Admission routes3
Has abstractyes

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