Spectrometry Imaging Research Articles

Roadmap of Terahertz Imaging 2021.

In this roadmap article, we have focused on the most recent advances in terahertz (THz) imaging with particular attention paid to the optimization and miniaturization of the THz imaging systems. Such systems entail enhanced functionality, reduced power consumption, and increased convenience, thus being geared toward the implementation of THz imaging systems in real operational conditions. The article will touch upon the advanced solid-state-based THz imaging systems, including room temperature THz sensors and arrays, as well as their on-chip integration with diffractive THz optical components. We will cover the current-state of compact room temperature THz emission sources, both optolectronic and electrically driven; particular emphasis is attributed to the beam-forming role in THz imaging, THz holography and spatial filtering, THz nano-imaging, and computational imaging. A number of advanced THz techniques, such as light-field THz imaging, homodyne spectroscopy, and phase sensitive spectrometry, THz modulated continuous wave imaging, room temperature THz frequency combs, and passive THz imaging, as well as the use of artificial intelligence in THz data processing and optics development, will be reviewed. This roadmap presents a structured snapshot of current advances in THz imaging as of 2021 and provides an opinion on contemporary scientific and technological challenges in this field, as well as extrapolations of possible further evolution in THz imaging.

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry.

Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocessing and modeling methods of hyperspectral images obtained from an unmanned aerial vehicle (UAV) platform for estimating the soil organic matter (SOM) and soil total nitrogen (STN) in farmland. The results showed that: (1) Multiplicative Scattering Correction (MSC) performed better in reducing image scattering noise than Standard Normal Variate (SNV) transformation or spectral derivatives, and it yielded a result with higher correlation and lower signal-to-noise ratio; (2) The proposed feature selection method combining Successive Projections Algorithm (SPA) and Competitive Adaptive Reweighted Sampling algorithm (CARS), could provide selective preference for hyperspectral bands. Exploiting this method, 24 and 22 feature bands were selected for SOM and STN estimation, respectively; (3) The particle swarm optimization (PSO) algorithm was employed to obtain optimized input weights and bias values of the extreme learning machine (ELM) model for more accurate prediction of SOM and STN. The improved PSO-ELM model based on the selected preference bands achieved higher prediction accuracy (R2 of 0.73 and RPD of 1.91 for SOM, R2 of 0.63, and RPD of 1.53 for STN) than support vector machine (SVM), partial least squares regression (PLSR), and the ELM model. This study provides an important guideline for monitoring soil nutrient for precision agriculture with imaging spectrometry.

Facial Treatment with 3-O-Cetyl Ascorbic Acid for Improvement of Skin Texture: Uptake, Effectiveness, and In Vitro Carcinogenicity Assessment

Ascorbic acid (AA) is a water-soluble vitamin that is found at high concentrations in normal skin. The important and well-known benefits of using AA in skin health include the stimulation of collagen synthesis and the assistance of protection against photo-oxidative damages. To maintain stability and improve drug delivery to the active site, a variety of AA derivatives have been chemically synthesized. Among these compounds, we focus here on a lipophilic derivative, 3-O-cetyl ascorbic acid (3-CetylAA), which remains poorly characterized for cosmetic applications. Uptake analysis in three healthy human volunteers’ skin was conducted using a serial tape-stripping technique detecting 3-CetylAA (on average, 128 ± 27 pmol per µg) in the stratum corneum after a 5-h topical treatment when treated with 25 mM 3-CetylAA-containing cream for 13 days twice daily and continuously. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of vertical cryosections of pig skin revealed the presence of 3-CetylAA in the epidermal layer after topical treatment with 3-CetylAA-containing cream. In sun-exposed human skin, 3-CetylAA improved the texture after treatment with 25 mM 3-CetylAA-containing cream for 4 weeks or more when used twice daily or continuously. An in vitro transformation assay using BALB/c 3T3 A31-1-1 cells demonstrated that 10 µM 3-CetylAA, which is the same concentration exhibited in vitro biological activities in another lipophilic AA derivative, 2-O-octadecyl ascorbic acid, was non-carcinogenic and did not potentiate the UVC-induced transformation frequency when applied for 3 days after UVC irradiation. These results demonstrate that 3-CetylAA is a promising candidate as a lipophilic derivative of AA for cosmetic purposes.

