High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams

Modeling the Thermoelastic Sample Response for Subdiffraction Infrared Spectroscopic Imaging

There is significant and increasing interest in using the photothermal effect to record infrared (IR) absorption spectra localized to volumes that are considerably smaller than the wavelength of excitation, i.e., subdiffraction imaging. As opposed to conventional IR microscopy, in which absorption and scattering of the illuminating light is measured, subdiffraction imaging can be achieved through detection of the sample's thermal response to IR absorption-induced heating. While this relationship has been examined by a variety of coarse-grained models, a generalized analysis of the dependence of temperature and surface deformation arising from an absorber below the surface has not been reported. Here, we present an analytical model to understand a sample's thermoelastic response in photothermal measurements. The model shows important dependence of the ability to record subdiffraction data on modulation frequency of exciting light, limitations imposed by optical sensing, and the potential to discern location of objects ultimately limited by noise and sharpness of the detecting mechanism. This foundational analysis should allow for better modeling, understanding, and harnessing of the relationship between absorption and sample response that underlies IR photothermal measurements.

Sensitive Discrete Frequency Mid-Infrared Absorption Spectroscopy Using Digitally Referenced Detection

Broadly tunable mid-infrared (IR) lasers, including quantum cascade lasers (QCL), are an asset for vibrational spectroscopy wherein high-intensity, coherent illumination can target specific spectral bands for rapid, direct chemical detection with microscopic localization. These emerging spectrometers are capable of high measurement throughputs with large detector signals from the high-intensity lasers and fast detection speeds as short as a single laser pulse, challenging the decades old benchmarks of Fourier transform infrared spectroscopy. However, noise in QCL emissions limits the feasible acquisition time for high signal-to-noise ratio (SNR) data. Here, we present an implementation that is broadly compatible with many laser-based spectrometer and microscope designs to address these limitations by leveraging high-speed digitizers and dual detectors to digitally reference each pulse individually. Digitally referenced detection (DRD) is shown to improve measurement sensitivity, with broad spectral indifference, regardless of imbalance due to dissimilarities among system designs or component manufacturers. We incorporated DRD into existing instruments and demonstrated its generalizability: a spectrometer with a 10-fold reduction in spectral noise, a microscope with reduced pixel dwell times to as low as 1 pulse while maintaining SNR normally achieved when operating 8-fold slower, and finally, a spectrometer to measure vibrational circular dichroism (VCD) with a ∼ 4-fold reduction in scan times. The approach not only proves versatile and effective but can also be tailored for specific applications with minimal hardware changes, positioning it as a simple and promising module for spectrometer designs using lasers.

Phase-shifting optothermal microscopy enables live-cell mid-infrared hyperspectral imaging of large cell populations at high confluency

Rapid live-cell hyperspectral imaging at large fields of view (FOVs) and high cell confluency remains challenging for conventional vibrational spectroscopy-based microscopy technologies. At the same time, imaging at high cell confluency and large FOVs is important for proper cell function and statistical significance of measurements, respectively. Here, we introduce phase-shifting mid-infrared optothermal microscopy (PSOM), which interprets molecular-vibrational information as the optical path difference induced by mid-infrared absorption and can take snapshot vibrational images over broad excitation areas at high live-cell confluency. By means of phase-shifting, PSOM suppresses noise to a quarter of current optothermal microscopy modalities to allow capturing live-cell vibrational images at FOVs up to 50 times larger than state of the art. PSOM also reduces illumination power flux density (PFD) down to four orders of magnitude lower than other conventional vibrational microscopy methods, such as coherent anti-Stokes Raman scattering (CARS), thus considerably decreasing the risk of cell photodamage.

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.

Phasor Representation Approach for Rapid Exploratory Analysis of Large Infrared Spectroscopic Imaging Data Sets

Infrared (IR) spectroscopic imaging is potentially useful for digital histopathology as it provides spatially resolved molecular absorption spectra, which can subsequently yield useful information by powerful artificial intelligence methods. A typical analysis pipeline in using IR imaging data for chemical pathology often involves iterative processes of segmentation, evaluation, and analysis that necessitate rapid data exploration. Here, we present a fast, reliable, and intuitive method based on a phasor representation of spectra and discuss its unique applicability for IR imaging data. We simulate different features extant in IR spectra and discuss their influence on the phasor waveforms; similarly, we undertake IR image analysis in the transform space to understand spectral similarity and variance. We demonstrate the potential of phasor analysis for biomedical tissue imaging using a variety of samples, using fresh frozen surgical prostate resections and formalin-fixed paraffin-embedded breast cancer tissue microarray samples as model systems that span common histopathology practice. To demonstrate further generalizability of this approach, we apply the method to data from different experimental conditions─including standard (5.5 μm × 5.5 μm pixel size) and high-definition (1.1 μm × 1.1 μm pixel size) Fourier transform IR (FTIR) spectroscopic imaging using transmission and transflection modes. Quantitative segmentation results from our approach are compared to previous studies, showing good agreement and quick visualization. The presented method is rapid, easy to use, and highly capable of deciphering compositional differences, presenting a convenient tool for exploratory analysis of IR imaging data.

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.

Development of Line-Detected UV-Vis Absorption Microscope and Its Application to Quantitative Evaluation of Lithium Surface Reactivity

Electrochemical reactions in practical batteries occur in confined environments where anode and cathode electrodes are separated only by a thin separator. Therefore, their electrochemical behaviors may differ from those obtained in the conventional experimental cells, where the two electrodes (working and counter electrodes) are largely separated compared to the batteries. The spatial and temporal distributions of the chemical species in the vicinity of each electrode are highly expected to be determined for quantitatively understanding the phenomena in confined environments. In the present study, we developed a line-detected UV-vis absorption microscope that simultaneously measures space-resolved UV-vis absorption spectra. This novel technique has been successfully applied to evaluate the reactivities of the highly reactive lithium (Li) surfaces in organic electrolyte solutions under in situ conditions. The quantitative evaluations of the dissolution rate of Li and the diffusion constant of the product were successfully realized by analyzing the space- and time-resolved absorption spectra based on Fick's law of diffusion. The microscopic technique is expected to open the door to understanding the fundamental electrochemistry in batteries.

