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Record W2067351990 · doi:10.2217/nnm.14.110

Designing A Better Theranostic Nanocarrier for Cancer Applications

2014· review· en· W2067351990 on OpenAlex
Trinh Nguyen, Amy Tekrony, Kristin Yaehne, David T. Cramb

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

VenueNanomedicine · 2014
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsNanocarriersLiposomeChorioallantoic membraneNanotechnologyFenestrationControlled releaseDrug carrierDrug deliveryChemistryPharmacologyMaterials scienceCancer researchMedicineAngiogenesis

Abstract

fetched live from OpenAlex

Nanocarriers show incredible potential in theranostic applications as they offer diagnostic capabilities along with the ability to encapsulate and protect drugs from degradation, be functionalized with targeting moieties and be designed with controlled release mechanisms. Most clinically approved nanocarrier drugs are liposomal formulations. As such, considerable research has been directed towards designing liposomal carriers that can release their payloads via exogenous or endogenous triggers. For triggered release to effectively increase drug bioavailability, nanocarriers must first accumulate at the tumor site via the enhanced retention and permeability effect. It has been demonstrated in the chicken embryo chorioallantoic membrane and murine xenografted models that nanoparticle surface charge and geometry, with respect to vascular endothelium fenestration size, drive this accumulation in angiogenic tissue.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.333
Teacher spread0.297 · 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