Localized corrosion induced surface modifications of Al-Cu-Li alloy studied by ToF-SIMS 3D imaging

Three-dimensional (3D) time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging is a promising tool in the analysis of surface modifications of alloy matrix and intermetallic particles induced by localized corrosion due to its good spatial resolution and very high sensitivity to chemical identification especially involving light mass elements like Li. In this paper, ToF-SIMS 3D chemical mapping combined with scanning electron microscopy was performed to study the localized corrosion of Al-Cu-Li alloy (AA2050-T8) in a region around an Al-Cu-Fe-Mn intermetallic particles (IMPs) in 0. 1 M NaCl solution. Initiation of corrosion was locally observed on the IMPs and between IMPs and matrix substrate. Moreover, a modified oxide/hydroxide layer was observed over IMPs compared to the matrix. This new corrosion layer was enriched with chlorides and Cu hydroxides. ToF-SIMS 3D imaging revealed that Li was present over the alloy matrix, while no Li was present over the IMPs in regions where localized corrosion occurred.

Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery

The 2018–2019 Central European drought had a grave impact on natural and managed ecosystems, affecting their health and productivity. We examined patterns in hyperspectral VNIR imagery using an unsupervised learning approach to improve ecosystem monitoring and the understanding of grassland drought responses. The main objectives of this study were (1) to evaluate the application of simplex volume maximisation (SiVM), an unsupervised learning method, for the detection of grassland drought stress in high-dimensional remote sensing data at the ecosystem scale and (2) to analyse the contributions of different spectral plant and soil traits to the computed stress signal. The drought status of the research site was assessed with a non-parametric standardised precipitation–evapotranspiration index (SPEI) and soil moisture measurements. We used airborne HySpex VNIR-1800 data from spring 2018 and 2019 to compare vegetation condition at the onset of the drought with the state after one year. SiVM, an interpretable matrix factorisation technique, was used to derive typical extreme spectra (archetypes) from the hyperspectral data. The classification of archetypes allowed for the inference of qualitative drought stress levels. The results were evaluated using a set of geophysical measurements and vegetation indices as proxy variables for drought-inhibited vegetation growth. The successful application of SiVM for grassland stress detection at the ecosystem canopy scale was verified in a correlation analysis. The predictor importance was assessed with boosted beta regression. In the resulting interannual stress model, carotenoid-related variables had among the highest coefficient values. The significance of the photochemical reflectance index that uses 512 nm as reference wavelength (PRI512) demonstrates the value of combining imaging spectrometry and unsupervised learning for the monitoring of vegetation stress. It also shows the potential of archetypical reflectance spectra to be used for the remote estimation of photosynthetic efficiency. More conclusive results could be achieved by using vegetation measurements instead of proxy variables for evaluation. It must also be investigated how the method can be generalised across ecosystems.

Protein hyper‐glycosylation is a metabolic feature of mouse and human brains with beta amyloid pathology

Glycomics is the study of complex carbohydrates throughout their metabolic lifecycle; precise profiling of these oligosaccharides has been shown to provide a critical understanding of the current state of a disease. N-linked glycans are a subset of the glycome containing co-translational modifications found on cell surface, secreted, and circulating proteins. Prior research shows glycosylation perturbations in Alzheimer's disease (AD), however, these patterns have not been extensively studied in specific brain regions with underlying disease pathology. Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a revolutionary technique that combines traditional mass spectrometry with high-resolution imaging to visualize microenvironmental glycan distribution. Using our improved, enzyme-assisted workflow, we can define sub-regional N-linked glycan features in multiple areas of the brain implicated in AD pathogenesis including the hippocampus and the frontal cortex. We saw a profound hyper N-linked glycosylation pattern in multiple (n=4) 5xFAD mouse model (beta-amyloid pathology) brain regions compared to age- and sex-matched, heterozygous littermate controls. Consistent with our in vivo findings, MALDI-MSI analysis of human AD hippocampus and frontal cortex tissue samples revealed a similar hyper glycosylation phenotype. Our studies suggest that beta-amyloid is a metabolic modifier of N-linked glycosylation and could be an exciting therapeutic approach as well as a potential biomarker for AD progression. In the future, we plan to use these results to further investigate specific glycosylation pathways that promote AD pathogenesis, and how these modifications contribute to ER stress and the unfolded protein response, inflammation, and neuronal cell death.

