Fourier transform infrared vibrational spectroscopic imaging: integrating microscopy and molecular recognition

Evaluating the pharmacological activities of Aloe perryi-Silver nanoparticles induced apoptosis against colon cancer cells (HCT-116)

Aloe perryi has been studied and possesses several activities, including antibacterial, antiparasitic, and anticancer properties. In this study, A. perryi was used as a reducing agent of silver ions into silver nanoparticles. Aloe perryi-silver nanoparticles (APS-NPs) were characterized and evaluated using characterization techniques. However, the antioxidative, antibacterial, and anticancer assays were studied to evaluate the pharmacological activities of APS-NPs. APS-NPs were developed and changed to dark brown and the maximum absorption was 442 nm. SEM (5-583 nm), TEM (4-110 nm), XRD (21.84 nm), and zeta potential analysis (63.39 nm) revealed that the APS-NPs were nano-sized, and the APS-NPs had a cubic crystalline structure, according to the XRD results. FTIR analysis suggested that functional groups of A. perryi metabolites were involved in forming APS-NPs. The zeta potential indicated that the APS-NPs were negatively charged (-32 mV), suggesting good stability. APS-NPs showed significant antioxidative stress activity by reducing DPPH-free radicles in a dose-dependent manner. APS-NPs-induced antibacterial effect against Staphylococcus aureus (S. aureus), Escherichia coli (E. coli), and Acinetobacter baumannii (A. baumannii). APS-NPs reduced the cell viability and cell migration of the human colon tumor cell line (HCT 116) compared with controls, indicating that APS-NPs could play a role in reducing metastasis and inducing cell apoptosis against colon cancer. In conclusion, the nanoparticle synthesis from A. perryi extract demonstrated excellent antioxidant, antibacterial, and anticancer activities, thus suggesting that our APS-NPs have the potential to be used as antioxidative and antibacterial in food and pharmaceutical industries.

Vibrational spectroscopy coupled with machine learning sheds light on the cellular effects induced by rationally designed TLR4 agonists

In this work, we present the potential of Fourier transform infrared (FTIR) microspectroscopy to compare on whole cells, in an unbiased and untargeted way, the capacity of bacterial lipopolysaccharide (LPS) and two rationally designed molecules (FP20 and FP20Rha) to activate molecular circuits of innate immunity. These compounds are important drug hits in the development of vaccine adjuvants and tumor immunotherapeutics. The biological assays indicated that FP20Rha was more potent than FP20 in inducing cytokine production in cells and in stimulating IgG antibody production post-vaccination in mice. Accordingly, the overall significant IR spectral changes induced by the treatment with LPS and FP20Rha were similar, lipids and glycans signals being the most diagnostic, while the effect of the less potent molecule FP20 on cells resulted to be closer to control untreated cells. We propose here the use of FTIR spectroscopy supported by artificial intelligence (AI) to achieve a more holistic understanding of the cell response to new drug candidates while screening them in cells.

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

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

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.

Bond-selective full-field optical coherence tomography

Optical coherence tomography (OCT) is a label-free, non-invasive 3D imaging tool widely used in both biological research and clinical diagnosis. Conventional OCT modalities can only visualize specimen tomography without chemical information. Here, we report a bond-selective full-field OCT (BS-FF-OCT), in which a pulsed mid-infrared laser is used to modulate the OCT signal through the photothermal effect, achieving label-free bond-selective 3D sectioned imaging of highly scattering samples. We first demonstrate BS-FF-OCT imaging of 1 µm PMMA beads embedded in agarose gel. Next, we show 3D hyperspectral imaging of up to 75 µm of polypropylene fiber mattress from a standard surgical mask. We then demonstrate BS-FF-OCT imaging on biological samples, including cancer cell spheroids and C. elegans. Using an alternative pulse timing configuration, we finally demonstrate the capability of BS-FF-OCT on imaging a highly scattering myelinated axons region in a mouse brain tissue slice.

Cadmium Sulfide Quantum Dots, Mitochondrial Function and Environmental Stress: A Mechanistic Reconstruction through In Vivo Cellular Approaches in Saccharomyces cerevisiae

Research on the effects of engineered nanomaterials (ENMs) on mitochondria, which represent one of the main actors in cell function, highlighted effects on ROS production, gametogenesis and organellar genome replication. Specifically, the mitochondrial effects of cadmium sulfide quantum dots (CdS QDs) exposure can be observed through the variation in enzymatic kinetics at the level of the respiratory chain and also by analyzing modifications of reagent and products in term of the bonds created and disrupted during the reactions through Fourier-transform infrared spectroscopy (FTIR). This study investigated both in intact cells and in isolated mitochondria to observe the response to CdS QDs treatment at the level of electron transport chain in the wild-type yeast Saccharomyces cerevisiae and in the deletion mutant Δtom5, whose function is implicated in nucleo-mitochondrial protein trafficking. The changes observed in wild type and Δtom5 strains in terms of an increase or decrease in enzymatic activity (ranging between 1 and 2 folds) also differed according to the genetic background of the strains and the respiratory chain functionality during the CdS QDs treatment performed. Results were confirmed by FTIR, where a clear difference between the QD effects in the wild type and in the mutant strain, Δtom5, was observed. The utilization of these genetic and biochemical approaches is instrumental to clarify the mitochondrial mechanisms implicated in response to these types of ENMs and to the stress response that follows the exposure.

