Time lapse synchrotron IR chemical imaging for observing the acclimation of a single algal cell to CO2 treatment

AbstractAlgae are the main primary producers in aquatic environments and therefore of fundamental importance for the global ecosystem. Mid-infrared (IR) microspectroscopy is a non-invasive tool that allows in principle studying chemical composition on a single-cell level. For a long time, however, mid-infrared (IR) imaging of living algal cells in an aqueous environment has been a challenge due to the strong IR absorption of water. In this study, we employed multi-beam synchrotron radiation to measure time-resolved IR hyperspectral images of individual Thalassiosira weissflogii cells in water in the course of acclimation to an abrupt change of CO2 availability (from 390 to 5000 ppm and vice versa) over 75 min. We used a previously developed algorithm to correct sinusoidal interference fringes from IR hyperspectral imaging data. After preprocessing and fringe correction of the hyperspectral data, principal component analysis (PCA) was performed to assess the spatial distribution of organic pools within the algal cells. Through the analysis of 200,000 spectra, we were able to identify compositional modifications associated with CO2 treatment. PCA revealed changes in the carbohydrate pool (1200–950 cm$$^{-1}$$ - 1 ), lipids (1740, 2852, 2922 cm$$^{-1}$$ - 1 ), and nucleic acid (1160 and 1201 cm$$^{-1}$$ - 1 ) as the major response of exposure to elevated CO2 concentrations. Our results show a local metabolism response to this external perturbation.

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Estimating and correcting interference fringes in infrared spectra in infrared hyperspectral imaging

The Analyst ◽

10.1039/c8an00093j ◽

2018 ◽

Vol 143 (19) ◽

pp. 4674-4683 ◽

Cited By ~ 5

Author(s):

Ghazal Azarfar ◽

Ebrahim Aboualizadeh ◽

Nicholas M. Walter ◽

Simona Ratti ◽

Camilla Olivieri ◽

...

Keyword(s):

Hyperspectral Imaging ◽

Infrared Spectra ◽

Correction Method ◽

Chemical Imaging ◽

Live Cell ◽

Aqueous Environment ◽

Imaging Data ◽

Interference Fringes ◽

Signal Correction

An algorithm based on EMSC (Extended Multiplicative Signal Correction) method is presented for removing fringes from live cell IR chemical imaging data in aqueous environment.

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Cleavage of Human Embryos: Options and Diversity

Acta Naturae ◽

10.32607/20758251-2016-8-3-88-96 ◽

2016 ◽

Vol 8 (3) ◽

pp. 88-96

Author(s):

Yu. K. Doronin ◽

I. V. Senechkin ◽

L. V. Hilkevich ◽

M. A. Kurcer

Keyword(s):

Time Lapse ◽

Reproductive Technologies ◽

Human Embryos ◽

Imaging Data ◽

Noninvasive Methods ◽

Topographic Features ◽

Time Parameters ◽

Embryo Cleavage ◽

Time Lapse Imaging ◽

Developmental Dynamics

In order to estimate the diversity of embryo cleavage relatives to embryo progress (blastocyst formation), time-lapse imaging data of preimplantation human embryo development were used. This retrospective study is focused on the topographic features and time parameters of the cleavages, with particular emphasis on the lengths of cleavage cycles and the genealogy of blastomeres in 2- to 8-cell human embryos. We have found that all 4-cell human embryos have four developmental variants that are based on the sequence of appearance and orientation of cleavage planes during embryo cleavage from 2 to 4 blastomeres. Each variant of cleavage shows a strong correlation with further developmental dynamics of the embryos (different cleavage cycle characteristics as well as lengths of blastomere cycles). An analysis of the sequence of human blastomere divisions allowed us to postulate that the effects of zygotic determinants are eliminated as a result of cleavage, and that, thereafter, blastomeres acquire the ability of own syntheses, regulation, polarization, formation of functional contacts, and, finally, of specific differentiation. This data on the early development of human embryos obtained using noninvasive methods complements and extend our understanding of the embryogenesis of eutherian mammals and may be applied in the practice of reproductive technologies.

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ИЗУЧЕНИЕ СТРУКТУРЫ ДНК В ПЛЕНКАХ МЕТОДОМ ИК-ФУРЬЕ-СПЕКТРОСКОПИИ

Биофизика ◽

10.31857/s0006302920060034 ◽

2020 ◽

Vol 65 (6) ◽

pp. 1058-1064

Author(s):

С.В. Пастон ◽

◽

А.М. Поляничко ◽

О.В. Шуленина ◽

Д.Н. Осинникова ◽

...

