Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterization of microstructures fabricated by two-photon polymerization using coherent anti-stokes Raman scattering microscopy.

ABSTRACT: We demonstrate the possibility to image microstructures fabricated by two-photon polymerization (TPP) using coherent anti-Stokes Raman scattering (CARS) microscopy. The imaging contrast based on chemical selectivity attained by CARS microscopy is used to gather qualitative information on TPP. Upon the basis of detailed knowledge of the characteristic signatures of the photoresist Raman spectrum, quantitative relationships between laser writing conditions and polymer cross-linking are demonstrated. The increase in degree of polymer conversion as a function of laser average power follows a sigmoidal profile which is interpreted in terms of a simple model based on the polymerization mechanism of the photoresist.

SUBMITTER: Baldacchini T

PROVIDER: S-EPMC3972915 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Characterization of microstructures fabricated by two-photon polymerization using coherent anti-stokes Raman scattering microscopy.

Baldacchini Tommaso T Zimmerley Maxwell M Kuo Chun-Hung CH Potma Eric O EO Zadoyan Ruben R

The journal of physical chemistry. B 20090901 38

We demonstrate the possibility to image microstructures fabricated by two-photon polymerization (TPP) using coherent anti-Stokes Raman scattering (CARS) microscopy. The imaging contrast based on chemical selectivity attained by CARS microscopy is used to gather qualitative information on TPP. Upon the basis of detailed knowledge of the characteristic signatures of the photoresist Raman spectrum, quantitative relationships between laser writing conditions and polymer cross-linking are demonstrate ...[more]

PMID: 19715350

Similar Datasets

Coherent anti-Stokes Raman scattering microscopy of single nanodiamonds.

Project description:Nanoparticles have attracted enormous attention for biomedical applications as optical labels, drug-delivery vehicles and contrast agents in vivo. In the quest for superior photostability and biocompatibility, nanodiamonds are considered one of the best choices due to their unique structural, chemical, mechanical and optical properties. So far, mainly fluorescent nanodiamonds have been utilized for cell imaging. However, their use is limited by the efficiency and costs in reliably producing fluorescent defect centres with stable optical properties. Here, we show that single non-fluorescing nanodiamonds exhibit strong coherent anti-Stokes Raman scattering (CARS) at the sp(3) vibrational resonance of diamond. Using correlative light and electron microscopy, the relationship between CARS signal strength and nanodiamond size is quantified. The calibrated CARS signal in turn enables the analysis of the number and size of nanodiamonds internalized in living cells in situ, which opens the exciting prospect of following complex cellular trafficking pathways quantitatively.

| S-EPMC4990125 | biostudies-literature

Hyperspectral coherent anti-Stokes Raman scattering microscopy imaging through turbid medium.

Project description:Coherent Raman microspectroscopy imaging is an emerging technique for noninvasive, chemically specific optical imaging, which can be potentially used to analyze the chemical composition and its distribution in biological tissues. In this report, a hierarchical cluster analysis was applied to hyperspectral coherent anti-Stokes Raman imaging of different chemical species through a turbid medium. It was demonstrated that by using readily available commercial software (Cytospec, Inc.) and cluster analysis, distinct chemical species can be imaged and identified through a rather thick layer of scattering medium. Once the clusters of different chemical composition were distinguished, a phase retrieval algorithm was used to convert coherent anti-Stokes Raman spectra to Raman spectra, which were used for chemical identification of hidden microscopic objects. In particular, applications to remote optical sensing of potential biological threats and to imaging through a layer of skin tissue were successfully demonstrated.

| S-EPMC3056314 | biostudies-other

Coherent anti-stokes Raman scattering (CARS) microscopy: a novel technique for imaging the retina.

Project description:PurposeTo image the cellular and noncellular structures of the retina in an intact mouse eye without the application of exogenous fluorescent labels using noninvasive, nondestructive techniques.MethodsFreshly enucleated mouse eyes were imaged using two nonlinear optical techniques: coherent anti-Stokes Raman scattering (CARS) and two-photon autofluorescence (TPAF). Cross sectional transverse sections and sequential flat (en face) sagittal sections were collected from a region of sclera approximately midway between the limbus and optic nerve. Imaging proceeded from the surface of the sclera to a depth of ?60 ?m.ResultsThe fluorescent signal from collagen fibers within the sclera was evident in the TPAF channel; the scleral collagen fibers showed no organization and appeared randomly packed. The sclera contained regions lacking TPAF and CARS fluorescence of ?3 to 15 ?m in diameter that could represent small vessels or scleral fibroblasts. Intense punctate CARS signals from the retinal pigment epithelial layer were of a size and shape of retinyl storage esters. Rod outer segments could be identified by the CARS signal from their lipid-rich plasma membranes.ConclusionsCARS microscopy can be used to image the outer regions of the mammalian retina without the use of a fluorescent dye or exogenously expressed recombinant protein. With technical advancements, CARS/TPAF may represent a new avenue for noninvasively imaging the retina and might complement modalities currently used in clinical practice.

| S-EPMC3643396 | biostudies-literature

Quantitative chemical imaging and unsupervised analysis using hyperspectral coherent anti-Stokes Raman scattering microscopy.