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.

Fourier-transform infrared spectroscopy: a universal optical sensing technique with auspicious application prospects in the diagnosis and management of autoimmune diseases

Autoimmune diseases (AIDs) are poorly understood clinical syndromes due to breakdown of immune tolerance towards specific types of self-antigens. They are generally associated with an inflammatory response mediated by lymphocytes T, autoantibodies or both. Ultimately, chronic inflammation culminates in tissue damages and clinical manifestations. AIDs affect 5% of the world population, and they represent the main cause of fatality in young to middle-aged females. In addition, the chronic nature of AIDs has a devastating impact on the patient's quality of life. It also places a heavy burden on the health care system. Establishing a rapid and accurate diagnosis is considered vital for an ideal medical management of these autoimmune disorders. However, for some AIDs, this task might be challenging. Vibrational spectroscopies, and more particularly Fourier-transform infrared (FTIR) spectroscopy, have emerged as universal analytical techniques with promising applications in the diagnosis of various types of malignancies and metabolic and infectious diseases. The high sensitivity of these optical sensing techniques and their minimal requirements for test reagents qualify them to be ideal analytical techniques. The aim of the current review is to explore the potential applications of FTIR spectroscopy in the diagnosis and management of most common AIDs. It also aims to demonstrate how this technique has contributed to deciphering the biochemical and physiopathological aspects of these chronic inflammatory diseases. The advantages that can be offered by this optical sensing technique over the traditional and gold standard methods used in the diagnosis of these autoimmune disorders have also been extensively discussed.

Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases

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

Mid-Infrared Photothermal Microscopy: Principle, Instrumentation, and Applications

Midinfrared photothermal (MIP) microscopy, also called optical photothermal infrared (O-PTIR) microscopy, is an emerging tool for bond-selective chemical imaging of living biological and material samples. In MIP microscopy, a visible probe beam detects the photothermal-based contrast induced by a vibrational absorption. With submicron spatial resolution, high spectral fidelity, and reduced water absorption background, MIP microscopy has overcome the limitations in infrared chemical imaging methods. In this review, we summarize the basic principle of MIP microscopy, the different origins of MIP contrasts, and recent technology development that pushed the resolution, speed, and sensitivity of MIP imaging to a new stage. We further emphasize its broad applications in life science and material characterization, and provide a perspective of future technical advances.

Attenuated total reflection-Fourier transform infrared spectroscopy: a universal analytical technique with promising applications in forensic analyses

Contemporary criminal investigations are based on the statements made by the victim and the eyewitnesses. They also rely on the physical evidences found in the crime scene. These evidences, and more particularly biological ones, have a great judicial value in the courtroom. They are usually used to revoke the suspect's allegations and confirm or refute the statements made by the victim and the witnesses. Stains of body fluids are biological evidences highly sought by forensic investigators. In many criminal cases, the success of the investigation relies on the correct identification and classification of these stains. Therefore, the adoption of reliable and accurate forensic analytical methods seems to be of vital importance to attain this objective. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) is a modern and universal analytical technique capable of fingerprint recognition of the analyte using minimal amount of the test sample. The current systematic review aims to through light on the fundamentals of this technique and to illustrate its wide range of applications in forensic investigations. ATR-FTIR is a nondestructive technique which has demonstrated an exceptional efficiency in detecting, identifying and discriminating between stains of various types of body fluids usually encountered in crime scenes. The ATR-FTIR spectral data generated from bloodstains can be used to deduce a wealth of information related to the donor species, age, gender, and race. These data can also be exploited to discriminate between stains of different types of bloods including menstrual and peripheral bloods. In addition, ATR-FTIR has a great utility in the postmortem investigations. More particularly, in estimating the postmortem interval and diagnosing death caused by extreme weather conditions. It is also useful in diagnosing some ambiguous death causes such as fatal anaphylactic shock and diabetic ketoacidosis.

Label-free differentiation of human pancreatic cancer, pancreatitis, and normal pancreatic tissue by molecular spectroscopy

SIGNIFICANCE

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer deaths with a best median survival of only 40 to 50 months for localized disease despite multimodal treatment. The standard tissue differentiation method continues to be pathology with histological staining analysis. Microscopic discrimination between inflammatory pancreatitis and malignancies is demanding.

AIM

We aim to accurately distinguish native pancreatic tissue using infrared (IR) spectroscopy in a fast and label-free manner.

APPROACH

Twenty cryopreserved human pancreatic tissue samples were collected from surgical resections. In total, more than 980,000 IR spectra were collected and analyzed using aMATLAB package. For differentiation of PDAC, pancreatitis, and normal tissue, a three-class training set for supervised classification was created with 25,000 spectra and the principal component analysis (PCA) score values for each cohort. Cross-validation was performed using the leaveone- out method. Validation of the algorithm was accomplished with 13 independent test samples.

