This PDF file contains the front matter associated with SPIE Proceedings Volume 9704, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

A detailed knowledge of optical properties of tissue is important for the development of non-invasive monitoring systems for clinical practice. However, tissue optical properties are rarely known in the mid-infrared wavelength range. Goniometry offers an opportunity to determine in particular the scattering properties of tissue. Here, a custom-built setup is presented for goniometric measurements in the mid-infrared based on quantum cascade lasers.

Resonant enhancement of Raman signals is a useful method to increase sensitivity in samples with low concentration such as biological tissue. The investigation of resonance profiles shows the optimal excitation wavelength and yields valuable information about the molecules themselves. However careful characterization and calibration of all experimental parameters affecting quantum yield is required in order to achieve comparability of the single spectra recorded. We present an experimental technique for measuring the resonance profiles of different amino acids. The absorption lines of these molecules are located in the ultraviolet (UV) wavelength range. One limitation for broadband measurement of resonance profiles is the limited availability of Raman filters in certain regions of the UV for blocking the Rayleigh scattered light. Here, a wavelength range from 244.8 nm to 266.0 nm was chosen. The profiles reveal the optimal wavelength for recording the Raman spectra of amino acids in aqueous solutions in this range. This study provides the basis for measurements on more complex molecules such as proteins in the human perilymph. The composition of this liquid in the inner ear is essential for hearing and cannot be analyzed non-invasively so far. The long term aim is to implement this technique as a fiber based endoscope for non-invasive measurements during surgeries (e. g. cochlear implants) making it available as a diagnostic tool for physicians. This project is embedded in the interdisciplinary cluster of excellence "Hearing for all" (H4A).

The high water content of meat, combined with all the nutrients it contains, make it vulnerable to spoilage at all stages of production and storage even when refrigerated at 5 °C. A non-destructive and in situ tool for meat sample testing, which could provide an accurate indication of the storage time of meat, would be very useful for the control of meat quality as well as for consumer safety. The proposed solution is based on Raman spectroscopy which is non-invasive and can be applied in situ. For the purposes of this project, 42 meat samples from 14 animals were obtained and three Raman spectra per sample were collected every two days for two weeks. The spectra were subsequently processed and the sample age was calculated using a set of linear differential equations. In addition, the samples were classified in categories corresponding to the age in 2-day steps (i.e., 0, 2, 4, 6, 8, 10, 12 or 14 days old), using linear discriminant analysis and cross-validation. Contrary to other studies, where the samples were simply grouped into two categories (higher or lower quality, suitable or unsuitable for human consumption, etc.), in this study, the age was predicted with a mean error of ~ 1 day (20%) or classified, in 2-day steps, with 100% accuracy. Although Raman spectroscopy has been used in the past for the analysis of meat samples, the proposed methodology has resulted in a prediction of the sample age far more accurately than any report in the literature.

Infrared (IR) spectroscopic imaging is an emerging modality for biological tissue analysis that has traditionally employed an interferometer for spectral discrimination. Recent technology developments have made discrete frequency sources, both lasers and filters, practical for imaging. The use of quantum cascade lasers in particular, presents new opportunities as well as challenges. Here we describe results from a novel point scanning confocal IR microscope and demonstrate the performance imaging several important spectral bands of lung tissue. Results show the possibility of discrete frequency (DF) absorbance measurements with RMS noise levels down to 0.34 mAU in 0.25 ms.

