Oxygenic Enrichment in Hybrid Ruthenium Sulfide Nanoclusters for an Optimized Photothermal Effect.
Houjuan ZhuZibiao LiEnyi YeDavid Tai LeongPublished in: ACS applied materials & interfaces (2021)
Transition-metal dichalcogenide (TMD)-based nanomaterials have been extensively explored for the photonic therapy. To the best of our knowledge, near-infrared (NIR) light is a requirement for the photothermal therapy (PTT) to achieve the feature of deep-tissue penetration, whereas no obvious absorption peaks existing in the NIR region for existing TMD nanomaterials limit their therapeutic efficacy. As one category of TMD nanomaterials, ruthenium sulfide-based nanomaterials have been less exploited in biomedical applications including tumor therapy so far. Here, we develop a facile biomineralization-assisted bottom-up strategy to synthesize oxygenic hybrid ruthenium sulfide nanoclusters (RuSx NCs) by regulating the oxygen amounts and sulfur defects for the optimized PTT. By regulating the increasing initial molar ratios of Ru to S, RuSx NCs with small sizes were endowed with increasing oxygen contents and sulfur defects, leading to the photothermal conversion efficiency (PCE) increasing from 32.8 to 41.9%, which were higher than that of most small-sized inorganic photothermal nanoagents. In contrast to commercial indocyanine green, these RuSx NCs exhibited higher photostability under NIR laser irradiation. The high PCE and superior photostability allowed RuSx NCs to effectively and completely ablate cancer cells. Thus, the proposed defect engineering strategy endows RuSx NCs with an excellent photothermal effect for the PTT of tumors of living mice, which also proves the potential of further exploring the properties of RuSx NCs for future biomedical applications.
Keyphrases
- photodynamic therapy
- drug release
- fluorescent probe
- cancer therapy
- drug delivery
- fluorescence imaging
- transition metal
- machine learning
- healthcare
- magnetic resonance
- sensitive detection
- magnetic resonance imaging
- high speed
- metabolic syndrome
- deep learning
- type diabetes
- risk assessment
- radiation induced
- mass spectrometry
- quantum dots
- soft tissue
- radiation therapy
- reduced graphene oxide
- climate change
- metal organic framework
- highly efficient
- cell therapy