Dynamic molecular monitoring of retina inflammation by in vivo Raman spectroscopy coupled with multivariate analysis

Mechanical Stimulation of Anti-Inflammatory and Antioxidant Hydrogels for Rapid Re-Epithelialization

The epithelium, an essential barrier to protect organisms against infection, exists in many organs. However, rapid re-epithelialization to restore tissue integrity and function in an adverse environment is challenging. In this work, a long-term anti-inflammatory and antioxidant hydrogel with mechanical stimulation for rapid re-epithelialization, mainly composed of the small molecule thioctic acid, biocompatible glycine, and γ-Fe2O3 nanoparticles is reported. Glycine-modified supramolecular thioctic acid is stable and possesses outstanding mechanical properties. The incorporating γ-Fe2O3 providing the potential contrast function for magnetic resonance imaging observation, can propel hydrogel reconfiguration to enhance the mechanical properties of the hydrogel underwater due to water-initiated release of Fe3+. In vitro experiments show that the hydrogels effectively reduced intracellular reactive oxygen species, guided macrophages toward M2 polarization, and alleviated inflammation. The effect of rapid re-epithelialization is ultimately demonstrated in a long urethral injury model in vivo, and the mechanical stimulation of hydrogels achieves effective functional replacement and ultimately accurate remodeling of the epithelium. Notably, the proposed strategy provides an advanced alternative treatment for patients in need of large-area epithelial reconstruction.

Window into the mind: Advanced handheld spectroscopic eye-safe technology for point-of-care neurodiagnostic

Traumatic brain injury (TBI), a major cause of morbidity and mortality worldwide, is hard to diagnose at the point of care with patients often exhibiting no clinical symptoms. There is an urgent need for rapid point-of-care diagnostics to enable timely intervention. We have developed a technology for rapid acquisition of molecular fingerprints of TBI biochemistry to safely measure proxies for cerebral injury through the eye, providing a path toward noninvasive point-of-care neurodiagnostics using simultaneous Raman spectroscopy and fundus imaging of the neuroretina. Detection of endogenous neuromarkers in porcine eyes' posterior revealed enhancement of high-wave number bands, clearly distinguishing TBI and healthy cohorts, classified via artificial neural network algorithm for automated data interpretation. Clinically, translating into reduced specialist support, this markedly improves the speed of diagnosis. Designed as a hand-held cost-effective technology, it can allow clinicians to rapidly assess TBI at the point of care and identify long-term changes in brain biochemistry in acute or chronic neurodiseases.

Raman Spectroscopy Spectral Fingerprints of Biomarkers of Traumatic Brain Injury

Traumatic brain injury (TBI) affects millions of people of all ages around the globe. TBI is notoriously hard to diagnose at the point of care, resulting in incorrect patient management, avoidable death and disability, long-term neurodegenerative complications, and increased costs. It is vital to develop timely, alternative diagnostics for TBI to assist triage and clinical decision-making, complementary to current techniques such as neuroimaging and cognitive assessment. These could deliver rapid, quantitative TBI detection, by obtaining information on biochemical changes from patient's biofluids. If available, this would reduce mis-triage, save healthcare providers costs (both over- and under-triage are expensive) and improve outcomes by guiding early management. Herein, we utilize Raman spectroscopy-based detection to profile a panel of 18 raw (human, animal, and synthetically derived) TBI-indicative biomarkers (N-acetyl-aspartic acid (NAA), Ganglioside, Glutathione (GSH), Neuron Specific Enolase (NSE), Glial Fibrillary Acidic Protein (GFAP), Ubiquitin C-terminal Hydrolase L1 (UCHL1), Cholesterol, D-Serine, Sphingomyelin, Sulfatides, Cardiolipin, Interleukin-6 (IL-6), S100B, Galactocerebroside, Beta-D-(+)-Glucose, Myo-Inositol, Interleukin-18 (IL-18), Neurofilament Light Chain (NFL)) and their aqueous solution. The subsequently derived unique spectral reference library, exploiting four excitation lasers of 514, 633, 785, and 830 nm, will aid the development of rapid, non-destructive, and label-free spectroscopy-based neuro-diagnostic technologies. These biomolecules, released during cellular damage, provide additional means of diagnosing TBI and assessing the severity of injury. The spectroscopic temporal profiles of the studied biofluid neuro-markers are classed according to their acute, sub-acute, and chronic temporal injury phases and we have further generated detailed peak assignment tables for each brain-specific biomolecule within each injury phase. The intensity ratios of significant peaks, yielding the combined unique spectroscopic barcode for each brain-injury marker, are compared to assess variance between lasers, with the smallest variance found for UCHL1 (σ2 = 0.000164) and the highest for sulfatide (σ2 = 0.158). Overall, this work paves the way for defining and setting the most appropriate diagnostic time window for detection following brain injury. Further rapid and specific detection of these biomarkers, from easily accessible biofluids, would not only enable the triage of TBI, predict outcomes, indicate the progress of recovery, and save healthcare providers costs, but also cement the potential of Raman-based spectroscopy as a powerful tool for neurodiagnostics.

