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Record W2141279134 · doi:10.1080/10731190600684041

Polymethylmethacrylate (PMMA) as an Embedding Medium Preserving Tissues and Foreign Materials Encroaching in Endovascular Devices

2006· article· en· W2141279134 on OpenAlexaff
Robert Guidoin, Ze Zhang, Yvan Douville, M.F. Baslé, F. Grizon, Г. Маринов, Christopher K. Zarins, A. P. Legrand, Randolph Guzman

Bibliographic record

VenueArtificial Cells Blood Substitutes and Biotechnology · 2006
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsSt. Boniface HospitalUniversité LavalUniversity of ManitobaHôpital Saint-François d'Assise
Fundersnot available
KeywordsEmbeddingMaterials sciencePolymethyl methacrylateBusinessComputer scienceComposite materialPolymerArtificial intelligence

Abstract

fetched live from OpenAlex

Problems of displacement, poor healing, degradation of the polymers and corrosion of the metallic frame in endovascular devices still require in-depth investigations. As the tissues and the foreign materials are in close contact, it is of paramount importance to efficiently investigate the interfaces between them. Inclusion in polymethymethacrylate (PMMA) permits us to obtain thin slides and preserve the capacity to perform the appropriate stainings. An AneuRx prosthesis was harvested in bloc with the surrounding tissues at the autopsy of a patient 25 months post deployment in a 5.7 cm diameter AAA and sectioned in the direction of the blood flow in two halves. A cross-section of the encapsulated distal segment together with the surrounding aneuryshmal sac was embedded in polymethylmethacrylate (PMMA). Further to complete polymerization, slices of the specimen were cut on a precision banding saw under coolant. They were affixed onto methacrylate slides with a UV cured adhesive. Binding and polishing were done on a numeric grinder and slices 25 to 30 microm in thickness were stained with toluidine blue prior to observation in light microscopy. Additional slices were prepared for scanning electron microscopy and X-ray energy dispersive spectrometry for determination of the elemental composition of the Nitinol stent. The aortic wall did not demonstrate complete integrity along with its circumference. Some areas of rupture were noted. The content of the sac was heavily shrunk and was mostly acellular. The walls of the device were very well encapsulated. The PMMA embedding permitted the polyester wall, the Nitinol wire and the collagen to keep in close contact. Scanning electron microscopy involved backscattered electrons and confirmed the corrosion the Nitinol wire at the boundary with living tissues. Based upon the results obtained, we believe that PMMA embedding is the most appropriate method to process endovascular devices for histological and material investigation. Needless to say, that paraffin embedding would have not been feasible for such a big size specimen involving different materials.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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