AIMC Topic: Lipid Droplets
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Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy.
Nature communications
Jul 1, 2025
Metabolic homeostasis requires engagement of catabolic and anabolic pathways consuming nutrients that generate and consume energy and biomass. Our current understanding of cell homeostasis and metabolism, including how cells utilize nutrients, comes ...
Artificial intelligence-enabled lipid droplets quantification: Comparative analysis of NIS-elements Segment.ai and ZeroCostDL4Mic StarDist networks.
Methods (San Diego, Calif.)
Feb 27, 2025
Lipid droplets (LDs) are dynamic organelles that are present in almost all cell types, with a particularly high prevalence in adipocytes. The phenotype of LDs in these cells reflects their maturity, metabolic activity and function. Although LDs quant...
Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells.
Current opinion in cell biology
Feb 29, 2024
Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explore...
Automated quantification of vacuole fusion and lipophagy in from fluorescence and cryo-soft X-ray microscopy data using deep learning.
Autophagy
Oct 31, 2023
During starvation in the yeast vacuolar vesicles fuse and lipid droplets (LDs) can become internalized into the vacuole in an autophagic process named lipophagy. There is a lack of tools to quantitatively assess starvation-induced vacuole fusion and...
Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.
Nature cell biology
Dec 7, 2021
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...
Electron Microscope Tomography
COS Cells
Lipid Droplets
Refractometry
Cell Nucleolus
Subcellular Fractions
Actins
Cell Membrane
Optical Imaging
Mice
Cell Line, Tumor
Humans
Mitochondria
Single-Cell Analysis
Animals
Chlorocebus aethiops
HeLa Cells
Imaging, Three-Dimensional
HEK293 Cells
Deep Learning
Cell Nucleus
3T3 Cells
Deep learning classification of lipid droplets in quantitative phase images.
PloS one
Apr 5, 2021
We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing,...
Label-Free Tomographic Imaging of Lipid Droplets in Foam Cells for Machine-Learning-Assisted Therapeutic Evaluation of Targeted Nanodrugs.
ACS nano
Jan 10, 2020
Lipid droplet (LD) accumulation, a key feature of foam cells, constitutes an attractive target for therapeutic intervention in atherosclerosis. However, despite advances in cellular imaging techniques, current noninvasive and quantitative methods hav...
Evaluating adipocyte differentiation of bone marrow-derived mesenchymal stem cells by a deep learning method for automatic lipid droplet counting.
Computers in biology and medicine
Jul 22, 2019
Stem cells are a group of competent cells capable of self-renewal and differentiating into osteogenic, chondrogenic, and adipogenic lineages. These cells provide the possibility of successfully treating patients. During differentiation into adipose t...
Automated System for Small-Population Single-Particle Processing Enabled by Exclusive Liquid Repellency.
SLAS technology
Jun 10, 2019
Exclusive liquid repellency (ELR) describes an extreme wettability phenomenon in which a liquid phase droplet is completely repelled from a solid phase when exposed to a secondary immiscible liquid phase. Earlier, we developed a multi-liquid-phase op...
Deep-learning based flat-fielding quantitative phase contrast microscopy.
Optics express
Mar 25, 2024
Quantitative phase contrast microscopy (QPCM) can realize high-quality imaging of sub-organelles inside live cells without fluorescence labeling, yet it requires at least three phase-shifted intensity images. Herein, we combine a novel convolutional ...
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