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.

Advances in Molecular and Microscale Characterization of Soil Organic Matter: Current Limitations and Future Prospects

Soil organic matter (SOM) comprises a continuum of organic materials from granular organic debris to small organic molecules and contains more organic carbon than global vegetation and the atmosphere combined. It has remarkable effects on soil ecological functions and the global carbon cycle as well as the fate of pollutants in the terrestrial ecosystem. Therefore, characterization of SOM is an important topic in soil science, ecology, and environmental science. Chemical complexity and spatial heterogeneity are by far the two biggest challenges to our understanding of SOM. Recent developments in analytical techniques and methods provide the opportunity to reveal SOM composition at the molecular level and to observe its distribution in soils at micro- and nanoscales, which have greatly improved our understanding of SOM. This paper reviews the outstanding advances in SOM characterization regarding these two issues from target and nontarget analyses comprising molecular marker analysis, ultrahigh-resolution mass spectrometry analysis, and in situ microscopic imaging techniques such as synchrotron-based spectromicroscopy, nanoscale secondary ion mass spectrometry, and emerging electron and optical microscopic imaging techniques. However, current techniques and methods remain far from unlocking the unknown properties of SOM. We systematically point out the limitations of the current technologies and outline the future prospects for comprehensive characterization of SOM at the molecular level and micro- and nanoscales, paying particular attention to issues of environmental concern.

Characterisation of breast cancer molecular signature and treatment assessment with vibrational spectroscopy and chemometric approach

Triple negative breast cancer (TNBC) is regarded as the most aggressive breast cancer subtype with poor overall survival and lack of targeted therapies, resulting in many patients with recurrent. The insight into the detailed biochemical composition of TNBC would help develop dedicated treatments. Thus, in this study Fourier Transform Infrared microspectroscopy combined with chemometrics and absorbance ratios investigation was employed to compare healthy controls with TNBC tissue before and after chemotherapy within the same patient. The primary spectral differences between control and cancer tissues were found in proteins, polysaccharides, and nucleic acids. Amide I/Amide II ratio decrease before and increase after chemotherapy, whereas DNA, RNA, and glycogen contents increase before and decrease after the treatment. The chemometric results revealed discriminatory features reflecting a clinical response scheme and proved the chemotherapy efficacy assessment with infrared spectroscopy is possible.

Advances in mid-infrared spectroscopy enabled by supercontinuum laser sources

Supercontinuum sources are all-fiber pulsed laser-driven systems that provide high power spectral densities within ultra-broadband spectral ranges. The tailored process of generating broadband, bright, and spectrally flat supercontinua-through a complex interplay of linear and non-linear processes-has been recently pushed further towards longer wavelengths and has evolved enough to enter the field of mid-infrared (mid-IR) spectroscopy. In this work, we review the current state and perspectives of this technology that offers laser-like emission properties and instantaneous broadband spectral coverage comparable to thermal emitters. We aim to go beyond a literature review. Thus, we first discuss the basic principles of supercontinuum sources and then provide an experimental part focusing on the quantification and analysis of intrinsic emission properties such as typical power spectral densities, brightness levels, spectral stability, and beam quality (to the best of the authors' knowledge, the M² factor for a mid-IR supercontinuum source is characterized for the first time). On this basis, we identify key competitive advantages of these alternative emitters for mid-IR spectroscopy over state-of-the-art technologies such as thermal sources or quantum cascade lasers. The specific features of supercontinuum radiation open up prospects of improving well-established techniques in mid-IR spectroscopy and trigger developments of novel analytical methods and instrumentation. The review concludes with a structured summary of recent advances and applications in various routine mid-IR spectroscopy scenarios that have benefited from the use of supercontinuum sources.

On the Limit of Detection in Infrared Spectroscopic Imaging

Infrared (IR) spectroscopic imaging instruments' performance can be characterized and optimized by an analysis of their limit of detection (LOD). Here we report a systematic analysis of the LOD for Fourier transform IR (FT-IR) and discrete frequency IR (DFIR) imaging spectrometers. In addition to traditional measurements of sample and blank data, we propose a decision theory perspective to pose the determination of LOD as a binary classification problem under different assumptions of noise uniformity and correlation. We also examine three spectral analysis approaches, namely, absorbance at a single frequency, average of absorbance over selected frequencies and total spectral distance - to suit instruments that acquire discrete or contiguous spectral bandwidths. The analysis is validated by refining the fabrication of a bovine serum albumin protein microarray to provide eight uniform spots from ∼2.8 nL of solution for each concentration over a wide range (0.05-10 mg/mL). Using scanning parameters that are typical for each instrument, we estimate a LOD of 0.16 mg/mL and 0.12 mg/mL for widefield and line scanning FT-IR imaging systems, respectively, using the spectral distance approach, and 0.22 mg/mL and 0.15 mg/mL using an optimal set of discrete frequencies. As expected, averaging and the use of post-processing techniques such as minimum noise fraction transformation results in LODs as low as ∼0.075 mg/mL that correspond to a spotted protein mass of ∼112 fg/pixel. We emphasize that these measurements were conducted at typical imaging parameters for each instrument and can be improved using the usual trading rules of IR spectroscopy. This systematic analysis and methodology for determining the LOD can allow for quantitative measures of confidence in imaging an analyte's concentration and a basis for further improving IR imaging technology.

