Spectroscopic imaging of biomaterials and biological systems with FTIR microscopy or with quantum cascade lasers

Advances in ATR-FTIR Spectroscopic Imaging for the Analysis of Tablet Dissolution and Drug Release

One of the major challenges in the development of effective pharmaceutical formulations for oral administration is the poor solubility of active pharmaceutical ingredients. For this reason, the dissolution process and drug release from solid oral dosage forms, such as tablets, is usually thoroughly studied in order to understand the dissolution behaviour under various conditions and optimize the formulation accordingly. Standard dissolution tests used in the pharmaceutical industry provide information on the amount of drug released over time; however, these do not allow for a detailed analysis of the underlying chemical and physical mechanisms of tablet dissolution. FTIR spectroscopic imaging, by contrast, does offer the ability to study these processes with high spatial and chemical specificity. As such, the method allows us to see the chemical and physical processes which occur inside the tablet as it dissolves. In this review, the power of ATR-FTIR spectroscopic imaging is demonstrated by presenting a number of successful applications of this chemical imaging technique to dissolution and drug release studies for a range of different pharmaceutical formulations and study conditions. Understanding these processes is essential for the development of effective oral dosage forms and optimization of pharmaceutical formulations.

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.

Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning

Tumor grade assessment is critical to the treatment of cancers. A pathologist typically evaluates grade by examining morphologic organization in tissue using hematoxylin and eosin (H&E) stained tissue sections. Fourier transform infrared spectroscopic (FT-IR) imaging provides an alternate view of tissue in which spatially specific molecular information from unstained tissue can be utilized. Here, we examine the potential of IR imaging for grading colon cancer in biopsy samples. We used a 148-patient cohort to develop a deep learning classifier to estimate the tumor grade using IR absorption. We demonstrate that FT-IR imaging can be a viable tool to determine colorectal cancer grades, which we validated on an independent cohort of surgical resections. This work demonstrates that harnessing molecular information from FT-IR imaging and coupling it with morphometry is a potential path to develop clinically relevant grade prediction models.

Development of multi-frequency impedance scanning electron microscopy

Nanometre-scale observation of specimens in water is indispensable in many scientific fields like biology, chemistry, material science and nanotechnology. Scanning electron microscopy (SEM) allows high-resolution images of biological samples to be obtained under high vacuum conditions but requires specific sample-preparation protocols. Therefore, there is a need for convenient and minimally invasive methods of observing samples in solution. We have developed a new type of impedance microscopy, namely multi-frequency impedance SEM (IP-SEM), which allows nanoscale imaging of various specimens in water while minimising radiation damage. By varying the frequency of the input voltage signal of the sine wave, the present system can detect dielectric properties of the sample’s composition at nanometre resolution. It also enables examination of unstained biological specimens and material samples in water. Furthermore, it can be used for diverse samples in liquids across a broad range of scientific subjects such as nanoparticles, nanotubes and organic and catalytic materials.

Oral Cancer Discrimination and Novel Oral Epithelial Dysplasia Stratification Using FTIR Imaging and Machine Learning

The Fourier transform infrared (FTIR) imaging technique was used in a transmission model for the evaluation of twelve oral hyperkeratosis (HK), eleven oral epithelial dysplasia (OED), and eleven oral squamous cell carcinoma (OSCC) biopsy samples in the fingerprint region of 1800–950 cm⁻¹. A series of 100 µm × 100 µm FTIR imaging areas were defined in each sample section in reference to the hematoxylin and eosin staining image of an adjacent section of the same sample. After outlier removal, signal preprocessing, and cluster analysis, a representative spectrum was generated for only the epithelial tissue in each area. Two representative spectra were selected from each sample to reflect intra-sample heterogeneity, which resulted in a total of 68 representative spectra from 34 samples for further analysis. Exploratory analyses using Principal component analysis and hierarchical cluster analysis showed good separation between the HK and OSCC spectra and overlaps of OED spectra with either HK or OSCC spectra. Three machine learning discriminant models based on partial least squares discriminant analysis (PLSDA), support vector machines discriminant analysis (SVMDA), and extreme gradient boosting discriminant analysis (XGBDA) were trained using 46 representative spectra from 12 HK and 11 OSCC samples. The PLSDA model achieved 100% sensitivity and 100% specificity, while both SVM and XGBDA models generated 95% sensitivity and 96% specificity, respectively. The PLSDA discriminant model was further used to classify the 11 OED samples into HK-grade (6), OSCC-grade (4), or borderline case (1) based on their FTIR spectral similarity to either HK or OSCC cases, providing a potential risk stratification strategy for the precancerous OED samples. The results of the current study support the application of the FTIR-machine learning technique in early oral cancer detection.

