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4 results for “Fluorescence lifetime imaging microscopy”

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zenodo48/100

Super-Resolved FRET Imaging by Confocal Fluorescence-Lifetime Single-Molecule Localization Microscopy

<p>FRET-based methods are a special tool for detecting interactions between (bio)molecules and their immediate environment. The spatial distribution of molecular interactions and functional states can be seen using FLIM (Fluorescence Lifetime IMaging) and FRET imaging. The spatial information, accuracy, and dynamic range of the observed signals are, however, constrained by the fact that conventional FLIM and FRET imaging only provides average information over an ensemble of molecules within a diffraction-limited volume. On the other hand, conventional Single Molecule Localization Microscopy (SMLM) relies on highly sensitive multi-pixel detectors (e.g. sCMOS or EM-CCD) whose time resolution is not suitable for fluorescence lifetime measurements.</p> <p>Here, we demonstrate a method for obtaining super-resolved FRET imaging using confocal fluorescence-lifetime single-molecule localization microscopy. The proof of concept was carried out using a DNA origami sample for performing DNA-PAINT measurements in combination with fluorogenic probes for reducing background signal. With this method, We show that FRET events separated by sub-diffraction distances can be distinguished based on lifetime modifications.</p>

opencc-by-4.0May 2023View details →
zenodo44/100

Insights into metabolic changes during epidermal differentiation as revealed by multiphoton microscopy with fluorescence lifetime imaging

<p>Rapid developments in the field of organotypic cultures has generated a growing need for effective quality control measures during tissue development. In this study, we correlate metabolic changes with epidermal differentiation and demonstrate that multiphoton microscopy with fluorescence lifetime imaging (MPM-FLIM) can be applied as a non-invasive approach to monitor epidermal differentiation of keratinocytes with respect to proliferative and differentiated states. &nbsp;Keratinocytes grown at 1.5 mM Ca2+ exhibited increased expression of differentiation markers KRT1 and KRT10 compared to 60 &mu;M Ca2+, and a metabolic shift from glycolysis to mitochondrial respiration. Fitting the fluorescence decay with a biexponential model revealed a decreased relative fraction of intracellular NADH and FAD after high calcium treatment, consistent with increased oxidative phosphorylation. Using these two parameters, the epidermal differentiation process could be monitored over a 96 h period. Implementing discriminating analysis based on k-means clustering generated clusters that correlated well with culturing time, suggesting that this methodology can be employed as part of an automated pipeline for monitoring keratinocyte differentiation.</p>

opencc-by-4.0May 2024View details →
zenodo40/100

Example of Fluorescence Lifetime Imaging Microscopy (FLIM) image stack in .ptu format

<p>The dataset is a 3D stack of fluorescence lifetime imaging microscopy (FLIM) images in ptu format to be used as test and training data. It contains the original .lif file (1) with the stack and a single plane image (to be opened using LAS X and LAS X SMD FLIM), exported raw FLIM data in .ptu format of the stack (3) and the single plane (2a) (to be opened in software capable of reading .ptu files) as well as an intensity image in .tif format (2b) of the single plane for a quick sample overview.</p> <p>The sample is a cross-section of hazel (<em>Corylus avellana</em>) &#39;diclinous male flower t.s.&#39; with Etzold staining provided by the company Zeiss (CZ 01/05). The dataset was generated using a Leica Stellaris 8 upright confocal laser scanning microscope using a 93x/1.4 glycerol immersion objective. Each image of the 65 slice stack with z step size of 0.287 &micro;m contains 512 x 512 pixels with a pixel size of 0.078 &micro;m x 0.078 &micro;m. Excitation was done with a white-light laser at 491 nm and a laser pulse rate of 40 MHz and a pixel dwell time of 2.0875 &micro;s. Images were acquired using a HyD X detector in counting mode in the spectral range of 496 to 739 nm using Leica Application Suite X (LAS X) version 4.4.0.24861 and LAS X SMD FLIM version 4.5.0 for FLIM image acquisition. 10 frames were accumulated per image. Metadata is available as text file (4a) and as metadata files from LAS X (4b).</p>

opencc-by-4.0Feb 2023View details →
zenodo36/100

Dataset related to article "Evaluation of cell metabolic adaptation in wound and tumour by fluorescence Lifetime imaging Microscopy"

<p>This record contains data related to article&nbsp;&quot;Evaluation of cell metabolic adaptation in wound and tumour by fluorescence Lifetime imaging Microscopy&quot;</p> <p>Abstract</p> <p>Acidic pH occurs in acute wounds progressing to healing as consequence of a cell metabolic adaptation in response to injury-induced tissue hypoperfusion. In tumours, high metabolic rate leads to acidosis affecting cancer progression. Acidic pH affects activities of remodelling cells in vitro. The pH measurement predicts healing in pathological wounds and success of surgical treatment of burns and chronic ulcers. However, current methods are limited to skin surface or based on detection of fluorescence intensity of specific sensitive probes that suffer of microenvironment factors. Herein, we ascertained relevance in vivo of cell metabolic adaptation in skin repair by interfering with anaerobic glycolysis. Moreover, a custom-designed skin imaging chamber, 2-Photon microscopy (2PM), fluorescence lifetime imaging (FLIM) and data mapping analyses were used to correlate maps of glycolytic activity in vivo as measurement of NADH intrinsic lifetime with areas of hypoxia and acidification in models of skin injury and cancer. The method was challenged by measuring the NADH profile by interfering with anaerobic glycolysis and oxidative phosphorylation in the mitochondrial respiratory chain. Therefore, intravital NADH FLIM represents a tool for investigating cell metabolic adaptation occurring in wounds, as well as the relationship between cell metabolism and cancer.</p>

opencc-by-4.0Jan 2021View details →

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