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Record W2782505166 · doi:10.1039/c7ra10155d

Tumor angiogenesis targeting and imaging using gold nanoparticle probe with directly conjugated cyclic NGR

2018· article· en· W2782505166 on OpenAlexaff
Minghao Wu, Yanyan Zhang, Ying Zhang, Mingjie Wu, Menglin Wu, Hongyi Wu, Lin Cao, Liang Li, Xue Li, Xuening Zhang

Bibliographic record

VenueRSC Advances · 2018
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsConjugated systemColloidal goldAngiogenesisNanoparticleNanotechnologyMaterials scienceChemistryCancer researchMedicinePolymer

Abstract

fetched live from OpenAlex

were further evaluated in a subcutaneous 4T1 xenograft model by CT imaging and immunohistochemistry study. These results showed that the GNPs-PEG@cNGR rapidly and specifically bound to the tumor vasculature after intravenous injection. Quantitative studies demonstrated that GNPs-PEG@cNGR showed significantly higher and faster tumor uptake after intravenous injection compared to unlabeled GNPs-PEG. Moreover, the distribution of tumor enhancement was consistent with the spatial distribution of angiogenic blood. These results suggest that the designed GNPs-PEG@cNGR probe may serve, in principle, as a promising CT contrast agent for targeted angiogenesis imaging and quantitative analysis.

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 score0.048
Threshold uncertainty score0.395

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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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