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Effects of Heating Temperature and Duration by Gold Nanorod Mediated Plasmonic Photothermal Therapy on Copolymer Accumulation in Tumor Tissue

2015· article· en· W2333145985 on OpenAlexfundno aff
Nick Frazier, Ryan Robinson, Abhijit Ray, Hamidreza Ghandehari

Bibliographic record

VenueMolecular Pharmaceutics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Cancer InstituteNational Institutes of HealthHuntsman Cancer InstituteMcGill UniversityUniversity of Utah
KeywordsPhotothermal therapyCopolymerNanorodPhotothermal effectMethacrylamideBiophysicsPolymerChemistryMaterials scienceHyperthermiaChemical engineeringNanotechnologyOrganic chemistryAcrylamideMedicineInternal medicine

Abstract

fetched live from OpenAlex

Previously, water-soluble N-(2-hydroxypropyl)methacrylamide (HPMA) copolymers have been used with gold nanorod (GNR) mediated plasmonic photothermal therapy (PPTT) to induce hyperthermia (43 °C for 10 min) and have been shown to improve delivery of hydrophobic drugs to treat cancer. However, it was unknown how altering the heating parameters (temperature and duration) of PPTT would affect HPMA copolymer accumulation and retention. This study aimed to investigate how changes in heating parameters, or thermal dose, would change polymer accumulation profiles with PPTT. It was observed that temperatures of either 40, 43, 46, or 49 °C at durations of 10 or 30 min had significant effects on HPMA copolymer accumulation. Mild temperatures led to transient enhancement in accumulation, but more severe temperatures led to tissue and vascular damage, creating slowed dynamics of inflow and outflow of the polymers from the tumor tissue.

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 score0.009
Threshold uncertainty score0.666

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 head0.021
GPT teacher head0.303
Teacher spread0.282 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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