Cancer cell viscoelasticity measurement by quantitative phase and flow stress induction.

Cell viscoelastic properties are affected by the cell cycle, differentiation, and pathological processes such as malignant transformation. Therefore, evaluation of the mechanical properties of the cells proved to be an approach to obtaining information on the functional state of the cells. Most of the currently used methods for cell mechanophenotyping are limited by low robustness or the need for highly expert operation. In this paper, the system and method for viscoelasticity measurement using shear stress induction by fluid flow is described and tested. Quantitative phase imaging (QPI) is used for image acquisition because this technique enables one to quantify optical path length delays introduced by the sample, thus providing a label-free objective measure of morphology and dynamics. Viscosity and elasticity determination were refined using a new approach based on the linear system model and parametric deconvolution. The proposed method allows high-throughput measurements during live-cell experiments and even through a time lapse, whereby we demonstrated the possibility of simultaneous extraction of shear modulus, viscosity, cell morphology, and QPI-derived cell parameters such as circularity or cell mass. Additionally, the proposed method provides a simple approach to measure cell refractive index with the same setup, which is required for reliable cell height measurement with QPI, an essential parameter for viscoelasticity calculation. Reliability of the proposed viscoelasticity measurement system was tested in several experiments including cell types of different Young/shear modulus and treatment with cytochalasin D or docetaxel, and an agreement with atomic force microscopy was observed. The applicability of the proposed approach was also confirmed by a time-lapse experiment with cytochalasin D washout, whereby an increase of stiffness corresponded to actin repolymerization in time.

Increasing the Image Contrast via Fast Fluorescence Photobleaching.

This paper focuses on the analysis of image sequences acquired during fast photobleaching using a standard wide-field microscope. We show that the photobleaching rate estimated for each pixel is not constant for the whole field of view, but it provides a new spatially variant parametric image related to the cell structure and diffusion of fluorophores. We also provide an alternative way to estimate a pixel-wise photobleaching rate with significantly less computation time than exponential model fitting.Clinical Relevance- This method provides an additional way how fluorescence photobleaching might be used for increasing the image contrast.

Parametric Deconvolution for Cancer Cells Viscoelasticity Measurements from Quantitative Phase Images.

In this contribution, we focused on optimising a dynamic flow-based shear stress system to achieve a reliable platform for cell shear modulus (stiffness) and viscosity assessment using quantitative phase imaging. The estimation of cell viscoelastic properties is influenced by distortion of the shear stress waveform, which is caused by the properties of the flow system components (i.e., syringe, flow chamber and tubing). We observed that these components have a significant influence on the measured cell viscoelastic characteristics. To suppress this effect, we applied a correction method utilizing parametric deconvolution of the flow system's optimized impulse response. Achieved results were compared with the direct fitting of the Kelvin-Voigt viscoelastic model and the basic steady-state model. The results showed that our novel parametric deconvolution approach is more robust and provides a more reliable estimation of viscosity with respect to changes in the syringe's compliance compared to Kelvin-Voigt model.

A Novel Gesture-Based Control System for Fluorescence Volumetric Data in Virtual Reality.

With the development of light microscopy, it is becoming increasingly easy to obtain detailed multicolor fluorescence volumetric data. The need for their appropriate visualization has become an integral part of fluorescence imaging. Virtual reality (VR) technology provides a new way of visualizing multidimensional image data or models so that the entire 3D structure can be intuitively observed, together with different object features or details on or within the object. With the need for imaging advanced volumetric data, demands for the control of virtual object properties are increasing; this happens especially for multicolor objects obtained by fluorescent microscopy. Existing solutions with universal VR controllers or software-based controllers with the need to define sufficient space for the user to manipulate data in VR are not usable in many practical applications. Therefore, we developed a custom gesture-based VR control system with a custom controller connected to the FluoRender visualization environment. A multitouch sensor disk was used for this purpose. Our control system may be a good choice for easier and more comfortable manipulation of virtual objects and their properties, especially using confocal microscopy, which is the most widely used technique for acquiring volumetric fluorescence data so far.

Self-supervised pretraining for transferable quantitative phase image cell segmentation.

In this paper, a novel U-Net-based method for robust adherent cell segmentation for quantitative phase microscopy image is designed and optimised. We designed and evaluated four specific post-processing pipelines. To increase the transferability to different cell types, non-deep learning transfer with adjustable parameters is used in the post-processing step. Additionally, we proposed a self-supervised pretraining technique using nonlabelled data, which is trained to reconstruct multiple image distortions and improved the segmentation performance from 0.67 to 0.70 of object-wise intersection over union. Moreover, we publish a new dataset of manually labelled images suitable for this task together with the unlabelled data for self-supervised pretraining.

Long-QT founder variant T309I-Kv7.1 with dominant negative pattern may predispose delayed afterdepolarizations under ß-adrenergic stimulation.

The variant c.926C > T (p.T309I) in KCNQ1 gene was identified in 10 putatively unrelated Czech families with long QT syndrome (LQTS). Mutation carriers (24 heterozygous individuals) were more symptomatic compared to their non-affected relatives (17 individuals). The carriers showed a mild LQTS phenotype including a longer QTc interval at rest (466 ± 24 ms vs. 418 ± 20 ms) and after exercise (508 ± 32 ms vs. 417 ± 24 ms), 4 syncopes and 2 aborted cardiac arrests. The same haplotype associated with the c.926C > T variant was identified in all probands. Using the whole cell patch clamp technique and confocal microscopy, a complete loss of channel function was revealed in the homozygous setting, caused by an impaired channel trafficking. Dominant negativity with preserved reactivity to ß-adrenergic stimulation was apparent in the heterozygous setting. In simulations on a human ventricular cell model, the dysfunction resulted in delayed afterdepolarizations (DADs) and premature action potentials under ß-adrenergic stimulation that could be prevented by a slight inhibition of calcium current. We conclude that the KCNQ1 variant c.926C > T is the first identified LQTS-related founder mutation in Central Europe. The dominant negative channel dysfunction may lead to DADs under ß-adrenergic stimulation. Inhibition of calcium current could be possible therapeutic strategy in LQTS1 patients refractory to ß-blocker therapy.