Cell wall polymer distribution in bamboo visualized with in situ imaging FTIR

To better understand the high recalcitrance of bamboo during bioconversion, the fine spatial distribution of polymers in bamboo was studied with Imaging FTIR microscopy under both transmission and ATR modes, combined with PCA data processing. The results demonstrated that lignin, xylan and hydroxycinnamic acid (HCA) were more concentrated in the fibers near the xylem conduit, while cellulose was evenly distributed across the whole fiber sheath. PCA processing produced a clear separation between bamboo fibers and parenchyma cells, indicating that the parenchyma cells contains more pectin and HCA than fibers. It also demonstrated that cellulose, xylan and S-lignin were concentrated most heavily in bamboo fiber secondary cell walls, while G-lignin, pectin and HCA were found more in the compound middle lamella. The revealed information regarding polymer distribution is of great significance for better understanding of the inherent design mechanism of plant cell wall and its efficient utilization.

API Content and Blend Uniformity Using Quantum Cascade Laser Spectroscopy Coupled with Multivariate Analysis

The process analytical technology (PAT) initiative proposed by the US Food and Drug Administration (FDA) suggests innovative methods to better understand pharmaceutical processes. The development of analytical methods that quantify active pharmaceutical ingredients (APIs) in powders and tablets is fundamental to monitoring and controlling a drug product's quality. Analytical methods based on vibrational spectroscopy do not require sample preparation and can be implemented during in-line manufacturing to maintain quality at each stage of operations. In this study, a mid-infrared (MIR) quantum cascade laser (QCL) spectroscopy-based protocol was performed to quantify ibuprofen in formulations of powder blends and tablets. Fourteen blends were prepared with varying concentrations from 0.0% to 21.0% (w/w) API. MIR laser spectra were collected in the spectral range of 990 to 1600 cm^-1. Partial least squares (PLS) models were developed to correlate the intensities of vibrational signals with API concentrations in powder blends and tablets. PLS models were evaluated based on the following figures of merit: correlation coefficient (R²), root mean square error of calibration, root mean square error of prediction, root mean square error of cross-validation, and relative standard error of prediction. QCL assisted by multivariate analysis was demonstrated to be accurate and robust for analysis of the content and blend uniformity of pharmaceutical compounds.

A microfluidic chip enables fast analysis of water microplastics by optical spectroscopy

Microplastics contaminating drinking water is a growing issue that has been the focus of a few recent studies, where a major bottleneck is the time-consuming analysis. In this work, a micro-optofluidic platform is proposed for fast quantification of microplastic particles, the identification of their chemical nature and size, especially in the 1-100 µm size range. Micro-reservoirs ahead of micro-filters are designed to accumulate all trapped solid particles in an ultra-compact area, which enables fast imaging and optical spectroscopy to determine the plastic nature and type. Furthermore, passive size sorting is implemented for splitting the particles according to their size range in different reservoirs. Besides, flow cytometry is used as a reference method for retrieving the size distribution of samples, where chemical nature information is lost. The proof of concept of the micro-optofluidic platform is validated using model samples where standard plastic particles of different size and chemical nature are mixed.

Biomedical applications of vibrational spectroscopy: Oral cancer diagnostics

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

Physicochemical changes of the chitosan/β-1,3-glucan/hydroxyapatite biocomposite caused by mesenchymal stem cells cultured on its surface in vitro

In the present study structural characteristics and physicochemical properties of tri-component biomaterial (consisting of chitosan, β-1,3-glucan and hydroxyapatite) seeded with mesenchymal stem cells were investigated with the use of diffuse reflectance infrared Fourier transform spectroscopy (DRIFT), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). In this study we use non-conventional approach of DRIFT spectroscopy for investigating biomaterial changes under simulated physiological conditions. Particular cell-induced changes were intended to be properly evaluated with analytical methods. Abovementioned techniques allowed to precisely assess the changes on the surface of the biomaterial caused by two kinds of stem cells (ADSCs - Adipose tissue-Derived Stem Cells and BMDSCs - Bone Marrow-Derived Stem Cells) cultured directly on the surface of bioceramic-based biomaterial. The bioactivity and biocompatibility of designed bone biomaterial were demonstrated and hence it seems to be a promising scaffold used in tissue engineering. Designed chitosan, β-1,3-glucan, and hydroxyapatite biomaterial was proven to be non-toxic, surgically handy with cellular compatibility. The obtained results are interesting and promising in terms of spectroscopic methods suitability for qualitative assessment of material-cell interactions.

