Model-Based Generation of Synthetic 3D Time-Lapse Sequences of Motile Cells with Growing Filopodia

International audienceThe existence of benchmark datasets is essential to objectively evaluate various image analysis methods. Nevertheless, manual annotations of fluorescence microscopy image data are very laborious and not often practicable, especially in the case of 3D+t experiments. In this work, we propose a simulation system capable of generating 3D time-lapse sequences of single motile cells with filopodial protrusions, accompanied by inherently generated ground truth. The system consists of three globally synchronized modules, each responsible for a separate task: the evolution of filopodia on a molecular level, linear elastic deformation of the entire cell with filopodia, and generation of realistic, time-coherent cell texture. The capability of our system is demonstrated by generating a synthetic 3D time-lapse sequence of a single lung cancer cell with two growing filopodia, visually resembling its real counterpart acquired using a confocal fluorescence microscope

Deep-learning-based segmentation of small extracellular vesicles in transmission electron microscopy images

Small extracellular vesicles (sEVs) are cell-derived vesicles of nanoscale size (~30-200 nm) that function as conveyors of information between cells, reflecting the cell of their origin and its physiological condition in their content. Valuable information on the shape and even on the composition of individual sEVs can be recorded using transmission electron microscopy (TEM). Unfortunately, sample preparation for TEM image acquisition is a complex procedure, which often leads to noisy images and renders automatic quantification of sEVs an extremely difficult task. We present a completely deep-learning-based pipeline for the segmentation of sEVs in TEM images. Our method applies a residual convolutional neural network to obtain fine masks and use the Radon transform for splitting clustered sEVs. Using three manually annotated datasets that cover a natural variability typical for sEV studies, we show that the proposed method outperforms two different state-of-the-art approaches in terms of detection and segmentation performance. Furthermore, the diameter and roundness of the segmented vesicles are estimated with an error of less than 10%, which supports the high potential of our method in biological applications.We want to acknowledge the support of NVIDIA Corporation with the donation of the Titan X (Pascal) GPU used for this research. This work was supported by the Spanish Ministry of Economy and Competitiveness (TEC2013-48552-C2-1-R, TEC2015-73064-EXP, TEC2016-78052-R) (EGM-AMB), a 2017 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (EGM-AMB), and the Czech Science Foundation (GA17-05048S)(MM-PM) and (GJ17-11776Y) (AK-VP)

Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis

Microfluidic devices are becoming mainstream tools to recapitulate in vitro the behavior of cells and tissues. In this study, we use microfluidic devices filled with hydrogels of mixed collagen-Matrigel composition to study the migration of lung cancer cells under different cancer invasion microenvironments. We present the design of the microfluidic device, characterize the hydrogels morphologically and mechanically and use quantitative image analysis to measure the migration of H1299 lung adenocarcinoma cancer cells in different experimental conditions. Our results show the plasticity of lung cancer cell migration, which turns from mesenchymal in collagen only matrices, to lobopodial in collagen-Matrigel matrices that approximate the interface between a disrupted basement membrane and the underlying connective tissue. Our quantification of migration speed confirms a biphasic role of Matrigel. At low concentration, Matrigel facilitates migration, most probably by providing a supportive and growth factor retaining environment. At high concentration, Matrigel slows down migration, possibly due excessive attachment. Finally, we show that antibody-based integrin blockade promotes a change in migration phenotype from mesenchymal or lobopodial to amoeboid and analyze the effect of this change in migration dynamics, in regards to the structure of the matrix. In summary, we describe and characterize a robust microfluidic platform and a set of software tools that can be used to study lung cancer cell migration under different microenvironments and experimental conditions. This platform could be used in future studies, thus benefitting from the advantages introduced by microfluidic devices: precise control of the environment, excellent optical properties, parallelization for high throughput studies and efficient use of therapeutic drugs.We would like to acknowledge the support of the Spanish Ministry of Economy and Competitiveness, under grants number DPI2012-38090-C03-02 and DPI2015-64221-C2-2-R (COS), TEC2013-48552-C2-1-R, TEC2016-78052-R, TEC2015-73064-EXP (AMB) and the Torres Quevedo program PTQ-11-04778 (RP); the Spanish Ministry of Health (FIS PI13/02313) (AR); the Czech Science Foundation, under grant number 302/12/G157 (MK, MMaška); and the European Research Council (ERC) through project ERC-2012-StG 306751 (JMGA)

Objective comparison of particle tracking methods

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers

Accelerating Live Single-Cell Signalling Studies.

The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state

Preoperative measurement of transformers - development of a new measuring the stand

Tato bakalářská práce pojednává o předprovozních měřeních na transformátorech, které mají být znovu zavedeny do provozu nebo výuky. Na transformátorech se dle ČSN EN 60076 má provádět diagnostika a měření, zjištění vnitřních zapojení vinutí, určení jmenovitých štítkových hodnot transformátorů, měření ztrát nakrátko a naprázdno, proudů naprázdno a napětí nakrátko. Z naměřených hodnot budou vypočteny náhradní parametry transformátorů. Na závěr práce bude provedeno vyhodnocení, jestli je možné uvedení nových standů do provozu nebo výuky.ObhájenoThis bachelor thesis discusses pre-operational measurement on the transformers. Those transformers might be stated as suitable for operation or education purposes according to standard ČSN EN 60076. Our transformers has to perform diagnostics and measurements according to ČSN EN 60076 such as detection winding connection of transformer, detection nominal values of transformer, open-circuit test, short-circuit test. Evaluation of the replacement parameters of the transformers from the measured values will be made. In the conclusion, the evaluation will be carried out if it possible to operate the transformers for operation or teaching

Optical pick-up of disc recording

Diplomová práce pojednává o bezkontaktním snímání gramofonového záznamu. Zabývá se dvěmi metodami a topoužitím laserového paprsku nebo CCD snímače pro snímání gramofonového záznamu. Zkoumá vhodnost použití průmyslové rastrové kamery s mikroobjektivem pro účely snímání gramofonové drážky. Práce dále pojednává o návrhu polohovacího zařízení pro polohování gramofonové desky a i pro polohování průmyslové kamery při snímání drážky. Další část se zabývá návrhem algoritmu pro snímání drážky, spojování snímků, extrakce audio stopy z pořízených snímku a jejího přehrávání. Zpracování snímků se provádí v prostředí MATLAB za využití algoritmů počítačového vidění. V neposlední řadě se práce zaměřuje na experimentální ověření detekce výrobních vad.ObhájenoThis thesis deals with the non-contact optical based methods of retrieving a phonograph record. It presents the use of the laser beam on a theoretical level, while the practical part concerns photographing of grooves using the raster industrial camera with micro-lenses. The following part of this paper is dedicated to the design of the structure of positioning devices for a gramophone record and the industrial camera. Next, an algorithm design for photographing grooves, merging images and sound extraction from the taken images, are presented. Processing of the data took place in a MATLAB using the computer vision technology. The final part of the thesis focuses on the experimental verification of detecting the manufacturing defects

Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs.

Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs