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Record W3192670554 · doi:10.1021/acsnano.1c04510

Specific Endothelial Cells Govern Nanoparticle Entry into Solid Tumors

2021· article· en· W3192670554 on OpenAlexafffund
Benjamin R. Kingston, Zachary P. Lin, Ben Ouyang, Presley MacMillan, Jessica Ngai, Abdullah M. Syed, Shrey Sindhwani, Warren C. W. Chan

Bibliographic record

VenueACS Nano · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanadian Cancer Society
KeywordsTumor microenvironmentNanoparticleEndothelial stem cellCancer researchTumor cellsCell biologyChemistryNanotechnologyMaterials scienceBiophysicsMedicineBiologyIn vitroBiochemistry

Abstract

fetched live from OpenAlex

The successful delivery of nanoparticles to solid tumors depends on their ability to pass through blood vessels and into the tumor microenvironment. Here, we discovered a subset of tumor endothelial cells that facilitate nanoparticle transport into solid tumors. We named these cells nanoparticle transport endothelial cells (N-TECs). We show that only 21% of tumor endothelial cells located on a small number of vessels are involved in transporting nanoparticles into the tumor microenvironment. N-TECs have an increased expression of genes related to nanoparticle transport and vessel permeability compared to other tumor endothelial cells. The N-TECs act as gatekeepers that determine the entry point, distribution, cell accessibility, and number of nanoparticles that enter the tumor microenvironment.

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 score0.102
Threshold uncertainty score0.749

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 head0.006
GPT teacher head0.230
Teacher spread0.224 · 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

Citations127
Published2021
Admission routes2
Has abstractyes

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