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Record W4401933448 · doi:10.1039/d4sm00638k

Probing the molecular determinants of the activation of toll-like receptor 2/6 by amyloid nanostructures through directed peptide self-assembly

2024· article· en· W4401933448 on OpenAlexafffund
Nadjib Kihal, Marie-Jeanne Archambault, Margaryta Babych, Ali Nazemi, Steve Bourgault

Bibliographic record

VenueSoft Matter · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsPROTEOUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeptideAmyloid (mycology)Context (archaeology)TLR2Supramolecular chemistryInnate immune systemReceptorChemistrySelf-assemblyCell biologyBiophysicsBiologyBiochemistryCrystallographyCrystal structure

Abstract

fetched live from OpenAlex

peptide, including addition of charged residues at the N-terminus and α-amidation of C-terminus, allowed the controlled formation of a diversity of architectures, including belt-like filaments, rigid nanorods as well as flat and twisted fibrils. These fully cytocompatible peptide nanostructures showed different potencies to activate TLR2/TLR6, which correlated with the charge exposed on the surface. These results further demonstrate the potent modulatory effect of N- and C-terminal electrostatic capping on the self-assembly of short synthetic β-peptides. This study also indicates that self-assembly into cross-β-sheet nanostructures is essential for the activation of the TLR2/TLR6 by amyloidogenic peptides, albeit the structural requirements of the engagement of this promiscuous immune receptor by the nanostructures remain challenging to precisely untangle.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.662

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 science0.0010.000
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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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