Circulating tumor cells (CTCs) that can be extracted from body fluids offer new prospects in cancer diagnostics. An overview about our recent achievements is presented to use Raman-based methodologies to distinguish cancer cells from normal blood cells. In a first approach, a microfluidic chip was developed to collect Raman spectra from optically trapped cells. Whereas sensitivities and specificities were promising, the throughput was not compatible with the expected low number of CTCs per million white blood cells. A second strategy immobilized up to 200,000 cells onto a microhole array made of silicon nitride. Rapid microscopic screening can be applied to pre-select a subset of cells from which Raman spectra are collected for specific CTC identification. As this approach is compatible with living cells and Raman spectroscopy with 785 nm excitation is non-destructive, a robotic arm can select positively identified CTCs for in-depth biochemical assessment. Finally, an in vivo approach directly collects CTCs from the blood stream. This way reduces the cell number to a manageable size that is subjected to Raman spectroscopy for cell typing and enumeration. An integrated acquisition mode was introduced to further increase the throughput and robustness of single cell classification.

Colorectal cancer (CRC) is the third most common cancer in men and women in the United States. Raman Molecular Imaging (RMI) is an effective technique to evaluate human tissue, cells and bodily fluids, including blood serum for disease diagnosis. ChemImage Corporation, in collaboration with clinicians, has been engaged in development of an in vitro diagnostic Raman assay focused on CRC detection. The Raman Assay for Colorectal Cancer (RACC) exploits the high specificity of Raman imaging to distinguish diseased from normal dried blood serum droplets without additional reagents. Pilot Study results from testing of hundreds of biobank patient samples have demonstrated that RACC detects CRC with high sensitivity and specificity. However, expanded clinical trials, which are ongoing, are revealing a host of important preanalytical considerations associated with sample collection, sample storage and stability, sample shipping, sample preparation and sample interferents, which impact detection performance. Results from recent clinical studies will be presented.

Colorectal cancer (CRC) is the third most common type of cancer and forth leading cause of cancer-related death. Early diagnosis is the key to long-term patient survival. Programmatic screening for the general population has shown to be cost-effective in reducing the incidence and mortality from CRC. Current CRC screening strategy relies on a broad range of test techniques such as fecal based tests and endoscopic exams. Occult blood tests like fecal immunochemical test is a cost effective way to detect CRC but have limited diagnostic values in detecting adenomatous polyp, the most treatable precursor to CRC. In the present work, we proposed the use of surface enhanced Raman spectroscopy (SERS) with silver nanoparticles as substrate to analyze blood plasma for detecting both CRC and adenomatous polyps. Blood plasma samples collected from healthy subjects and patients diagnosed with adenomas and CRC were prepared with nanoparticles and measured using a real-time fiber optic probe based Raman system. The collected SERS spectra are analyzed with partial least squares-discriminant analysis. Classification of normal versus CRC plus adenomatous polyps achieved diagnostic sensitivity of 86.4% and specificity of 80%. This exploratory study suggests that blood plasma SERS analysis has potential to become a screening test for detecting both CRC and adenomas.

Despite the demonstrated potential as an accurate cancer diagnostic tool, Raman spectroscopy (RS) is yet to be adopted by the clinic for histopathology reviews. The Stratified Medicine through Advanced Raman Technologies (SMART) consortium has begun to address some of the hurdles in its adoption for cancer diagnosis. These hurdles include awareness and acceptance of the technology, practicality of integration into the histopathology workflow, data reproducibility and availability of transferrable models. We have formed a consortium, in joint efforts, to develop optimised protocols for tissue sample preparation, data collection and analysis. These protocols will be supported by provision of suitable hardware and software tools to allow statistically sound classification models to be built and transferred for use on different systems. In addition, we are building a validated gastrointestinal (GI) cancers model, which can be trialled as part of the histopathology workflow at hospitals, and a classification tool. At the end of the project, we aim to deliver a robust Raman based diagnostic platform to enable clinical researchers to stage cancer, define tumour margin, build cancer diagnostic models and discover novel disease bio markers.