RESULTS

Reclassification of the training set and the independent test samples revealed an overall accuracy of more than 90% using a discrimination algorithm.

CONCLUSION

IR spectroscopy in combination with PCA and supervised classification is an efficient analytical method to reliably distinguish between benign and malignant pancreatic tissues. It opens up a wide research field for oncological and surgical applications.

Flow Cytometry as a Rapid Alternative to Quantify Small Microplastics in Environmental Water Samples

The most frequently used method to quantify microplastics (MPs) visually by microscope is time consuming and labour intensive, where the method is also hindered by the size limitation at 10 µm or even higher. A method is proposed to perform pre-concentration of MPs by vacuum filtration, hydrogen peroxide wet digestion, fluorescent staining and flow cytometric determination to rapidly detect and quantify small MPs sized from 1–50 µm. The method performance was evaluated by the spiking of seven different types of polymer, including polystyrene (PS), low-density polyethylene (LDPE), polypropylene (PP), poly(methyl methacrylate) (PMMA), polyvinyl chloride (PVC), polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) at different levels (400, 4000, 40,000 particles mL−1), with a satisfactory overall % recoveries (101 ± 19.4%) observed, where in general no significant difference between the two methods was observed. Furthermore, a pre-concentration process by vacuum filtration was introduced to reduce the matrix effect. After pre-concentration, satisfactory % recoveries and accuracy in MP counts resulted from both ultrapure water (94.33 ± 11.16%) and sea water (103.17 ± 9.50%) samples. The validated method using flow cytometry can be used to quantify MPs in environmental water samples that can reduce time and human resources.

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

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

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.

Label-Free Diagnosis of Pulmonary Fat Embolism Using Fourier Transform Infrared (FT-IR) Spectroscopic Imaging

The diagnosis of pulmonary fat embolism (PFE) is of great significance in the field of forensic medicine because it can be considered a major cause of death or a vital reaction. Conventional histological analysis of lung tissue specimens is a widely used method for PFE diagnosis. However, variable and labor-intensive tissue staining procedures impede the validity and informativeness of histological image analysis. To obtain complete information from tissues, a method based on infrared imaging of unlabeled tissue sections was developed to identify pulmonary fat emboli in the present study. We selected 15 PFE-positive lung samples and 15 PFE-negative samples from real cases. Oil red O (ORO) staining and infrared spectral imaging collection were both performed on all lung tissue samples. And the fatty tissue of the abdominal wall and the embolized lipid droplets in the lungs were taken for comparison. The results of the blind, evaluation by pathologists, showed good agreement between the infrared spectral imaging of the lung tissue and the standard histological stained images. Fourier transform infrared (FT-IR) spectroscopic imaging significantly simplifies the typical painstakingly laborious histological staining procedure. And we found a difference between lipid droplets embolized in abdominal wall fat and lung tissue.

Label-Free Live-Cell Imaging of Internalized Microplastics and Cytoplasmic Organelles with Multicolor CARS Microscopy

As the bioaccumulation of microplastics (MPs) is considered as a potential health risk, many efforts have been made to understand the cellular dynamics and cytotoxicity of MPs. Here, we demonstrate that label-free multicolor coherent anti-Stokes Raman scattering (CARS) microscopy enables separate vibrational imaging of internalized MPs and lipid droplets (LDs) with indistinguishable shapes and sizes in live cells. By simultaneously obtaining polystyrene (PS)- and lipid-specific CARS images at two very different frequencies, 1000 and 2850 cm^-1, respectively, we successfully identify the local distribution of ingested PS beads and native LDs in Caenorhabditis elegans. We further show that the movements of PS beads and LDs in live cells can be separately tracked in real time, which allows us to characterize their individual intracellular dynamics. We thus anticipate that our multicolor CARS imaging method could be of great use to investigate the cellular transport and cytotoxicity of MPs without additional efforts for pre-labeling to MPs.

Culture-independent susceptibility determination of E. coli isolated directly from patients’ urine using FTIR and machine-learning

One of the most common human bacterial infections is the urinary tract infection (UTI).

Extraction and detection methods of microplastics in food and marine systems: A critical review

The ubiquitous presence of microplastics as contaminants in the ecosystem has become a matter of environmental concern gaining considerable attention in the research community as well as public arena. Lack of efficient collection and improper management of plastic have resulted in the enormous amounts of plastic wastes landing into the marine systems with oceans being the ultimate sink. Due to non-biodegradability, these plastics break down into smaller fragments over a period of time leading to consumption by aquatic species, threatening marine life. In the recent years, a wide range of food products has also been contaminated with microplastics directly affecting human health. This review focuses on the separation and identification technologies for extraction and detection of microplastics in food and marine ecosystems. Efficient technologies like floatation, membrane separation, chemical treatment, enzymatic treatment, and other miscellaneous techniques have been discussed considering their merits and demerits. Additionally, identification technologies like optical detection, scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy, thermo-analytical methods, and hyperspectral imaging have been emphasized for the detection of microplastic particles. The emerging techniques like enzymatic digestion combined with hyperspectral imaging could be a possible way for obtaining higher separation efficiency and characterization with minimal harm to food sample. This article narrows the gap for choosing a standard separation technology for microplastic detection in food matrices keeping in mind the composition, particle size, shape, data visualization techniques and cost.