High-resolution infrared microspectroscopic characterization of cartilage cell microenvironment

The lateral resolution of infrared spectroscopy has been inadequate for accurate biochemical characterization of the cell microenvironment, a region regulating biochemical and biomechanical signals to cells. In this study, we demonstrate the capacity of a high-resolution Fourier transform infrared microspectroscopy (HR-FTIR-MS) to characterize the collagen content of this region. Specifically, we focus on the collagen content in the cartilage cell (chondrocyte) microenvironment of healthy and osteoarthritic (OA) cartilage. Human tibial cartilage samples (N = 28) were harvested from 7 cadaveric donors and graded for OA severity (healthy, early OA, advanced OA). HR-FTIR-MS was used to analyze the collagen content of the chondrocyte microenvironment of five distinct zones across the tissue depth. HR-FTIR-MS successfully showed collagen content distribution across chondrocytes and their environment. In zones 2 and 3 (10 - 50% of the tissue thickness), we observed that collagen content was smaller (P < 0.05) in early OA compared to the healthy tissue in the vicinity of cells (pericellular region). The collagen content loss was extended to the extracellular matrix in advanced OA tissue. No significant differences in the collagen content of the chondrocyte microenvironment were observed between the groups in the most superficial (0-10%) and deep zones (50-100%). HR-FTIR-MS revealed collagen loss in the early OA cartilage pericellular region before detectable changes in the extracellular matrix in advanced OA. HR-FTIR-MS-based compositional assessment enables a better understanding of OA-related changes in tissues. This technique can be used to identify new disease mechanisms enabling better intervention strategies. STATEMENT OF SIGNIFICANCE: Osteoarthritis (OA) is the most common degenerative joint disease causing pain and disability. While significant progress has been made in OA research, OA pathogenesis is still poorly understood and current OA treatments are mainly palliative. This study demonstrates that high-resolution FTIR microspectroscopy (HR-FTIR-MS) can characterize OA-induced compositional changes in the cell microenvironment (pericellular matrix) during the early disease stages before tissue changes in the extracellular matrix become apparent. This technique may further enable the identification of new OA mechanisms and improve our current understanding of OA pathogenesis, thus, enabling the development of better treatment methods.

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.

Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy

Mid-infrared Spectroscopic Imaging (MIRSI) provides spatially-resolved molecular specificity by measuring wavelength-dependent mid-infrared absorbance. Infrared microscopes use large numerical aperture objectives to obtain high-resolution images of heterogeneous samples. However, the optical resolution is fundamentally diffraction-limited, and therefore wavelength-dependent. This significantly limits resolution in infrared microscopy, which relies on long wavelengths (2.5 μm to 12.5 μm) for molecular specificity. The resolution is particularly restrictive in biomedical and materials applications, where molecular information is encoded in the fingerprint region (6 μm to 12 μm), limiting the maximum resolving power to between 3 μm and 6 μm. We present an unsupervised curvelet-based image fusion method that overcomes limitations in spatial resolution by augmenting infrared images with label-free visible microscopy. We demonstrate the effectiveness of this approach by fusing images of breast and ovarian tumor biopsies acquired using both infrared and dark-field microscopy. The proposed fusion algorithm generates a hyperspectral dataset that has both high spatial resolution and good molecular contrast. We validate this technique using multiple standard approaches and through comparisons to super-resolved experimentally measured photothermal spectroscopic images. We also propose a novel comparison method based on tissue classification accuracy.

Autofluorescence spectroscopy and multivariate analysis for predicting the induced damages to other organs due to liver fibrosis

When our liver does not work well, it can induce damage to other organs causing their dysfunction. With this background, we aim to study the effect of liver fibrosis on other organs such as heart, lungs, kidney and spleen by assessing the variations in the inherent emission property of the tissue, using fluorescence spectroscopy. Fluorescence emission spectra from excised organs of liver fibrosis induced rats were collected at excitation wavelengths 320 and 410 nm. Optical redox ratio derived from the spectral data supported by multivariate statistical analysis, principal component analysis followed by linear discriminant analysis (PCA-LDA) distinguished between control and fibrosis induced groups. The two different excitation wavelength provided variations in the endogenous flurophores collagen, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD), lipopigments and porphyrins. Additionally, evaluation of redox ratio provided variations in tissue metabolic activity of different organs. The PCA-LDA modelling yielded a sensitivity of 85 to 97% and specificity of 80 to 96% on 320 nm excitation and a sensitivity of 72 to 100% and specificity of 59 to 100% on 410 nm excitation. Fluorescence emission spectral study along with multivariate analysis paved way to identify the biochemical alterations caused to other organs due to the development of liver fibrosis, which could lead to their damage and dysfunction.

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

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

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Snapshot three-dimensional absorption imaging of microscopic specimens

Snapshot projection optical tomography (SPOT) uses a micro-lens array (MLA) to simultaneously capture the projection images of a three-dimensional (3D) specimen corresponding to different viewing directions. Compared to other light-field imaging techniques using an MLA, SPOT is dual telecentric and can block high-angle stray rays without sacrificing the light collection efficiency. Using SPOT, we recently demonstrated snapshot 3D fluorescence imaging. Here we demonstrate snapshot 3D absorption imaging of microscopic specimens. For the illumination, we focus the incoherent light from a light-emitting diode onto a pinhole, which is placed at a conjugate plane to the sample plane. SPOT allows us to capture the ray bundles passing through the specimen along different directions. The images recorded by an array of lenslets can be related to the projections of 3D absorption coefficient along the viewing directions of lenslets. Using a tomographic reconstruction algorithm, we obtain the 3D map of absorption coefficient. We apply the developed system to different types of samples, which demonstrates the optical sectioning capability. The transverse and axial resolutions measured with gold nanoparticles are 1.3 μm and 2.3 μm, respectively.

Infrared Microspectroscopy With Multivariate Analysis to Differentiate Oral Hyperplasia From Squamous Cell Carcinoma: A Proof of Concept for Early Diagnosis

BACKGROUND AND OBJECTIVES

Despite having numerous advances in therapeutics, mortality and morbidity due to oral cancer incidence are still very high. Early detection can improve the chances of survival in most patients. However, diagnosis at early stages can be challenging as premalignant conditions are usually asymptomatic. Currently, histological assessment remains the gold standard for diagnosis. Early diagnosis poses challenges to pathologists due to less severe morphological changes associated with early stages. Therefore, a fast and robust method of detection based on molecular changes is needed for early diagnosis. © 2021 Wiley Periodicals LLC.