Raman spectroscopy (RS) is proving to be a valuable tool for real time noninvasive skin cancer detection via optical fiber probe. However, current methods utilizing RS for skin cancer diagnosis rely on statistically based algorithms to provide tissue classification and do not elucidate the underlying biophysical changes of skin tissue. Therefore, we aim to use RS to explore skin biochemical and structural characteristics and then correlate the Raman spectrum of skin tissue with its disease state. We have built a custom confocal micro-Raman spectrometer system with an 830nm laser light. The high resolution capability of the system allows us to measure spectroscopic features from individual tissue components in situ. Raman images were collected from human skin samples from Mohs surgical biopsy, which were then compared with confocal laser scanning, two-photon fluorescence and hematoxylin and eosin-stained images to develop a linear model of skin tissue Raman spectra. In this model, macroscopic tissue spectra obtained from RS fiber probe were fit into a linear combination of individual basis spectra of primary skin constituents. The fit coefficient of the model explains the biophysical changes spanning a range of normal and various disease states. The model allows for determining parameters similar to that a pathologist is familiar reading and will be a significant guidance in developing RS diagnostic decision schemes.

Raman spectroscopy is a unique optical vibrational spectroscopic technique which is capable of probing biochemical and biomolecular structures and conformations associated with disease transformation. Raman probe is a key component to facilitate the in vivo tissue diagnosis by using Raman spectroscopy. The diagnostic performance of the two different endoscope-based fiber-optic Raman probe designs (i.e., beveled and volume Raman probes) were evaluated for real-time, in vivo diagnosis of gastric dysplasia at endoscopy. The beveled Raman probe provides approximately 2-fold improvements in tissue Raman to autofluorescence intensity ratios as compared to the use of volume Raman probe. The diagnostic accuracy of gastric dysplasia using beveled Raman probe is 93.0% (sensitivity of 92.5%; specificity of 93.1%), which is superior to the diagnostic performance (accuracy of 88.4%; sensitivity of 85.8%; specificity of 88.6%) using the volume Raman probe. Biomolecular modeling is finally employed to extract the different Raman active components interrogated by the two types of endoscope-based Raman probes.

Determination of cancerous and normal kidney tissues during partial, simple or radical nephrectomy surgery was performed by using differences in the IR absorption spectra of extracellular fluid taken from the corresponding tissue areas. The samples were prepared by stamping of the kidney tissue on ATR diamond crystal. The spectral measurements were performed directly in the OR during surgery for 58 patients. It was found that intensities of characteristic spectral bands of glycogen (880-1200 cm^-1) in extracellular fluid are sensitive to the type of the tissue and can be used as spectral markers of tumours. Characteristic spectral band of lactic acid (1730 cm^-1) - product of the anaerobic glycolysis, taking place in the cancer cells is not suitable for use as a spectral marker of cancerous tissue, since it overlaps with the band of carbonyl stretch in phospholipids and fatty acids. Results of hierarchical cluster analysis of the spectra show that the spectra of healthy and tumour tissue films can be reliably separated into two groups. On the other hand, possibility to differentiate between tumours of different types and grades remains in question. While the fluid from highly malignant G3 tumour tissue contains highly pronounced glycogen spectral bands and can be well separated from benign and G1 tumours by principal component analysis, the variations between spectra from sample to sample prevent from obtaining conclusive results about the grouping between different tumour types and grades. The proposed method is instant and can be used in situ and even in vivo.

Raman spectroscopy is a rapid technique for the identification of cancers. Its coupling with a hypodermic needle provides a minimally invasive instrument with the potential to aid real time assessment of suspicious lesions in vivo and guide surgery. A fibre optic Raman needle probe was utilised in this study to evaluate the classification ability of the instrument as a diagnostic tool together with multivariate analysis, through measurements of tissues from different animal species as well as various different porcine tissue types. Cross validation was performed and preliminary classification accuracies were calculated as 100% for the identification of tissue type and 97.5% for the identification of animal species. A lymph node sample was also measured using the needle probe to assess the use of the technique for human tissue and hence its efficiency as a clinical instrument. This needle probe has been demonstrated to have the capabilities to classify tissue samples based on their biochemical components. The Raman needle probe also has the potential to act as a diagnostic and surgical tool to delineate cancerous from non-cancerous cells in real time, thus assisting complete removal of a tumour.

