Infrared spectroscopic imaging: the next generation

Signatures of top versus bottom illuminations and their predicted implications for infrared transmission microspectroscopy

Since both top and bottom illuminations are widely used in infrared transmission measurements, in this paper, we study the effects of different illuminations on the signatures in infrared microspectroscopy. By simulating a series of dielectric samples, we show that their extinction efficiency,Q ext $$ {Q}_{\mathrm{ext}} $$ , remains unchanged when the direction of the incident plane wave is reversed, even though the field distributions both inside and outside of the sample may be dramatically different. We find features inQ ext $$ {Q}_{\mathrm{ext}} $$ that are correlated with whispering gallery modes for one beam direction and correspond to completely different field distributions for the opposite beam direction. In addition, by linking the optical theorem and the reciprocity relation of far-field scattered field, we rigorously prove the invariance ofQ ext $$ {Q}_{\mathrm{ext}} $$ for arbitrary dielectric targets under opposite plane-wave illuminations. Furthermore, we show the difference in the apparent absorbance spectrum for opposite beam directions when considering numerical apertures.

Inspiring a convergent engineering approach to measure and model the tissue microenvironment

Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.

Vibrational imaging of metabolites for improved microbial cell strains

Significance

Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing.

Aim

This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism.

Approach

We provide an overview of the analytical instrumentation currently used in the "test" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity.

Results

Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level.

Conclusions

Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.

Structural characterization of amyloid aggregates with spatially resolved infrared spectroscopy

The self-assembly of proteins and peptides into ordered structures called amyloid fibrils is a hallmark of numerous diseases, impacting the brain, heart, and other organs. The structure of amyloid aggregates is central to their function and thus has been extensively studied. However, the structural heterogeneities between aggregates as they evolve throughout the aggregation pathway are still not well understood. Conventional biophysical spectroscopic methods are bulk techniques and only report on the average structural parameters. Understanding the structure of individual aggregate species in a heterogeneous ensemble necessitates spatial resolution on the length scale of the aggregates. Recent technological advances have led to augmentation of infrared (IR) spectroscopy with imaging modalities, wherein the photothermal response of the sample upon vibrational excitation is leveraged to provide spatial resolution beyond the diffraction limit. These combined approaches are ideally suited to map out the structural heterogeneity of amyloid ensembles. AFM-IR, which integrates IR spectroscopy with atomic force microscopy enables identification of the structural facets the oligomers and fibrils at individual aggregate level with nanoscale resolution. These capabilities can be extended to chemical mapping in diseased tissue specimens with submicron resolution using optical photothermal microscopy, which combines IR spectroscopy with optical imaging. This book chapter provides the basic premise of these novel techniques and provides the typical methodology for using these approaches for amyloid structure determination. Detailed procedures pertaining to sample preparation and data acquisition and analysis are discussed and the aggregation of the amyloid β peptide is provided as a case study to provide the reader the experimental parameters necessary to use these techniques to complement their research efforts.

Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check

Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

Translating Biospectroscopy Techniques to Clinical Settings: A New Paradigm in Point-of-Care Screening and/or Diagnostics

As healthcare tools increasingly move towards a more digital and computational format, there is an increasing need for sensor-based technologies that allow for rapid screening and/or diagnostics [...].

Bond-selective fluorescence imaging with single-molecule sensitivity

Bioimaging harnessing optical contrasts and chemical specificity is of vital importance in probing complex biology. Vibrational spectroscopy based on mid-infrared (mid-IR) excitation can reveal rich chemical information about molecular distributions. However, its full potential for bioimaging is hindered by the achievable sensitivity. Here, we report bond selective fluorescence-detected infrared-excited (BonFIRE) spectral microscopy. BonFIRE employs two-photon excitation in the mid-IR and near-IR to upconvert vibrational excitations to electronic states for fluorescence detection, thus encoding vibrational information into fluorescence. The system utilizes tuneable narrowband picosecond pulses to ensure high sensitivity, biocompatibility, and robustness for bond-selective biological interrogations over a wide spectrum of reporter molecules. We demonstrate BonFIRE spectral imaging in both fingerprint and cell-silent spectroscopic windows with single-molecule sensitivity for common fluorescent dyes. We then demonstrate BonFIRE imaging on various intracellular targets in fixed and live cells, neurons, and tissues, with promises for further vibrational multiplexing. For dynamic bioanalysis in living systems, we implement a high-frequency modulation scheme and demonstrate time-lapse BonFIRE microscopy of live HeLa cells. We expect BonFIRE to expand the bioimaging toolbox by providing a new level of bond-specific vibrational information and facilitate functional imaging and sensing for biological investigations.

Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging

Chemical imaging, especially mid-infrared spectroscopic microscopy, enables label-free biomedical analyses while achieving expansive molecular sensitivity. However, its slow speed and poor image quality impede widespread adoption. We present a microscope that provides high-throughput recording, low noise, and high spatial resolution where the bottom-up design of its optical train facilitates dual-axis galvo laser scanning of a diffraction-limited focal point over large areas using custom, compound, infinity-corrected refractive objectives. We demonstrate whole-slide, speckle-free imaging in ~3 min per discrete wavelength at 10× magnification (2 μm/pixel) and high-resolution capability with its 20× counterpart (1 μm/pixel), both offering spatial quality at theoretical limits while maintaining high signal-to-noise ratios (>100:1). The data quality enables applications of modern machine learning and capabilities not previously feasible - 3D reconstructions using serial sections, comprehensive assessments of whole model organisms, and histological assessments of disease in time comparable to clinical workflows. Distinct from conventional approaches that focus on morphological investigations or immunostaining techniques, this development makes label-free imaging of minimally processed tissue practical.

Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy

A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm-1 and 1285 cm-1 in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.

Digital Histopathology by Infrared Spectroscopic Imaging

Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. First, this review summarizes IR imaging instrumentation especially suited to histopathology, analyses of its performance, and major trends. Second, an overview of data processing methods and application of machine learning is given, with an emphasis on the emerging use of deep learning. Third, a discussion on workflows in pathology is provided, with four categories proposed based on the complexity of methods and the analytical performance needed. Last, a set of guidelines, termed experimental and analytical specifications for spectroscopic imaging in histopathology, are proposed to help standardize the diversity of approaches in this emerging area.

Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases

Chronic liver diseases (CLDs) are a major public health problem. Despite the progress achieved in fighting against viral hepatitis, the emergence of non-alcoholic fatty liver disease might pose a serious challenge to the public's health in the coming decades. Medical management of CLDs represents a substantial burden on the public health infrastructures. The health care cost of these diseases is an additional burden that weighs heavily on the economies of developing countries. Effective management of CLDs requires the adoption of reliable and cost-effective screening and diagnosing methods to ensure early detection and accurate clinical assessment of these diseases. Vibrational spectroscopies have emerged as universal analytical methods with promising applications in various industrial and biomedical fields. These revolutionary analytical techniques rely on analyzing the interaction between a light beam and the test sample to generate a spectral fingerprint. This latter is defined by the analyte's chemical structure and the molecular vibrations of its functional groups. Raman spectroscopy and surface-enhanced Raman spectroscopy have been used in combination with various chemometric tests to diagnose a wide range of malignant, metabolic and infectious diseases. The aim of the current review is to cast light on the use of these optical sensing methods in the diagnosis of CLDs. The vast majority of research works that investigated the potential application of these spectroscopic techniques in screening and detecting CLDs were discussed here. The advantages and limitations of these modern analytical methods, as compared with the routine and gold standard diagnostic approaches, were also reviewed in details.

Cell Phase Identification in a Three-Dimensional Engineered Tumor Model by Infrared Spectroscopic Imaging

Cell cycle progression plays a vital role in regulating proliferation, metabolism, and apoptosis. Three-dimensional (3D) cell cultures have emerged as an important class of in vitro disease models, and incorporating the variation occurring from cell cycle progression in these systems is critical. Here, we report the use of Fourier transform infrared (FT-IR) spectroscopic imaging to identify subtle biochemical changes within cells, indicative of the G1/S and G2/M phases of the cell cycle. Following previous studies, we first synchronized samples from two-dimensional (2D) cell cultures, confirmed their states by flow cytometry and DNA quantification, and recorded spectra. We determined two critical wavenumbers (1059 and 1219 cm-1) as spectral indicators of the cell cycle for a set of isogenic breast cancer cell lines (MCF10AT series). These two simple spectral markers were then applied to distinguish cell cycle stages in a 3D cell culture model using four cell lines that represent the main stages of cancer progression from normal cells to metastatic disease. Temporal dependence of spectral biomarkers during acini maturation validated the hypothesis that the cells are more proliferative in the early stages of acini development; later stages of the culture showed stability in the overall composition but unique spatial differences in cells in the two phases. Altogether, this study presents a computational and quantitative approach for cell phase analysis in tissue-like 3D structures without any biomarker staining and provides a means to characterize the impact of the cell cycle on 3D biological systems and disease diagnostic studies using IR imaging.

Space-resolved chemical information from infrared extinction spectra

A new method is presented for the extraction of the complex index of refraction from the extinction efficiency, [Formula: see text], of homogeneous and layered dielectric spheres that simultaneously removes scattering effects and corrects measured extinction spectra for systematic experimental errors such as baseline shifts, tilts, curvature, and scaling. No reference spectrum is required and fit functions may be used that automatically satisfy the Kramers-Kronig relations. Thus, the method yields the complex refractive index of a sample for unambiguous interpretation of the chemical information of the sample. In the case of homogeneous spheres, the method also determines the radius of the sphere. In the case of layered spheres, the method determines the substances within each layer. Only a single-element detector is required. Using numerically computed [Formula: see text] data of polymethyl-methacrylate and polystyrene homogeneous and layered spheres, we show that the new reconstruction algorithm is accurate and reliable. Reconstructing the complex refractive index from a published, experimentally measured raw absorbance spectrum shows that the new method simultaneously corrects spectra for scattering effects and, given shape information, corrects raw spectra for systematic errors that result in spectral distortions such as baseline shifts, tilts, curvature, and scaling.

