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1.
ACS Nano ; 2024 Aug 08.
Artículo en Inglés | MEDLINE | ID: mdl-39116033

RESUMEN

Monotherapy, especially the use of antibodies targeting vascular endothelial growth factor (VEGF), has shown limitations in treating choroidal neovascularization (CNV) since reactive oxygen species (ROS) also exacerbate CNV formation. Herein, we developed a combination therapy based on a DNA origami platform targeting multiple components of ocular neovascularization. Our study demonstrated that ocular neovascularization was markedly suppressed by intravitreal injection of a rectangular DNA origami sheet modified with VEGF aptamers (Ap) conjugated to an anti-VEGF antibody (aV) via matrix metalloproteinase (MMP)-cleavable peptide linkers in a mouse model of CNV. Typically, the DNA origami-based therapeutic platform selectively accumulates in neovascularization lesions owing to the dual-targeting ability of the aV and Ap, followed by the cleavage of the peptide linker by MMPs to release the antibody. Together, the released antibody and Ap inhibited VEGF activity. Moreover, the residual bare DNA origami could effectively scavenge ROS, reducing oxidative stress at CNV sites and thus maximizing the synergistic effects of inhibiting neovascularization.

2.
Anal Chem ; 96(23): 9684-9692, 2024 06 11.
Artículo en Inglés | MEDLINE | ID: mdl-38804540

RESUMEN

Herein, we report a DNA origami plasmonic nanoantenna for the programmable surface-enhanced Raman scattering (SERS) detection of cytokine release syndrome (CRS)-associated cytokines (e.g., tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ)) in cancer immunotherapy. Typically, the nanoantenna was made of self-assembled DNA origami nanotubes (diameter: ∼19 nm; length: ∼90 nm) attached to a silver nanoparticle-modified silicon wafer (AgNP/Si). Each DNA origami nanotube contains one miniature gold nanorod (AuNR) inside (e.g., length: ∼35 nm; width: ∼7 nm). Intriguingly, TNF-α and IFN-γ logically regulate the opening of the nanotubes and the dissociation of the AuNRs from the origami structure upon binding to their corresponding aptamers. On this basis, we constructed a complete set of Boolean logic gates that read cytokine molecules as inputs and return changes in Raman signals as outputs. Significantly, we demonstrated that the presented system enables the quantification of TNF-α and IFN-γ in the serum of tumor-bearing mice receiving different types of immunotherapies (e.g., PD1/PD-L1 complex inhibitors and STING agonists). The sensing results are consistent with those of the ELISA. This strategy fills a gap in the use of DNA origami for the detection of multiple cytokines in real systems.


Asunto(s)
Técnicas Biosensibles , Citocinas , ADN , Oro , Inmunoterapia , Nanopartículas del Metal , Espectrometría Raman , Animales , Ratones , ADN/química , Citocinas/metabolismo , Citocinas/sangre , Oro/química , Nanopartículas del Metal/química , Humanos , Plata/química , Nanotubos/química , Neoplasias , Interferón gamma/sangre , Interferón gamma/metabolismo , Factor de Necrosis Tumoral alfa/metabolismo , Factor de Necrosis Tumoral alfa/sangre
3.
iScience ; 26(10): 107821, 2023 Oct 20.
Artículo en Inglés | MEDLINE | ID: mdl-37731613

RESUMEN

Current gaseous sensors hardly discriminate trace volatile organic compounds at the ppt level. Herein, we present an integrated platform for simultaneously enabling rapid preconcentration, reliable surface-enhanced Raman scattering, (SERS) detection and automatic identification of trace aldehydes at the ppt level. For rapid preconcentration, we demonstrate that the nozzle-like microfluidic concentrator allows the enrichment of rare gaseous analytes by five-fold in only 0.01 ms. The enriched gas is subsequently captured and detected by an integrated silicon-based SERS chip, which is made of zeolitic imidazolate framework-8 coated silver nanoparticles grown in situ on a silicon wafer. After SERS measurement, a fully connected deep neural network is built to extract faint features in the spectral dataset and discriminate volatile organic compound classes. We demonstrate that six kinds of gaseous aldehydes at 100 ppt could be detected and classified with an identification accuracy of ∼80.9% by using this platform.

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