The realization of label-free molecule specific imaging of morphology and chemical composition of tissue at subcellular spatial resolution in real time is crucial for many envisioned applications in medicine, e.g., precise surgical guidance and non-invasive histopathologic examination of tissue. Thus, new approaches for a fast and reliable in vivo and near in vivo (ex corpore in vivo) tissue characterization to supplement routine pathological diagnostics is needed. Spectroscopic imaging approaches are particularly important since they have the potential to provide a pathologist with adequate support in the form of clinically-relevant information under both ex vivo and in vivo conditions. In this contribution it is demonstrated, that multimodal nonlinear microscopy combining coherent anti-Stokes Raman scattering (CARS), two photon excited fluorescence (TPEF) and second harmonic generation (SHG) enables the detection of characteristic structures and the accompanying molecular changes of widespread diseases, particularly of cancer and atherosclerosis. The detailed images enable an objective evaluation of the tissue samples for an early diagnosis of the disease status. Increasing the spectral resolution and analyzing CARS images at multiple Raman resonances improves the chemical specificity. To facilitate handling and interpretation of the image data characteristic properties can be automatically extracted by advanced image processing algorithms, e.g., for tissue classification. Overall, the presented examples show the great potential of multimodal imaging to augment standard intraoperative clinical assessment with functional multimodal CARS/SHG/TPEF images to highlight functional activity and tumor boundaries. It ensures fast, label-free and non-invasive intraoperative tissue classification paving the way towards in vivo optical pathology.

Infrared microscopy can be performed to observe dynamic processes on a microscopic scale. Fourier-transform infrared spectroscopy-based microscopes are bound to limitations regarding time resolution, which hampers their potential for imaging fast moving systems. In this manuscript we present a quantum cascade laser-based infrared microscope which overcomes these limitations and readily achieves standard video frame rates. The capabilities of our setup are demonstrated by observing dynamical processes at their specific time scales: fermentation, slow moving Amoeba Proteus and fast moving Caenorhabditis elegans. Mid-infrared sampling rates between 30 min and 20 ms are demonstrated.

FTIR spectroscopy using a thermal light source has been the dominant method for obtaining infrared spectra since the 1950’s. Unfortunately the limited surface brightness and low spatial coherence of black-body radiators limits the spectral SNR in microspectroscopy and stand-off detection. Two recent innovations are addressing this problem a) FTIR instruments illuminated by high-spatial coherence broad-band supercontinuum sources and b) high spatial coherence narrow-band EC-QCL’s. Here we ask whether these two approaches offer equivalent sensitivity. By noting an analogy with near-infrared optical coherence tomography we rigorously show that the high temporal coherence of the EC-QCL brings an additional, very large SNR advantage over an FTIR instrument illuminated by a supercontinuum source under otherwise matched conditions. Specifically if a spectrum containing N points is recorded by both instruments using the same illumination intensity and the same detector noise level, then the EC-QCL can deliver a given spectral SNR in a time xN shorter than the FTIR instrument. This factor can reach x100, potentially even x1000, in realistic applications. We exploit the analogy with OCT further by developing a mid-infrared “swept laser”, using commercially available components, in which the tuning rate is much higher than in commercial EC-QCL devices. We use this swept laser to demonstrate the SNR advantage experimentally, using a custom-made EC-QCL spectrometer and PDMS polymer samples. We explore the potential upper limits on spectral acquisition rates, both from the fundamental kinetics of gain build-up in the external cavity and from likely mechanical limits on cavity tuning rates.