Spectral imaging at high definition and high speed in the mid-infrared

Spectral imaging in the mid-infrared (MIR) range provides simultaneous morphological and chemical information of a wide variety of samples. However, current MIR technologies struggle to produce high-definition images over a broad spectral range at acquisition rates that are compatible with real-time processes. We present a novel spectral imaging technique based on nondegenerate two-photon absorption of temporally chirped optical MIR pulses. This approach avoids complex image processing or reconstruction and enables high-speed acquisition of spectral data cubes (xyω) at high-pixel density in under a second.

Performance Evaluation of Focal Plane Array (FPA)-FTIR and Synchrotron Radiation (SR)-FTIR Microspectroscopy to Classify Rice Components

The development of biochemical analysis techniques to study heterogeneous biological samples is increasing. These techniques include synchrotron radiation Fourier transform infrared (SR-FTIR) microspectroscopy. This method has been applied to analyze biological tissue with multivariate statistical analysis to classify the components revealed by the spectral data. This study aims to compare the efficiencies of SR-FTIR microspectroscopy and focal plane array (FPA)-FTIR microspectroscopy when classifying rice tissue components. Spectral data were acquired for mapping the same sample areas from both techniques. Principal component analysis and cluster imaging were used to investigate the biochemical variations of the tissue types. The classification was based on the functional groups of pectin, protein, and polysaccharide. Four layers from SR-FTIR microspectroscopy including pericarp, aleurone layer, sub-aleurone layer, and endosperm were classified using cluster imaging, while FPA-FTIR microspectroscopy could classify only three layers of pericarp, aleurone layer, and endosperm. Moreover, SR-FTIR microspectroscopy increased the image contrast of the biochemical distribution in rice tissue more efficiently than FPA-FTIR microspectroscopy. We have demonstrated the capability of the high-resolution synchrotron technique and its ability to clarify small structures in rice tissue. The use of this technique might increase in future studies of tissue characterization.

Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy

Infrared microspectroscopy is a powerful tool in the analysis of biological samples. However, strong electromagnetic scattering may occur since the wavelength of the incident radiation and the samples may be of comparable size. Based on the Mie theory of single spheres, correction algorithms have been developed to retrieve pure absorbance spectra. Studies of the scattering characteristics of samples of different types, obtained by microspectroscopy, have been performed. However, the detailed, microscopic effects of the coupling of the samples on signatures in spectra, obtained by infrared microspectroscopy, are still not clear. The aim of this paper is to investigate how the coupling of spherical samples influences the spectra. Applying the surface integral equation (SIE) method, we simulate small dielectric spheres, arranged as double-spheres or small arrays of spheres. We find that the coupling of the spheres hardly influences the broad oscillations observed in infrared spectra (the Mie wiggles) unless the radii of the spheres are different or the angle between the direction of the incident radiation and the normal of the plane where the spheres are located is large. Sharp resonance features in the spectra (the Mie ripples) are affected by the coupling of the spheres and this effect depends on the polarization of the incident wave. Experiments are performed to verify our conclusions.

Research on NCFCP compact broadband NIR detector imaging and energy transfer function

Nonlinear crystal frequency conversion imaging with direct detection by silicon-based detectors is an effective way to break through the limitations for existing near-infrared (NIR) detectors with expensive cost and high noise. In this paper, a broadband NIR detector imaging scheme based on the principle of nonlinear crystal frequency conversion (NCFCP) was proposed. A thin film of nonlinear crystal frequency conversion material (NCFCM) combined with a silicon-based detector was used to form a broadband NIR detector. The theoretically investigated energy transfer function was used as a guidance for experiment. Meanwhile, the relationship between the imaging effect and the energy transfer of the NCFCP-based compact broadband NIR detector in the NIR band was measured experimentally. The accuracy of the theoretical study had been verified by the measured transfer results.

Resolution Limit in Infrared Chemical Imaging

Chemical imaging combines the spatial specificity of optical microscopy with the spectral selectivity of vibrational spectroscopy. Mid-infrared (IR) absorption imaging instruments are now able to capture high-quality spectra with microscopic spatial detail, but the limits of their ability to resolve spatial and spectral objects remain less understood. In particular, the sensitivity of measurements to chemical and spatial changes and rules for optical design have been presented, but the influence of spectral information on spatial sensitivity is as yet relatively unexplored. We report an information theory-based approach to quantify the spatial localization capability of spectral data in chemical imaging. We explicitly consider the joint effects of the signal-to-noise ratio and spectral separation that have significance in experimental settings to derive resolution limits in IR spectroscopic imaging.

Beamshaping for infrared hyperspectral imaging: a sequential optimization for infrared source coupling

Focal plane array (FPA) detectors have escalated Fourier transform infrared (FTIR) microspectroscopy to a potent hyperspectral imaging method. Yet, despite the instrumental multiplex/multichannel advantages, the fidelity of the hyperspectral images relies on the throughput as the total flux of the source is divided among each FPA pixel. Additionally, maintaining the spectral resolution requires a certain level of collimation of the beam which adversely affect the flux of high étendue source. To this end, we propose an implementation of two deformable mirror (DM) sensorless adaptive optics system for infrared (IR) source coupling. The deflection shape of each DM membrane is optimized individually to deal with the beam intensity and the rays' direction in a separate manner, while preserving the spectral quality across the entire mid-IR range. This paper contemplates the choice of metrics in sequential optimization in conjunction with two variations of stochastic parallel gradient descent optimization algorithm. We discuss this approach with respect to a state-of-the-art FTIR microscope.

