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Record W2528813446 · doi:10.1002/adma.201602763

Gold Nanorods, DNA Origami, and Porous Silicon Nanoparticle‐functionalized Biocompatible Double Emulsion for Versatile Targeted Therapeutics and Antibody Combination Therapy

2016· article· en· W2528813446 on OpenAlexaff
Feng Kong, Hongbo Zhang, Xiangmeng Qu, Xu Zhang, Dong Chen, Ruihua Ding, Ermei Mäkilä, Jarno Salonen, Hélder A. Santos, Mingtan Hai

Bibliographic record

VenueAdvanced Materials · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCape Breton University
FundersEuropean Research CouncilChina Scholarship CouncilAcademy of FinlandJane ja Aatos Erkon SäätiöNational Science Foundation
KeywordsNanotechnologyPhotothermal therapyBiocompatible materialMaterials scienceNanorodNanoparticleColloidal goldEmulsionChemistryBiomedical engineeringMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Gold nanorods, DNA origami, and porous silicon nanoparticle-functionalized biocompatible double emulsion are developed for versatile molecular targeted therapeutics and antibody combination therapy. This advanced photothermal responsive all-in-one biocompatible platform can be easily formed with great therapeutics loading capacity for different cancer treatments with synergism and multidrug resistance inhibition, which has great potential in advancing biomedical applications. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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 score0.017
Threshold uncertainty score0.526

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 head0.015
GPT teacher head0.294
Teacher spread0.279 · 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

Citations68
Published2016
Admission routes1
Has abstractyes

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