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1.
ACS Appl Mater Interfaces ; 16(7): 8554-8569, 2024 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-38323816

RESUMO

Optical imaging and spectroscopic modalities are of considerable current interest for in vivo cancer detection and image-guided surgery, but the turbid or scattering nature of biomedical tissues has severely limited their abilities to detect buried or occluded tumor lesions. Here we report the development of a dual-modality plasmonic nanostructure based on colloidal gold nanostars (AuNSs) for simultaneous surface-enhanced Raman scattering (SERS) and photoacoustic (PA) detection of tumor phantoms embedded (hidden) in ex vivo animal tissues. By using red blood cell membranes as a naturally derived biomimetic coating, we show that this class of dual-modality contrast agents can provide both Raman spectroscopic and PA signals for the detection and differentiation of hidden solid tumors with greatly improved depths of tissue penetration. Compared to previous polymer-coated AuNSs, the biomimetic coatings are also able to minimize protein adsorption and cellular uptake when exposed to human plasma without compromising their SERS or PA signals. We further show that tumor-targeting peptides (such as cyclic RGD) can be noncovalently inserted for targeting the ανß3-integrin receptors expressed on metastatic cancer cells and tracked via both SERS and PA imaging (PAI). Finally, we demonstrate image-guided resections of tumor-mimicking phantoms comprising metastatic tumor cells buried under layers of skin and fat tissues (6 mm in thickness). Specifically, PAI was used to determine the precise tumor location, while SERS spectroscopic signals were used for tumor identification and differentiation. This work opens the possibility of using these biomimetic dual-modality nanoparticles with superior signal and biological stability for intraoperative cancer detection and resection.


Assuntos
Nanopartículas Metálicas , Nanoestruturas , Neoplasias , Animais , Humanos , Meios de Contraste , Análise Espectral Raman/métodos , Biomimética , Neoplasias/diagnóstico por imagem , Imagem Óptica/métodos , Nanopartículas Metálicas/química
2.
Materials (Basel) ; 15(15)2022 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-35955311

RESUMO

Pipes are commonly used to transport fuels, air, water, gas, hydraulic power, and other fluid-like materials in engine rooms, houses, factories, airplanes, and ships. Thus, pipe routing is essential in many industrial applications, including ship construction, machinery manufacturing, house building, laying out engine rooms, etc. To be functional, a pipe system should be economical while satisfying spatial constraints and safety regulations. Numerous routing algorithms have been published to optimize the pipe length and the number of elbows. However, relatively few methods have been designed to lay out pipes which strictly meet the spatial constraints and safety regulations. This article proposes a distance-field-based piping algorithm to remedy this problem. The proposed method converts the workspace into a 3D image and computes a distance field upon the workspace first. It then creates a feasible space out of the workspace by peeling the distance field and segmenting the 3D image. The resultant feasible space is collision-free and satisfies the spatial constraints and safety regulations. In the following step, a path-finding process, subjected to a cost function, is triggered to arrange the pipe inside the feasible space. Consequently, the cost of the pipe is optimized, and the pipe path rigidly meets the spatial constraints and safety regulations. The proposed method works effectively even if the workspace is narrow and complicated. In three experiments, the proposed method is employed to lay out pipes inside an underwater vehicle, a machinery room, and a two-story house, respectively. Not only do the resultant pipes possess minimal costs, but they also meet the spatial constraints and safety regulations, as predicted. In addition to developing the routing procedure, we also design a visualization subsystem to reveal the progression of the piping process and the variation of the workspace in the run time. Based on the displayed images, users can therefore evaluate the quality of the pipes on the fly and tune the piping parameters if necessary.

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