Mid-infrared spectral reconstruction with dielectric metasurfaces and dictionary learning

Mid-infrared (MIR) spectroscopy has numerous industrial applications and is usually performed with Fourier-transform infrared (FTIR) spectrometers. While these work well for many purposes, there is currently much interest in alternative approaches that are smaller and lighter, i.e., MIR microspectrometers. Here we investigate all-dielectric metasurfaces as spectral filters for MIR microspectrometers. Two metasurface types are studied. For the first, we design, fabricate, and test a metasurface with a narrow and angularly tunable transmission stop band. We use it to reconstruct the transmission spectra of various materials. The second metasurface, investigated theoretically, possesses narrow passband features via symmetry-protected bound states in the continuum.

Microemitter-Based IR Spectroscopy and Imaging with Multilayer Graphene Thermal Emission

IR analyses such as Fourier transform infrared spectroscopy (FTIR) are widely used in many fields; however, the performance of FTIR is limited by the slow speed (∼10 Hz), large footprint (∼ millimeter), and glass bulb structure of IR light sources. Herein, we present IR spectroscopy and imaging based on multilayer-graphene microemitters, which have distinct features: a planar structure, bright intensity, a small footprint (sub-μm²), and high modulation speed of >50 kHz. We developed an IR analysis system based on the multilayer-graphene microemitter and performed IR absorption spectroscopy. We show two-dimensional IR chemical imaging that visualizes the distribution of the chemical information. In addition, we present high-spatial-resolution IR imaging with a spatial resolution of ∼1 μm, far higher than the diffraction limit. The graphene-based IR spectroscopy and imaging can open new routes for IR applications in chemistry, material science, medicine, biology, electronics, and physics.

Mid-infrared microscopy via position correlations of undetected photons

Quantum imaging with undetected photons (QIUP) has recently emerged as a new powerful imaging tool. Exploiting the spatial entanglement of photon pairs, it allows decoupling of the sensing and detection wavelengths, facilitating imaging in otherwise challenging spectral regions by leveraging mature silicon-based detection technology. All existing implementations of QIUP have so far utilised the momentum correlations within the biphoton states produced by spontaneous parametric downconversion. Here, for the first time, we implement and examine theoretically and numerically the complementary scenario - utilising the tight position correlations formed within photon pairs at birth. This image plane arrangement facilitates high resolution imaging with comparative experimental ease, and we experimentally show resolutions below 10 μm at a sensing wavelength of 3.7 μm. Moreover, we present a quantitative numerical model predicting the imaging capabilities of QIUP for a wide range of parameters. Finally, by imaging mouse heart tissue at the mid-IR to reveal morphological features on the cellular level, we further demonstrate the viability of this technique for the life sciences. These results offer new perspectives on the capabilities of QIUP for label-free widefield mid-IR microscopy, enabling real-world biomedical as well as industrial imaging applications.

Evaluation of distributional homogeneity of pharmaceutical formulation using laser direct infrared imaging

The distributional homogeneity of chemicals is a key parameter of solid pharmaceutical formulations. Indeed, it may affect the efficacy of the drug and consequently its safety. Chemical imaging offers a unique insight enabling the visualisation of the different constituents of a pharmaceutical tablet. It allows identifying ingredients poorly distributed offering the possibility to optimize the process parameters or to adapt characteristics of incoming raw materials to increase the final product quality. Among the available chemical imaging tools, Raman imaging is one of the most widely used since it offers a high spatial resolution with well-resolved peaks resulting in a high spectral specificity. However, Raman imaging suffers from sample autofluorescence and long acquisition times. Recently commercialised, laser direct infrared reflectance imaging (LDIR) is a quantum cascade laser (QCL) based imaging technique that offers the opportunity to rapidly analyse samples. In this study, a typical pharmaceutical formulation blend composed of two active pharmaceutical ingredients and three excipients was aliquoted at different mixing timepoints. The collected aliquots were tableted and analysed using both Raman and LDIR imaging. The distributional homogeneity indexes of one active ingredient image were then computed and compared. The results show that both techniques achieved similar conclusions. However, the analysis times were drastically different. While Raman imaging required a total analysis time of 4 h per tablet to obtain the distribution map of acetylsalicylic acid with a step size of 100 µm, it only took 7.5 min to achieve the same result with LDIR. The results obtained in the present study show that LDIR is a promising technique for the analysis of pharmaceutical formulations and that it could be a valuable tool when developing new pharmaceutical formulations.

Applications of infrared spectroscopy in polysaccharide structural analysis: Progress, challenge and perspective

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Functional properties of polysaccharides depend on their structural features.

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IR spectroscopy is widely used in polysaccharide structural analysis.

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Classical applications of IR spectroscopy in polysaccharide are reviewed.

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IR integrating techniques can considerably expand its application scope.