Keyword(s):

Molecular Weight ◽

Hydration Shell ◽

Aqueous Environment ◽

Ir Absorption ◽

Sodium Ions ◽

High Molecular Weight Dna ◽

Dna Hydration ◽

Na Ions ◽

Phosphate Groups ◽

Dna Film

The aqueous environment and ionic surrounding are the most important factors determining the conformation of DNA and its functioning in the cell. The specificity of the interaction between DNA and cations is especially pronounced with a decrease in water activity. In this work, we studied the B-A transition in high molecular weight DNA with a decrease of humidity in the film with different contents of Na+ ions using FTIR spectroscopy. The IR spectrum of DNA is not only very sensitive to the state of its secondary structure, but also allows us to estimate the amount of water bound to DNA. Upon dehydration of the DNA film, changes characteristic of the B-A transition were observed in the IR absorption spectrum. Using thermogravimetric analysis, it was shown that the degree of DNA hydration reaches the saturation level at a relative humidity of 60% and decreases slightly upon further drying. It has been established that with increasing Na+ concentration, the amount of water strongly bound to DNA decreases. Along with it, sodium ions destroy the hydration shell of DNA and are able to interact directly with phosphate groups.

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Unsupervised Identification of Targeted Spectra Applying Rank1-NMF and FCC Algorithms in Long-Wave Hyperspectral Infrared Imagery

Remote Sensing ◽

10.3390/rs13112125 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2125

Author(s):

Bardia Yousefi ◽

Clemente Ibarra-Castanedo ◽

Martin Chamberland ◽

Xavier P. V. Maldague ◽

Georges Beaudoin

Keyword(s):

Matched Filter ◽

Principal Component ◽

Hyperspectral Data ◽

Clustering Methods ◽

Spectral Angle Mapper ◽

Long Wave ◽

Clustering Approach ◽

Spectral Comparison ◽

Computational Simplicity ◽

Mineral Identification

Clustering methods unequivocally show considerable influence on many recent algorithms and play an important role in hyperspectral data analysis. Here, we challenge the clustering for mineral identification using two different strategies in hyperspectral long wave infrared (LWIR, 7.7–11.8 μm). For that, we compare two algorithms to perform the mineral identification in a unique dataset. The first algorithm uses spectral comparison techniques for all the pixel-spectra and creates RGB false color composites (FCC). Then, a color based clustering is used to group the regions (called FCC-clustering). The second algorithm clusters all the pixel-spectra to directly group the spectra. Then, the first rank of non-negative matrix factorization (NMF) extracts the representative of each cluster and compares results with the spectral library of JPL/NASA. These techniques give the comparison values as features which convert into RGB-FCC as the results (called clustering rank1-NMF). We applied K-means as clustering approach, which can be modified in any other similar clustering approach. The results of the clustering-rank1-NMF algorithm indicate significant computational efficiency (more than 20 times faster than the previous approach) and promising performance for mineral identification having up to 75.8% and 84.8% average accuracies for FCC-clustering and clustering-rank1 NMF algorithms (using spectral angle mapper (SAM)), respectively. Furthermore, several spectral comparison techniques are used also such as adaptive matched subspace detector (AMSD), orthogonal subspace projection (OSP) algorithm, principal component analysis (PCA), local matched filter (PLMF), SAM, and normalized cross correlation (NCC) for both algorithms and most of them show a similar range in accuracy. However, SAM and NCC are preferred due to their computational simplicity. Our algorithms strive to identify eleven different mineral grains (biotite, diopside, epidote, goethite, kyanite, scheelite, smithsonite, tourmaline, pyrope, olivine, and quartz).

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EXPRESS: Design Considerations for Discrete Frequency Infrared Microscopy Systems

Applied Spectroscopy ◽

10.1177/00037028211013372 ◽

2021 ◽

pp. 000370282110133

Author(s):

Rohit Bhargava ◽

Yamuna Dilip Phal ◽

Kevin Yeh

Keyword(s):

Imaging System ◽

Chemical Imaging ◽

Optical Component ◽

Imaging Systems ◽

Imaging Data ◽

Discrete Frequency ◽

Figures Of Merit ◽

Design Considerations ◽

Hardware Implementations ◽

Measurement Capabilities

Discrete frequency infrared (DFIR) chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, considerations in the design of all-IR microscopes have not yet been compiled. Here we describe the evolution of IR microscopes, provide rationales for design choices, and the major considerations for each optical component that together comprise an imaging system. We analyze design choices in illustrative examples that use these components to optimize performance, under their particular constraints. We then summarize a framework to assess the factors that determine an instrumentâs performance mathematically. Finally, we summarize the design and analysis approach by enumerating performance figures of merit for spectroscopic imaging data that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.