Non-invasive cell analyses are increasingly important for medical field. A CARS microscope is one of the non-invasive imaging equipments and enables to obtain images indicating molecular distribution. Some studies on discrimination of cell state by using CARS images of lipid are reported. However, due to low signal intensity, it is still challenging to obtain images of the fingerprint region (800~1800 cm^-1), in which many spectrum peaks correspond to compositions of a cell. Here, to identify cell differentiation by using multiplex CARS, we investigated hyperspectral imaging of fingerprint region of living cells. To perform multiplex CARS, we used a prototype of a compact light source, which consists of a microchip laser, a single-mode fiber, and a photonic crystal fiber to generate supercontinuum light. Assuming application to regenerative medicine, we chose a cartilage cell, whose differentiation is difficult to be identified by change of the cell morphology. Because one of the major components of cartilage is collagen, we focused on distribution of proline, which accounts for approximately 20% of collagen in general. The spectrum quality was improved by optical adjustments about power branching ratio and divergence of broadband Stokes light. Hyperspectral images were successfully obtained by the improvement. Periphery of a cartilage cell was highlighted in CARS image of proline, and this result suggests correspondence with collagen generated as extracellular matrix. A possibility of cell analyses by using CARS hyperspectral imaging was indicated.

We report the development of a polarization-resolved hyperspectral stimulated Raman scattering (SRS) imaging technique based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of dental caries. In our imaging system, hyperspectral SRS images (512×512 pixels) in both fingerprint region (800-1800 cm^-1) and high-wavenumber region (2800-3600 cm^-1) are acquired in minutes by scanning the wavelength of OPO output, which is a thousand times faster than conventional confocal micro Raman imaging. SRS spectra variations from normal enamel to caries obtained from the hyperspectral SRS images show the loss of phosphate and carbonate in the carious region. While polarization-resolved SRS images at 959 cm^-1 demonstrate that the caries has higher depolarization ratio. Our results demonstrate that the polarization resolved-hyperspectral SRS imaging technique developed allows for rapid identification of the biochemical and structural changes of dental caries.

In vivo confocal Raman spectroscopy is a powerful non-invasive technique able to analyse the skin constituents. This technique was applied to transdermal perfusion studies of the vitamin A derivative in human skin. The composition of the stratum corneum (lipid bilayer) is decisive for the affinity and transport of the vitamin through skin. The vitamin A is significantly absorbed by human skin when applied with water in oil emulsion or hydro-alcoholic gel. The purpose of this study is to elucidate the behaviour of vitamin A derivative into human skin without the presence of enhancers. The results showed that the intensity band of the derivative (around 1600 cm^-1), which represents the -C=O vibrational mode, was detected in different stratum corneum depths (up to 20 μm). This Raman peak of vitamin A derivative has non-coincident band with the Raman spectra of the skin epidermis, demonstrating that compound penetrated in forearm skin.

Exosomes are small (~100nm) membrane bound vesicles excreted by cells as part of their normal biological processes. These extracellular vesicles are currently an area of intense research, since they were recently found to carry functional mRNA that allows transfer of proteins and other cellular instructions between cells. Exosomes have been implicated in a wide range of diseases, including cancer. Cancer cells are known to have increased exosome production, and may use those exosomes to prepare remote environments for metastasis. Therefore, there is a strong need to develop characterization methods to help understand the structure and function of these vesicles. However, current techniques, such as proteomics and genomics technologies, rely on aggregating a large amount of exosome material and reporting on chemical content that is averaged over many millions of exosomes. Here we report on the use of laser-tweezers Raman spectroscopy (LTRS) to probe individual vesicles, discovering distinct heterogeneity among exosomes both within a cell line, as well as between different cell lines. Through principal components analysis followed by hierarchical clustering, we have identified four “subpopulations” of exosomes shared across seven cell lines. The key chemical differences between these subpopulations, as determined by spectral analysis of the principal component loadings, are primarily related to membrane composition. Specifically, the differences can be ascribed to cholesterol content, cholesterol to phospholipid ratio, and surface protein expression. Thus, we have shown LTRS to be a powerful method to probe the chemical content of single extracellular vesicles.