Polysaccharides are important biomacromolecules with numerous beneficial functions and a wide range of industrial applications. Functions and properties of polysaccharides are closely related to their structural features. Infrared (IR) spectroscopy is a well-established technique which has been widely applied in polysaccharide structural analysis. In this paper, the principle of IR and interpretation of polysaccharide IR spectrum are briefly introduced. Classical applications of IR spectroscopy in polysaccharide structural elucidation are reviewed from qualitative and quantitative aspects. Some advanced IR techniques including integrating with mass spectrometry (MS), microscopy and computational chemistry are introduced and their applications are emphasized. These emerging techniques can considerably expand application scope of IR, thus exert a more important effect on carbohydrate characterization. Overall, this review seeks to provide a comprehensive insight to applications of IR spectroscopy in polysaccharide structural analysis and highlights the importance of advanced IR-integrating techniques.

Label-Free Histology and Evaluation of Human Pancreatic Cancer with Coherent Nonlinear Optical Microscopy

Surgeries achieving maximal tumor resection remain the major effective treatment of pancreatic cancer. Rapid and precise intraoperative diagnosis of pancreatic tissues is critical for optimum surgical outcomes but is challenging for the current staining-based histological methods. We demonstrated that label-free coherent nonlinear optical microscopy with combined stimulated Raman scattering (SRS) and second harmonic generation (SHG) could reveal key diagnostic features of both normal and cancerous human pancreatic tissues. Adjacent pairs of tissue sections from resection margins of 37 patients were imaged by SRS and hematoxylin and eosin staining for direct comparison, demonstrating high diagnostic concordance (Cohen's kappa, κ > 0.97) between them. Fresh unprocessed tissues showed well-preserved histoarchitectures including pancreatic ducts, islets, acini, and nerves. Moreover, the area ratios of collagen fibers were analyzed and found to correlate with the drainage pancreatic amylase level (odds ratio = 28.0, p = 0.0017). Our results indicated that SRS/SHG histology provides potential for rapid intraoperative diagnosis of pancreatic cancer as well as a predictive value of postoperative pancreatic fistula.

Compliance of the fish outflow tract is altered by thermal acclimation through connective tissue remodelling

To protect the gill capillaries from high systolic pulse pressure, the fish heart contains a compliant non-contractile chamber called the bulbus arteriosus which is part of the outflow tract (OFT) which extends from the ventricle to the ventral aorta. Thermal acclimation alters the form and function of the fish atria and ventricle to ensure appropriate cardiac output at different temperatures, but its impact on the OFT is unknown. Here we used ex vivo pressure-volume curves to demonstrate remodelling of passive stiffness in the rainbow trout (Oncorhynchus mykiss) bulbus arteriosus following more than eight weeks of thermal acclimation to 5, 10 and 18°C. We then combined novel, non-biased Fourier transform infrared spectroscopy with classic histological staining to show that changes in compliance were achieved by changes in tissue collagen-to-elastin ratio. In situ gelatin zymography and SDS-PAGE zymography revealed that collagen remodelling was underpinned, at least in part, by changes in activity and abundance of collagen degrading matrix metalloproteinases. Collectively, we provide the first indication of bulbus arteriosus thermal remodelling in a fish and suggest this remodelling ensures optimal blood flow and blood pressure in the OFT during temperature change.

Label-Free Infrared Spectroscopic Imaging Reveals Heterogeneity of β-Sheet Aggregates in Alzheimer's Disease

The aggregation of the amyloid beta (Aβ) protein into plaques is a pathological feature of Alzheimer's disease (AD). While amyloid aggregates have been extensively studied in vitro, their structural aspects and associated chemistry in the brain are not fully understood. In this report, we demonstrate, using infrared spectroscopic imaging, that Aβ plaques exhibit significant heterogeneities in terms of their secondary structure and phospholipid content. We show that the capabilities of discrete frequency infrared imaging (DFIR) are ideally suited for characterization of amyloid deposits in brain tissues and employ DFIR to identify nonplaque β-sheet aggregates distributed throughout brain tissues. We further demonstrate that phospholipid-rich β-sheet deposits exist outside of plaques in all diseased tissues, indicating their potential clinical significance. This is the very first application of DFIR toward a characterization of protein aggregates in an AD brain and provides a rapid, label-free approach that allows us to uncover β-sheet heterogeneities in the AD, which may be significant for targeted therapeutic strategies in the future.

Design Considerations for Discrete Frequency Infrared Microscopy Systems

Discrete frequency infrared 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, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument's performance mathematically. Finally, we provide a validation approach by enumerating performance metrics 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.

Application of 2D IR Bioimaging: Hyperspectral Images of Formalin-Fixed Pancreatic Tissues and Observation of Slow Protein Degradation

We used two-dimensional IR bioimaging to study the structural heterogeneity of formalin-fixed mouse pancreas. Images were generated from the hyperspectral data sets by plotting quantities associated with the amide I vibrational mode, which is created by the backbone carbonyl stretch. Images that measure the fundamental vibrational frequencies, cross peaks, and anharmonic shifts are presented. Histograms are generated for each quantity, providing averaged values and distributions around the mean that serve as metrics for protein structures. Images were generated from tissue that had been stored in a formalin fixation for 3, 8, and 48 weeks. Over this period, all three metrics show that that the β-sheet content of the samples increased, consistent with protein aggregation. Our results indicate that formalin fixation does not entirely arrest the degradation of a protein structure in pancreas tissue.

