MétaCan
Menu
Back to cohort
Record W1991204740 · doi:10.2174/157341310797575069

Nano- and Biotechnological Approaches in Current and Future Generation of Cardiovascular Stents

2010· article· en· W1991204740 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Nanoscience · 2010
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRestenosisStentDrug deliveryNanotechnologyAngioplastyMaterials scienceBiomedical engineeringMedicineCardiologyRadiology

Abstract

fetched live from OpenAlex

Drug eluting stents (DESs) have considerably reduced the occurrence of restenosis followed by balloon angioplasty. But the recent concerns of late stent thrombosis have rekindled an interest in developing an improved stent. A multidisciplinary approach of nanotechnology and biotechnology is the next frontier for this. This presents a comprehensive overview of the evolving nanobiotechnological approaches for biomedical implants and articulates the potential of these technologies to design the next generation stent. A diverse range of nano-delivery systems are being used to transport drugs, genes and oligonucleotides from the stent surface to remodel the damaged local vascular biology. In addition, the review encompasses the upcoming technologies which include modulation of the stent surface nano-topography by regulating the nanocoatings, use of nanotubes to increase the biocompatibility and promote endothelial cell proliferation, inhibit smooth muscle cell growth, and deliver 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.691

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.271
Teacher spread0.210 · 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