Micro-dialysis can be used for continuously harvesting body fluids, while a multi-component analysis of the dialysates by infrared spectrometry offers splendid opportunities for monitoring substrates and metabolites such as glucose, lactate and others small enough to penetrate the semi-permeable dialysis membranes. However, a drawback of this process are variable recovery rates, which can be observed especially for subcutaneously implanted catheters in human subjects. Isotonic perfusates were investigated with acetate and mannitol as recovery markers for the dialysis of human serum at 37°C to mimic in vivo patient monitoring. The latter non-ionic substance has been suggested for application when other ionic substances such as bicarbonate or pH are also to be determined. Simultaneously for acetate and mannitol, the depletion of the marker substances from the perfusates using different micro-dialysis devices was investigated under various flow-rates. Relationships between relative dialysate marker concentrations and glucose recovery rates were determined based on multivariate calibrations. For quantification, classical least squares with reference spectra for modelling the serum dialysates was used, rendering a basis for reliable blood glucose and lactate measurements.

The aging process involves the reduction in the production of the major components of skin tissue. During intrinsic aging and photoaging processes, in dermis of human skin, fibroblasts become senescent and have decreased activity, which produce low levels of collagen. Moreover, there is accumulation of advanced glycation end products (AGEs). AGEs have incidence in the progression of age-related diseases, principally in diabetes mellitus and in Alzheimer's diseases. AGEs causes intracellular damage and/or apoptosis leading to an increase of the free radicals, generating a crosslink with skin proteins and oxidative stress. The aim of this study is to detect AGEs markers on human skin by in vivo Confocal Raman spectroscopy. Spectra were obtained by using a Rivers Diagnostic System, 785 nm laser excitation and a CCD detector from the skin surface down to 120 μm depth. We analyzed the confocal Raman spectra of the skin dermis of 30 women volunteers divided into 3 groups: 10 volunteers with diabetes mellitus type II, 65–80 years old (DEW); 10 young healthy women, 20–33 years old (HYW); and 10 elderly healthy women, 65–80 years old (HEW). Pentosidine and glucosepane were the principally identified AGEs in the hydroxyproline and proline Raman spectral region (1000–800 cm^–1), in the 1.260–1.320 cm^–1 region assignable to alpha-helical amide III modes, and in the Amide I region. Pentosidine and glucosepane calculated vibrational spectra were performed through Density Functional Theory using the B3LYP functional with 3-21G basis set. Difference between the Raman spectra of diabetic elderly women and healthy young women, and between healthy elderly women and healthy young women were also obtained with the purpose of identifying AGEs Raman bands markers. AGEs peaks and collagen changes have been identified and used to quantify the glycation process in human skin.

Non- and minimally-invasive techniques can provide advantages in the monitoring and clinical diagnostics in renal diseases. Although renal biopsy may be useful in establishing diagnosis in several diseases, it is an invasive approach and impractical for longitudinal disease monitoring. To address this unmet need, we have developed two techniques based on Raman spectroscopy. First, we have investigated the potential of diagnosing and staging nephritis by analyzing kidney tissue Raman spectra using multivariate techniques. Secondly, we have developed a urine creatinine sensor based on surface-enhanced Raman spectroscopy with performance near commercial assays which require relatively laborious sample preparation and longer time.

Otitis media (OM) is the leading cause of acute physician visits and prescription of antibiotics for children. Current standard techniques to diagnose acute otitis media (AOM) are limited by their ability to probe only changes in symptoms of the bacterial infection that cause AOM. Furthermore, they are not able to detect the presence of or identify bacteria causing AOM, which is important for diagnosis and proper antibiotic treatment. Our goal is to detect the presence of and identify the pathogens involved in causing AOM based on their biochemical profile using Raman spectroscopy (RS). An inVia confocal Raman microscope (Renishaw) at 785 nm was used to detect bacteria causing AOM in vitro. The three main bacteria that cause AOM, Haemophilus influenzae, Moraxella catarrhalis, and Streptococcus pneumoniae were cultured in chocolate agar and Mueller-Hinton agar to determine which agar type would minimize Raman signal from the growth agar. Preliminary results identified specific Raman spectral features characteristic of S. pneumoniae. RS has the potential to accurately diagnose AOM, which will help in identifying the antibiotic that will be most beneficial for the patient and ultimately decrease the course of infection.