Computed tomography imaging spectrometry based on superiorization and guided image filtering.

Computed tomography imaging spectrometry (CTIS) is a snapshot hyperspectral imaging technique that can obtain a three-dimensional (${2D +}\lambda$) data cube of the target scene within a single exposure. Previous studies of CTIS suggest that reconstructions usually suffer from severe artifacts due to the limited number of projections available. To overcome this limitation, an iterative algorithm combining superiorization and guided image filtering is proposed to explore the intrinsic properties of the hyperspectral data cube as well as the characteristics of zero-order diffraction for the first time, to the best of our knowledge. Results from both simulative studies and proof-of-concept experiments demonstrate its superiority in suppressing artifacts and improving precision over the frequently used expectation maximization algorithm.

Visualizing the Journey of Fenofibrate through the Rat Gastrointestinal Tract by Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging.

Mapping the spatial distribution of a drug throughout the gastrointestinal tract (GIT) after oral ingestion can provide novel insights into the interaction between the drug, the oral drug delivery system, and the GIT. Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a molecular imaging technique that can analyze molecules in the cryosections of tissues, determining their localization with a spatial resolution of 10-100 μm. The overall aim of this study was to use MALDI-MSI to visualize the distribution and spatial location of a model prodrug (fenofibrate) through the rat GIT. Furthermore, the distribution and spatial colocalization of taurocholate and phospholipids in the rat GIT in relation to fenofibrate were investigated. Rats were given a fenofibrate suspension of 10 mg/mL by oral gavage. Blood samples were drawn, and the rats were euthanized at three different time points. The GIT was collected and frozen, and MALDI-MSI was applied on cross sections of the stomach and intestine. Fenofibrate was detected by MALDI-MSI throughout the GIT, which also revealed that fenofibrate was hydrolyzed to the active drug fenofibric acid already in the stomach. Furthermore, the presence of lyso-phosphatidylcholine (lyso-PC) and taurocholate was confirmed in the lumen of the small intestine. MALDI-MSI was shown to be a useful qualitative tool for localizing parent prodrugs and active drugs, with a possibility for gaining insight into not only the location for activation but also the role of endogenous molecules in the process.

Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing

Hyperspectral (HS) imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to process and analyze these HS products, mainly by seasoned experts. However, with an ever-growing volume of data, the bulk of costs in manpower and material resources poses new challenges for reducing the burden of manual labor and improving efficiency. For this reason, it is urgent that more intelligent and automatic approaches for various HS RS applications be developed. Machine learning (ML) tools with convex optimization have successfully undertaken the tasks of numerous artificial intelligence (AI)-related applications; however, their ability to handle complex practical problems remains limited, particularly for HS data, due to the effects of various spectral variabilities in the process of HS imaging and the complexity and redundancy of higher-dimensional HS signals. Compared to convex models, nonconvex modeling, which is capable of characterizing more complex real scenes and providing model interpretability technically and theoretically, has proven to be a feasible solution that reduces the gap between challenging HS vision tasks and currently advanced intelligent data processing models.

High temperature Zircaloy-4 oxidation in water vapour-containing environments examined with Raman imaging and labelled oxygen

High Temperature oxidation of Zircaloy-4 was studied in N2–O2–H2O gas mixtures using labelled 18O2, thermogravimetry, Raman imaging and mass spectrometry. Samples were either exposed to N2–18O2–H2O gas mixtures, or two-stage oxidised first in 18O2, then in H216O - N2 or 16O2 - N2 atmospheres. In the pre-transition, diffusion-controlled regime, mostly steam contributes to the zirconia formation, while in the nitrogen-catalysed post transition regime both oxygen and steam contribute to the oxidation. These results were tentatively explained by competitive adsorption of oxygen and steam at the gas/solid interfaces, and the formation of porosity in the oxide layers.

