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Record W4386122134 · doi:10.3389/fimmu.2023.1232586

MyD88-dependent Toll-like receptor 2 signaling modulates macrophage activation on lysate-adsorbed Teflon™ AF surfaces in an in vitro biomaterial host response model

2023· article· en· W4386122134 on OpenAlexafffund
Laura A. McKiel, Laurel L. Ballantyne, Gian Luca Negri, Kimberly A. Woodhouse, Lindsay E. Fitzpatrick

Bibliographic record

VenueFrontiers in Immunology · 2023
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersHospital for Sick ChildrenMinistry of Colleges and UniversitiesScheme for Promotion of Academic and Research CollaborationCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaQueen's University
KeywordsChemistryCCL5ChemokineProtein adsorptionFibronectinMolecular biologyLysisReceptorCell biologyBiophysicsIn vitroAdsorptionBiologyBiochemistryCell

Abstract

fetched live from OpenAlex

The adsorbed protein layer on an implanted biomaterial surface is known to mediate downstream cell-material interactions that drive the host response. While the adsorption of plasma-derived proteins has been studied extensively, the adsorption of damage-associated molecular patterns (DAMPs) derived from damaged cells and matrix surrounding the implant remains poorly understood. Previously, our group developed a DAMP-adsorption model in which 3T3 fibroblast lysates were used as a complex source of cell-derived DAMPs and we demonstrated that biomaterials with adsorbed lysate potently activated RAW-Blue macrophages via Toll-like receptor 2 (TLR2). In the present study, we characterized the response of mouse bone marrow derived macrophages (BMDM) from wildtype (WT), TLR2 -/- and MyD88 -/- mice on Teflon™ AF surfaces pre-adsorbed with 10% plasma or lysate-spiked plasma (10% w/w total protein from 3T3 fibroblast lysate) for 24 hours. WT BMDM cultured on adsorbates derived from 10% lysate in plasma had significantly higher gene and protein expression of IL-1β, IL-6, TNF-α, IL-10, RANTES/CCL5 and CXCL1/KC, compared to 10% plasma-adsorbed surfaces. Furthermore, the upregulation of pro-inflammatory cytokine and chemokine expression in the 10% lysate in plasma condition was attenuated in TLR2 -/- and MyD88 -/- BMDM. Proteomic analysis of the adsorbed protein layers showed that even this relatively small addition of lysate-derived proteins within plasma (10% w/w) caused a significant change to the adsorbed protein profile. The 10% plasma condition had fibrinogen, albumin, apolipoproteins, complement, and fibronectin among the top 25 most abundant proteins. While proteins layers generated from 10% lysate in plasma retained fibrinogen and fibronectin among the top 25 proteins, there was a disproportionate increase in intracellular proteins, including histones, tubulins, actins, and vimentin. Furthermore, we identified 7 DAMPs or DAMP-related proteins enriched in the 10% plasma condition (fibrinogen, apolipoproteins), compared to 39 DAMPs enriched in the 10% lysate in plasma condition, including high mobility group box 1 and histones. Together, these findings indicate that DAMPs and other intracellular proteins readily adsorb to biomaterial surfaces in competition with plasma proteins, and that adsorbed DAMPs induce an inflammatory response in adherent macrophages that is mediated by the MyD88-dependent TLR2 signaling pathway.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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 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

Citations8
Published2023
Admission routes2
Has abstractyes

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