STUDY DESIGN/MATERIAL AND METHODS

In the present study, Fourier transform infrared (FTIR) spectroscopic imaging has been used to differentiate early-stage oral hyperplasia from adjacent normal (AN) and oral squamous cell carcinoma (OSCC). Hyperplasia is often considered as an initial event in the pathogenesis of oral cancer and OSCC is the most common advanced stage of malignancy. Differentiating normal versus hyperplasia and hyperplasia versus OSCC can remain quite challenging on occasion using conventional staining as the histological assessment is based on morphological changes.

RESULTS

Unsupervised hierarchical cluster analysis (UHCA) has been performed on FTIR images of multiple tissues together that provided some degree of classification among tissue groups. The AN epithelium clustered distinctively using UHCA from both hyperplasia and grades 1 and 2 of OSCC. An increase in the content of DNA, denaturation of protein, and altered lipid structures were more clearly elucidated with spectral analysis.

CONCLUSION

This study demonstrates a simple strategy to differentiate early-stage oral hyperplasia from AN and OSCC using UHCA. This study also proposes a future alternative method where FTIR imaging can be used as a diagnostic tool for cancer at early stages.

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.

Mapping sub-cellular protein aggregates and lipid inclusions using synchrotron ATR-FTIR microspectroscopy

Visualising direct biochemical markers of cell physiology and disease pathology at the sub-cellular level is an ongoing challenge in the biological sciences. A suite of microscopies exists to either visualise sub-cellular architecture or to indirectly view biochemical markers (e.g. histochemistry), but further technique developments and innovations are required to increase the range of biochemical parameters that can be imaged directly, in situ, within cells and tissue. Here, we report our continued advancements in the application of synchrotron radiation attenuated total reflectance Fourier transform infrared (SR-ATR-FTIR) microspectroscopy to study sub-cellular biochemistry. Our recent applications demonstrate the much needed capability to map or image directly sub-cellular protein aggregates within degenerating neurons as well as lipid inclusions within bacterial cells. We also characterise the effect of spectral acquisition parameters on speed of data collection and the associated trade-offs between a realistic experimental time frame and spectral/image quality. Specifically, the study highlights that the choice of 8 cm^-1 spectral resolutions provide a suitable trade-off between spectral quality and collection time, enabling identification of important spectroscopic markers, while increasing image acquisition by ∼30% (relative to 4 cm^-1 spectral resolution). Further, this study explores coupling a focal plane array detector with SR-ATR-FTIR, revealing a modest time improvement in image acquisition time (factor of 2.8). Such information continues to lay the foundation for these spectroscopic methods to be readily available for, and adopted by, the biological science community to facilitate new interdisciplinary endeavours to unravel complex biochemical questions and expand emerging areas of study.

Highly Strong and Solvent-Resistant Cellulose Nanocrystal Photonic Films for Optical Coatings

Cellulose nanocrystals (CNCs) are powerful photonic building blocks for the fabrication of biosourced colored films. A combination of the advantages of self-assembled CNCs and multiple templating agents offers access to the development of novel physicochemical sensors, structural coatings, and optic devices. However, due to the inherent brittleness and water instability of CNC-derived materials, their further applications are widely questionable and restrictive. Here, a soft polymer of poly(vinyl alcohol) (PVA) was introduced into the rigid CNC system to balance molecular interactions, whereafter two hard/soft nanocomposites were fastened through a cross-linking reaction of glutaraldehyde (GA), resulting in a highly flexible, water-stable, and chiral nematic CNC composite film through an evaporation-induced self-assembly technique. For a 1.5 wt % GA-cross-linked 70 wt % CNC loading film, its treatment with harsh hydrophilic exposure (soaking in a strong acid, strong base, and seawater) and various organic solvents show exceptional solvent-resistant abilities. Furthermore, the film can even withstand a weight of 167 g cm^-2 without failure, which is a highly stiff and durable character. Importantly, the film remains a highly ordered chiral nematic organization, being able to act as a highly transparent substrate for selective reflection of left-handed circularly polarized light, preparing fully covered and patterned full-color coatings on various substrates. Our work paves the way for applications in low-cost, durable, and photonic cellulosic coatings.

Analysis of Fixed and Live Single Cells Using Optical Photothermal Infrared with Concomitant Raman Spectroscopy

This paper reports the first use of a novel completely optically based photothermal method (O-PTIR) for obtaining infrared spectra of both fixed and living cells using a quantum cascade laser (QCL) and optical parametric oscillator (OPO) laser as excitation sources, thus enabling all biologically relevant vibrations to be analyzed at submicron spatial resolution. In addition, infrared data acquisition is combined with concomitant Raman spectra from exactly the same excitation location, meaning the full vibrational profile of the cell can be obtained. The pancreatic cancer cell line MIA PaCa-2 and the breast cancer cell line MDA-MB-231 are used as model cells to demonstrate the capabilities of the new instrumentation. These combined modalities can be used to analyze subcellular structures in both fixed and, more importantly, live cells under aqueous conditions. We show that the protein secondary structure and lipid-rich bodies can be identified on the submicron scale.

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.

Synchrotron Radiation-Based FTIR Microspectroscopic Imaging of Traumatically Injured Mouse Brain Tissue Slices

Traumatic brain injury (TBI) is a health problem of global concern because of its serious adverse effects on public health and social economy. A technique that can be used to precisely detect TBI is highly demanded. Here, we report on a synchrotron radiation-based Fourier transform infrared (SR-FTIR) microspectroscopic imaging technique that can be exploited to identify TBI-induced injury by examining model mouse brain tissue slices. The samples were first examined by conventional histopathological techniques including hematoxylin and eosin (H&E) staining and 2,3,5-triphenyltetrazolium chloride staining and then spectroscopically imaged by SR-FTIR. SR-FTIR results show that the contents of protein and nucleic acid in the injured region are lower than their counterparts in the normal region. The injured and normal regions can be unambiguously distinguished from each other by the principle component analysis of the SR-FTIR spectral data corresponding to protein or nucleic acid. The images built from the spectral data of protein or nucleic acid clearly present the injured region of the brain tissue, which is in good agreement with the H&E staining image and optical image of the sample. Given the label-free and fingerprint features, the demonstrated method suggests potential application of SR-FTIR spectroscopic mapping for the digital and intelligent diagnosis of TBI by providing spatial and chemical information of the sample simultaneously.