Background-Suppressed High-Throughput Mid-Infrared Photothermal Microscopy via Pupil Engineering

Mid-infrared photothermal (MIP) microscopy has been a promising label-free chemical imaging technique for functional characterization of specimens owing to its enhanced spatial resolution and high specificity. Recently developed wide-field MIP imaging modalities have drastically improved speed and enabled high-throughput imaging of micron-scale subjects. However, the weakly scattered signal from subwavelength particles becomes indistinguishable from the shot-noise as a consequence of the strong background light, leading to limited sensitivity. Here, we demonstrate background-suppressed chemical fingerprinting at a single nanoparticle level by selectively attenuating the reflected light through pupil engineering in the collection path. Our technique provides over 3 orders of magnitude background suppression by quasi-darkfield illumination in the epi-configuration without sacrificing lateral resolution. We demonstrate 6-fold signal-to-background noise ratio improvement, allowing for simultaneous detection and discrimination of hundreds of nanoparticles across a field of view of 70 μm × 70 μm. A comprehensive theoretical framework for photothermal image formation is provided and experimentally validated with 300 and 500 nm PMMA beads. The versatility and utility of our technique are demonstrated via hyperspectral dark-field MIP imaging of S. aureus and E. coli bacteria and MIP imaging of subcellular lipid droplets inside C. albicans and cancer cells.

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.

Microplastic particles in the aquatic environment: A systematic review

Microplastics (MPs) pollution has become one of the most severe environmental concerns today. MPs persist in the environment and cause adverse effects in organisms. This review aims to present a state-of-the-art overview of MPs in the aquatic environment. Personal care products, synthetic clothing, air-blasting facilities and drilling fluids from gas-oil industries, raw plastic powders from plastic manufacturing industries, waste plastic products and wastewater treatment plants act as the major sources of MPs. For MPs analysis, pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), Py-MS methods, Raman spectroscopy, and FT-IR spectroscopy are regarded as the most promising methods for MPs identification and quantification. Due to the large surface area to volume ratio, crystallinity, hydrophobicity and functional groups, MPs can interact with various contaminants such as heavy metals, antibiotics and persistent organic contaminants. Among different physical and biological treatment technologies, the MPs removal performance decreases as membrane bioreactor (> 99%) > activated sludge process (~98%) > rapid sand filtration (~97.1%) > dissolved air floatation (~95%) > electrocoagulation (> 90%) > constructed wetlands (88%). Chemical treatment methods such as coagulation, magnetic separations, Fenton, photo-Fenton and photocatalytic degradation also show moderate to high efficiency of MP removal. Hybrid treatment technologies show the highest removal efficacies of MPs. Finally, future research directions for MPs are elaborated.

The what, how, why, and when of dendrochemistry: (paleo)environmental information from the chemical analysis of tree rings

The chemical analysis of tree rings has attracted the interest of researchers in the past five decades in view of the possibility of exploiting this biological indicator as a widely available, high-resolution environmental archive. Information regarding the surrounding environment can be derived either by directly measuring environmental variables (nutrient availability, presence of pollutants, etc.) or by exploiting proxies (e.g. paleoclimatic and paleoenvironmental reconstructions). This review systematically covers the topic and provides a critical view on the reliability of dendrochemical information. First, we introduce the determinable chemical species, such as major elements, trace metals, isotopic ratios, and organic compounds, together with a brief description of their uptake mechanisms and functions in trees. Subsequently, we present the possibilities offered by analytical techniques in the field of tree ring analysis, focusing on direct methods and recent developments. The latter strongly improved the details of the accessible information, enabling the investigation of complex phenomena associated with plant life and encouraging the direct analysis of new analytes, particularly minor organic compounds. With regard to their applications, dendrochemical proxies have been used to trace several processes, such as environmental contamination, paleoclimate reconstruction, global environmental changes, tree physiology, extreme events, ecological trends, and dendroprovenance. Several case studies are discussed for each proposed application, with special emphasis on the reliability of tracing each process. Starting from the reviewed literature data, the second part of the paper is devoted to the critical assessment of the reliability of tree ring proxies. We provide an overview of the current knowledge, discuss the limitations of the inferences that may be drawn from the dendrochemical data, and provide recommendations for the best practices to be used for their validation. Finally, we present the future perspectives related to the advancements in analytical instrumentation and further extension of application fields.

