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Record W1963977788 · doi:10.1021/ar200017e

Lipoprotein-Inspired Nanoparticles for Cancer Theranostics

2011· review· en· W1963977788 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

VenueAccounts of Chemical Research · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNanocarriersLipoproteinCancerLDL receptorChemistryCancer cellDrug deliveryCancer researchNanotechnologyCholesterolPharmacologyMedicineBiochemistryInternal medicineMaterials science

Abstract

fetched live from OpenAlex

Over hundreds of millions of years, animals have evolved endogenous lipoprotein nanoparticles for shuttling hydrophobic molecules to different parts of the body. In the last 70 years, scientists have developed an understanding of lipoprotein function, often in relationship to lipid transport and heart disease. Such biocompatible, lipid-protein complexes are also ideal for loading and delivering cancer therapeutic and diagnostic agents, which means that lipoprotein and lipoprotein-inspired nanoparticles also offer opportunities for cancer theranostics. By mimicking the endogenous shape and structure of lipoproteins, the nanocarrier can remain in circulation for an extended period of time, while largely evading the reticuloendothelial cells in the body's defenses. The small size (less than 30 nm) of the low-density (LDL) and high-density (HDL) classes of lipoproteins allows them to maneuver deeply into tumors. Furthermore, lipoproteins can be targeted to their endogenous receptors, when those are implicated in cancer, or to other cancer receptors. In this Account, we review the field of lipoprotein-inspired nanoparticles related to the delivery of cancer imaging and therapy agents. LDL has innate cancer targeting potential and has been used to incorporate diverse hydrophobic molecules and deliver them to tumors. Nature's method of rerouting LDL in atherosclerosis provides a strategy to extend the cancer targeting potential of lipoproteins beyond its narrow purview. Although LDL has shown promise as a drug nanocarrier for cancer imaging and therapy, increasing evidence indicates that HDL, the smallest lipoprotein, may also be of use for drug targeting and uptake into cancer cells. We also discuss how synthetic HDL-like nanoparticles, which do not include human or recombinant proteins, can deliver molecules directly to the cytoplasm of certain cancer cells, effectively bypassing the endosomal compartment. This strategy could allow HDL-like nanoparticles to be used to deliver drugs that have increased activity in the cytoplasm. Lipoprotein nanoparticles have evolved to be ideal delivery vehicles, and because of that specialized function, they have the potential to improve cancer theranostics.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.864
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.130
GPT teacher head0.431
Teacher spread0.301 · 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