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.

Vibrational Spectroscopic Analyses and Imaging of the Early Middle Ages Hemp Bast Fibres Recovered from Lake Sediments

Fourier Transform Infrared (FT-IR) spectroscopy and imaging combined with hierarchical cluster analysis (HCA) was applied to analyse biochemical properties of Early Middle Ages hemp (Cannabis sativa L.) bast fibres collected from lake bottom sediment of lake Słone. The examined plant macrofossil material constitutes residues of the hemp retting process that took place in the 7th–8th century. By comparison of three samples: untreated isolated bast fibres, and fibres incubated overnight at 4 and 37 °C, we were able to mimic the retting conditions. Using FT-IR qualitative and semi-quantitative assessment of the primary polysaccharides content, total protein content, and their spatial distribution was performed within the hemp fibres. The concentration of cellulose remained vastly unchanged, while the concentration of lignin and pectin was the highest in the untreated sample. The spatial distributions of compounds were heterogeneous in the untreated and 4 °C-incubated samples, and homogenous in the specimen processed at 37 °C. Interestingly, a higher amide content was detected in the latter sample indicating the highest degree of enzymatic degradation. In this study, we show that the spectroscopic methods allow for a non-destructive evaluation of biochemical composition of plant fibres without preparation, which can be an appropriate approach for studying ancient plant remains.

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.

ATR-FTIR spectroscopy and spectroscopic imaging for the analysis of biopharmaceuticals

Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy is a label-free, non-destructive technique that can be applied to a vast range of biological applications, from imaging cancer tissues and live cells, to determining protein content and protein secondary structure composition. This review summarises the recent advances in applications of ATR-FTIR spectroscopy to biopharmaceuticals, the application of this technique to biosimilars, and the current uses of FTIR spectroscopy in biopharmaceutical production. We discuss the use of ATR-FTIR spectroscopic imaging to investigate biopharmaceuticals, and finally, give an outlook on the possible future developments and applications of ATR-FTIR spectroscopy and spectroscopic imaging to this field. Throughout the review comparisons will be made between FTIR spectroscopy and alternative analytical techniques, and areas will be identified where FTIR spectroscopy could perhaps offer a better alternative in future studies. This review focuses on the most recent advances in the field of using ATR-FTIR spectroscopy and spectroscopic imaging to characterise and evaluate biopharmaceuticals, both in industrial and academic research based environments.

Collagen maturity and mineralization in mesenchymal stem cells cultured on the hydroxyapatite-based bone scaffold analyzed by ATR-FTIR spectroscopic imaging

Modern bone tissue engineering is based on the use of implants in the form of biomaterials, which are used as scaffolds for osteoprogenitor or stem cells. The task of the scaffolds is to temporarily sustain the function, proliferation and differentiation of bone tissue to enable its regeneration. The aim of this work is to use the macro ATR-FTIR spectroscopic imaging for analysis of the ceramic-based biomaterial (chitosan/β-1,3-glucan/hydroxyapatite). Specifically, during long-term culture of mesenchymal cells derived from adipose tissue (ADSCs) and bone marrow (BMDSCs) on the surface of scaffold. Infrared spectroscopy allows the acquisition of information on both the organic and inorganic parts of the tested composite. This innovative spectroscopic approach proved to be very suitable for studying the formation of new bone tissue and ECM components, sample staining and demineralization are not required and consequently the approach is rapid and cost-effective. The novelty of this study focuses on the innovatory use of ATR-FTIR imaging to evaluate the molecular structure and maturity of collagen as well as mineral matrix formation and crystallization in the context of bone regenerative medicine. Our research has shown that the biomaterial investigated on this work facilitates the formation of valid bone ECM of the stem cells types studied, as a result of the synthesis of type I collagen and mineral content deposition. Nevertheless, ADSC cells have been proven to produce a greater amount of collagen with a lower content of helical secondary structures, at the same time showing a higher mineralization intensity compared to BMDSC cells. Considering the above results, it could be stated that the developed scaffold is a promising material for biomedical applications, including modification of bone implants to increase their biocompatibility.

