skip to main content

Attention:

The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Thursday, June 13 until 2:00 AM ET on Friday, June 14 due to maintenance. We apologize for the inconvenience.


Search for: All records

Creators/Authors contains: "Nguyen, Trung Duc"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Two-photon excited fluorescence (TPEF) is a powerful technique that enables the examination of intrinsic retinal fluorophores involved in cellular metabolism and the visual cycle. Although previous intensity-based TPEF studies in non-human primates have successfully imaged several classes of retinal cells and elucidated aspects of both rod and cone photoreceptor function, fluorescence lifetime imaging (FLIM) of the retinal cells under light-dark visual cycle has yet to be fully exploited. Here we demonstrate a FLIM assay of photoreceptors and retinal pigment epithelium (RPE) that reveals key insights into retinal physiology and adaptation. We found that photoreceptor fluorescence lifetimes increase and decrease in sync with light and dark exposure, respectively. This is likely due to changes in all-trans-retinol and all-trans-retinal levels in the outer segments, mediated by phototransduction and visual cycle activity. During light exposure, RPE fluorescence lifetime was observed to increase steadily over time, as a result of all-trans-retinol accumulation during the visual cycle and decreasing metabolism caused by the lack of normal perfusion of the sample. Our system can measure the fluorescence lifetime of intrinsic retinal fluorophores on a cellular scale, revealing differences in lifetime between retinal cell classes under different conditions of light and dark exposure.

     
    more » « less
  2. Free, publicly-accessible full text available February 13, 2025
  3. Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

     
    more » « less
    Free, publicly-accessible full text available June 14, 2024
  4. Periasamy, Ammasi ; So, Peter T. ; König, Karsten (Ed.)
  5. Abstract

    Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termedflimGANE(fluorescencelifetimeimaging based onGenerativeAdversarialNetworkEstimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and thatflimGANEprovides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability,flimGANEis particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.

     
    more » « less