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

Preliminary study for the application of Raman spectroscopy for the identification of Leishmania infected dogs

Raman spectroscopy is a rapid qualitative and quantitative technique that allows the simultaneous determination of several components in biological fluids. This methodology concerns an alternative technique to distinguish between non-healthy and healthy subjects. Leishmaniasis is a zoonosis of world interest, the most important agent is L. infantum. Dogs are the principal reservoirs affected by a broad spectrum of clinical features. During a clinical exam, blood samples were collected in tubes without anticoagulants, from twenty two dogs. One aliquot was used for serological test for Leishmaniasis, one aliquot was subjected to the Raman spectroscopic analysis. Animals were divided into two groups of equal subjects, Leishmania group (LG) constituted by infected dogs, and control group (CG) constituted by healthy dogs. The acquired spectra were different in the region 1200-1370 cm^-1, in which it is possible to distinguish the amide III vibration (~ 1300 cm^-1). In LG, an evident shift to the shortwave region is observed in spectral frequencies of the band centered at ~ 1250 cm^-1. Our results distinguished between LD group and CG. Further studies are necessary to exclude the effect of metabolic modification due to disease on the recorded spectra changes and to consolidate the achievability of Raman spectroscopy as rapid and less expensive diagnosis of Leishmaniasis.

Raman Spectroscopic Study of Amyloid Deposits in Gelatinous Drop-like Corneal Dystrophy

The genetic and histopathological features of the cornea of a Polish patient with Gelatinous Drop-like Corneal Dystrophy (GDCD) and the molecular composition with Raman spectroscopy of corneal deposits were examined. A 62 year-old Polish woman was diagnosed with GDCD and underwent penetrating corneal transplant. A blood sample was collected, and genetic analysis was performed. The cornea was processed for light microscopy and Raman analysis. The genetic exam revealed a previously undescribed homozygous 1-base pair deletion in exon 1 of TACSTD2 gene (c.185delT), resulting in a frame shift causing a premature stop codon. When compared with a control cornea, in GDCD cornea stained with PAS evident deposits were present over the anterior stroma, with apple green birefringence under polarized light. Raman spectroscopy showed peculiar differences between normal and GDCD cornea, consisting in peaks either of different height or undetectable in the normal cornea and related to amyloid. The possible causative role of the novel mutation was discussed and Raman spectroscopy as a further morphological tool in the evaluation of corneal dystrophies, characterized by the deposition of abnormal materials, was suggested.

Raman Spectroscopy Technique: A Non-Invasive Tool in Celiac Disease Diagnosis

Celiac disease (CD) is diagnosed by a combination of specific serology and typical duodenal lesions. The histological confirmation of CD, mandatory in the majority of patients with suspected CD, is based on invasive and poorly tolerated procedures, such as upper gastrointestinal endoscopy. In this study we propose an alternative and non-invasive methodology able to confirm the diagnosis of CD based on the analysis of serum samples using the Raman spectroscopy technique. Three different bands centered at 1650, 1450 and 1003 cm^-1 have been considered and the A₁₄₅₀/A₁₀₀₃ and A₁₆₅₀/A₁₀₀₃ ratios have been computed to discriminate between CD and non-CD subjects. The reliability of the methodology was validated by statistical analysis using receiver operating characteristic (ROC) curves. The Youden index was also determined to obtain optimal cut-off points. The obtained results highlighted that the proposed methodology was able to distinguish between CD and non-CD subjects with 98% accuracy. The optimal cut-off points revealed, for both the A₁₄₅₀/A₁₀₀₃ and A₁₆₅₀/A₁₀₀₃ ratios, high values of sensitivity and specificity (>95.0% and >92.0% respectively), confirming that Raman spectroscopy may be considered a valid alternative to duodenal biopsy and demonstrates spectral changes in the secondary structures of the protein network.