Astrocytes Are More Vulnerable than Neurons to Silicon Dioxide Nanoparticle Toxicity in Vitro

Some studies have shown that silicon dioxide nanoparticles (SiO₂-NPs) can reach different regions of the brain and cause toxicity; however, the consequences of SiO₂-NPs exposure on the diverse brain cell lineages is limited. We aimed to investigate the neurotoxic effects of SiO₂-NP (0–100 µg/mL) on rat astrocyte-rich cultures or neuron-rich cultures using scanning electron microscopy, Attenuated Total Reflection-Fourier Transform Infrared spectroscopy (ATR-FTIR), FTIR microspectroscopy mapping (IQ mapping), and cell viability tests. SiO₂-NPs were amorphous particles and aggregated in saline and culture media. Both astrocytes and neurons treated with SiO₂-NPs showed alterations in cell morphology and changes in the IR spectral regions corresponding to nucleic acids, proteins, and lipids. The analysis by the second derivative revealed a significant decrease in the signal of the amide I (α-helix, parallel β-strand, and random coil) at the concentration of 10 µg/mL in astrocytes but not in neurons. IQ mapping confirmed changes in nucleic acids, proteins, and lipids in astrocytes; cell death was higher in astrocytes than in neurons (10–100 µg/mL). We conclude that astrocytes were more vulnerable than neurons to SiO₂-NPs toxicity. Therefore, the evaluation of human exposure to SiO₂-NPs and possible neurotoxic effects must be followed up.

Transmission Fourier Transform Infrared Spectroscopic Imaging, Mapping, and Synchrotron Scanning Microscopy with Zinc Sulfide Hemispheres on Living Mammalian Cells at Sub-Cellular Resolution

Fourier transform infrared (FT-IR) spectroscopic imaging and microscopy of single living cells are established label-free technique for the study of cell biology. The constant driver to improve the spatial resolution of the technique is due to the diffraction limit given by infrared (IR) wavelength making subcellular study challenging. Recently, we have reported, with the use of a prototype zinc sulfide (ZnS) transmission cell made of two hemispheres, that the spatial resolution is improved by the factor of the refractive index of ZnS, achieving a λ/2.7 spatial resolution using the synchrotron-IR microscopy with a 36× objective with numerical aperture of 0.5. To refine and to demonstrate that the ZnS hemisphere transmission device can be translated to standard bench-top FT-IR imaging systems, we have, in this work, modified the device to achieve a more precise path length, which has improved the spectral quality of the living cells, and showed for the first time that the device can be applied to study live cells with three different bench-top FT-IR imaging systems. We applied focal plane array (FPA) imaging, linear array, and a synchrotron radiation single-point scanning method and demonstrated that in all cases, subcellular details of individual living cells can be obtained. Results have shown that imaging with the FPA detector can measure the largest area in a given time, while measurements from the scanning methods produced a smoother image. Synchrotron radiation single-point mapping produced the best quality image and has the flexibility to introduce over sampling to produce images of cells with great details, but it is time consuming in scanning mode. In summary, this work has demonstrated that the ZnS hemispheres can be applied in all three spectroscopic approaches to improve the spatial resolution without any modification to the existing microscopes.

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.

Model-based correction algorithm for Fourier Transform infrared microscopy measurements of complex tissue-substrate systems