Infrared spectral microscopy as a tool to monitor lung fibrosis development in a model system

Tissue fibrosis is a progressive and destructive disease process that can occur in many different organs including the liver, kidney, skin, and lungs. Fibrosis is typically initiated by inflammation as a result of chronic insults such as infection, chemicals and autoimmune diseases. Current approaches to examine organ fibrosis are limited to radiological and histological analyses. Infrared spectroscopic imaging offers a potential alternative approach to gain insight into biochemical changes associated with fibrosis progression. In this study, we demonstrate that IR imaging of a mouse model of pulmonary fibrosis can identify biochemical changes observed with fibrosis progression and the beginning of resolution using K-means analysis, spectral ratios and multivariate data analysis. This study demonstrates that IR imaging may be a useful approach to understand the biochemical events associated with fibrosis initiation, progression and resolution for both the clinical setting and for assessing novel anti-fibrotic drugs in a model system.

Resolution Enhancement in Wide-Field IR Imaging and Time-Domain Spectroscopy Using Dielectric Microspheres

Wide-field imaging through dielectric microspheres has emerged in recent years as a simple and effective approach for generating super-resolution images at visible wavelengths. We present, to our knowledge, the first demonstration that dielectric microspheres can be used in a wide-field infrared (IR) microscope to enhance the far field resolution. We have observed a substantial improvement in resolution and magnification when images are collected through polystyrene microspheres. In addition, we demonstrate that spectroscopic imaging with a pulse-shaper based femtosecond mid-IR laser system is possible through the dielectric microspheres, which is a promising first step toward applying this technique to ultrafast IR imaging methods such as pump-probe and 2DIR microscopy.

Synchrotron Photothermal Infrared Nanospectroscopy of Drug-Induced Phospholipidosis in Macrophages

Synchrotron resonance-enhanced infrared atomic force microscopy (RE-AFM-IR) is a near-field photothermal vibrational nanoprobe developed at Diamond Light Source (DLS), capable of measuring mid-infrared absorption spectra with spatial resolution around 100 nm. The present study reports a first application of synchrotron RE-AFM-IR to interrogate biological soft matter at the subcellular level, in this case, on a cellular model of drug-induced phospholipidosis (DIPL). J774A-1 macrophages were exposed to amiodarone (10 μM) or medium for 24 h and chemically fixed. AFM topography maps revealed amiodarone-treated cells with enlarged cytoplasm and very thin regions corresponding to collapsed vesicles. IR maps of the whole cell were analyzed by exploiting the RE-AFM-IR overall signal, i.e., the integrated RE-AFM-IR signal amplitude versus AFM-derived cell thickness, also on lateral resolution around 100 nm. Results show that vibrational band assignment was possible, and all characteristic peaks for lipids, proteins, and DNA/RNA were identified. Both peak ratio and unsupervised chemometric analysis of RE-AFM-IR nanospectra generated from the nuclear and perinuclear regions of untreated and amiodarone-treated cells showed that the perinuclear region (i.e., cytoplasm) of amiodarone-treated cells had significantly elevated band intensities in the regions corresponding to phosphate and carbonyl groups, indicating detection of phospholipid-rich inclusion bodies typical for cells with DIPL. The results of this study are of importance to demonstrate not only the applicability of Synchrotron RE-AFM-IR to soft biological matters with subcellular spatial resolution but also that the spectral information gathered from an individual submicron sample volume enables chemometric identification of treatment and biochemical differences between mammalian cells.

Origin of micro-scale heterogeneity in polymerisation of photo-activated resin composites

Photo-activated resin composites are widely used in industry and medicine. Despite extensive chemical characterisation, the micro-scale pattern of resin matrix reactive group conversion between filler particles is not fully understood. Using an advanced synchrotron-based wide-field IR imaging system and state-of-the-art Mie scattering corrections, we observe how the presence of monodispersed silica filler particles in a methacrylate based resin reduces local conversion and chemical bond strain in the polymer phase. Here we show that heterogeneity originates from a lower converted and reduced bond strain boundary layer encapsulating each particle, whilst at larger inter-particulate distances light attenuation and monomer mobility predominantly influence conversion. Increased conversion corresponds to greater bond strain, however, strain generation appears sensitive to differences in conversion rate and implies subtle distinctions in the final polymer structure. We expect these findings to inform current predictive models of mechanical behaviour in polymer-composite materials, particularly at the resin-filler interface.

Resin-based-composites are widely used in industry and medicine but the influence of the filler particles on the reactive group conversion in photocurable resins is yet to be elucidated. Here the authors observe reduced local conversion and chemical bond strain in silica filler acrylate composite using synchrotron-based wide-field IR imaging.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

All-digital histopathology by infrared-optical hybrid microscopy

Optical microscopy for biomedical samples requires expertise in staining to visualize structure and composition. Midinfrared (mid-IR) spectroscopic imaging offers label-free molecular recording and virtual staining by probing fundamental vibrational modes of molecular components. This quantitative signal can be combined with machine learning to enable microscopy in diverse fields from cancer diagnoses to forensics. However, absorption of IR light by common optical imaging components makes mid-IR light incompatible with modern optical microscopy and almost all biomedical research and clinical workflows. Here we conceptualize an IR-optical hybrid (IR-OH) approach that sensitively measures molecular composition based on an optical microscope with wide-field interferometric detection of absorption-induced sample expansion. We demonstrate that IR-OH exceeds state-of-the-art IR microscopy in coverage (10-fold), spatial resolution (fourfold), and spectral consistency (by mitigating the effects of scattering). The combined impact of these advances allows full slide infrared absorption images of unstained breast tissue sections on a visible microscope platform. We further show that automated histopathologic segmentation and generation of computationally stained (stainless) images is possible, resolving morphological features in both color and spatial detail comparable to current pathology protocols but without stains or human interpretation. IR-OH is compatible with clinical and research pathology practice and could make for a cost-effective alternative to conventional stain-based protocols for stainless, all-digital pathology.