In Vivo Molecular Changes in the Retina of Patients With Multiple Sclerosis

Purpose

Raman spectroscopy allows molecular changes to be quantified in vivo from the tissues like the retina. Here we aimed to assess the metabolic changes in the retina of patients with multiple sclerosis (MS).

Methods

We built a Raman spectroscopy prototype by connecting a scanning laser ophthalmoscope to a spectrophotometer. We defined the spectra of 10 molecules participating on energy supply, axon biology, or synaptic damage, which have been shown to be altered in the brain of patients with MS: cytochrome C, flavin adenine dinucleotide (FAD), nicotinamide adenine dinucleotide (NADH), N-acetyl-aspartate (NAA), excitotoxicity, glutamate, amyloid β (Aβ), τ and α-synuclein (SNCA), phosphatidyl-ethanolamine, and phosphatidyl-choline. We studied these molecules in a prospective cohort of patients with MS, either in the chronic phase or during relapses of acute optic neuritis (AON).

Results

Significant changes to all these molecules were associated with age in healthy individuals. There was a significant decrease in NADH and a trend toward a decrease in NAA in patients with MS, as well as an increase in Aβ compared with healthy controls. Moreover, NADH and FAD increased over time in a longitudinal analysis of patients with MS, whereas Aβ diminished. In patients with acute retinal inflammation due to AON, there was a significant increase in FAD and a decrease in SNCA in the affected retina. Moreover, glutamate levels increased in the affected eyes after a 6-month follow-up.

Conclusions

Alterations of molecules related to axonal degeneration are observed during neuroinflammation and show dynamic changes over time, suggesting progressive neurodegeneration.

Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study

The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies.

Spectroscopic detection of traumatic brain injury severity and biochemistry from the retina

Traumatic brain injury (TBI) is a major burden on healthcare services worldwide, where scientific and clinical innovation is needed to provide better understanding of biochemical damage to improve both pre-hospital assessment and intensive care monitoring. Here, we present an unconventional concept of using Raman spectroscopy to measure the biochemical response to the retina in an ex-vivo murine model of TBI. Through comparison to spectra from the brain and retina following injury, we elicit subtle spectral changes through the use of multivariate analysis, linked to a decrease in cardiolipin and indicating metabolic disruption. The ability to classify injury severity via spectra of the retina is demonstrated for severe TBI (82.0 %), moderate TBI (75.1 %) and sham groups (69.4 %). By showing that optical spectroscopy can be used to explore the eye as the window to the brain, we lay the groundwork for further exploitation of Raman spectroscopy for indirect, non-invasive assessment of brain chemistry.

Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy

The presence of biomarkers characteristic for Alzheimer’s disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer’s disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer’s disease identification.

Confocal Raman spectroscopy: Evaluation of a non-invasive technique for the detection of topically applied ketorolac tromethamine in vitro and in vivo

Current information about the pharmacokinetics of an ocular drug can only be achieved by invasive sampling. However, confocal Raman spectroscopy bears the potential to quantify drug concentrations non-invasively. In this project, we evaluated the detection and quantification of ocular ketorolac tromethamine levels with confocal Raman spectroscopy after topical administration. Confocal Raman spectroscopy and high-performance liquid chromatography (HPLC) were compared in terms of sensitivity of detection. Enucleated pig eyes were treated with different concentrations of ketorolac. Hereafter, ketorolac concentrations in the aqueous humor of pig eyes were analyzed by confocal Raman spectroscopy and HPLC. Subsequently, twelve rabbits were treated with Acular™ for four weeks. At several time points, ketorolac concentrations in aqueous humor of the rabbits were measured by confocal Raman spectroscopy followed by drawing an aqueous humor sample for HPLC analysis. In ketorolac treated pig eyes, both ex vivo Raman spectroscopy as well as HPLC were able to detect ketorolac in a broad concentration range. However, in vivo confocal Raman spectroscopy in rabbits was unable to detect ketorolac in contrast to HPLC. To conclude, confocal Raman spectroscopy has the capacity to detect ketorolac tromethamine in vitro, but currently lacks sensitivity for in vivo detection.

