Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 788

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Duality of Iron Oxide Nanoparticles in Cancer Therapy: Amplification of Heating Efficiency by Magnetic Hyperthermia and Photothermal Bimodal Treatment

Espinosa, Ana, Di Corato, Riccardo, Kolosnjaj-Tabi, Jelena, Flaud, Patrice, Pellegrino, Teresa, Wilhelm, Claire·2016·ACS Nano

Abstract

The pursuit of innovative, multifunctional, more efficient, and safer treatments is a major challenge in preclinical nanoparticle-mediated thermotherapeutic research. Here, we report that iron oxide nanoparticles have the dual capacity to act as both magnetic and photothermal agents. We further explore every key aspect of this magnetophotothermal approach, choosing iron oxide nanocubes for their high efficiency for the magnetic hyperthermia modality itself. In aqueous suspension, the nanocubes' exposure to both: an alternating magnetic field and near-infrared laser irradiation (808 nm), defined as the DUAL-mode, amplifies the heating effect 2- to 5-fold by comparison with magnetic stimulation alone, yielding unprecedented heating powers (specific loss powers) up to 5000 W/g. In cancer cells, the laser excitation restores the optimal efficiency of magnetic hyperthermia, otherwise inhibited by intracellular confinement, resulting in a remarkable heating efficiency in the DUAL-mode (up to 15-fold amplification), with respect to the magnetophotothermal mode. As a consequence, the dual action yielded complete apoptosis-mediated cell death. In solid tumors in vivo, single-mode treatments (magnetic or laser hyperthermia) reduced tumor growth, while DUAL-mode treatment resulted in complete tumor regression, mediated by heat-induced tumoral cell apoptosis and massive denaturation of the collagen fibers, and a long-lasting thermal efficiency over repeated treatments.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acsnano.5b07249

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 788

Metadata

Authors
Espinosa, A., Di Corato, R., Kolosnjaj-Tabi, J., Flaud, P., Pellegrino, T., & Wilhelm, C.
Venue
ACS Nano
Published
2016-01-20
Volume
10
Issue
2
Pages
2436-2446
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2291888828
Cited by
788
References
54
FWCI
43.62
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.