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Effective processing and evaluation of chemical imaging data with respect to morphological features of the zebrafish embryo

Analytical and Bioanalytical Chemistry ◽

10.1007/s00216-020-03131-4 ◽

2021 ◽

Author(s):

Katharina Halbach ◽

Timothy Holbrook ◽

Thorsten Reemtsma ◽

Stephan Wagner

Keyword(s):

Inductively Coupled Plasma ◽

Zebrafish Embryo ◽

Statistical Significance ◽

Software Tool ◽

Chemical Imaging ◽

Imaging Data ◽

Inductively Coupled ◽

Spatially Resolved ◽

Icp Ms ◽

Plasma Mass Spectrometry

AbstractA workflow was developed and implemented in a software tool for the automated combination of spatially resolved laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) data and data on the morphology of the biological tissue. Making use of a recently published biological annotation software, FishImager automatically assigns the biological feature as regions of interest (ROIs) and overlays them with the quantitative LA-ICP-MS data. Furthermore, statistical tools including cluster algorithms can be applied to the elemental intensity data and directly compared with the ROIs. This is effectively visualized in heatmaps. This allows gaining statistical significance on distribution and co-localization patterns. Finally, the biological functions of the assigned ROIs can then be easily linked with elemental distributions. We demonstrate the versatility of FishImager with quantitative LA-ICP-MS data of the zebrafish embryo tissue. The distribution of natural elements and xenobiotics is analyzed and discussed. With the help of FishImager, it was possible to identify compartments affected by toxicity effects or biological mechanisms to eliminate the xenobiotic. The presented workflow can be used for clinical and ecotoxicological testing, for example. Ultimately, it is a tool to simplify and reproduce interpretations of imaging LA-ICP-MS data in many applications. Graphical abstract

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Hyperspectral Image Classification with Localized Graph Convolutional Filtering

Remote Sensing ◽

10.3390/rs13030526 ◽

2021 ◽

Vol 13 (3) ◽

pp. 526

Author(s):

Shengliang Pu ◽

Yuanfeng Wu ◽

Xu Sun ◽

Xiaotong Sun

Keyword(s):

Hyperspectral Image ◽

Principal Component ◽

Representation Learning ◽

Classification Performance ◽

Hyperspectral Data ◽

Spectral Graph Theory ◽

Feature Reduction ◽

Graph Representation ◽

Novel Method ◽

Local Graph

The nascent graph representation learning has shown superiority for resolving graph data. Compared to conventional convolutional neural networks, graph-based deep learning has the advantages of illustrating class boundaries and modeling feature relationships. Faced with hyperspectral image (HSI) classification, the priority problem might be how to convert hyperspectral data into irregular domains from regular grids. In this regard, we present a novel method that performs the localized graph convolutional filtering on HSIs based on spectral graph theory. First, we conducted principal component analysis (PCA) preprocessing to create localized hyperspectral data cubes with unsupervised feature reduction. These feature cubes combined with localized adjacent matrices were fed into the popular graph convolution network in a standard supervised learning paradigm. Finally, we succeeded in analyzing diversified land covers by considering local graph structure with graph convolutional filtering. Experiments on real hyperspectral datasets demonstrated that the presented method offers promising classification performance compared with other popular competitors.

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Mid-Infrared Spectroscopy as a Rapid Tool to Qualitatively Predict the Effects of Species, Regions and Roasting on the Nutritional Composition of Australian Acacia Seed Species

Molecules ◽

10.3390/molecules26071879 ◽

2021 ◽

Vol 26 (7) ◽

pp. 1879

Author(s):

Oladipupo Q. Adiamo ◽

Yasmina Sultanbawa ◽

Daniel Cozzolino

Keyword(s):

