Evidence map›Paper›PMID 32406215›Full record

ReviewJournal of biomedical optics2020

Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.

Rupsa Datta, Tiffany M Heaster, Joe T Sharick, Amani A Gillette, Melissa C Skala

Open access · goldAbstract readReview
In one paragraph

Review in Journal of biomedical optics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 398 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
398citing papers in PubMed, 1 pooled it
82.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

398 citing papers in PubMed, 1 synthesis or guideline pooled it, 812 citations in OpenAlex.

  1. Pooled it
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338 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Rupsa DattaMorgridge Institute for Research, Madison, Wisconsin, United States.
Tiffany M HeasterMorgridge Institute for Research, Madison, Wisconsin, United States.
Joe T SharickMorgridge Institute for Research, Madison, Wisconsin, United States.
Amani A GilletteMorgridge Institute for Research, Madison, Wisconsin, United States.
Melissa C SkalaMorgridge Institute for Research, Madison, Wisconsin, United States.
Morgridge Institute for Research · USUniversity of Wisconsin–Madison · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Christian Capitini · 1985 to 2026
$142.6M
Harnessing human brain and liver microphysiological systems for testing therapeutics for metastatic melanomaU01TR002383 · NCATS · VANDERBILT UNIVERSITY · PI MURPHY, WILLIAM L., TAYLOR, D. LANSING · 2018 to 2022
$7.6M
Optical imaging to predict cell-level genetic heterogeneity and treatment sensitivity in colorectal cancerR37CA226526 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI DEMING, DUSTIN A · 2018 to 2024
$4.2M
Optical imaging of pancreas cancer organoids for drug development and personalized treatmentR01CA211082 · NCI · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI SKALA, MELISSA CAROLINE · 2017 to 2021
$3.5M
(PQ7) Quantitative in vivo optical imaging of tumor heterogeneityR01CA205101 · NCI · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI SKALA, MELISSA CAROLINE · 2016 to 2020
$1.9M
Cellular-level Optical Metabolic Imaging to Predict Drug Response in CancerR01CA185747 · NCI · VANDERBILT UNIVERSITY · PI SKALA, MELISSA CAROLINE · 2014 to 2019
$1.6M
3D biomimetic image-based stromal models of pancreatic cancer for drug screeningR21CA224280 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI CAMPAGNOLA, PAUL J, SKALA, MELISSA CAROLINE · 2018 to 2019
$373k
NCATS NIH HHS U01 TR002383NCI NIH HHS P30 CA014520NCI NIH HHS R01 CA185747NCI NIH HHS R01 CA205101NCI NIH HHS R01 CA211082NCI NIH HHS R21 CA224280NCI NIH HHS R37 CA226526
6 · The paper itself

Abstract

significanceFluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy.

aimWe provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications. APPROACH: This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed.

conclusionsFLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments.

Indexed as

Fluorescence Resonance Energy TransferFluorescent DyesEnergy TransferMicroscopy, FluorescenceFluorescent Dyescell heterogeneityfluorescence lifetimeimage analysismicroscopyreview

Identifiers

PMID32406215
PMCPMC7219965
OpenAlexW3025520212

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.