Standardized methods for testing the quality attributes of plant-based foods: Milk and cream alternatives

The food industry is creating a diverse range of plant-based alternatives to dairy products, such as milks, creams, yogurts, and cheeses due to the increasing demand from consumers for more sustainable, healthy, and ethical products. These dairy alternatives are often designed to mimic the desirable physicochemical, functional, and sensory properties of real dairy products, such as their appearance, texture, mouthfeel, flavor, and shelf-life. At present, there is a lack of systematic testing methods to characterize the properties of plant-based dairy alternatives. The purpose of this review is to critically evaluate existing methods and recommend a series of standardized tests that could be used to quantify the properties of fluid plant-based milk alternatives (milk and cream). These methods could then be used to facilitate the design of milk alternatives with somewhat similar attributes as real dairy milk by comparing their properties under standardized conditions. Moreover, they could be used to facilitate comparison of the properties of milk alternatives developed in different laboratories.

Label-free imaging of fibroblast membrane interfaces and protein signatures with vibrational infrared photothermal and phase signals

Label-free vibrational imaging of biological samples has attracted significant interest due to its integration of structural and chemical information. Vibrational infrared photothermal amplitude and phase signal (VIPPS) imaging provide label-free chemical identification by targeting the characteristic resonances of biological compounds that are present in the mid-infrared fingerprint region (3 µm - 12 µm). High contrast imaging of subcellular features and chemical identification of protein secondary structures in unlabeled and labeled fibroblast cells embedded in a collagen-rich extracellular matrix is demonstrated by combining contrast from absorption signatures (amplitude signals) with sensitive detection of different heat properties (lock-in phase signals). We present that the detectability of nano-sized cell membranes is enhanced to well below the optical diffraction limit since the membranes are found to act as thermal barriers. VIPPS offers a novel combination of chemical imaging and thermal diffusion characterization that paves the way towards label-free imaging of cell models and tissues as well as the study of intracellular heat dynamics.

Environmental fate and impacts of microplastics in aquatic ecosystems: a review

Wide usage of plastic products leads to the global occurrence of microplastics (MPs) in the aquatic environment. Due to the small size, they can be bio-ingested, which may cause certain health effects. The present review starts with summarizing the main sources of various types of MPs and their occurrences in the aquatic environment, as well as their transportation and degradation pathways. The analysis of migration of MPs in water environments shows that the ultimate fate of most MPs in water environments is cracked into small fragments and sinking into the bottom of the ocean. The advantages and disadvantages of existing methods for detection and analysis of MPs are summarized. In addition, based on recent researches, the present review discusses MPs as carriers of organic pollutants and microorganisms, and explores the specific effects of MPs on aquatic organisms in the case of single and combined pollutants. Finally, by analysing the causes and influencing factors of their trophic transfer, the impact of MPs on high-level trophic organisms is explored.

The sources, fate and impacts of microplastics in aquatic ecosystems.

Microplastics: Holistic overview of source, identification, interaction, health and environmental implications and strategies of abatement

Microplastic (MP) is currently a subject of discussion in all parts of the world because it has increasingly over the years become the dominant source of pollution in marine ecosystem. Huge number of these Mps emanate from waste management, decommissioning of ships and oil rigs, plastic products in aquaculture and fishery, sewage treatment, consumer products, agricultural production, transportation, offshore oil and gas production and city dust and wears. Microplastic are characteristically non- biodegradable or durable, exhibits buoyancy, travel long distances, complex with toxic chemicals and bioaccumulate being invisible to the human eye. Classification of MPs into primary and secondary based on source and established standard protocols visa-vis the sampling and identification in matrices were critically reviewed. Physicochemical processes for identification of MPs such as pyrolysis-Gas chromatography/Mass spectrometry, FTIR, Raman spectroscopy, SEM-GS and TGA/MS were reviewed. Deleterious chemicals such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), dioxins, phthalates, polycyclic aromatic hydrocarbons (PAHs) and persistent organic chemicals (POCs) associated with MPs and mechanisms of chelation were appraised. Several menace and health hazards such as hepatic inflammation, genetic mutation, increase in reactive oxygen species (ROS) /oxidative stress, tissue necrosis and proliferation of cells linked with MPs were also discussed. Furthermore, green approaches to arresting the menace such as replacing polymer products with biopolymer an eco-friendly alternative, recycling of plastic products, use of paper bags and glass materials and abrogation of consumer products laced with microbeads were advocated.

Automated rapid & intelligent microplastics mapping by FTIR microscopy: A Python-based workflow

The analysis of environmental microplastic particles using FTIR microscopy is a challenging task, due to the very high number of individual particles within a single sample. Therefore, automatable, fast and robust approaches are highly requested. Micro particles were commonly enriched on filters, and sub- or the whole filter area was investigated, which took more than 20h and produced millions of data, which had to be evaluated. This paper presents a new approach of such filter area analysis using an intelligent algorithm to measure only those spots on a filter that would produce evaluable FTIR data. Empty spaces or IR absorbers like carbon black particles were not measured which successfully reduced the total analysis time from 50h to 7h. The presented method is based on system independent Python workflow and can easily be implemented on other FTIR systems.