Characterization of colorectal mucus using infrared spectroscopy: a potential target for bowel cancer screening and diagnosis

Biological materials presenting early signs of cancer would be beneficial for cancer screening/diagnosis. In this respect, the suitability of potentially exploiting mucus in colorectal cancer was tested using infrared spectroscopy in combination with statistical modeling. Twenty-six paraffinized colon tissue biopsy sections containing mucus regions from 20 individuals (10 normal and 16 cancerous) were measured using mid-infrared spectroscopic imaging. A digital de-paraffinization, followed by cluster analysis driven digital color-coded multi-staining segmented the infrared images into various histopathological features such as epithelium, connective tissue, stroma, and mucus regions within the tissue sections. Principal component analysis followed by supervised linear discriminant analysis was carried out on pure mucus and epithelial spectra from normal and cancerous regions of the tissue. For the mucus-based classification, a sensitivity of 96%, a specificity of 83%, and an area under the curve performance of 95% was obtained. For the epithelial tissue-based classification, a sensitivity of 72%, a specificity of 88%, and an area under the curve performance of 89% was obtained. The mucus spectral profiles further showed contributions indicative of glycans including that of sialic acid changes between these pathology groups. The study demonstrates that infrared spectroscopic analysis of mucus discriminates colorectal cancers with high sensitivity. This concept could be exploited to develop screening/diagnostic approaches complementary to histopathology.

Recent trends in the application of Fourier Transform Infrared (FT-IR) spectroscopy in Heritage Science: from micro- to non-invasive FT-IR

The relevance of FT-IR spectroscopy in heritage science has experienced a constant grow in the last two decades owing to analytical peculiarities that make it an extremely useful tool to answer the questions posed by the study and conservation of art-historical and archaeological materials. High versatility, sensitivity and molecular specificity are, in fact, all requirements that FT-IR spectroscopy fulfils allowing for the investigation of the chemical properties of heritage materials spanning from the micro- to the macro-scale and offering a variety of approaches to minimize sample manipulation and maximize extracted information. Molecular identification and localisation at high lateral resolution of organic and inorganic components in micro-samples was, over recently, the mostly exploited use of FT-IR in heritage science; however, benefiting from technological progress and advances in optical materials and components achieved in the last decade, it now stands out also for non-invasive surface analysis of artworks by fully portable instrumentation.

Quantitative infrared spectroscopy of environmentally sensitive and rough materials

Fourier transform infrared (FTIR) spectroscopy is a widely used characterization technique for studying chemical compositions and light-matter interactions in the infrared range. However, it remains challenging to use conventional FTIR equipment to characterize materials that are environmentally sensitive and/or have rough surfaces due to their dynamic response to external stimuli (e.g., humidity) and light scattering from the sample surface. Here, we describe an approach enabling quantitative infrared spectroscopy measurements of these challenging samples, including transmittance, reflectance, and emissivity. We designed and 3D-printed a miniaturized environmental chamber that can be directly inserted into the sample holder of a conventional integrating sphere to perform total transmission and reflection measurements in controlled environments. Moreover, a calibration method was developed to exclude light scattering from rough surfaces of the sample and the distortion created by infrared windows. To illustrate the potential application of this method, we have performed quantitative infrared measurements, both specular and diffusive, on a sapphire standard reference with a specular surface, as well as a textile sample that has a rough surface and is dynamically responsive to changes in humidity. The calibrated results measured with the equipped chamber match those measured without the IR windows, demonstrating the viability of our environmental chamber and the proposed calibration method. This quantitative infrared spectroscopy measurement technique may help advance fields such as metasurfaces and adaptive textiles, where samples are often rough, dynamically responsive, and/or environmentally sensitive.

Infrared nanospectroscopic mapping of a single metaphase chromosome

The integrity of the chromatin structure is essential to every process occurring within eukaryotic nuclei. However, there are no reliable tools to decipher the molecular composition of metaphase chromosomes. Here, we have applied infrared nanospectroscopy (AFM-IR) to demonstrate molecular difference between eu- and heterochromatin and generate infrared maps of single metaphase chromosomes revealing detailed information on their molecular composition, with nanometric lateral spatial resolution. AFM-IR coupled with principal component analysis has confirmed that chromosome areas containing euchromatin and heterochromatin are distinguishable based on differences in the degree of methylation. AFM-IR distribution of eu- and heterochromatin was compared to standard fluorescent staining. We demonstrate the ability of our methodology to locate spatially the presence of anticancer drug sites in metaphase chromosomes and cellular nuclei. We show that the anticancer 'rule breaker' platinum compound [Pt[N(p-HC6F4)CH2]2py2] preferentially binds to heterochromatin, forming localized discrete foci due to condensation of DNA interacting with the drug. Given the importance of DNA methylation in the development of nearly all types of cancer, there is potential for infrared nanospectroscopy to be used to detect gene expression/suppression sites in the whole genome and to become an early screening tool for malignancy.

High-resolution, high-contrast mid-infrared imaging of fresh biological samples with ultraviolet-localized photoacoustic microscopy

Mid-infrared (MIR) microscopy provides rich chemical and structural information about biological samples, without staining. Conventionally, the long MIR wavelength severely limits the lateral resolution owing to optical diffraction; moreover, the strong MIR absorption of water ubiquitous in fresh biological samples results in high background and low contrast. To overcome these limitations, we propose a method that employs photoacoustic detection highly localized with a pulsed ultraviolet (UV) laser on the basis of the Grüneisen relaxation effect. For cultured cells, our method achieves water-background suppressed MIR imaging of lipids and proteins at UV resolution, at least an order of magnitude finer than the MIR diffraction limits. Label-free histology using this method is also demonstrated in thick brain slices. Our approach provides convenient high-resolution and high-contrast MIR imaging, which can benefit diagnosis of fresh biological samples.

