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Record W1978952565 · doi:10.1503/cjs.003711

Periprosthetic osteolysis: genetics, mechanisms and potential therapeutic interventions

2012· review· en· W1978952565 on OpenAlex
Shahryar Noordin, Bassam A. Masri

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Surgery · 2012
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsSpinal Cord Injury BCUniversity of British Columbia
Fundersnot available
KeywordsMedicineOsteolysisPeriprostheticProinflammatory cytokineBone resorptionParacrine signallingCancer researchImmunologyArthroplastySurgeryInflammationInternal medicine

Abstract

fetched live from OpenAlex

Aseptic loosening and periprosthetic osteolysis occur as a result of the biological response to particulate wear debris and are one of the leading causes of arthroplasty failure. Periprosthetic osteolysis originates from chronic inflammatory responses triggered by implant-derived particulate debris, which cause recruitment of cells, including macrophages, fibroblasts, lymphocytes and osteoclasts. These cells secrete proinflammatory and osteoclastogenic cytokines, exacerbating the inflammatory response. In addition to their direct activation by phagocytosis, there are contributing autocrine and paracrine effects that create a complex milieu within the periprosthetic space, which ultimately governs the development of osteolysis. Chronic cell activation may upset the delicate balance between bone formation and bone resorption leading to periprosthetic osteolysis. This article summarizes the genetic mechanisms underlying periprosthetic loosening and identifies potential therapeutic agents.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.843

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.101
GPT teacher head0.306
Teacher spread0.205 · 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