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Record W4301486543

Photothermal ablation of pancreatic cancer cells with hybrid iron-oxide core gold-shell nanoparticles

2013· article· en· W4301486543 on OpenAlexaboutno aff
Zilu Zhang, J Nicolai, D Procissi, Yingying Huan, Omary RA, Larson AC

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2013
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsnot available
Fundersnot available
KeywordsPhotothermal therapyColloidal goldMaterials scienceAblationNanoparticleNanotechnologyPancreatic cancerShell (structure)Iron oxideCore (optical fiber)CancerMedicineComposite materialMetallurgyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Yang Guo,1 Zhuoli Zhang,1 Dong-Hyun Kim,1,5 Weiguo Li,1 Jodi Nicolai,1 Daniel Procissi,1 Yi Huan,2 Guohong Han,3 Reed A Omary,1,4,5 Andrew C Larson1,4,5 1Department of Radiology, Northwestern University, Chicago, IL, USA; 2Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 3Department of Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 4Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA; 5Robert H Lurie Comprehensive Cancer Center, Chicago, IL, USA Purpose: Photothermal ablation is a minimally invasive approach, which typically involves delivery of photothermal sensitizers to targeted tissues. The purpose of our study was to demonstrate that gold nanoparticles are phagocytosed by pancreatic cancer cells, thus permitting magnetic resonance imaging (MRI) of sensitizer delivery and photothermal ablation. Patients and methods: Iron-oxide core/gold-shell nanoparticles (GoldMag®, 30 nm diameter; Xi'an GoldMag Biotechnology Co, Xi'an, People's Republic of China) were used. In a 96-well plate, 3 × 104 PANC-1 (human pancreatic cancer cell line) cells were placed. GoldMag (0, 25, or 50 µg/mL) was added to each well and 24 hours allowed for cellular uptake. Samples were then divided into two groups: one treated with photothermal ablation (7.9 W/cm2) for 5 minutes, the other not treated. Photothermal ablation was performed using laser system (BWF5; B&W Tek, Inc, Newark, DE, USA). Intraprocedural temperature changes were measured using a fiber optic temperature probe (FTP-LN2; Photon Control Inc, Burnaby, BC, Canada). After 24 hours, the remaining number of viable cells was counted using trypan blue staining; cell proliferation percentage was calculated based on the total number of viable cells after treatment compared with control. MRI of GoldMag uptake was performed using a 7.0T ClinScan system (Bruker BioSpin, Ettlingen, Germany). Results: Temperature curves demonstrated that with increased GoldMag uptake, laser irradiation produced higher temperature elevations in the corresponding samples; temperature elevations of 12.89°C, 35.16°C, and 79.51°C were achieved for 0, 25, and 50 µg/mL GoldMag. Without photothermal ablation, the cell proliferation percentage changed from 100% to 71.3% and 47.0% for cells treated with 25 and 50 µg/mL GoldMag. Photothermal ablation of PANC-1 cells demonstrated an effective treatment response, specifically a reduction to only 61%, 21.9%, and 2.3% cell proliferation for cells treated with 0, 25, and 50 µg/mL GoldMag. MRI was able to visualize GoldMag uptake within PANC-1 cells. Conclusion: Our findings suggest that photothermal ablation may be effective in the treatment of pancreatic cancer. GoldMag nanoparticles could serve as photothermal sensitizers, and MRI is feasible to quantify delivery. Keywords: photothermal ablation therapy, hybrid nanoparticles, magnetic resonance imaging

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.106
GPT teacher head0.418
Teacher spread0.312 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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