Rapid chemically selective 3D imaging in the mid-infrared

The emerging technique of mid-infrared optical coherence tomography (MIR-OCT) takes advantage of the reduced scattering of MIR light in various materials and devices, enabling tomographic imaging at deeper penetration depths. Because of challenges in MIR detection technology, the image acquisition time is, however, significantly longer than for tomographic imaging methods in the visible/near-infrared. Here we demonstrate an alternative approach to MIR tomography with high-speed imaging capabilities. Through femtosecond nondegenerate two-photon absorption of MIR light in a conventional Si-based CCD camera, we achieve wide-field, high-definition tomographic imaging with chemical selectivity of structured materials and biological samples in mere seconds.

Bond-selective imaging by optically sensing the mid-infrared photothermal effect

Mid-infrared (IR) spectroscopic imaging using inherent vibrational contrast has been broadly used as a powerful analytical tool for sample identification and characterization. However, the low spatial resolution and large water absorption associated with the long IR wavelengths hinder its applications to study subcellular features in living systems. Recently developed mid-infrared photothermal (MIP) microscopy overcomes these limitations by probing the IR absorption-induced photothermal effect using a visible light. MIP microscopy yields submicrometer spatial resolution with high spectral fidelity and reduced water background. In this review, we categorize different photothermal contrast mechanisms and discuss instrumentations for scanning and widefield MIP microscope configurations. We highlight a broad range of applications from life science to materials. We further provide future perspective and potential venues in MIP microscopy field.

Perspectives on infrared spectroscopic imaging from cancer diagnostics to process analysis

This perspective paper discusses the recent and potential developments in the application of infrared spectroscopic imaging, with a focus on Fourier transform infrared (FTIR) spectroscopic imaging. The current state-of-the-art has been briefly reported, that includes recent trends and advances in applications of FTIR spectroscopic imaging to biomedical systems. Here, some new opportunities for research in the biomedical field, particularly for cancer diagnostics, and also in the engineering field of process analysis; as well as challenges in FTIR spectroscopic imaging are discussed. Current and future prospects that will bring spectroscopic imaging technologies to the frontier of advanced medical diagnostics and to process analytics in engineering applications will be outlined in this opinion paper.

Detecting nitrile-containing small molecules by infrared photothermal microscopy

The use of infrared (IR) photothermal microscopy (IR-PTM) is emerging for imaging chemical substances in various samples. In this research, we demonstrated the use of a nitrile group as a vibrational tag to image target molecules in the low water-background region. We performed IR photothermal imaging of trifluoromethoxy carbonyl cyanide phenylhydrazone (FCCP) in cells and confirmed the high spatial resolution by photothermal detection using visible light as a probe beam. We imaged FCCP-treated HeLa cells and confirmed that the photothermal signal was indeed produced from the vibrational tag in lipid droplets. We also compared the results with nitrile imaging by stimulated Raman scattering (SRS) microscopy. From both the calculated and experimental results, IR-PTM demonstrated a signal-to-noise ratio (SNR) several tens of times better than that of SRS microscopy on the basis of the same power input.

The effect of deformation of absorbing scatterers on Mie-type signatures in infrared microspectroscopy

Mie-type scattering features such as ripples (i.e., sharp shape-resonance peaks) and wiggles (i.e., broad oscillations), are frequently-observed scattering phenomena in infrared microspectroscopy of cells and tissues. They appear in general when the wavelength of electromagnetic radiation is of the same order as the size of the scatterer. By use of approximations to the Mie solutions for spheres, iterative algorithms have been developed to retrieve pure absorbance spectra. However, the question remains to what extent the Mie solutions, and approximations thereof, describe the extinction efficiency in practical situations where the shapes of scatterers deviate considerably from spheres. The aim of the current study is to investigate how deviations from a spherical scatterer can change the extinction properties of the scatterer in the context of chaos in wave systems. For this purpose, we investigate a chaotic scatterer and compare it with an elliptically shaped scatterer, which exhibits only regular scattering. We find that chaotic scattering has an accelerating effect on the disappearance of Mie ripples. We further show that the presence of absorption and the high numerical aperture of infrared microscopes does not explain the absence of ripples in most measurements of biological samples.

Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how "spectral fingerprints" can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.

INFORM: INFrared-based ORganizational Measurements of tumor and its microenvironment to predict patient survival

The structure and organization of a tumor and its microenvironment are often associated with cancer outcomes due to spatially varying molecular composition and signaling. A persistent challenge is to use this physical and chemical spatial organization to understand cancer progression. Here, we present a high-definition infrared imaging-based organizational measurement framework (INFORM) that leverages intrinsic chemical contrast of tissue to label unique components of the tumor and its microenvironment. Using objective and automated computational methods, further, we determine organization characteristics important for prediction. We show that the tumor spatial organization assessed with this framework is predictive of overall survival in colon cancer that adds to capability from clinical variables such as stage and grade, approximately doubling the risk of death in high-risk individuals. Our results open an all-digital avenue for measuring and studying the association between tumor spatial organization and disease progression.

Characterization of connective tissues using near-infrared spectroscopy and imaging

Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue's biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.