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Fast and intelligent FTIR microscopy area mapping without FPA detector

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Total time reduction from 50 h to 7 h

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Platform independent approach based on Python

Investigation of Biochemical Alterations in Ischemic Stroke Using Fourier Transform Infrared Imaging Spectroscopy-A Preliminary Study

Objective: Brain damage, long-term disability and death are the dreadful consequences of ischemic stroke. It causes imbalance in the biochemical constituents that distorts the brain dynamics. Understanding the sub-cellular alterations associated with the stroke will contribute to deeper molecular understanding of brain plasticity and recovery. Current routine approaches examining lipid and protein biochemical changes post stoke can be difficult. Fourier Transform Infrared (FTIR) imaging spectroscopy can play a vital role in detecting these molecular alterations on a sub-cellular level due to its high spatial resolution, accuracy and sensitivity. This study investigates the biochemical and molecular changes in peri-infract zone (PIZ) (contiguous area not completely damaged by stroke) and ipsi-lesional white matter (WM) (right below the stroke and PIZ regions) nine weeks post photothrombotic ischemic stroke in rats. Materials and Methods: FTIR imaging spectroscopy and transmission electron microscopy (TEM) techniques were applied to investigate brain tissue samples while hematoxylin and eosin (H&E) stained images of adjacent sections were prepared for comparison and examination the morphological changes post stroke. Results: TEM results revealed shearing of myelin sheaths and loss of cell membrane, structure and integrity after ischemic stroke. FTIR results showed that ipsi-lesional PIZ and WM experienced reduction in total protein and total lipid content compared to contra-lesional hemisphere. The lipid/protein ratio reduced in PIZ and adjacent WM indicated lipid peroxidation, which results in lipid chain fragmentation and an increase in olefinic content. Protein structural change is observed in PIZ due to the shift from random coli and α-helical structures to β-sheet conformation. Conclusion: FTIR imaging bio-spectroscopy provide novel biochemical information at sub-cellular levels that be difficult to be obtained by routine approaches. The results suggest that successful therapeutic strategy that is based on administration of anti-oxidant therapy, which could reduce and prevent neurotoxicity by scavenging the lipid peroxidation products. This approach will mitigate tissue damage in chronic ischemic period. FTIR imaging bio-spectroscopy can be used as a powerful tool and offer new approach in stroke and neurodegenerative diseases research.

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.

Microplastics in freshwater systems: A review on occurrence, environmental effects, and methods for microplastics detection

The continuous increase in synthetic plastic production and poor management in plastic waste have led to a tremendous increase in the dumping into our aqueous environment. Consequently, microplastics commonly defined as sizes less than 5 mm are produced and stay in both seawater and freshwater environment. The presence of microplastics as a new type of emerging contaminant has become a great issue of concerns from public and government authorities. The sources of microplastics to freshwater systems are many with the largest portion from wastewater treatment plants. The abundance of microplastics varies with the location, from above 1 million pieces per cubic meter to less than 1 piece in 100 cubic meters. Microplastics can cause several harmful physical effects on humans and living organisms through such mechanisms as entanglement and ingestion. The microplastics can act as carriers of various toxins such as additives from industrial production processes and persistent contaminants by the sorption in waters. Those toxins may cause great health problems to humans. A few studies on the fishes demonstrated that the microplastics and the associated toxins are bio-accumulated and cause such problems as intestinal damage and change in metabolic profiles. In studies of microplastics, fresh water is first sampled by the nets with typical mesh size of 330 μm for collection of microplastics. After the volume reducing process, the samples will then go through the purification process including density separation by such inorganic salts as sodium chloride and digestion process by oxidizing agents or enzymes. The sequence of these two processes (namely purification and digestion) is dependent on the sample type. The purified samples can be studied by several analytical methods. The commonly used methods for the qualification studies are FTIR spectroscopy, Raman spectroscopy, pyrolysis-GC/MS, and liquid chromatography. A tagging method can be used in the quantification study. Our literature study finds that there is still no universal accepted quantification and qualification tools of microplastics in fresh waters. More work is anticipated so as to obtain accurate information on microplastics in freshwater, which can then be used for the better assessment of the environmental risk.

Development of molecular-selective differential interference contrast microscopy utilizing stimulated Raman scattering

Development of a differential interference contrast (DIC) stimulated Raman scattering (SRS) microscope is presented. In the apparatus, a coherent SRS signal generated from the sample is overlapped with a reference beam that is also focused on the same sample. The signal intensity correlates with the height difference between the point generating the SRS signal and the focal point of the reference beam. We applied the developed apparatus for imaging of Si surfaces with structures with heights of 50-350 nm. We also obtained the DIC-SRS image of the Si surface buried by liquid crystal. The structures of the interface between Si and liquid crystal were well observed when both the SRS signals due to Si and liquid crystal were utilized. It was also revealed that DIC-SRS microscopy is an effective tool to obtain molecular-selective images of structured interfaces with a height of less than several tens of nanometers buried by optically transparent media.