A Neural Network Method for Classification of Sunlit and Shaded Components of Wheat Canopies in the Field Using High-Resolution Hyperspectral Imagery

(1) Background: Information rich hyperspectral sensing, together with robust image analysis, is providing new research pathways in plant phenotyping. This combination facilitates the acquisition of spectral signatures of individual plant organs as well as providing detailed information about the physiological status of plants. Despite the advances in hyperspectral technology in field-based plant phenotyping, little is known about the characteristic spectral signatures of shaded and sunlit components in wheat canopies. Non-imaging hyperspectral sensors cannot provide spatial information; thus, they are not able to distinguish the spectral reflectance differences between canopy components. On the other hand, the rapid development of high-resolution imaging spectroscopy sensors opens new opportunities to investigate the reflectance spectra of individual plant organs which lead to the understanding of canopy biophysical and chemical characteristics. (2) Method: This study reports the development of a computer vision pipeline to analyze ground-acquired imaging spectrometry with high spatial and spectral resolutions for plant phenotyping. The work focuses on the critical steps in the image analysis pipeline from pre-processing to the classification of hyperspectral images. In this paper, two convolutional neural networks (CNN) are employed to automatically map wheat canopy components in shaded and sunlit regions and to determine their specific spectral signatures. The first method uses pixel vectors of the full spectral features as inputs to the CNN model and the second method integrates the dimension reduction technique known as linear discriminate analysis (LDA) along with the CNN to increase the feature discrimination and improves computational efficiency. (3) Results: The proposed technique alleviates the limitations and lack of separability inherent in existing pre-defined hyperspectral classification methods. It optimizes the use of hyperspectral imaging and ensures that the data provide information about the spectral characteristics of the targeted plant organs, rather than the background. We demonstrated that high-resolution hyperspectral imagery along with the proposed CNN model can be powerful tools for characterizing sunlit and shaded components of wheat canopies in the field. The presented method will provide significant advances in the determination and relevance of spectral properties of shaded and sunlit canopy components under natural light conditions.

Absolute cross sections and asymmetry parameters for photodetachment of C−(4So)

Absolute total cross sections and asymmetry parameters for the photodetachment of the ${}^{4}{S}^{o}$ ground state of ${\mathrm{C}}^{\ensuremath{-}}$ are reported for photon energies ranging from threshold to 6 eV. The total cross sections were measured using the animated crossed beam technique incorporating corrections for saturation, while the asymmetry parameters were obtained using velocity map imaging spectrometry. The measured values are in good agreement with theoretical results obtained from an $R$-matrix calculation using polarized pseudostates.

Use of stable isotope-tagged thymidine and multi-isotope imaging mass spectrometry (MIMS) for quantification of human cardiomyocyte division.

Quantification of cellular proliferation in humans is important for understanding biology and responses to injury and disease. However, existing methods require administration of tracers that cannot be ethically administered in humans. We present a protocol for the direct quantification of cellular proliferation in human hearts. The protocol involves administration of non-radioactive, non-toxic stable isotope 15Nitrogen-enriched thymidine (15N-thymidine), which is incorporated into DNA during S-phase, in infants with tetralogy of Fallot, a common form of congenital heart disease. Infants with tetralogy of Fallot undergo surgical repair, which requires the removal of pieces of myocardium that would otherwise be discarded. This protocol allows for the quantification of cardiomyocyte proliferation in this discarded tissue. We quantitatively analyzed the incorporation of 15N-thymidine with multi-isotope imaging spectrometry (MIMS) at a sub-nuclear resolution, which we combined with correlative confocal microscopy to quantify formation of binucleated cardiomyocytes and cardiomyocytes with polyploid nuclei. The entire protocol spans 3-8 months, which is dependent on the timing of surgical repair, and 3-4.5 researcher days. This protocol could be adapted to study cellular proliferation in a variety of human tissues.