Local-dependency of morphological and optical properties between breast cancer cell lines

Breast cancer is the most malignant type of cancer in women and is a global health problem, with mortality by metastasis being the main factor among others. Currently, detection and diagnosis of breast cancer is achieved through a variety of procedures, such as clinical examination, medical imaging, biopsy, and histopathological analysis. In contrast, spectroscopic analysis has a variety of advantages such as being noninvasive, not destroying biological materials, and not requiring additional histological analysis. In this study, various approaches using Raman spectroscopy, atomic force microscopy (AFM), and optical microscopy were used together to differentiate between and characterize normal breast cell lines (MCF-10A) and breast cancer cell lines (MDA-MB-231, MDA-MB-453). Raman spectra of normal breast cell and breast cancer cell lines confirmed visual differences in the concentrations of various compounds. These spectra were also analyzed using principle component analysis (PCA), and the PCA results showed reliable separation of the three cell lines and the cancer cell lines (MDA-MB-231, MDA-MB-453). With these results, optically synchronizing the AFM morphology, the Raman spectroscopy, and the visible RGB optical transmission intensity provided contrasts for not only conformational differences but also intracellular variation between the normal and cancer cell lines. We observed the inherent characteristic that there is no local difference in cancer cells regardless of morphology in a wide range of optical properties such as absorption, scattering and inelastic scattering.

Assessment of tissue-specific multifactor effects in environmental -omics studies of heterogeneous biological samples: Combining hyperspectral image information and chemometrics

The use of hyperspectral imaging techniques in biological studies has increased in the recent years. Hyperspectral images (HSI) provide chemical information and preserve the morphology and original structure of heterogeneous biological samples, which can be potentially useful in environmental -omics studies when effects due to several factors, e.g., contaminant exposure, phenotype,…, at a specific tissue level need to be investigated. Yet, no available strategies exist to exploit adequately this kind of information. This work offers a novel chemometric strategy to pass from the raw image information to useful knowledge in terms of statistical assessment of the multifactor effects of interest in -omic studies. To do so, unmixing of the hyperspectral image measurement is carried out to provide tissue-specific information. Afterwards, several specific ANOVA-Simultaneous Component Analysis (ASCA) models are generated to properly assess and interpret the diverse effect of the factors of interest on the spectral fingerprints of the different tissues characterized. The unmixing step is performed by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) on multisets of biological images related to each studied condition and provides reliable HSI spectral signatures and related image maps for each specific tissue in the regions imaged. The variability associated with these signatures within a population is obtained through an MCR-based resampling step on representative pixel subsets of the images analyzed. All spectral fingerprints obtained for a particular tissue in the different conditions studied are used to obtain the related ASCA model that will help to assess the significance of the factors studied on the tissue and, if relevant, to describe the associated fingerprint modifications. The potential of the approach is assessed in a real case of study linked to the investigation of the effect of exposure time to chlorpyrifos-oxon (CPO) on ocular tissues of different phenotypes of zebrafish larvae from Raman HSI of eye cryosections. The study allowed the characterization of melanin, crystalline and internal eye tissue and the phenotype, exposure time and the interaction of the two factors were found to be significant in the changes found in all kind of tissues. Factor-related changes in the spectral fingerprint were described and interpreted per each kind of tissue characterized.

Biological and Medical Applications of Multivariate Curve Resolution Assisted Raman Spectroscopy

Biological specimens such as cells, tissues and biofluids (urine, blood) contain mixtures of many different biomolecules, all of which contribute to a Raman spectrum at any given point. The separation and identification of pure biochemical components remains one of the biggest challenges in Raman spectroscopy. Multivariate curve resolution, a matrix factorization method, is a powerful, yet flexible, method that can be used with constraints, such as non-negativity, to decompose a complex spectroscopic data matrix into a small number of physically meaningful pure spectral components along with their relative abundances. This paper reviews recent applications of multivariate curve resolution by alternating least squares analysis to Raman spectroscopic and imaging data obtained either in vivo or in vitro from biological and medical samples.

Unravelling the Metabolic Progression of Breast Cancer Cells to Bone Metastasis by Coupling Raman Spectroscopy and a Novel Use of Mcr-Als Algorithm

Raman spectroscopy (RS) has shown promise as a tool to reveal biochemical changes that occur in cancer processes at the cellular level. However, when analyzing clinical samples, RS requires improvements to be able to resolve biological components from the spectra. We compared the strengths of Multivariate Curve Resolution (MCR) versus Principal Component Analysis (PCA) to deconvolve meaningful biological components formed by distinct mixtures of biological molecules from a set of mixed spectra. We exploited the flexibility of the MCR algorithm to easily accommodate different initial estimates and constraints. We demonstrate the ability of MCR to resolve undesired background signals from the RS that can be subtracted to obtain clearer cancer cell spectra. We used two triple negative breast cancer cell lines, MDA-MB 231 and MDA-MB 435, to illustrate the insights obtained by RS that infer the metabolic changes required for metastasis progression. Our results show that increased levels of amino acids and lower levels of mitochondrial signals are attributes of bone metastatic cells, whereas lung metastasis tropism is characterized by high lipid and mitochondria levels. Therefore, we propose a method based on the MCR algorithm to achieve unique biochemical insights into the molecular progression of cancer cells using RS.