Mitigating fringing in discrete frequency infrared imaging using time-delayed integration

Infrared (IR) spectroscopic microscopes provide the potential for label-free quantitative molecular imaging of biological samples, which can be used to aid in histology, forensics, and pharmaceutical analysis. Most IR imaging systems use broadband illumination combined with a spectrometer to separate the signal into spectral components. This technique is currently too slow for many biomedical applications such as clinical diagnosis, primarily due to the availability of bright mid-infrared sources and sensitive MCT detectors. There has been a recent push to increase throughput using coherent light sources, such as synchrotron radiation and quantum cascade lasers. While these sources provide a significant increase in intensity, the coherence introduces fringing artifacts in the final image. We demonstrate that applying time-delayed integration in one dimension can dramatically reduce fringing artifacts with minimal alterations to the standard infrared imaging pipeline. The proposed technique also offers the potential for less expensive focal plane array detectors, since linear arrays can be more readily incorporated into the proposed framework.

Mid-infrared spectroscopy and microscopy of subcellular structures in eukaryotic cells with atomic force microscopy – infrared spectroscopy

Atomic force microscopy – infrared (AFM-IR) spectroscopy allows spectroscopic studies in the mid-infrared (mid-IR) spectral region with a spatial resolution better than is allowed by the diffraction limit. We show that the high spatial resolution can be used to perform spectroscopic and imaging studies at the subcellular level in fixed eukaryotic cells. We collect AFM-IR images of subcellular structures that include lipid droplets, vesicles and cytoskeletal filaments, by relying on the intrinsic contrast from IR light absorption. We also obtain AFM-IR absorption spectra of individual subcellular structures. Most spectra show features that are recognizable in the IR absorption spectra of cells and tissue obtained with FTIR technology, including absorption bands characteristic of phospholipids and polypeptides. The quality of the spectra and of the images opens the way to structure and composition studies at the subcellular level using mid-IR absorption spectroscopy.

Atomic force microscopy – infrared (AFM-IR) spectroscopy allows spectroscopic studies in the mid-infrared (mid-IR) spectral region with a spatial resolution better than is allowed by the diffraction limit.

Quantitative Chemical Analysis at the Nanoscale Using the Photothermal Induced Resonance Technique

Photothermal induced resonance (PTIR), also known as AFM-IR, is a scanning probe technique that provides sample composition information with a lateral resolution down to 20 nm. Interest in PTIR stems from its ability to identify unknown samples at the nanoscale thanks, in first approximation, to the direct comparability of PTIR spectra with far-field infrared databases. The development of rapidly tuning quantum cascade lasers has increased the PTIR throughput considerably, making nanoscale hyperspectral imaging within a reasonable time frame possible. Consequently, a better understanding of PTIR signal generation and of the fine details of PTIR analysis has become of paramount importance for extending complex IR analysis methods developed in the far-field, e.g., for classification and hyperspectral imaging, to nanoscale PTIR spectra. Here we calculate PTIR spectra via thin-film optics, to identify subtle changes (band shifts, deviation from linear approximation, etc.) for common sample parameters in the case of PTIR with total internal reflection illumination. Results show signal intensity linearity and small band shifts as long as the sample is prepared correctly, with band shifts typically smaller than macroscale attenuated total reflection (ATR) spectroscopy. Finally, a generally applicable algorithm to retrieve the pure imaginary component of the refractive index (i.e., the chemically specific information) is provided to overcome the PTIR spectra nonlinearity.

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

Triglyceride dependent differentiation of obesity in adipose tissues by FTIR spectroscopy coupled with chemometrics

The excess deposition of triglycerides in adipose tissue is the main reason of obesity and causes excess release of fatty acids to the circulatory system resulting in obesity and insulin resistance. Body mass index and waist circumference are not precise measure of obesity and obesity related metabolic diseases. Therefore, in the current study, it was aimed to propose triglyceride bands located at 1770-1720 cm^-1 spectral region as a more sensitive obesity related biomarker using the diagnostic potential of Fourier Transform Infrared (FTIR) spectroscopy in subcutaneous (SCAT) and visceral (VAT) adipose tissues. The adipose tissue samples were obtained from 10 weeks old male control (DBA/2J) (n = 6) and four different obese BFMI mice lines (n = 6 per group). FTIR spectroscopy coupled with hierarchical cluster analysis (HCA) and principal component analysis (PCA) was applied to the spectra of triglyceride bands as a diagnostic tool in the discrimination of the samples. Successful discrimination of the obese, obesity related insulin resistant and control groups were achieved with high sensitivity and specificity. The results revealed the power of FTIR spectroscopy coupled with chemometric approaches in internal diagnosis of abdominal obesity based on the spectral differences in the triglyceride region that can be used as a spectral marker.