Polymeric microfluidic continuous flow mixer combined with hyperspectral FT-IR imaging for studying rapid biomolecular events

Early reaction intermediates in protein folding, such as those resulting in β-amyloid formation due to transient misfolding, emerge within a few hundred microseconds. Here, we report a method to obtain sub-millisecond temporal resolution and molecular structural information of protein (mis-)folding events by using a microfluidic continuous-flow mixer (MCFM) in combination with Fourier transform infrared (FT-IR) imaging. The MCFMs are made out of cyclic olefin copolymer (COC) films, because this approach allows for rapid prototyping of different mixer designs. Furthermore, COC offers high IR transparency between 1500 and 2500 cm^-1, thus maximizing the signal to noise ratio of the IR data obtained from a sample of interest. By combining narrow and wide channel widths in MCFM design, the platform provides fast mixing (460 μs) to induce protein (mis-)folding, and it maximizes the residence time in the observing area, so a wide range of reaction timescales can be captured in a single image. We validated the platform for its ability to induce and observe sub-millisecond processes by studying two systems: (i) the mixing of H₂O and D₂O and (ii) the mixing induced deprotonation of carboxylic acid. First, we observed excellent agreement between simulated and experimental data of the on-chip mixing of H₂O and D₂O, which verifies the distance-reaction time relationships based on simulation. Second, deprotonation of carboxylic acid by on-chip mixing with sodium hydroxide solution validates the ability of the platform to induce rapid pH jump that is needed for some biomolecular reactions. Finally, we studied the methanol-induced partial-unfolding of ubiquitin to show that our platform can be used to study biomolecular events 'on-pathway' using FT-IR imaging. We successfully extracted kinetic and structural details of the conformational changes along the channel. Our results are in agreement with prior studies that required more elaborate stopped flow approaches to acquire data for different time points. In summary, the reported method uses an easy-to-fabricate microfluidic mixer platform integrated with hyperspectral FT-IR imaging for rapid acquisition of structural details and kinetic parameters of biomolecular reactions. This approach does not need stopped flow or molecular imaging probes, as required respectively for alternative FT-IR spectroscopy and fluorescence approaches.

Far-Field Super-Resolution Vibrational Spectroscopy

Potential label-free alternatives to super-resolution fluorescence techniques have been the focus of considerable research due to the challenges intrinsic in the reliance on fluorescent tags. In this Feature, we discuss efforts to develop super-resolution techniques based on vibrational spectroscopies and address possible sample applications as well as future potential resolution enhancements.

Understanding Secondary Structures of Silk Materials via Micro- and Nano-Infrared Spectroscopies

The secondary structures (also termed conformations) of silk fibroin (SF) in animal silk fibers and regenerated SF materials are critical in determining mechanical performance and function of the materials. In order to understand the structure-mechanics-function relationships of silk materials, a variety of advanced infrared spectroscopic techniques, such as micro-infrared spectroscopies (micro-IR spectroscopies for short), synchrotron micro-IR spectroscopy, and nano-infrared spectroscopies (nano-IR spectroscopies for short), have been used to determine the conformations of SF in silk materials. These IR spectroscopic methods provide a useful toolkit to understand conformations and conformational transitions of SF in various silk materials with spatial resolution from the nano-scale to the micro-scale. In this Review, we first summarize progress in understanding the structure and structure-mechanics relationships of silk materials. We then discuss the state-of-the-art micro- and nano-IR spectroscopic techniques used for silk materials characterization. We also provide a systematic discussion of the strategies to collect high-quality spectra and the methods to analyze these spectra. Finally, we demonstrate the challenges and directions for future exploration of silk-based materials with IR spectroscopies.

Hyperspectral Tissue Image Segmentation Using Semi-Supervised NMF and Hierarchical Clustering

Hyperspectral imaging (HSI) of tissue samples in the mid-infrared (mid-IR) range provides spectro-chemical and tissue structure information at sub-cellular spatial resolution. Disease states can be directly assessed by analyzing the mid-IR spectra of different cell types (e.g., epithelial cells) and sub-cellular components (e.g., nuclei), provided that we can accurately classify the pixels belonging to these components. The challenge is to extract information from hundreds of noisy mid-IR bands at each pixel, where each band is not very informative in itself, making annotations of unstained tissue HSI images particularly tricky. Because the tissue structure is not necessarily identical between the two sections, only a few regions in unstained HSI image can be annotated with high confidence, even when serial (or adjacent) hematoxylin and eosin stained section is used as a visual guide. In order to completely use both labeled and unlabeled pixels in training images, we have developed an HSI pixel classification method that uses semi-supervised learning for both spectral dimension reduction and hierarchical pixel clustering. Compared to the supervised classifiers, the proposed method was able to account for the vast differences in the spectra of sub-cellular components of the same cell type and to achieve an F1 score of 71.18% on twofold cross-validation across 20 tissue images. To generate further interest in this promising modality, we have released our source code and also showed that disease classification is straightforward after HSI image segmentation.

Integrating Microfabrication into Biological Investigations: the Benefits of Interdisciplinarity

The advent of micro and nanotechnologies, such as microfabrication, have impacted scientific research and contributed to meaningful real-world applications, to a degree seen during historic technological revolutions. Some key areas benefitting from the invention and advancement of microfabrication platforms are those of biological and biomedical sciences. Modern therapeutic approaches, involving point-of-care, precision or personalized medicine, are transitioning from the experimental phase to becoming the standard of care. At the same time, biological research benefits from the contribution of microfluidics at every level from single cell to tissue engineering and organoids studies. The aim of this commentary is to describe, through proven examples, the interdisciplinary process used to develop novel biological technologies and to emphasize the role of technical knowledge in empowering researchers who are specialized in a niche area to look beyond and innovate.

