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تسجيل مستخدم جديدSmall Gold Nanorods with Tunable Absorption for Photothermal Microscopy in Cells
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Over the last decade, single-molecule optical microscopy has become the gold-standard approach to decipher complex molecular processes in cellular environments. [1-3] Single-molecule fluorescence microscopy has several advantages such as ease of application, high sensitivity, low invasiveness and versatility due the large number of available fluorescent probes. It bears however some drawbacks related to the poor photostability of organic dye molecules [4] and auto-fluorescent proteins [5-7] and and to the relatively large size of semiconductor nanoparticles in the context of live cell applications. [4,8,9] The overall size of the functional biomarkers is a general issue for any imaging approach because of steric hindrance effects in confined cell regions. Small red-shifted nano-emitters that are highly photostable are not currently available, while they would combine the best physical and optical penetration properties in biological tissues. Although single-molecule absorption microscopy was early used to detect single-molecules [10] at cryogenic temperatures, it is only with the advent of photothermal microscopy [11,12] that practical applications of absorption microscopy were developed in single-molecule research. Photothermal imaging (PhI)
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We investigate chemo-photothermal effects of gold nanorods (GNRs) coated using mesoporous silica (mSiO2) loading doxorubicin (DOX). When the mesoporous silica layer is embedded by doxorubicin drugs, a significant change in absorption spectra enable t
o quantify the drug loading. We carry out photothermal experiments on saline and livers of mice having GNRs@mSiO2 and GNRs@mSiO2-DOX. We also inject the gold nanostructures into many tumor-implanted mice and use laser illumination on some of them. By measuring weight and size of tumors, the distinct efficiency of photothermal therapy and chemotherapy on treatment is determined. We experimentally confirm the accumulation of gold nanostructures in liver.
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. In the ordered aggregates, there is lateral coupling which causes blueshifts in the plasmonic resonance, while in the random aggregates there are redshifts in the plasmonic resonance. The plasmon response of latter could be tailored up to the second infrared biological therapeutic window. It has been observed that the aggregates show higher absorption power and therefore, higher temperature rise compared to the single gold nanorod or monodispersive nanorods. The absorption resonance peak position of the random aggregate depends on the incident and polarization angles of the incident light. The aggregation of the nanoparticles often inherently occurs in the biological medium which affects the photothermal process. This study helps to understand the photothermal heating of nanoparticle aggregates and the use of the optimal light source concerning the absorption peak of the aggregates suspension for therapeutic uses.
In this Letter we show how a single beam optical trap offers the means for three-dimensional manipulation of semiconductor nanorods in solution. Furthermore rotation of the direction of the electric field provides control over the orientation of the
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Adherent cells exert traction forces on to their environment, which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures. This traction can be measured in a perturbation-free manner with traction force mi
croscopy (TFM). In TFM, traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular traction forces.
The role and importance of mechanical properties of cells and tissues in cellular function, development as well as disease has widely been acknowledged, however standard techniques currently used to assess them exhibit intrinsic limitations. Recently
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