Inflammatory bowel disease (IBD) is an idiopathic disease that is typically characterized by chronic inflammation of the gastrointestinal tract. Recently much effort has been devoted to the development of novel diagnostic tools that can assist physicians for fast, accurate, and automated diagnosis of the disease. Previous research based on Raman spectroscopy has shown promising results in differentiating IBD patients from normal screening cases. In the current study, we examined IBD patients in vivo through a colonoscope-coupled Raman system. Optical diagnosis for IBD discrimination was conducted based on full-range spectra using multivariate statistical methods. Further, we incorporated several feature selection methods in machine learning into the classification model. The diagnostic performance for disease differentiation was significantly improved after feature selection. Our results showed that improved IBD diagnosis can be achieved using Raman spectroscopy in combination with multivariate analysis and feature selection.

Infrared (IR) spectroscopic imaging has been applied to study histology of cardiovascular tissue, primarily using Fourier transform IR (FTIR) Imaging. Here we describe results for histologic imaging of cardiac biopsies using a fast, discrete frequency IR (DFIR) imaging system. Histologic classification of tissue is understood in terms of the constituent frequencies and speeded up by careful optimization of the data acquired. Results are compared to FTIR imaging in terms of the signal to noise ratio and information content.

Schwannoma are rare benign neural neoplasia. The clinical diagnosis could be improved if novel optical techniques are performed. Among these techniques, FT-IR is one of the currently techniques which has been applied for samples discrimination using biochemical information with minimum sample preparation. In this work, we report a case of a schwannoma in the cervical region. A histological examination described a benign process. An immunohistochemically examination demonstrated positivity to anti-S100 protein antibody, indicating a diagnosis of schwannoma. The aim of this analysis was to characterize FT-IR spectrum of the neoplastic and normal tissue in the fingerprint (1000-1800 cm^-1) and high wavenumber region (2800-3600 cm^-1). The IR spectra were collect from tumor tissue and normal nerve samples by a FT-IR spectrophotometer (Spotlight Perkin Elmer 400, USA) with 64 scans, and resolution of 4 cm⁻¹. A total of twenty spectra were recorded (10 from schwannoma and 10 from nerve). Multivariate Analysis was used to classify the data. Through average and standard deviation analysis we observed that the main spectral change occurs at ≈1600 cm^-1 (amide I) and ≈1400 cm^-1 (amide III) in the fingerprint region, and in CH2/CH3 protein-lipids and OH-water vibrations for the high wavenumber region. In conclusion, FT-IR could be used as a technique for schwannoma analysis helping to establish specific diagnostic.

Diabetes mellitus (DM) and arterial hypertension (AH) are common diseases that, if untreated, predispose the patient to renal failure. This study aimed to evaluate possible biomarkers in the urine of patients with DM and AH capable to predict the chronic renal disease, by means of Raman spectroscopy. Urines were obtained from patients with DM and AH, and separated into four groups: no symptoms of diseases related to DM and AH (G1), with low clinical complications (G2), with severe clinical complications (G3), and with chronic kidney disease (G4) arised from DM and AH. It has been used a dispersive Raman spectrometer (830nm, 250mW, 20s accumulation). In the spectra of urine it was identified Raman peaks at 680cm-1 (creatinine), 1004cm-1 (urea) and 1128cm-1 (glucose). The results revealed that G2, G3 and G4 presented the creatinine peak with lower intensity than G1 (p < 0.05). It was observed that G2, G3 and G4 showed lower intensity of the urea peak compared to G1 (p < 0.05) and G4 showed lower intensity compared to G2 and G3 (p < 0.05). Despite not significant, the glucose peak showed lower intensity in G1 when compared to the other groups. A model for classification of groups according to clinical criteria, using Sparse Multinomial Logistic Regression, taking as inputs the intensities of creatine, urea and glucose peaks allowed correct classification of 88.9% for G1, 36.8% for G2, 43.8% for G3 and 84.2% for G4. These results demonstrated the possibility of obtaining diagnostic information for complications of kidney disease associated to DM and AH, particularly the renal failure.