Project description:In this work, we report a method to acquire and analyze hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy images of organic materials and biological samples resulting in an unbiased quantitative chemical analysis. The method employs singular value decomposition on the square root of the CARS intensity, providing an automatic determination of the components above noise, which are retained. Complex CARS susceptibility spectra, which are linear in the chemical composition, are retrieved from the CARS intensity spectra using the causality of the susceptibility by two methods, and their performance is evaluated by comparison with Raman spectra. We use non-negative matrix factorization applied to the imaginary part and the nonresonant real part of the susceptibility with an additional concentration constraint to obtain absolute susceptibility spectra of independently varying chemical components and their absolute concentration. We demonstrate the ability of the method to provide quantitative chemical analysis on known lipid mixtures. We then show the relevance of the method by imaging lipid-rich stem-cell-derived mouse adipocytes as well as differentiated embryonic stem cells with a low density of lipids. We retrieve and visualize the most significant chemical components with spectra given by water, lipid, and proteins segmenting the image into the cell surrounding, lipid droplets, cytosol, and the nucleus, and we reveal the chemical structure of the cells, with details visualized by the projection of the chemical contrast into a few relevant channels.

| S-EPMC3889493 | biostudies-literature

Analysis of aquaporin-mediated diffusional water permeability by coherent anti-stokes Raman scattering microscopy.

Project description:Water can pass through biological membranes via two pathways: simple diffusion through the lipid bilayer, or water-selective facilitated diffusion through aquaporins (AQPs). Although AQPs play an important role in osmotic water permeability (P(f)), the role of AQPs in diffusional water permeability remains unclear because of the difficulty of measuring diffusional water permeability (P(d)). Here, we report an accurate and instantaneous method for measuring the P(d) of a single HeLa S3 cell using coherent anti-Stokes Raman scattering (CARS) microscopy with a quick perfusion device for H(2)O/D(2)O exchange. Ultra-high-speed line-scan CARS images were obtained every 0.488 ms. The average decay time constant of CARS intensities (τ(CARS)) for the external solution H(2)O/D(2)O exchange was 16.1 ms, whereas the intracellular H(2)O/D(2)O exchange was 100.7 ± 19.6 ms. To evaluate the roles of AQP in diffusional water permeability, AQP4 fused with enhanced green fluorescent protein (AQP4-EGFP) was transiently expressed in HeLa S3 cells. The average τ(CARS) for the intracellular H(2)O/D(2)O exchange in the AQP4-EGFP-HeLa S3 cells was 43.1 ± 15.8 ms. We also assessed the cell volume and the cell surface area to calculate P(d). The average P(d) values for the AQP4-EGFP-HeLa S3 cells and the control EGFP-HeLa S3 cells were 2.7 ± 1.0 × 10(-3) and 8.3 ± 2.6 × 10(-4) cm/s, respectively. AQP4-mediated water diffusion was independent of the temperature but was dependent on the expression level of the protein at the plasma membrane. These results suggest the possibility of using CARS imaging to investigate the hydrodynamics of single mammalian cells as well as the regulation of AQPs.

| S-EPMC3207164 | biostudies-literature

Bayesian Quantification for Coherent Anti-Stokes Raman Scattering Spectroscopy.

Project description:We propose a Bayesian statistical model for analyzing coherent anti-Stokes Raman scattering (CARS) spectra. Our quantitative analysis includes statistical estimation of constituent line-shape parameters, the underlying Raman signal, the error-corrected CARS spectrum, and the measured CARS spectrum. As such, this work enables extensive uncertainty quantification in the context of CARS spectroscopy. Furthermore, we present an unsupervised method for improving spectral resolution of Raman-like spectra requiring little to no a priori information. Finally, the recently proposed wavelet prism method for correcting the experimental artifacts in CARS is enhanced by using interpolation techniques for wavelets. The method is validated using CARS spectra of adenosine mono-, di-, and triphosphate in water, as well as equimolar aqueous solutions of d-fructose, d-glucose, and their disaccharide combination sucrose.

| S-EPMC7458428 | biostudies-literature

Label-free cellular imaging by broadband coherent anti-Stokes Raman scattering microscopy.

