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Record W3102265121 · doi:10.1002/adtp.202000196

VCAM‐1‐Targeted Gene Delivery Nanoparticles Localize to Inflamed Endothelial Cells and Atherosclerotic Plaques

2020· article· en· W3102265121 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

VenueAdvanced Therapeutics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsEndothelial stem cellContext (archaeology)VCAM-1EndotheliumGene deliveryTransfectionCancer researchChemistryMedicineCell biologyCell adhesionCellBiologyBiochemistryIn vitroGeneInternal medicine

Abstract

fetched live from OpenAlex

Abstract The ability to target nanoparticles to the dysfunctional endothelium may present a new and innovative therapy for cardiovascular disease. In this work, an anti‐inflammatory gene therapy nanoparticle targeted to VCAM‐1, a protein overexpressed by inflamed endothelial cells located within atherosclerotic plaque, is developed. Targeting is accomplished via a peptide‐grafted coating for the nanoparticles. Nanoparticle binding to VCAM‐1 is probed via surface plasmon resonance with imaging to determine kinetics and binding dynamics. Targeted nanoparticles are internalized by transfected inflamed primary endothelial cells more than nontargeted controls (80% vs 30% positive cells) under both static and dynamic flow conditions. The nanoparticles also bind specifically to VCAM‐1+ endothelial cells within atherosclerotic plaque from mouse models in both the aortic sinus and whole aorta. Taken together, this nanoparticle formulation may be an effective and specific strategy for anti‐inflammatory therapy within the context of atherosclerosis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.846

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)0.0000.000

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 head0.018
GPT teacher head0.240
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