Optimization of alginate microcapsules containing cells overexpressing α-l-iduronidase using Box-Behnken design

Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease caused by deficiency of α-l-iduronidase (IDUA), which results in the lysosomal accumulation of glycosaminoglycans (GAG) leading to widespread clinical manifestations. The microencapsulation of IDUA overexpressing recombinant cells has been considered as a promising strategy for the treatment of MPS I. This study aimed at the optimization of alginate microcapsules containing recombinant BHK (Baby Hamster Kidney) cells (rBHK) overexpressing IDUA produced by electrostatic extrusion technique. The alginate microcapsule (MC-A) optimization study was carried out by means of an experimental Box-Behnken Design that allowed the simultaneous evaluation of the influence of voltage (kV), alginate/cell suspension flow (mL/h), and alginate concentration (%) on size and IDUA activity. The optimal conditions of voltage (10kV), flow (25mL/h), and alginate concentration (1.3%) made possible to obtain the smallest microcapsules showing the highest IDUA activity. After optimization, the microcapsules were sequentially coated with PLL and alginate (MC-APA) to increase their stability. MC-A and MC-APA presented monodisperse populations (span<1.22) with an average diameter of less than 350μm. The coating increased the mechanical stability of MC-APA by about 6-fold and modulated the permeability to the enzyme. Surface analyzes of MC-APA showed the presence of PLL bands, suggesting that the last alginate layer appears to have only partially coated the PLL. After 30days of subcutaneous implantation of the MC-APA microcapsules containing rBHK cells in a MPS I murine model, a significant increase in IDUA activity was observed in the skin near the implant. Histological analysis revealed an inflammatory infiltrate at the application site, which did not prevent the release of the enzyme under the conditions evaluated. Taken together, the overall results demonstrate the feasibility of MC-APA as a potential alternative for local treatment of MPS I.

Using Infrared Spectroscopy and Multivariate Analysis to Detect Antibiotics' Resistant Escherichia coli Bacteria

Bacterial pathogens are one of the primary causes of human morbidity worldwide. Historically, antibiotics have been highly effective against most bacterial pathogens; however, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Early and rapid determination of bacterial susceptibility to antibiotics has become essential in many clinical settings and, sometimes, can save lives. Currently classical procedures require at least 48 h for determining bacterial susceptibility, which can constitute a life-threatening delay for effective treatment. Infrared (IR) microscopy is a rapid and inexpensive technique, which has been used successfully for the detection and identification of various biological samples; nonetheless, its true potential in routine clinical diagnosis has not yet been established. In this study, we evaluated the potential of this technique for rapid identification of bacterial susceptibility to specific antibiotics based on the IR spectra of the bacteria. IR spectroscopy was conducted on bacterial colonies, obtained after 24 h culture from patients' samples. An IR microscope was utilized, and a computational classification method was developed to analyze the IR spectra by novel pattern-recognition and statistical tools, to determine E. coli susceptibility within a few minutes to different antibiotics, gentamicin, ceftazidime, nitrofurantoin, nalidixic acid, ofloxacin. Our results show that it was possible to classify the tested bacteria into sensitive and resistant types, with success rates as high as 85% for a number of examined antibiotics. These promising results open the potential of this technique for faster determination of bacterial susceptibility to certain antibiotics.

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm⁻¹. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine.

In hyperspectral imaging a broadband spectrum is recorded at each pixel, which creates information-rich images. Here, the authors combine this concept with Fourier transform infrared nanospectroscopy to achieve 5,000-pixel, nanoscale-resolution images at wavelengths between 5 and 10 micrometres.

A quantitative framework for the analysis of multimodal optical microscopy images

BACKGROUND

Multimodal optical microscopy, a set of imaging techniques based on unique, yet complementary contrast mechanisms and spatially and temporally co-registered data acquisition, has emerged as a powerful biomedical tool. However, the analysis of the dense, high-dimensional datasets acquired by these instruments remains mostly qualitative and restricted to analysis of each modality individually.

METHODS

Using a custom-built multimodal nonlinear optical microscope, high dimensional datasets were acquired for automated classification of functional cell states as well as identification of histopathological features in tissues slices. Supervised classification of cell death modes was performed through support vector machines (SVM) and semi-supervised classification of tissue slices was performed through the use of the expectation maximization (EM) algorithm.

RESULTS

Applications of these techniques to the automated classification of cell death modes as well as to the identification of tissue components in fixed ex vivo tissue slices are presented. The analysis techniques developed provide a direct link between multimodal image contrast and biological structure and function, resulting in highly accurate classification in both settings.

CONCLUSIONS

Quantification of multimodal optical microscopy images through statistical modeling of the high dimensional data acquired gives a strong correlation between biological structure and function and image contrast. These methods are sensitive to the identification of diagnostic, cellular-level features important in a variety of clinical settings.

Improvement of Spatial Resolution for Nonlinear Raman Microscopy by Spatial Light Modulation

The development of a stimulated Raman scattering (SRS) microscope with a wavefront modulation unit is presented. In the apparatus, two beams for introducing the SRS process were focused into the sample with an objective lens. In the pathway of the Stokes beam, which is one of the two incident beams, a spatial light modulator (SLM) was located. Using the SLM, the wavefront of the Stokes beam was modulated to make the shape of the focal point a concentric circular pattern. By this spot shaping technique, the area where the SRS signal generates is restricted. The instrument response function (IRF) of the SRS microscope was examined by measuring the SRS intensity while scanning the sample position. From the result, the width of the IRF was reduced by about 15% by the wavefront modulation. It is suggested that the introduction of SLM is a way to improve the IRF of vibrational spectroscopic microscopes.