Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Locomotion of microspheres for super-resolution imaging.

ABSTRACT: Super-resolution virtual imaging by micron sized transparent beads (microspheres) was recently demonstrated by Wang et al. Practical applications in microscopy require control over the positioning of the microspheres. Here we present a method of positioning and controllable movement of a microsphere by using a fine glass micropipette. This allows sub-diffraction imaging at arbitrary points in three dimensions, as well as the ability to track moving objects. The results are relevant to a broad scope of applications, including sample inspection, microfabrication, and bio-imaging.

SUBMITTER: Krivitsky LA

PROVIDER: S-EPMC3863983 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Locomotion of microspheres for super-resolution imaging.

Krivitsky Leonid A LA Wang Jia Jun JJ Wang Zengbo Z Luk'yanchuk Boris B

Scientific reports 20131216

Super-resolution virtual imaging by micron sized transparent beads (microspheres) was recently demonstrated by Wang et al. Practical applications in microscopy require control over the positioning of the microspheres. Here we present a method of positioning and controllable movement of a microsphere by using a fine glass micropipette. This allows sub-diffraction imaging at arbitrary points in three dimensions, as well as the ability to track moving objects. The results are relevant to a broad sc ...[more]

PMID: 24336231

Similar Datasets

Super resolution for root imaging.

Project description:Premise:High-resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above-ground plant attributes. However, the acquisition of high-resolution images of plant roots is more challenging than above-ground data collection. An effective super-resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods:We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non-plant-root images, (ii) training with plant-root images, and (iii) pretraining the model with non-plant-root images and fine-tuning with plant-root images. The architectures of the SR models were based on two state-of-the-art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results:In our experiments, we observed that the SR models improved the quality of low-resolution images of plant roots in an unseen data set in terms of the signal-to-noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non-root data sets. Discussion:The incorporation of a deep learning-based SR model in the imaging process enhances the quality of low-resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal-to-noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

| S-EPMC7394708 | biostudies-literature

Dual-modal super-resolution ultrasound and NIR-II fluorescence imaging of ischemic stroke with ICG-doped porous PLGA microspheres.

Project description:Ischemic stroke, resulting from the obstruction of blood flow to the brain, remains a leading cause of morbidity and mortality worldwide. Traditional imaging modalities, such as magnetic resonance imaging and computed tomography, while effective for identifying stroke locations, are often limited in their ability to detect early pathological changes due to constraints in spatial resolution and sensitivity. This study introduces a novel dual-modal imaging approach that employs indocyanine green-doped porous poly (lactic-co-glycolic acid) (PLGA) microspheres (ICG-pPLGA MPs) for super-resolution ultrasound and near-infrared II (NIR-II) fluorescence imaging of ischemic stroke. The porous structure of ICG-pPLGA MPs enhances their stability, prolongs their circulation time, and improves ultrasound contrast compared to commercial lipid microbubbles. Additionally, the NIR-II fluorescence allows for high-resolution and noninvasive visualization of superficial vasculature. In a rat model of ischemic stroke, we demonstrate the capability of ICG-pPLGA MPs to achieve high-resolution imaging of cerebrovascular structures and functions, surpassing the imaging performance of standard diffusion-weighted imaging. Our findings underscore the potential of this dual-modal imaging technique using ICG-pPLGA MPs to accurately characterize microvascular changes during ischemic events, thus offering valuable insights for early diagnosis and therapeutic monitoring.

| S-EPMC11803314 | biostudies-literature

DrFLINC Contextualizes Super-resolution Activity Imaging.

Project description:Super-resolution activity imaging maps the biochemical architecture of living cells yet currently overlooks the locations of collaborating regulators/effectors. Building on the fluorescence fluctuation increase by contact (FLINC) principle, here we devise Dronpa-chromophore-removed FLINC (DrFLINC), where the nonfluorescent Dronpa can nevertheless enhance TagRFP-T fluorescence fluctuations. Exploiting DrFLINC, we develop a superior red label and a next-generation activity sensor for context-rich super-resolution biosensing.

| S-EPMC8575660 | biostudies-literature

Quantitative super-resolution imaging with qPAINT.

Project description:Counting molecules in complexes is challenging, even with super-resolution microscopy. Here, we use the programmable and specific binding of dye-labeled DNA probes to count integer numbers of targets. This method, called quantitative points accumulation in nanoscale topography (qPAINT), works independently of dye photophysics for robust counting with high precision and accuracy over a wide dynamic range. qPAINT was benchmarked on DNA nanostructures and demonstrated for cellular applications by quantifying proteins in situ and the number of single-molecule FISH probes bound to an mRNA target.

| S-EPMC4941813 | biostudies-literature

Multiplexed protein and drug imaging by super-resolution ion beam imaging

Project description:Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.

