Improving FLIM Resolution with Mean-Shift Super-Resolution Microscopy, an analytical approach DOI
Mario González-Gutiérrez, Esley Torres, Adán Guerrero

et al.

Published: Nov. 15, 2023

Fluorescence Lifetime Imaging Microscopy (FLIM) is utilized to study the spatial distribution of fluorophores and assess molecular properties within cells or tissues. However, FLIM faces lifetime blurring due convolution fluorophore light with microscope's point spread function, diminishing resolution affecting distributions. In this research, we developed a model based on photophysical principles examine impact Mean-Shift Super-Resolution microscopy (MSSR) approach FLIM's resolution. Through simulations isolated lifetimes 1.0 3.0 ns, demonstrated that MSSR enhances beyond diffraction limit reduces blurring. Experimental validations will be beneficial further support these findings, potentially contributing increased accuracy in various medical biomedical imaging applications.

Language: Английский

Fluorescence Lifetime Imaging Techniques—A Review on Principles, Applications and Clinical Relevance DOI Creative Commons
Vladislav I. Shcheslavskiy, Marina V. Shirmanova, Konstantin Yashin

et al.

Journal of Biophotonics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

ABSTRACT This article gives an overview of the most frequently used fluorescence‐lifetime imaging (FLIM) techniques, their capabilities, and typical applications. Starting from a general introduction to fluorescence phosphorescence lifetime, we will show that lifetime or, more accurately, decay function fluorophore is direct indicator interaction with its molecular environment. FLIM therefore than simple contrast technique in microscopy—it imaging. techniques can be classified into time‐domain frequency‐domain analogue photon counting scanning wide‐field techniques. these technical principles describe features peculiarities different use. An extended section dedicated TCSPC FLIM, addressing unique capabilities make especially interesting biological systems.

Language: Английский

Citations

0
Development of AI-assisted microscopy frameworks through realistic simulation with pySTED DOI Creative Commons
Anthony Bilodeau,

Albert Michaud-Gagnon,

Julia Chabbert

et al.

Nature Machine Intelligence, Journal Year: 2024, Volume and Issue: 6(10), P. 1197 - 1215

Published: Sept. 26, 2024

Language: Английский

Citations

2
Measuring Metabolic Changes in Cancer Cells Using Two‐Photon Fluorescence Lifetime Imaging Microscopy and Machine‐Learning Analysis DOI Creative Commons
Jiaxin Zhang, Ulrike Wallrabe, Karsten H. Siller

et al.

Journal of Biophotonics, Journal Year: 2024, Volume and Issue: 18(1)

Published: Nov. 25, 2024

Two-photon (2P) fluorescence lifetime imaging microscopy (FLIM) was used to track cellular metabolism with drug treatment of auto-fluorescent coenzymes NAD(P)H and FAD in living cancer cells. Simultaneous excitation at 800 nm both compared traditional sequential 740/890 plus another alternative 740/800 nm, before after adding doxorubicin an time course. Changes redox states single cell resolution were by three analysis methods: our recently introduced ratio (FLIRR: NAD(P)H-a

Language: Английский

Citations

2
快速荧光寿命显微成像技术及其在活体应用的研究进展（特邀） DOI Open Access

林方睿 Lin Fangrui,

王义强 Wang Yiqiang,

易敏 Yi Min

et al.

Laser & Optoelectronics Progress, Journal Year: 2024, Volume and Issue: 61(6), P. 0618005 - 0618005

Published: Jan. 1, 2024

荧光寿命显微成像(FLIM)已经广泛应用于生命科学研究领域,具有高灵敏和高特异性的特点,在对组织微环境进行定量表征方面具有独特优势,但由于成像速度相对较慢,限制了FLIM的活体应用。近年来,随着光电子器件和人工智能等技术的发展,开启了FLIM活体成像新篇章。介绍通过优化硬件和算法两方面提升时域和频域FLIM技术的成像速度,以及其在生物医学基础研究和临床疾病诊断中的应用研究进展。最后,对活体FLIM成像的未来发展进行展望。

Citations

1
Deep learning-based virtual H& E staining from label-free autofluorescence lifetime images DOI Creative Commons
Qiang Wang, Ahsan R. Akram, David A. Dorward

et al.

npj Imaging, Journal Year: 2024, Volume and Issue: 2(1)

Published: June 28, 2024

Abstract Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence imaging microscopy (FLIM) can capture these enabling comprehensive analyses Despite fundamental importance and wide application FLIM biomedical clinical sciences, existing methods for analysing images often struggle to provide rapid precise interpretations without reliable references, such as histology images, which are usually unavailable alongside images. To address this issue, we propose deep learning (DL)-based approach generating virtual Hematoxylin Eosin (H&E) staining. By combining an advanced DL model with contemporary image quality metric, generate clinical-grade H&E-stained from label-free acquired on unstained tissue Our experiments also show that inclusion information, extra dimension beyond intensity, results more accurate reconstructions staining when compared using intensity-only This advancement allows instant interpretation at cellular level complexities associated co-registering Consequently, able identify distinct signatures seven different cell types commonly found tumour microenvironment, opening up new opportunities towards biomarker-free across multiple cancer types.