Model-based algorithms have recently attracted much attention for data pre-processing in tissue mapping and imaging by Fourier transform infrared micro-spectroscopy (FTIR). Their versatility, robustness and computational performance enabled the improvement of spectral quality by mitigating the impact of scattering and fringing in FTIR spectra of chemically homogeneous biological systems. However, to date, no comprehensive algorithm has been optimized and automated for large-area FTIR imaging of histologically complex tissue samples. Herein, for the first time, we propose a unique, integrated and fully-automated Multiple Linear Regression Multi-Reference (MLR-MR) method for correcting linear baseline effects due to diffuse scattering, for compensating substrate thickness inhomogeneity and accounting for sample chemical heterogeneity in FTIR images. In particular, the algorithm uses multiple-reference spectra for histologically heterogeneous biological samples. The performance of the procedure was demonstrated for FTIR imaging of chemically complex rat brain frontal cortex tissue samples, mounted onto Ultralene® films. The proposed MLR-MR correction algorithm allows the efficient retrieval of "pure" absorbance spectra and greatly improves the histological fidelity of FTIR imaging data, as compared with the one-reference approach. In addition, the MLR-MR algorithm here presented opens up the possibility for extracting information on substrate thickness variability, thus enabling the indirect evaluation of its topography. As a whole, the MLR-MR procedure can be easily extended to more complex systems for which Mie scattering effects must also be eliminated.

A review of applications of principles of quantum physics in oncology: do quantum physics principles have any role in oncology research and applications?

Background:

Research in the applications of the principles of quantum physics in oncology has progressed significantly over the past decades; and several research groups with professionals from diverse scientific background, including electrical engineers, mathematicians, biologists, atomic physicists, computer programmers, and biochemists, are working collaboratively in an unprecedented and pioneering economic, organisational and human effort searching for a wider and more effective, potentially definitive, understanding of the cancers. It is hypothesised that the principles of quantum physics could open new and broader understanding of the cancers and the development of new effective, targeted, accurate, personalised and possibly definitive cancer treatment.

Materials and methods:

This paper reports on a review of recent studies in the field of the applications of the principles of quantum physics in biology, chemistry, biochemistry and quantum physics in cancer research, including quantum physics principles and cancer, quantum modelling techniques, quantum dots and its applications in oncology, quantum cascade laser histopathology and quantum computing applications.

Conclusions:

The applications of the principles of quantum physics in oncology, chemistry and biology are providing new perspectives and greater insights into a long-studied disease, which could result in a greater understanding of the cancers and the potential for personalised and definitive treatment methods.

Fourier transform infrared spectroscopic imaging of colon tissues: evaluating the significance of amide I and C-H stretching bands in diagnostic applications with machine learning

Fourier transform infrared (FTIR) spectroscopic imaging of colon biopsy tissues in transmission combined with machine learning for the classification of different stages of colon malignancy was carried out in this study. Two different approaches, an optical and a computational one, were applied for the elimination of the scattering background during the measurements and compared with the results of the machine learning model without correction for the scattering. Several different data processing pathways were implemented in order to obtain a high accuracy of the prediction model. This study demonstrates, for the first time, that C-H stretching and amide I bands are of little to no significance in the classification of the colon malignancy, based on the Gini importance values by random forest (RF). The best prediction outcome is found when supervised RF classification was carried out in the fingerprint region of the spectral data between 1500 and 1000 cm^-1 (excluding the contribution of amide I and II bands). An overall prediction accuracy higher than 90% is achieved through the RF. The results also show that dysplastic and hyperplastic tissues are well distinguished. This leads to the insight that the important differences between hyperplastic and dysplastic colon tissues lie within the fingerprint region of FTIR spectra. In this study, computational correction performed better than optical correction, but the findings show that the disease states of colon biopsies can be distinguished effectively without elimination of Mie scattering effect. Graphical abstract.

Three-dimensional depth profiling of prostate tissue by micro ATR-FTIR spectroscopic imaging with variable angles of incidence

Variable angle micro ATR-FTIR, via the insertion of circular apertures, was used to measure tissue samples at various penetration depths.

Thermal effect on dispersive infrared spectroscopic imaging of prostate cancer tissue

A system that combines dispersive infrared micro-spectroscopic imaging and thermography has been developed to study the effect of thermal radiation on the infrared absorption spectra of prostate biopsy samples. The system allows the distribution of thermal signal intensity as a function of emissivity to be interpreted from the integrated absorbance obtained by spectroscopic imaging. Biochemical differences between cancer and benign areas within the specimens are identified in the spectra. Side-by-side comparison of H&E stained adjacent tissue sections with infrared images constructed before and after the removal of thermal effect showed that the latter strongly support differentiation of regions within tissues. The use of spectral bands at discrete wavelengths significantly reduced spectral acquisition time, making this technique promising as a future clinical diagnostic tool. A systemic methodology was implemented to process the data, first by k-means clustering on the second derivative spectra without a priori knowledge, followed by principal component analysis (PCA). Four distinct regions within the tissue samples were successfully classified based on the antisymmetric stretching mode of the methylene functional group. Separation between data in clusters occurs when projecting spectra on a PCA score plot on a plane made by first 2 principal components. The significance of the disparity was verified with statistical test. Regulation of signal to chopper and detector enables simultaneous acquisition of infrared and thermal images of the prostate biopsy tissues.

