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Record W2921368798 · doi:10.1039/c9nr01306g

Potentiating photodynamic therapy of ICG-loaded nanoparticles by depleting GSH with PEITC

2019· article· en· W2921368798 on OpenAlex
Hang Hu, Jitang Chen, Hai Yang, Xuetao Huang, Honglian Wu, Yuxin Wu, Fenfang Li, Yunfei Yi, Chen Xiao, Yihui Li, Yuxiang Tang, Zifu Li, Bixiang Zhang, Xiangliang Yang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNanoscale · 2019
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsPancreas Centre (Canada)
FundersNational Key Research and Development Program of ChinaHuazhong University of Science and TechnologyNational Natural Science Foundation of China
KeywordsPhotodynamic therapyPhenethyl isothiocyanateNanoparticleIndocyanine greenCancer researchChemistryMaterials scienceNanotechnologyMedicineCancerPathologyInternal medicine

Abstract

fetched live from OpenAlex

Photodynamic therapy (PDT) is a clinically approved cancer treatment which utilizes reactive oxygen species (ROS) to eradicate cancer cells. But the high concentration of GSH inside tumor cells can neutralize the generated ROS during PDT, resulting in an insufficient therapeutic effect. To address this issue, we combined ICG-loaded nanoparticles with PEITC for potent PDT. ICG encapsulated in novel hydroxyethyl starch-oleic acid conjugate (HES-OA) nanoparticles (∼50 nm) exhibited excellent stability and efficient singlet oxygen generation under laser irradiation, promoted cellular uptake, and enhanced tumor accumulation, whilst PEITC depleted intracellular GSH significantly. As a result, PDT based on ICG-loaded NPs combined with PEITC synergistically suppressed cancer cells both in vitro and in vivo. Potentiating ICG-loaded NPs with PEITC represents a novel and efficient strategy to enhance PDT efficacy.

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.

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 score0.003
Threshold uncertainty score0.723

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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