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Record W2232432829

Safety of plasma-based sterilization: surface modifications of polymeric medical devices induced by Sterrad and Plazlyte processes.

2002· article· en· W2232432829 on OpenAlexaff
Sophie Lerouge, Maryam Tabrizian, M. R. Wertheimer, R. Marchand, L’H. Yahia

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSterilization (economics)X-ray photoelectron spectroscopyPolymerMaterials scienceWettingContact angleScanning electron microscopeEthylene oxideChemical engineeringSurface modificationOxideComposite materialCopolymerMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

Plasma-based sterilization is a promising alternative to the use of pure ethylene oxide (EO), for low-temperature clinical sterilization of medical instruments and devices. However, few studies have been published that evaluate its safety in terms of possible damage to materials, particularly polymers. The objective of this work was to evaluate polymer surface modifications induced by commercial plasma-based sterilizers, in comparison with pure EO: Samples from 5 polymer-based devices were subjected to 1, 5, and 10 sterilization cycles by Sterrad-100, Plazlyte, and pure EO. Surface analysis was carried out by X-ray photoelectron spectroscopy (XPS), dynamic contact angle measurements (DCA), and scanning electron microscopy (SEM). Surface oxidation and wettability changes were observed on all samples sterilized by plasma-based techniques, the degree of modifications depending on the sterilizer (Sterrad, Plazlyte) and the type of polymer. Drastic changes of surface appearance were also observed by SEM on PVC samples sterilized by Plazlyte and by pure EO. Possible repercussions on safety are discussed.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.038
GPT teacher head0.245
Teacher spread0.207 · 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

Citations53
Published2002
Admission routes1
Has abstractyes

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