Denoising influence on discrete frequency classification results for quantum cascade laser based infrared microscopy

Currently, there is great interest in bringing the application of IR spectroscopy into the clinic. This however will require a significant reduction in measurement time as Fourier Transform Infrared (FT-IR) imaging takes hours to days to scan a clinically relevant specimen. A potential remedy for this issue is the use of Quantum Cascade Laser Infrared (QCL IR) microscopy performed in Discrete Frequency (DF) mode for maximum speed gain. This gain could be furthermore improved by applying a proper denoising algorithm that takes into account the specific data structure. We have recently compared spectral and spatial denoising techniques in the context of Fourier Transform IR (FT-IR) imaging and showed that the optimal methods depend heavily on the exact data structure. In general multivariate denoising methods such as Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) are the most effective for a dataset containing multiple bands. Histologic classification of QCL IR images of pancreatic tissue using Random Forest was therefore performed to investigate which denoising schemes are the most optimal for such experimental data structure. This work is the first to show the effects of denoising on classification accuracy of QCL data and is likely to be transferable to other QCL microscopes and other modalities using DF imaging, e.g. AFM-IR or CARS/SRS imaging.

Diffraction limited mid-infrared reflectance microspectroscopy with a supercontinuum laser

Chemical mapping was demonstrated with a mid-infrared (MIR) microspectroscopy setup based on a supercontinuum source (SC) emitting in the spectral range from 1.55 to 4.5 µm and a MEMS-based Fabry-Pérot filter spectrometer. Diffraction limited spatial resolution in reflection geometry was achieved. A multilayer film consisting of different polymers and mixtures thereof was measured and results were compared to those gained with a conventional FTIR microscope equipped with a thermal MIR source. Results show that compared to thermal sources, the application of the SC source results in higher signal-to-noise ratios together with better spatial resolution and faster scanning. Furthermore, diffraction limited imaging of red blood cells was demonstrated for the first time in the MIR spectral region in reflection mode. The distinctive characteristics of the MIR spectral region in conjunction with the high brightness, spatial coherence and broadband nature of supercontinuum radiation show the potential for improving infrared microscopy significantly.

Infrared Evaluation of Enantiometric Amount and Application to Racemization at the Interface Between L- and D-Alanine

Amino acids, except for glycine, have two types of molecular structures, L- and D-forms, which are enantiomers. As the L- and D-form molecules have identical chemical and physical properties, they cannot be easily identified by conventional methods. In this study, we found that the amount and the spatial distribution of D-enantiomers in an L-alanine (CH₃CH(COOH)NH₂) matrix in evaporated thin films, which is one of amino acid molecules, can be evaluated quantitatively using an infrared micro spectroscopy with synchrotron radiation. This method was applied to the evaluation of the volume fraction of a racemic component appearing at the interface between L- and D-alanine thin films.

Recent advances in the applications of vibrational spectroscopic imaging and mapping to pharmaceutical formulations

Vibrational spectroscopic imaging and mapping approaches have continued in their development and applications for the analysis of pharmaceutical formulations. Obtaining spatially resolved chemical information about the distribution of different components within pharmaceutical formulations is integral for improving the understanding and quality of final drug products. This review aims to summarise some key advances of these technologies over recent years, primarily since 2010. An overview of FTIR, NIR, terahertz spectroscopic imaging and Raman mapping will be presented to give a perspective of the current state-of-the-art of these techniques for studying pharmaceutical samples. This will include their application to reveal spatial information of components that reveals molecular insight of polymorphic or structural changes, behaviour of formulations during dissolution experiments, uniformity of materials and detection of counterfeit products. Furthermore, new advancements will be presented that demonstrate the continuing novel applications of spectroscopic imaging and mapping, namely in FTIR spectroscopy, for studies of microfluidic devices. Whilst much of the recently developed work has been reported by academic groups, examples of the potential impacts of utilising these imaging and mapping technologies to support industrial applications have also been reviewed.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.