Click-correlative light\xa0and electron microscopy (click-AT-CLEM) for imaging and tracking azido-functionalized sphingolipids in bacteria

Sphingolipids, including ceramides, are a diverse group of structurally related lipids composed of a sphingoid base backbone coupled to a fatty acid side chain and modified terminal hydroxyl group. Recently, it has been shown that sphingolipids show antimicrobial activity against a broad range of pathogenic microorganisms. The antimicrobial mechanism, however, remains so far elusive. Here, we introduce ‘click-AT-CLEM’, a labeling technique for correlated light and electron microscopy (CLEM) based on the super-resolution array tomography (srAT) approach and bio-orthogonal click chemistry for imaging of azido-tagged sphingolipids to directly visualize their interaction with the model Gram-negative bacterium Neisseria meningitidis at subcellular level. We observed ultrastructural damage of bacteria and disruption of the bacterial outer membrane induced by two azido-modified sphingolipids by scanning electron microscopy and transmission electron microscopy. Click-AT-CLEM imaging and mass spectrometry clearly revealed efficient incorporation of azido-tagged sphingolipids into the outer membrane of Gram-negative bacteria as underlying cause of their antimicrobial activity.

Mechanism for Scavenging of Amyloid-Β by Hybrid Silica Nanobowls: Diagnostic and Therapeutic Applications for AΒ Pathology

Amyloid beta (Aβ) oligomers are a toxic species implicated in Alzheimer's disease. We report hybrid silica nanoparticles – nanobowls (NB), enveloped in a temperature sensitive lipid-polymer coating, with high affinity (Kd 600nM) for Aβ. Attributed to this, we demonstrate that NB scavenge extracellular and membrane associated Aβ in neuronal cells. Time dependent confocal imaging and fluorescence spectrometry elucidate the mechanism by which NB bind Aβ above the coating's transition temperature. Shedding of the coating to cell membranes is reported as the rate-limiting step for scavenging.

Aerosolisation in endonasal endoscopic pituitary surgery.

PurposeTo determine the particle size, concentration, airborne duration and spread during endoscopic endonasal pituitary surgery in actual patients in a theatre setting.MethodsThis observational study recruited a convenience sample of three patients. Procedures were performed in a positive pressure operating room. Particle image velocimetry and spectrometry with air sampling were used for aerosol detection.ResultsIntubation and extubation generated small particles (< 5 µm) in mean concentrations 12 times greater than background noise (p < 0.001). The mean particle concentrations during endonasal access were 4.5 times greater than background (p = 0.01). Particles were typically large (> 75 µm), remained airborne for up to 10 s and travelled up to 1.1 m. Use of a microdebrider generated mean aerosol concentrations 18 times above baseline (p = 0.005). High-speed drilling did not produce aerosols greater than baseline. Pituitary tumour resection generated mean aerosol concentrations less than background (p = 0.18). Surgical drape removal generated small and large particles in mean concentrations 6.4 times greater than background (p < 0.001).ConclusionIntubation and extubation generate large amounts of small particles that remain suspended in air for long durations and disperse through theatre. Endonasal access and pituitary tumour resection generate smaller concentrations of larger particles which are airborne for shorter periods and travel shorter distances.

Spatial Analysis of Phosphatidylinositol Molecular Species in Pork Chop Tissues Using Matrix-assisted Laser Desorption/ionization-Mass Spectrometry Imaging.

