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Record W2521094228 · doi:10.1038/am.2016.146

Magnetic nanoparticle-promoted droplet vaporization for in vivo stimuli-responsive cancer theranostics

2016· article· en· W2521094228 on OpenAlex
Yang Zhou, Ronghui Wang, Zhaogang Teng, Zhigang Wang, Bing Hu, Michael C. Kolios, Hangrong Chen, Nan Zhang, Yanjie Wang, Pan Li, Wu Xing, Guangming Lu, Yu Chen, Yuanyi Zheng

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

VenueNPG Asia Materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsToronto Metropolitan University
FundersNational Key Research and Development Program of ChinaNational Science Foundation
KeywordsMaterials scienceVaporizationNanotechnologyIn vivoNanoparticleMagnetic nanoparticlesBiomedical engineeringCancerMagnetic resonance imagingIron oxide nanoparticlesMedicineRadiologyChemistry

Abstract

fetched live from OpenAlex

The development of efficient strategies for in vivo stimuli-responsive cancer treatment and personalized biomedicine is a great challenge. To overcome the critical issues and limitations of traditional protocols using acoustic droplet vaporization and optical droplet vaporization in stimuli-responsive tumor treatment, we herein report a new strategy, magnetic droplet vaporization (MDV), based on nanobiotechnology, for efficient magnetic field-responsive cancer theranostics. Perfluorohexane (PFH)-encapsulated superparamagnetic hollow iron oxide nanoparticles with a high magnetic-thermal energy transfer capability quickly respond to an external alternating current (a.c.) magnetic field to produce thermal energy and raise the temperature of the surrounding tumor tissue. The encapsulated PFH, with a desirable boiling point of ~56 °C, can be vaporized to enhance the performance of ultrasound imaging of tumors, as systematically demonstrated both in vitro and in vivo. The magnetic–thermal energy transfer further ablated and removed tumors in mice tumor xenograft models. This unique MDV principle with high versatility and performance is expected to broaden the biomedical applications of nanotechnology and promote clinical translations of intelligent diagnostic and therapeutic modalities, especially for battling cancer. Hollow iron nanoparticles can enhance both the imaging and complete removal of tumours in live mice using magnetically simulated heat. Ultrasound molecular imaging is one of the safest ways to track cancerous cell growth, but its success depends on producing gas-filled microbubbles that attach to the targeted tissue. As an alternative to optical or acoustic microbubble generators, Yu Chen from the Shanghai Institute of Ceramics, Yuanyi Zheng from Shanghai Sixth People's Hospital and colleagues have used superparamagnetic iron oxide probes with an encapsulated, low-boiling-point gas inside their nanoshells. After injecting the probes into breast cancer cells, the team applied a non-intrusive alternating-current magnetic field. This stimulus generated thermal energy that raised tissue temperature slightly, releasing numerous microbubbles through vapourization. The ultrasound-guided probes could then heat tumours sufficiently to stop regrowth using longer field exposure times. A novel magnetic droplet vaporization strategy was developed for efficient magnetic field-responsive cancer theranostics. Perfluorohexane (PFH)-encapsulated superparamagnetic hollow iron oxide nanoparticles with high magnetic-thermal energy transfer capability quickly respond to external alternating current (a.c.) magnetic field to produce thermal energy and raise the surrounding temperature of tumor tissue. The encapsulated PFH with desirable boiling point of about 56 °C can be vaporized to enhance the ultrasound imaging performance for responsive imaging. Such a magnetic–thermal energy transfer can further completely ablate and remove the tumor against a mice tumor xenograft model.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.005
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0050.000

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 head0.018
GPT teacher head0.268
Teacher spread0.251 · 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