Project description:Raman microspectroscopy can provide the chemical contrast needed to characterize the complex intracellular environment and macromolecular organization in cells without exogenous labels. It has shown a remarkable ability to detect chemical changes underlying cell differentiation and pathology-related chemical changes in tissues but has not been widely adopted for imaging, largely due to low signal levels. Broadband coherent anti-Stokes Raman scattering (B-CARS) offers the same inherent chemical contrast as spontaneous Raman but with increased acquisition rates. To date, however, only spectrally resolved signals from the strong CH-related vibrations have been used for CARS imaging. Here, we obtain Raman spectral images of single cells with a spectral range of 600-3200 cm?¹, including signatures from weakly scattering modes as well as CH vibrations. We also show that B-CARS imaging can be used to measure spectral signatures of individual cells at least fivefold faster than spontaneous Raman microspectroscopy and can be used to generate maps of biochemical species in cells. This improved spectral range and signal intensity opens the door for more widespread use of vibrational spectroscopic imaging in biology and clinical diagnostics.

| S-EPMC2955349 | biostudies-other

Monitoring of lipid storage in Caenorhabditis elegans using coherent anti-Stokes Raman scattering (CARS) microscopy.

Project description:Better understanding of the fundamental mechanisms behind metabolic diseases requires methods to monitor lipid stores on single-cell level in vivo. We have used Caenorhabditis elegans as a model organism to demonstrate the limitations of fluorescence microscopy for imaging of lipids compared with coherent anti-Stokes Raman scattering (CARS) microscopy, the latter allowing chemically specific and label-free imaging in living organisms. CARS microscopy was used to quantitatively monitor the impact of genetic variations in metabolic pathways on lipid storage in 60 specimens of C. elegans. We found that the feeding-defective mutant pha-3 contained a lipid volume fraction one-third of that found in control worms. In contrast, mutants (daf-2, daf-4 dauer) with deficiencies in the insulin and transforming growth factors (IGF and TGF-beta) signaling pathways had lipid volume fractions that were 1.4 and 2 times larger than controls, respectively. This was observed as an accumulation of small-sized lipid droplets in the hypodermal cells, hosting as much as 40% of the total lipid volume in contrast to the 9% for the wild-type larvae. Spectral CARS microscopy measurements indicated that this is accompanied by a shift in the ordering of the lipids from gel to liquid phase. We conclude that the degree of hypodermal lipid storage and the lipid phase can be used as a marker of lipid metabolism shift. This study shows that CARS microscopy has the potential to become a sensitive and important tool for studies of lipid storage mechanisms, improving our understanding of phenomena underlying metabolic disorders.

| S-EPMC1976189 | biostudies-literature

Label-free evaluation of hepatic microvesicular steatosis with multimodal coherent anti-Stokes Raman scattering microscopy.

Project description:Hepatic microvesicular steatosis is a hallmark of drug-induced hepatotoxicity and early-stage fatty liver disease. Current histopathology techniques are inadequate for the clinical evaluation of hepatic microvesicular steatosis. In this paper, we explore the use of multimodal coherent anti-Stokes Raman scattering (CARS) microscopy for the detection and characterization of hepatic microvesicular steatosis. We show that CARS microscopy is more sensitive than Oil Red O histology for the detection of microvesicular steatosis. Computer-assisted analysis of liver lipid level based on CARS signal intensity is consistent with triglyceride measurement using a standard biochemical assay. Most importantly, in a single measurement procedure on unprocessed and unstained liver tissues, multimodal CARS imaging provides a wealth of critical information including the detection of microvesicular steatosis and quantitation of liver lipid content, number and size of lipid droplets, and lipid unsaturation and packing order of lipid droplets. Such information can only be assessed by multiple different methods on processed and stained liver tissues or tissue extracts using current standard analytical techniques. Multimodal CARS microscopy also permits label-free identification of lipid-rich non-parenchymal cells. In addition, label-free and non-perturbative CARS imaging allow rapid screening of mitochondrial toxins-induced microvesicular steatosis in primary hepatocyte cultures. With its sensitivity and versatility, multimodal CARS microscopy should be a powerful tool for the clinical evaluation of hepatic microvesicular steatosis.

| S-EPMC3511365 | biostudies-literature

Automated identification of subcellular organelles by coherent anti-stokes Raman scattering.

Project description:Coherent anti-Stokes Raman scattering (CARS) is an emerging tool for label-free characterization of living cells. Here, unsupervised multivariate analysis of CARS datasets was used to visualize the subcellular compartments. In addition, a supervised learning algorithm based on the "random forest" ensemble learning method as a classifier, was trained with CARS spectra using immunofluorescence images as a reference. The supervised classifier was then used, to our knowledge for the first time, to automatically identify lipid droplets, nucleus, nucleoli, and endoplasmic reticulum in datasets that are not used for training. These four subcellular components were simultaneously and label-free monitored instead of using several fluorescent labels. These results open new avenues for label-free time-resolved investigation of subcellular components in different cells, especially cancer cells.

| S-EPMC4017266 | 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