Language: Английский

Citations

1
Development of AI-assisted microscopy frameworks through realistic simulation in pySTED DOI Creative Commons
Anthony Bilodeau,

Albert Michaud-Gagnon,

Julia Chabbert

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 29, 2024

Abstract The integration of artificial intelligence (AI) into microscopy systems significantly enhances performance, optimizing both the image acquisition and analysis phases. Development AI-assisted super-resolution is often limited by access to large biological datasets, as well difficulties benchmark compare approaches on heterogeneous samples. We demonstrate benefits a realistic STED simulation platform, pySTED , for development deployment AI-strategies microscopy. environment provided allows augmentation data training deep neural networks, online optimization strategies, reinforcement learning models, that can be deployed successfully real microscope.

Language: Английский

Citations

0
A NIR-Fluorochrome for Live Cell Dual Emission and Lifetime Tracking from the First Plasma Membrane Interaction to Subcellular and Extracellular Locales DOI Creative Commons

Eden Booth,

Massimiliano Garrè, Dan Wu

et al.

Molecules, Journal Year: 2024, Volume and Issue: 29(11), P. 2474 - 2474

Published: May 24, 2024

Molecular probes with the ability to differentiate between subcellular variations in acidity levels remain important for investigation of dynamic cellular processes and functions. In this context, a series cyclic peptide PEG bio-conjugated dual near-infrared emissive BF2-azadipyrromethene fluorophores maxima emissions at 720 nm (at pH > 6) 790 < 5) have been developed their aqueous solution photophysical properties determined. Their inter-converting fluorescence lifetime characteristics were exploited track spatial temporal progression from first contact plasma membrane locales release within extracellular vesicles. A pH-dependent reversible phenolate/phenol interconversion on fluorophore controlled changes emission responses corresponding changes. Live-cell confocal microscopy experiments metastatic breast cancer cell line MDA-MB-231 confirmed usability imaging over prolonged periods. All three derivatives performed as capable real-time continuous fundamental such interaction, tracking endocytosis, lysosomal/large acidic vesicle accumulation, efflux vesicles without perturbing function. Furthermore, provided valuable insights regarding through intracellular microenvironments time. Overall, unique these show excellent potential use information-rich probes.

Language: Английский

Citations

0
FLIMPA: A versatile software for Fluorescence Lifetime Imaging Microscopy Phasor Analysis DOI Creative Commons
Sofia Kapsiani, Nino F. Läubli, Edward Ward

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

Abstract Fluorescence lifetime imaging microscopy (FLIM) is an advanced technique capable of providing a deeper understanding the molecular environment fluorophore. While FLIM data were traditionally analysed through exponential fitting fluorophores’ emission decays, use phasor plots increasingly becoming preferred standard. This due to their ability visualise distribution fluorescent lifetimes within sample, offering insights into interactions in sample without need for model assumptions regarding decay behaviour fluorophores. However, so far most researchers have had rely on commercial plot software packages, which are closed-source and proprietary formats. In this paper, we introduce FLIMPA, opensource, stand-alone analysis that provides many features found software, more. FLIMPA fully developed Python offers tools visualisation. It enhances comparison by integrating points from multiple trials experimental conditions single plot, while also possibility explore detailed, localised individual samples. We apply cell-based assay quantification microtubule depolymerisation, measured fluorescence changes SiR-tubulin, response various concentrations Nocodazole, depolymerising drug relevant anti-cancer treatment.

Language: Английский

Citations

0
The Quantitative In Vivo Assessment of Diabetic and Non‐Diabetic Skin Wound Healing Using Phasor‐FLIM Approach DOI
Hala Zuhayri,

Tatiana B. Lepekhina,

Viktor V. Nikolaev

et al.

Journal of Biophotonics, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 29, 2024

ABSTRACT A quantitative assessment of wound status in a murine model was developed using phasor plot presentation fluorescence lifetime imaging microscopy (FLIM) data. The is based on calculating Bhattacharyya distance between g coordinates FLIM data density distributions and healthy skin. approach validated for both diabetic non‐diabetic mice wounds, including during low‐dose photodynamic therapy (LDPDT). Analysis revealed shift the coordinates, suggesting altered metabolic processes involved healing. distances LDPDT groups were closer to zero compared control group, which not treated by LDPDT. that consistent with literature regarding positive role accelerating healing diabetes mellitus impairing

Language: Английский

Citations

0
Improving FLIM Resolution with Mean-Shift Super-Resolution Microscopy, an analytical approach DOI
Mario González-Gutiérrez, Esley Torres, Adán Guerrero

et al.

Published: Nov. 15, 2023

Fluorescence Lifetime Imaging Microscopy (FLIM) is utilized to study the spatial distribution of fluorophores and assess molecular properties within cells or tissues. However, FLIM faces lifetime blurring due convolution fluorophore light with microscope's point spread function, diminishing resolution affecting distributions. In this research, we developed a model based on photophysical principles examine impact Mean-Shift Super-Resolution microscopy (MSSR) approach FLIM's resolution. Through simulations isolated lifetimes 1.0 3.0 ns, demonstrated that MSSR enhances beyond diffraction limit reduces blurring. Experimental validations will be beneficial further support these findings, potentially contributing increased accuracy in various medical biomedical imaging applications.

Language: Английский

Citations

0