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Record W2092782818 · doi:10.1111/cid.12231

The Effect of Platelet Proteins Released in Response to Titanium Implant Surfaces on Macrophage Pro‐Inflammatory Cytokine Gene Expression

2014· article· en· W2092782818 on OpenAlexvenueno aff
Mohammed A. Alfarsi, Stephen Hamlet, Sašo Ivanovski

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2014
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
FundersKing Khalid UniversityGriffith University
KeywordsCytokinePlatelet activationPlateletMacrophageTumor necrosis factor alphaCell biologyImmunologyMolecular biologyMaterials scienceChemistryMedicineIn vitroBiochemistryBiology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Platelets are one of the earliest cell types to interact with surgically inserted titanium implants. This in vitro study investigated the effect of titanium surface-induced platelet releasate on macrophage cytokine gene expression. MATERIALS AND METHODS: To mimic the in vivo temporal sequence of platelet arrival and protein production at the implant surface and the subsequent effect of these proteins on mediators of the immune response, the levels of platelet attachment and activation in response to culture on smooth polished, sandblasted and acid-etched (SLA), and hydrophilic-modified SLA (modSLA) titanium surfaces were first determined by microscopy and protein assay. The subsequent effect of the platelet-released proteins on human THP-1 macrophage cytokine gene expression was determined by polymerase chain reaction array after 1 and 3 days of macrophage culture on the titanium surfaces in platelet-releasate conditioned media. RESULTS: Platelet attachment was surface dependent with decreased attachment observed on the hydrophilic (modSLA) surface. The platelet releasate, when considered independently of the surface effect, elicited an overall pro-inflammatory response in macrophage cytokine gene expression, that is, the expression of typical pro-inflammatory cytokine genes such as TNF, IL1a, IL1b, and CCL1 was significantly up-regulated whereas the expression of anti-inflammatory cytokine genes such as IL10, CxCL12, and CxCL13 was significantly down-regulated. However, following platelet exposure to different surface modifications, the platelet releasate significantly attenuated the macrophage pro-inflammatory response to microrough (SLA) titanium and hastened an anti-inflammatory response to hydrophilic (modSLA) titanium. CONCLUSIONS: Theses results demonstrate that titanium surface topography and chemistry are able to influence the proteomic profile released by platelets, which can subsequently influence macrophage pro-inflammatory cytokine expression. This immunomodulation may be an important mechanism via which titanium surface modification influences osseointegration.

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 integrity0.0000.000
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 head0.043
GPT teacher head0.408
Teacher spread0.365 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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