Direct label-free imaging of brain tissue using synchrotron light: a review of new spectroscopic tools for the modern neuroscientist

The incidence of brain disease and brain disorders is increasing on a global scale. Unfortunately, development of new therapeutic strategies has not increased at the same rate, and brain diseases and brain disorders now inflict substantial health and economic impacts. A greater understanding of the fundamental neurochemistry that underlies healthy brain function, and the chemical pathways that manifest in brain damage or malfunction, are required to enable and accelerate therapeutic development. A previous limitation to the study of brain function and malfunction has been the limited number of techniques that provide both a wealth of biochemical information, and spatially resolved information (i.e., there was a previous lack of techniques that provided direct biochemical or elemental imaging at the cellular level). In recent times, a suite of direct spectroscopic imaging techniques, such as Fourier transform infrared spectroscopy (FTIR), X-ray fluorescence microscopy (XFM), and X-ray absorption spectroscopy (XAS) have been adapted, optimized and integrated into the field of neuroscience, to fill the above mentioned capability-gap. Advancements at synchrotron light sources, such as improved light intensity/flux, increased detector sensitivities and new capabilities of imaging/optics, has pushed the above suite of techniques beyond "proof-of-concept" studies, to routine application to study complex research problems in the field of neuroscience (and other scientific disciplines). This review examines several of the major advancements that have occurred over the last several years, with respect to FTIR, XFM and XAS capabilities at synchrotron facilities, and how the increases in technical capabilities have being integrated and used in the field of neuroscience.

Native Nano-electrospray Differential Mobility Analyzer (nES GEMMA) Enables Size Selection of Liposomal Nanocarriers Combined with Subsequent Direct Spectroscopic Analysis

Gas-phase electrophoresis employing a nano-electrospray differential mobility analyzer (nES DMA), aka gas-phase electrophoretic mobility molecular analyzer (nES GEMMA), enables nanoparticle separation in the gas-phase according to their surface-dry diameter with number-based concentration detection. Moreover, particles in the nanometer size range can be collected after size selection on supporting materials. It has been shown by subsequent analyses employing orthogonal methods, for instance, microscopic or antibody-based techniques, that the surface integrity of collected analytes remains intact. Additionally, native nES GEMMA demonstrated its applicability for liposome characterization. Liposomes are nanometer-sized, biodegradable, and rather labile carriers (nanoobjects) consisting of a lipid bilayer encapsulating an aqueous lumen. In nutritional and pharmaceutical applications, these vesicles allow shielded, targeted transport and sustained release of bioactive cargo material. To date, cargo quantification is based on bulk measurements after bilayer rupture. In this context, we now compare capillary electrophoresis and spectroscopic characterization of vesicles in solution (bulk measurements) to the possibility of spectroscopic investigation of individual, size-separated/collected liposomes after nES GEMMA. Surface-dried, size-selected vesicles were collected intact on calcium fluoride (CaF₂) substrates and zinc selenide (ZnSe) prisms, respectively, for subsequent spectroscopic investigation. Our proof-of-principle study demonstrates that the off-line hyphenation of gas-phase electrophoresis and confocal Raman spectroscopy allows detection of isolated, nanometer-sized soft material/objects. Additionally, atomic force microscopy-infrared spectroscopy (AFM-IR) as an advanced spectroscopic system was employed to access molecule-specific information with nanoscale lateral resolution. The off-line hyphenation of nES GEMMA and AFM-IR is introduced to enable chemical imaging of single, i.e., individual, liposome particles.

Biochemical Changes in Irradiated Oral Mucosa: A FTIR Spectroscopic Study

Radiation exposure during the course of treatment in head and neck cancer (HNC) patients can induce both structural and biochemical anomalies. The present study is focused on utilizing infrared imaging for the identification of the minor biochemical alterations in the oral mucosa. Chemical maps generated using glycoprotein band indicates its differential distribution along the superficial layer. Spectra extracted from this layer suggests changes in overall nucleic acid and protein content in response to the therapeutic irradiation. Discrimination among control and irradiated groups have been achieved using principal component analysis. Findings of this preliminary study further support prospective utilization of Fourier Transform InfraRed (FTIR) imaging as a non-destructive, label-free tool for objective assessment of the oral mucosa in patient groups with or without radiation therapy.

SIproc: an open-source biomedical data processing platform for large hyperspectral images

There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

Retinal oxidative stress at the onset of diabetes determined by synchrotron FTIR widefield imaging: towards diabetes pathogenesis

Diabetic retinopathy is a microvascular complication of diabetes that can lead to blindness. In the present study, we aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the neuroretina at the onset of diabetes. High-resolution synchrotron Fourier transform infrared (s-FTIR) wide field microscopy coupled with multivariate analysis (PCA-LDA) was employed to identify biomarkers of diabetic retinopathy with spatial resolution at the cellular level. We compared the retinal tissue prepared from 6-week-old Ins2^Akita/+ heterozygous (Akita/+, N = 6; a model of diabetes) male mice with the wild-type (control, N = 6) mice. Male Akita/+ mice become diabetic at 4-weeks of age. Significant differences (P < 0.001) in the presence of biomarkers associated with diabetes and segregation of spectra were achieved. Differentiating IR bands attributed to nucleic acids (964, 1051, 1087, 1226 and 1710 cm^-1), proteins (1662 and 1608 cm^-1) and fatty acids (2854, 2923, 2956 and 3012 cm^-1) were observed between the Akita/+ and the WT samples. A comparison between distinctive layers of the retina, namely the photoreceptor retinal layer (PRL), outer plexiform layer (OPL), inner nucleus layer (INL) and inner plexiform layer (IPL) suggested that the photoreceptor layer is the most susceptible layer to oxidative stress in short-term diabetes. Spatially-resolved chemical images indicated heterogeneities and oxidative-stress induced alterations in the diabetic retina tissue morphology compared with the WT retina. In this study, the spectral biomarkers and the spatial biochemical alterations in the diabetic retina and in specific layers were identified for the first time. We believe that the conclusions drawn from these studies will help to bridge the gap in our understanding of the molecular and cellular mechanisms that contribute to the pathobiology of diabetic retinopathy.