Combining hyperspectral imaging and chemometrics to assess and interpret the effects of environmental stressors on zebrafish eye images at tissue level

Changes on an organism by the exposure to environmental stressors may be characterized by hyperspectral images (HSI), which preserve the morphology of biological samples, and suitable chemometric tools. The approach proposed allows assessing and interpreting the effect of contaminant exposure on heterogeneous biological samples monitored by HSI at specific tissue levels. In this work, the model example used consists of the study of the effect of the exposure of chlorpyrifos-oxon on zebrafish tissues. To assess this effect, unmixing of the biological sample images followed by tissue-specific classification models based on the unmixed spectral signatures is proposed. Unmixing and classification are performed by multivariate curve resolution-alternating least squares (MCR-ALS) and partial least squares-discriminant analysis (PLS-DA), respectively. Crucial aspects of the approach are: (1) the simultaneous MCR-ALS analysis of all images from 1 population to take into account biological variability and provide reliable tissue spectral signatures, and (2) the use of resolved spectral signatures from control and exposed populations obtained from resampling of pixel subsets analyzed by MCR-ALS multiset analysis as information for the tissue-specific PLS-DA classification models. Classification results diagnose the presence of a significant effect and identify the spectral regions at a tissue level responsible for the biological change.

In vivo analysis of mucosal lipids reveals histological disease activity in ulcerative colitis using endoscope-coupled Raman spectroscopy

The goal of this study is to evaluate endoscopic Raman spectroscopy as a noninvasive technique to determine histological inflammatory status of colitis. Colon mucosal composition was investigated in vivo from patients with ulcerative colitis (UC) and from age- and body mass index (BMI) matched controls using endoscope-coupled Raman spectroscopy. The results were co-registered with histological assessment of inflammatory status at the same locations. Substantial decreases (50-60%) in the content of phosphotidylcholines (PCs) and total lipids were observed in inflamed colon tissue (histology grade 1, 2 and 3) compared to those from the quiescent (histology grade 0) and from the controls. No significant difference was observed in lipids or PC contents between control and grade 0, or among grades 1 - 3. The degree of lipid unsaturation increased in the inflamed tissue regardless of disease severity. The inflammation-associated alterations in lipids and PC are observed independent of BMI or the anatomical locations for data collection. Multivariate analysis using support vector machine (SVM) algorithm classified the spectra of the controls or the inactive colitis from those of inflamed tissue with a sensitivity of 83.5% and 97.1% respectively. Our results showed that mucosal lipid content is related to the microscopic disease activity, and thus could serve as a valuable spectral marker to differentiate active colitis from the quiescent.

Optical coherence tomography: A quantitative tool to measure neurodegeneration and facilitate testing of novel treatments for tissue protection in multiple sclerosis

Optical coherence tomography (OCT) is a relatively new imaging technology that has been introduced as a powerful biomarker in neurological disease, including multiple sclerosis. In this review, OCT as an imaging technique, its reproducibility and validation in multiple sclerosis, application to other neurodegenerative diseases and future technological directions are discussed.

Rapid spontaneous Raman light sheet microscopy using cw-lasers and tunable filters

We perform rapid spontaneous Raman 2D imaging in light-sheet microscopy using continuous wave lasers and interferometric tunable filters. By angularly tuning the filter, the cut-on/off edge transitions are scanned along the excited Stokes wavelengths. This allows obtaining cumulative intensity profiles of the scanned vibrational bands, which are recorded on image stacks; resembling a spectral version of the knife-edge technique to measure intensity profiles. A further differentiation of the stack retrieves the Raman spectra at each pixel of the image which inherits the 3D resolution of the host light sheet system. We demonstrate this technique using solvent solutions and composites of polystyrene beads and lipid droplets immersed in agar and by imaging the C-H (2800-3100cm(-1)) region in a C. elegans worm. The image acquisition time results in 4 orders of magnitude faster than confocal point scanning Raman systems, allowing the possibility of performing fast spontaneous Raman·3D-imaging on biological samples.

Potential use of multivariate curve resolution for the analysis of mass spectrometry images

The application of MCR-ALS to mass spectrometry imaging data provides spatial distribution and MS spectra of components, allowing compound identification.