Rapid, accurate and sensitive DNA analysis is critically important for the diagnostic of genetic diseases. The most common method preferred in practice is fluorescence based microarrays to analyze the DNA. However, there exist some disadvantages related to the above-mentioned method such as the overlapping of the fluorescence emission wavelengths that can diminish in the performance of multiplexing, needed to obtain fluorescence spectra from each dye and photo degradation. In this study, a novel SERS based DNA analysis approach, which is Raman active dye-free and independent of SERS substrate properties, is developed. First, the single strand DNA probe is attached to the SERS substrate and half of the complimentary DNA is attached to gold nanoparticles, as well. We hypothesize that in the presence of target DNA, the complimentary DNA coupled colloids will bind to the SERS substrate surface via hybridization of single strand target DNA. To test this hypothesis, we used UV/Vis spectroscopy, atomic for microscopy (AFM) and dynamic light scattering (DLS). DNA analysis is demonstrated by a peak shift of the certain peak of the small molecules attached to the SERS substrate surface instead of SERS spectrum obtained in the presence of target DNA from the Raman reporter molecules. The degree of peak shifting will be used for the quantification of the target DNA in the sample. Plasmonic properties of SERS substrates and reproducibility issues will not be considerable due to the use of peak shifting instead of peak intensity for the qualitative analysis.

Surgical site infections (SSIs) are common post-surgical complications that remain significant clinical problems, as they are associated with substantial mortality and morbidity. As such, there is significant interest in the development of minimally invasive techniques that permit early detection of SSIs. To this end, we are applying a compact, clinically deployable Raman spectrometer coupled to an optical fibre probe to the study of bacteria, with the long term goal of using Raman spectroscopy to detect infection in vivo. Our system comprises a 785 nm laser diode for excitation and a commercial (Ocean Optics, Inc.) Raman spectrometer for detection. Here we discuss the design, optimisation and validation of this system, and describe our first experiences interrogating bacterial cells (Escherichia coli) in vitro.

The onset of osteoarthritis (OA)in articular cartilage is characterized by degradation of extracellular matrix (ECM). Specifically, breakage of cross-links between collagen fibrils in the articular cartilage leads to loss of structural integrity of the bulk tissue. Since there are no broadly accepted, non-invasive, label-free tools for diagnosing OA at its early stage, Raman spectroscopyis therefore proposed in this work as a novel, non-destructive diagnostic tool. In this study, collagen thin films were employed to act as a simplified model system of the cartilage collagen extracellular matrix. Cross-link formation was controlled via exposure to glutaraldehyde (GA), by varying exposure time and concentration levels, and Raman spectral information was collected to quantitatively characterize the cross-link assignments imparted to the collagen thin films during treatment. A novel, quantitative method was developed to analyze the Raman signal obtained from collagen thin films. Segments of Raman signal were decomposed and modeled as the sum of individual bands, providing an optimization function for subsequent curve fitting against experimental findings. Relative changes in the concentration of the GA-induced pyridinium cross-links were extracted from the model, as a function of the exposure to GA. Spatially resolved characterization enabled construction of spectral maps of the collagen thin films, which provided detailed information about the variation of cross-link formation at various locations on the specimen. Results showed that Raman spectral data correlate with glutaraldehyde treatment and therefore may be used as a proxy by which to measure loss of collagen cross-links in vivo. This study proposes a promising system of identifying onset of OA and may enable early intervention treatments that may serve to slow or prevent osteoarthritis progression.