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) is a powerful technique for visualizing lipids in biological tissues. Phosphatidylinositol (PI), a phospholipid in pork, is a major source of inositol in animal-derived foods believed to be protective against diseases related to pregnancy and cancer. However, the distribution of PI molecular species in pork is not well understood. Here, we performed MALDI-MSI analysis to investigate the distribution and composition of PI molecular species in pork chop comprising Longissimus thoracis et lumborum muscle (loin), intermuscular fat tissue, transparent tissue, and spinalis muscle. Twelve diacyl-PI molecular species were identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (MS/MS) and MALDI-MS/MS analysis and visualized using MALDI-MSI. Spinalis muscle had the highest amount of identified PI molecular species, followed by loin, transparent tissue, and intermuscular fat tissue. The diacyl-PI molecular species containing hexadecadienoic, oleic, linoleic and eicosadienoic acids at the sn-2 position were mainly abundant in the loin and spinalis muscle, whereas those containing mead, arachidonic, docosatetraenoic, and docosapentaenoic acids at the sn-2 position were mainly abundant in both muscles as well as transparent tissues. Notably, the balance of PI molecular species differed among the tissues depending on fatty acid compositions at the sn-2 position. These results suggested that MALDI-MSI is a promising tool for assessing the association between individual pork tissues and the protective effects of PI molecular species against diseases related to pregnancy and cancer. To the best of our knowledge, this is the first report showing tissue-specific distributions of PI molecular species in pork chop using MALDI-MSI.

Application of Satellite Remote Sensing for Detection of Abiotic Stress in Coniferous Landscapes

In the article is made an overview of the application of different satellite remote sensing methods and technologies in detection of the abiotic stress in coniferous landscapes. The review paper is discussing in short the application of different remote sensing technologies such as: satellite multispectral and infrared (thermal), imaging spectrometry and fluorescence imaging. The studied period spans from the onset of the satellite remote sensing in the 1960s until present day. In conclusion, are drawn requirements for the perspective technologies in satellite remote sensing which should address the fast and reliable detection of the manifestation of abiotic stress in coniferous landscapes.

Design and Characterization of a Novel Tool for the Antigenic Enrichment of Actinobacillus pleuropneumoniae Outer Membrane.

Production and isolation of recombinant proteins are costly and work-intensive processes, especially in immunology when tens or hundreds of potential immunogens need to be purified for testing. Here we propose an alternative method for fast screening of immunogen candidates, based on genetic engineering of recombinant bacterial strains able to express and expose selected antigens on their outer membrane. In Actinobacillus pleuropneumoniae, a Gram-negative porcine pathogen responsible for extensive economic losses worldwide, we identified a conserved general secretion pathway (GSP) domain in the N-terminal part of the outer membrane protein ApfA (ApfA stem: ApfAs). ApfAs was used as an outer membrane anchor, to which potential immunogens can be attached. To enable confirmation of correct positioning, ApfAs, was cloned in combination with the modified acyl carrier protein (ACP) fluorescent tag ACP mini (ACPm) and the putative immunogen VacJ. The chimeric construct was inserted in the pMK-express vector, subsequently transformed into A. pleuropneumoniae for expression. Flow cytometry, fluorescence imaging and mass spectrometry analysis were employed to demonstrate that the outer membrane of the transformed strain was enriched with the chimeric ApfAs-ACPm-VacJ antigen. Our results confirmed correct positioning of the chimeric ApfAs-ACPm-VacJ antigen and supported this system’s potential as platform technology enabling antigenic enrichment of the outer membrane of A. pleuropneumoniae.

Methods Of Increasing Spectral Resolution Of Imaging Spectrometers Built On The Basis Of Multi–channel Radiation Detectors

The article proposes the methods of object shooting by means of a spectrometer based on a multi-channel radiation detector and further processing of its results allowing spectral resolution of such spectrometers significantly to increase with the same original spatial resolution. The mathematical model of the shooting process is provided. It is determined that restoration of spectral radiance of objects based on the shooting data using the proposed method is a mathematically incorrect inverse task. The Greville method, the method of wavelet transformation, the Tikhonov regularisation method, and the Godunov method were considered as methods for its solution. The results of computational modelling of the considered methods are shown and it is found that restoration of spectral radiance of objects based on the shooting data using the considered methods is possible and relative error of restoration is at a fraction of per cent scale. It is determined that the wavelet transformation method is an optimal method of solution of the incorrect spectral radiance restoration task. It is also shown that the proposed method of imaging spectrometry is applicable both when using matrix radiation detectors with increased number of narrow-band filters and when using widely spread standard three-channel matrix RGB detectors of radiation.