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Record W2075754394 · doi:10.3390/ma1010025

Modulating the Release Kinetics of Paclitaxel from Membrane-Covered Stents Using Different Loading Strategies

2008· article· en· W2075754394 on OpenAlexafffund
Georg Sydow-Plum, Ziyad S. Haidar, Yahye Merhi, Maryam Tabrizian

Bibliographic record

VenueMaterials · 2008
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMontreal Heart InstituteMcGill University
FundersCanadian Institutes of Health ResearchFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsMembranePaclitaxelHyaluronic acidPolyethylene oxideMaterials scienceAdhesionChitosanViability assayChemical engineeringMonolayerExtended releaseChemistryPolymer chemistryBiophysicsBiomedical engineeringCellNanotechnologyComposite materialPharmacologySurgeryOrganic chemistryBiochemistryPolymerMedicine

Abstract

fetched live from OpenAlex

Membrane-covered Express2TM Monorail® stents composed of chitosan (CH) blended with polyethylene oxide (PEO) in 70:30% wt (CH-PEO) were coated with a monolayer of hyaluronic acid (HA). This significantly improved the resistance to platelet adhesion and demonstrated excellent mechanical properties, resisting the harsh conditions during stent crimping and subsequent inflation. CH-PEO/HA membrane was then combined with a paclitaxel (Pac) delivery system via three different approaches for comparison of release profiles of Pac. The activity of Pac in these systems was confirmed since its presence in the membrane significantly decreased cell viability of U937 macrophages. Presented results are promising for applications requiring different release patterns of hydrophobic drugs.

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

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 head0.061
GPT teacher head0.283
Teacher spread0.222 · 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 teacher head, 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

Citations6
Published2008
Admission routes2
Has abstractyes

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