Highly specific and label-free histological identification of microcrystals in fresh human gout tissues with stimulated Raman scattering

Gout is a common metabolic disease with growing burden, caused by monosodium urate (MSU) microcrystal deposition. In situ and chemical-specific histological identification of MSU is crucial in the diagnosis and management of gout, yet it remains inaccessible for current histological methods. Methods: Stimulated Raman scattering (SRS) microscopy was utilized to image MSU based on its fingerprint Raman spectra. We first tested SRS for the diagnosis capability of gout and the differentiation power from pseudogout with rat models of acute gout arthritis, calcium pyrophosphate deposition disease (CPDD) and comorbidity. Then, human synovial fluid and surgical specimens (n=120) were were imaged with SRS to obtain the histopathology of MSU and collagen fibers. Finally, quantitative SRS analysis was performed in gout tissue of different physiological phases (n=120) to correlate with traditional histopathology including H&E and immunohistochemistry staining. Results: We demonstrated that SRS is capable of early diagnosis of gout, rapid detection of MSU in synovial fluid and fresh unprocessed surgical tissues, and accurate differentiation of gout from pseudogout in various pathophysiological conditions. Furthermore, quantitative SRS analysis revealed the optical characteristics of MSU deposition at different pathophysiological stages, which were found to matched well with corresponding immunofluorescence histochemistry features. Conclusion: Our work demonstrated the potential of SRS microscopy for rapid intraoperative diagnosis of gout and may facilitate future fundamental researches of MSU-based diseases.

Compressed FTIR spectroscopy using low-rank matrix reconstruction

Fourier transform infrared (FTIR) spectroscopy is a powerful technique in analytical chemistry. Typically, spatially distributed spectra of the substance of interest are conducted simultaneously using FTIR spectrometers equipped with array detectors. Scanning-based methods such as near-field FTIR spectroscopy, on the other hand, are a promising alternative providing higher spatial resolution. However, serial recording severely limits their application due to the long acquisition times involved and the resulting stability issues. We demonstrate that it is possible to significantly reduce the measurement time of scanning methods by applying the mathematical technique of low-rank matrix reconstruction. Data from a previous pilot study of Leishmania strains are analyzed by randomly selecting 5% of the interferometer samples. The results obtained for bioanalytical fingerprinting using the proposed approach are shown to be essentially the same as those obtained from the full set of data. This finding can significantly foster the practical applicability of high-resolution serial scanning techniques in analytical chemistry and is also expected to improve other applications of FTIR spectroscopy and spectromicroscopy.

Nonvolatile, Reconfigurable and Narrowband Mid-Infrared Filter Based on Surface Lattice Resonance in Phase-Change Ge2Sb2Te5

We propose a nonvolatile, reconfigurable, and narrowband mid-infrared bandpass filter based on surface lattice resonance in phase-change material Ge2Sb2Te5. The proposed filter is composed of a two-dimensional gold nanorod array embedded in a thick Ge2Sb2Te5 film. Results show that when Ge2Sb2Te5 transits from the amorphous state to the crystalline state, the narrowband reflection spectrum of the proposed filter is tuned from 3.197 μm to 4.795 μm, covering the majority of the mid-infrared regime, the peak reflectance decreases from 72.6% to 25.8%, and the corresponding quality factor decreases from 19.6 to 10.3. We show that the spectral tuning range can be adjusted by varying the incidence angle or the lattice period. By properly designing the gold nanorod sizes, we also show that the quality factor can be greatly increased to 70 at the cost of relatively smaller peak reflection efficiencies, and that the peak reflection efficiency can be further increased to 80% at the cost of relatively smaller quality factors. We expect that this work will advance the engineering of Ge2Sb2Te5-based nonvalatile tunable surface lattice resonances and will promote their applications especially in reconfigurable narrowband filters.

Deep convolutional neural network recovers pure absorbance spectra from highly scatter-distorted spectra of cells

Infrared spectroscopy of cells and tissues is prone to Mie scattering distortions, which grossly obscure the relevant chemical signals. The state-of-the-art Mie extinction extended multiplicative signal correction (ME-EMSC) algorithm is a powerful tool for the recovery of pure absorbance spectra from highly scatter-distorted spectra. However, the algorithm is computationally expensive and the correction of large infrared imaging datasets requires weeks of computations. In this paper, we present a deep convolutional descattering autoencoder (DSAE) which was trained on a set of ME-EMSC corrected infrared spectra and which can massively reduce the computation time for scatter correction. Since the raw spectra showed large variability in chemical features, different reference spectra matching the chemical signals of the spectra were used to initialize the ME-EMSC algorithm, which is beneficial for the quality of the correction and the speed of the algorithm. One DSAE was trained on the spectra, which were corrected with different reference spectra and validated on independent test data. The DSAE outperformed the ME-EMSC correction in terms of speed, robustness, and noise levels. We confirm that the same chemical information is contained in the DSAE corrected spectra as in the spectra corrected with ME-EMSC.

Microscopy with undetected photons in the mid-infrared

Owing to its capacity for unique (bio)-chemical specificity, microscopy with mid-infrared (IR) illumination holds tremendous promise for a wide range of biomedical and industrial applications. The primary limitation, however, remains detection, with current mid-IR detection technology often marrying inferior technical capabilities with prohibitive costs. Here, we experimentally show how nonlinear interferometry with entangled light can provide a powerful tool for mid-IR microscopy while only requiring near-IR detection with a silicon-based camera. In this proof-of-principle implementation, we demonstrate widefield imaging over a broad wavelength range covering 3.4 to 4.3 μm and demonstrate a spatial resolution of 35 μm for images containing 650 resolved elements. Moreover, we demonstrate that our technique is suitable for acquiring microscopic images of biological tissue samples in the mid-IR. These results form a fresh perspective for potential relevance of quantum imaging techniques in the life sciences.