Principal Component ◽

Nutritional Composition ◽

Human Consumption ◽

Mid Infrared ◽

Mir Spectroscopy ◽

As Species ◽

Before And After ◽

Mir Spectra ◽

Main Components ◽

Rapid Tool

In recent times, the popularity of adding value to under-utilized legumes have increased to enhance their use for human consumption. Acacia seed (AS) is an underutilized legume with over 40 edible species found in Australia. The study aimed to qualitatively characterize the chemical composition of 14 common edible AS species from 27 regions in Australia using mid-infrared (MIR) spectroscopy as a rapid tool. Raw and roasted (180 °C, 5, 7, and 9 min) AS flour were analysed using MIR spectroscopy. The wavenumbers (1045 cm−1, 1641 cm−1, and 2852–2926 cm−1) in the MIR spectra show the main components in the AS samples. Principal component analysis (PCA) of the MIR data displayed the clustering of samples according to species and roasting treatment. However, regional differences within the same AS species have less of an effect on the components, as shown in the PCA plot. Statistical analysis of absorbance at specific wavenumbers showed that roasting significantly (p < 0.05) reduced the compositions of some of the AS species. The results provided a foundation for hypothesizing the compositional similarity and/or differences among AS species before and after roasting.

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Characterization of Pharmaceutical Tablets Using UV Hyperspectral Imaging as a Rapid Line to Line Analysis Tool

Sensors ◽

10.3390/s21134436 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4436

Author(s):

Mohammad Al Ktash ◽

Mona Stefanakis ◽

Barbara Boldrini ◽

Edwin Ostertag ◽

Marc Brecht

Keyword(s):

Hyperspectral Imaging ◽

Large Scale ◽

Solid Phase ◽

Ultra Violet ◽

Principal Component ◽

Ccd Camera ◽

Conveyor Belt ◽

Hyperspectral Data ◽

Analysis Tool ◽

Sample Set

A laboratory prototype for hyperspectral imaging in ultra-violet (UV) region from 225 to 400 nm was developed and used to rapidly characterize active pharmaceutical ingredients (API) in tablets. The APIs are ibuprofen (IBU), acetylsalicylic acid (ASA) and paracetamol (PAR). Two sample sets were used for a comparison purpose. Sample set one comprises tablets of 100% API and sample set two consists of commercially available painkiller tablets. Reference measurements were performed on the pure APIs in liquid solutions (transmission) and in solid phase (reflection) using a commercial UV spectrometer. The spectroscopic part of the prototype is based on a pushbroom imager that contains a spectrograph and charge-coupled device (CCD) camera. The tablets were scanned on a conveyor belt that is positioned inside a tunnel made of polytetrafluoroethylene (PTFE) in order to increase the homogeneity of illumination at the sample position. Principal component analysis (PCA) was used to differentiate the hyperspectral data of the drug samples. The first two PCs are sufficient to completely separate all samples. The rugged design of the prototype opens new possibilities for further development of this technique towards real large-scale application.

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Optimisation of Magnification Levels for near Infrared Chemical Imaging of Blending of Pharmaceutical Powders

Journal of Near Infrared Spectroscopy ◽

10.1255/jnirs.730 ◽

2007 ◽

Vol 15 (3) ◽

pp. 137-151 ◽

Cited By ~ 12

Author(s):

Hua Ma ◽

Carl A. Anderson

Keyword(s):

Near Infrared ◽

Image Data ◽

Principal Component ◽

Chemical Imaging ◽

Field Of View ◽

Pharmaceutical Dosage Forms ◽

Component Distribution ◽

Circular Field ◽

Pharmaceutical Powder ◽

Magnification Level

A critical parameter in the evaluation of pharmaceutical dosage forms by hyperspectral imaging is the level of magnification. If the magnification (as set by the optical objective) is inadequate to resolve the relevant features, then the value of the imaging is diminished; if the magnification level is greater than is required, then the field of view is unnecessarily reduced. The purpose of this study was to determine an optimum magnification level for the study of powder mixing. Relevant features in this system include distribution of individual components within samples and the overall content of a given sample. In the present study, three magnification levels of near infrared (NIR) chemical imaging objectives were evaluated for their effects on imaging a blend of pharmaceutical materials (powders). High, medium and low objective magnification levels were investigated by comparing the resulting blend surface images of a two-component (salicylic acid and lactose) pharmaceutical powder mixture. Multiple images from high and medium magnification were concatenated so that an equivalent field of view was obtained for all magnification levels. Univariate images, principal component analysis score images, partial least squares predicted images and spectra extracted from different intensity regions in the area images were analysed qualitatively and quantitatively for comparison. A series of images spanning a strip across the centre of the circular field were collected at each magnification level and compared with respect to surface features elucidated and area of blend surface imaged. Analyses of images indicate that the three magnification levels delineate the component distribution for this particular powder system similarly. Images obtained at the low magnification level demonstrated adequate resolution and provided the broadest view of the blend surface. It is concluded that the low optical magnification level was adequate for the system being studied and is the preferred mode for pharmaceutical powder blend image data collection for this system.

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