2021-05-25 | GSE141138 | GEO

Fast super-resolution imaging with ultra-high labeling density achieved by joint tagging super-resolution optical fluctuation imaging.

Project description:Previous stochastic localization-based super-resolution techniques are largely limited by the labeling density and the fidelity to the morphology of specimen. We report on an optical super-resolution imaging scheme implementing joint tagging using multiple fluorescent blinking dyes associated with super-resolution optical fluctuation imaging (JT-SOFI), achieving ultra-high labeling density super-resolution imaging. To demonstrate the feasibility of JT-SOFI, quantum dots with different emission spectra were jointly labeled to the tubulin in COS7 cells, creating ultra-high density labeling. After analyzing and combining the fluorescence intermittency images emanating from spectrally resolved quantum dots, the microtubule networks are capable of being investigated with high fidelity and remarkably enhanced contrast at sub-diffraction resolution. The spectral separation also significantly decreased the frame number required for SOFI, enabling fast super-resolution microscopy through simultaneous data acquisition. As the joint-tagging scheme can decrease the labeling density in each spectral channel, thereby bring it closer to single-molecule state, we can faithfully reconstruct the continuous microtubule structure with high resolution through collection of only 100 frames per channel. The improved continuity of the microtubule structure is quantitatively validated with image skeletonization, thus demonstrating the advantage of JT-SOFI over other localization-based super-resolution methods.

| S-EPMC4322366 | biostudies-literature

Super-Resolution Imaging Reveals Dynamic Reticular Cytoophidia.

Project description:CTP synthase (CTPS) can form filamentous structures termed cytoophidia in cells in all three domains of life. In order to study the mesoscale structure of cytoophidia, we perform fluorescence recovery after photobleaching (FRAP) and stimulated emission depletion (STED) microscopy in human cells. By using an EGFP dimeric tag as a tool to explore the physical properties of cytoophidia, we find that cytoophidia are dynamic and reticular. The reticular structure of CTPS cytoophidia may provide space for other components, such as IMPDH. In addition, we observe CTPS granules with tentacles.

| S-EPMC9569780 | biostudies-literature

Super-resolution label-free volumetric vibrational imaging.

Project description:Innovations in high-resolution optical imaging have allowed visualization of nanoscale biological structures and connections. However, super-resolution fluorescence techniques, including both optics-oriented and sample-expansion based, are limited in quantification and throughput especially in tissues from photobleaching or quenching of the fluorophores, and low-efficiency or non-uniform delivery of the probes. Here, we report a general sample-expansion vibrational imaging strategy, termed VISTA, for scalable label-free high-resolution interrogations of protein-rich biological structures with resolution down to 78 nm. VISTA achieves decent three-dimensional image quality through optimal retention of endogenous proteins, isotropic sample expansion, and deprivation of scattering lipids. Free from probe-labeling associated issues, VISTA offers unbiased and high-throughput tissue investigations. With correlative VISTA and immunofluorescence, we further validated the imaging specificity of VISTA and trained an image-segmentation model for label-free multi-component and volumetric prediction of nucleus, blood vessels, neuronal cells and dendrites in complex mouse brain tissues. VISTA could hence open new avenues for versatile biomedical studies.

| S-EPMC8206358 | biostudies-literature

Color-Coded Super-Resolution Small-Molecule Imaging.

Project description:Although the development of super-resolution microscopy dates back to 1994, its applications have been primarily focused on visualizing cellular structures and targets, including proteins, DNA and sugars. We now report on a system that allows both monitoring of the localization of exogenous small molecules in live cells at low resolution and subsequent super-resolution imaging by using stochastic optical reconstruction microscopy (STORM) on fixed cells. This represents a powerful new tool to understand the dynamics of subcellular trafficking associated with the mode and mechanism of action of exogenous small molecules.

| S-EPMC5291120 | biostudies-literature

Adaptive optics improves multiphoton super-resolution imaging.

Project description:We improve multiphoton structured illumination microscopy using a nonlinear guide star to determine optical aberrations and a deformable mirror to correct them. We demonstrate our method on bead phantoms, cells in collagen gels, nematode larvae and embryos, Drosophila brain, and zebrafish embryos. Peak intensity is increased (up to 40-fold) and resolution recovered (up to 176 ± 10 nm laterally, 729 ± 39 nm axially) at depths ∼250 μm from the coverslip surface.

| S-EPMC7749710 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data