Hyperspectral infrared microscopy with visible light

Hyperspectral microscopy is an imaging technique that provides spectroscopic information with high spatial resolution. When applied in the relevant wavelength region, such as in the infrared (IR), it can reveal a rich spectral fingerprint across different regions of a sample. Challenges associated with low efficiency and high cost of IR light sources and detector arrays have limited its broad adoption. Here, we introduce a new approach to IR hyperspectral microscopy, where the IR spectral map is obtained with off-the-shelf components built for visible light. The method is based on the nonlinear interference of correlated photons generated via parametric down-conversion. In this proof-of-concept we demonstrate the chemical mapping of a patterned sample, where different areas have distinctive IR spectroscopic fingerprints. The method provides a wide field of view, fast readout, and negligible heat delivered to the sample, which opens prospects for its further development for applications in material and biological studies.

Grayscale representation of infrared microscopy images by extended multiplicative signal correction for registration with histological images

Fourier-transform infrared (FTIR) microspectroscopy is rounding the corner to become a label-free routine method for cancer diagnosis. In order to build infrared-spectral based classifiers, infrared images need to be registered with Hematoxylin and Eosin (H&E) stained histological images. While FTIR images have a deep spectral domain with thousands of channels carrying chemical and scatter information, the H&E images have only three color channels for each pixel and carry mainly morphological information. Therefore, image representations of infrared images are needed that match the morphological information in H&E images. In this paper, we propose a novel approach for representation of FTIR images based on extended multiplicative signal correction highlighting morphological features that showed to correlate well with morphological information in H&E images. Based on the obtained representations, we developed a strategy for global-to-local image registration for FTIR images and H&E stained histological images of parallel tissue sections.

Infrared chemical imaging through non-degenerate two-photon absorption in silicon-based cameras

Chemical imaging based on mid-infrared (MIR) spectroscopic contrast is an important technique with a myriad of applications, including biomedical imaging and environmental monitoring. Current MIR cameras, however, lack performance and are much less affordable than mature Si-based devices, which operate in the visible and near-infrared regions. Here, we demonstrate fast MIR chemical imaging through non-degenerate two-photon absorption (NTA) in a standard Si-based charge-coupled device (CCD). We show that wide-field MIR images can be obtained at 100 ms exposure times using picosecond pulse energies of only a few femtojoules per pixel through NTA directly on the CCD chip. Because this on-chip approach does not rely on phase matching, it is alignment-free and does not necessitate complex postprocessing of the images. We emphasize the utility of this technique through chemically selective MIR imaging of polymers and biological samples, including MIR videos of moving targets, physical processes and live nematodes.

Closed-loop atomic force microscopy-infrared spectroscopic imaging for nanoscale molecular characterization

Atomic force microscopy-infrared (AFM-IR) spectroscopic imaging offers non-perturbative, molecular contrast for nanoscale characterization. The need to mitigate measurement artifacts and enhance sensitivity, however, requires narrowly-defined and strict sample preparation protocols. This limits reliable and facile characterization; for example, when using common substrates such as Silicon or glass. Here, we demonstrate a closed-loop (CL) piezo controller design for responsivity-corrected AFM-IR imaging. Instead of the usual mode of recording cantilever deflection driven by sample expansion, the principle of our approach is to maintain a zero amplitude harmonic cantilever deflection by CL control of a subsample piezo. We show that the piezo voltage used to maintain a null deflection provides a reliable measure of the local IR absorption with significantly reduced noise. A complete analytical description of the CL operation and characterization of the controller for achieving robust performance are presented. Accurate measurement of IR absorption of nanothin PMMA films on glass and Silicon validates the robust capability of CL AFM-IR in routine mapping of nanoscale molecular information.

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%.

Mid-Infrared Frequency Comb Generation and Spectroscopy with Few-Cycle Pulses and χ^{(2)} Nonlinear Optics

The mid-infrared atmospheric window of 3-5.5  μm holds valuable information regarding molecular composition and function for fundamental and applied spectroscopy. Using a robust, mode-locked fiber-laser source of <11  fs pulses in the near infrared, we explore quadratic (χ^{(2)}) nonlinear optical processes leading to frequency comb generation across this entire mid-infrared atmospheric window. With experiments and modeling, we demonstrate intrapulse difference frequency generation that yields few-cycle mid-infrared pulses in a single pass through periodically poled lithium niobate. Harmonic and cascaded χ^{(2)} nonlinearities further provide direct access to the carrier-envelope offset frequency of the near infrared driving pulse train. The high frequency stability of the mid-infrared frequency comb is exploited for spectroscopy of acetone and carbonyl sulfide with simultaneous bandwidths exceeding 11 THz and with spectral resolution as high as 0.003  cm^{-1}. The combination of low noise and broad spectral coverage enables detection of trace gases with concentrations in the part-per-billion range.