Time-Lapse Microscopy

Collins, John Leslie; Knippenberg, Bart van; Ding, Kai; Kofman, Alexander

doi:10.5772/intechopen.81199

Cited by 5 publications

(6 citation statements)

References 284 publications

(263 reference statements)

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“…Real-time imaging of living cells is a very powerful and versatile tool to study the dynamics of biological processes. [1] Ectopic expression of chosen cellular proteins, fused to appropriate fluorescent tags, is an invaluable tool for tracking a range of intracellular events on a single cell basis. [1,2] For instance, key events of mitosis, such as chromosome segregation, have been studied using time-lapse fluorescence microscopy on mammalian cells stably expressing mCherry-tagged histone H2B.…”

Section: Introductionmentioning

confidence: 99%

Tracing endogenous proteins in living cells through electrotransfer of mRNA encoding chromobodies

Juncker,

Richert,

Masson

et al. 2023

Preprint

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Chromobodies made of nanobodies fused to fluorescent proteins are powerful tools for targeting and tracing intracellular proteins in living cells. Typically, this is achieved by transfecting plasmids encoding the chromobodies. However, an excess of unbound chromobody relative to the endogenous antigen can result in high background fluorescence in live cell imaging. Here, we overcome this problem by using mRNA encoding chromobodies. Our approach allows one to precisely control the amount of chromobody expressed inside the cell by adjusting the amount of transfected mRNA. To challenge our method, we evaluate three chromobodies targeting intracellular proteins of different abundance and cellular localization, namely lamin A/C, Dnmt1 and actin. We demonstrate that expression of chromobodies in living cells by transfection of tuned amounts of the corresponding mRNAs allows the accurate tracking of their cellular targets by time-lapse fluorescence microscopy.

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Section: Introductionmentioning

confidence: 99%

Tracing endogenous proteins in living cells through electrotransfer of mRNA encoding chromobodies

Juncker,

Richert,

Masson

et al. 2023

Preprint

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“…Furthermore, since single embryo transfer (SET) reduces the risk of multiple pregnancies and offers health advantages for the fetus and the mother, transferring the single best embryo is the safest approach possible and is recommended whenever possible [6][7][8]. Traditional embryo analysis based on morphological evaluation under a microscope is time-consuming, subjective, and leads to deterioration of optimal culture conditions when the embryo is removed from the incubator to be put under the microscope [9]. Although time-lapse imaging (TLI) systems for IVF are now available as an effective tool that allows the noninvasive analysis of embryos through continuous monitoring, the assessment made with TLI systems is still prone to human error [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

İnsan Embriyo Segmentasyonu için U-Net Tabanlı Modellerin Karşılaştırılması

UYSAL

YOZGATLI

YILDIZCAN

et al. 2022

Bilişim Teknolojileri Dergisi

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The quality of human embryos produced during in vitro fertilization is conventionally graded by clinical embryologists and this process is time-consuming and prone to human error. Artificial intelligence methods may be used to grade images captured by time-lapse microscopy (TLM). Segmentation of embryos from the background of TLM images is an essential step for embryo quality assessment as the background of the embryo has various artifacts which may mislead the grading algorithms. In this study, we performed a comparative analysis of automated day-5 human embryo (blastocyst) image segmentation methods based on deep learning. Four fully convolutional deep models, including U-Net and its three variants, were created using the combination of two gradient descent-based optimizers and two-loss functions and compared to our proposed model. The experimental results on the test set confirmed that our customized Dilated Inception U-Net model with Adam optimizer and Dice loss outperformed other U-Net variants with Dice coefficient, Jaccard index, accuracy, and precision of 98.68%, 97.52%, 99.20%, and 98.52%, respectively.

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“…However, fewer protocols exist to examine the earlier developmental stages, i.e., to determine whether drugs inhibit adherence and/or the intermediate phases of biofilm formation (Abdelmegeed & Shaaban, 2013;McCall, Pathirana, Prabhakar, Cullen, & Edgerton, 2019;Nagy et al, 2014). Time-lapse microscopy is the technique to capture a sequence of images at regular time intervals (Collins, van Knippenberg, Ding, & Kofman, 2019). Time-lapse microscopy has previously been used to examine the growth rate of biofilms qualitatively, by visually evaluating the effect of the drug (Kawai, Yamagishi, & Mikamo, 2017), or quantitatively, by measuring the thickness of biofilms grown in the presence of drug (Kaneko et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Time‐lapse microscopy is the technique to capture a sequence of images at regular time intervals (Collins, van Knippenberg, Ding, & Kofman, 2019). Time‐lapse microscopy has previously been used to examine the growth rate of biofilms qualitatively, by visually evaluating the effect of the drug (Kawai, Yamagishi, & Mikamo, 2017), or quantitatively, by measuring the thickness of biofilms grown in the presence of drug (Kaneko et al., 2013).…”

Section: Introductionmentioning

confidence: 99%

High‐Throughput Computational Analysis of Biofilm Formation from Time‐Lapse Microscopy

Salama

Gerstein

2021

Current Protocols

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Candida albicans biofilm formation in the presence of drugs can be examined through time-lapse microscopy. In many cases, the images are used qualitatively, which limits their utility for hypothesis testing. We employed a machinelearning algorithm implemented in the Orbit Image Analysis program to detect the percent area covered by cells from each image. This is combined with custom R scripts to determine the growth rate, growth asymptote, and time to reach the asymptote as quantitative proxies for biofilm formation. We describe stepby-step protocols that go from sample preparation for time-lapse microscopy through image analysis parameterization and visualization of the model fit.

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Time-Lapse Microscopy

Cited by 5 publications

References 284 publications

Tracing endogenous proteins in living cells through electrotransfer of mRNA encoding chromobodies

Tracing endogenous proteins in living cells through electrotransfer of mRNA encoding chromobodies

İnsan Embriyo Segmentasyonu için U-Net Tabanlı Modellerin Karşılaştırılması

High‐Throughput Computational Analysis of Biofilm Formation from Time‐Lapse Microscopy

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