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Record W4220949514 · doi:10.1002/smll.202270050

Targeted Nanoparticle for Co‐delivery of HER2 siRNA and a Taxane to Mirror the Standard Treatment of HER2<b>+</b> Breast Cancer: Efficacy in Breast Tumor and Brain Metastasis (Small 11/2022)

2022· article· en· W4220949514 on OpenAlexaff
Worapol Ngamcherdtrakul, Daniel S. Bejan, William Cruz‐Muñoz, Moataz Reda, Husam Y. Zaidan, Natnaree Siriwon, Suphalak Khamruang Marshall, Ruijie Wang, Molly A. Nelson, Justin P. C. Rehwaldt, Joe W. Gray, Kullervo Hynynen, Wassana Yantasee

Bibliographic record

VenueSmall · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsTaxaneBreast cancerDocetaxelDrug deliveryMesoporous silicaCancer researchNanoparticleMedicineCancerMaterials scienceOncologyNanotechnologyInternal medicineChemistryMesoporous material

Abstract

fetched live from OpenAlex

Breast Cancer Treatment In article number 2107550, Wassana Yantasee and co-workers develop polymer-decorated mesoporous silica nanoparticles for HER2-positive breast cancer treatment. This patented versatile platform can co-deliver multiple therapeutic classes to ensure that they reach the target cells at the same time to fully realize their synergy. Illustrated herein are nanoparticles with three drug cargos: HER2 antibody, HER2 siRNA, and chemotherapeutic docetaxel.

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)0.001
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 score0.026
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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