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Sara Moradi Tuchayi,1 Ying Wang,1 Isaac J Pence,1 Alex Fast,1 Anat Stemmer-Rachamimov,2 Conor L Evans,1 R Rox Anderson,1 Lilit Garibyan1 1Wellman Center for Photomedicine, Massachusetts General Hospital, Department of Dermatology, Harvard Medical School, Boston, MA, USA; 2Massachusetts General Hospital and Department of Pathology, Harvard Medical School, Boston, MA, USACorrespondence: Lilit Garibyan, Wellman Center for Photomedicine, Massachusetts General Hospital, 50 Blossom Street-Thier 2, Boston, MA, 02114, USA, Tel +1 617-726-2005, Email lgaribyan@mgh.harvard.eduBackground: Cryoneurolysis uses tissue cooling as an opioid-sparing, long-lasting treatment for peripheral nerve pain. A nerve-selective method for cryoneurolysis by local injection of ice-slurry was developed to allow cryoneurolysis to be performed with a standard needle and syringe, similar to peripheral nerve blocks. Since the treatment of patients with chronic pain may require repeated injections, we investigated the safety and tolerance of repeated treatments in a rat model.Methods: Three repeated ice-slurry treatments, given 6 weeks apart were performed around the rat sciatic nerve. Nerve and surrounding tissues were collected up to 4 months after the third treatment for analysis. Coherent anti-Stokes Raman scattering (CARS) microscopy was used to study effects on myelin sheaths and axon structure. Immunofluorescence (IF) staining was used to study effects on axon density. Hematoxylin and Eosin (H&E) staining was used to examine histologic effects on sciatic nerve and surrounding tissue.Results: Histologic and CARS image analysis of nerve tissue collected months after three injections demonstrated recovery of nerve structure, myelin organization and axon density to baseline levels, without any residual inflammation, scarring or neuroma formation. No inflammation or scarring was detected in surrounding skin and muscle tissues.Conclusion: Repeated ice-slurry injections cause temporary, nerve-selective and reversible changes in the peripheral nerve. There was no histologic damage to surrounding skin and muscle tissues. Repeated treatments with injectable ice-slurry for cryoneurolysis appear to be safe and well tolerated. Clinical studies for patients with chronic pain are warranted.Keywords: pain treatment, slurry, cooling, multiple treatments

Theranostics, the combination of diagnosis and therapy, has long held promise as a means to achieving personalised precision cancer treatments. However, despite its potential, theranostics has yet to realise significant clinical translation, largely due the complexity and overriding toxicity concerns of existing theranostic nanoparticle strategies. Methods: Here, we present an alternative nanoparticle-free theranostic approach based on simultaneous Raman spectroscopy and photodynamic therapy (PDT) in an integrated clinical platform for cancer theranostics. Results: We detail the compatibility of Raman spectroscopy and PDT for cancer theranostics, whereby Raman spectroscopic diagnosis can be performed on PDT photosensitiser-positive cells and tissues without inadvertent photosensitiser activation/photobleaching or impaired diagnostic capacity. We further demonstrate that our theranostic platform enables in vivo tumour diagnosis, treatment, and post-treatment molecular monitoring in real-time. Conclusion: This system thus achieves effective theranostic performance, providing a promising new avenue towards the clinical realisation of theranostics.

Establishing the precise timeline of a crime can be challenging as current analytical techniques used suffer from many limitations and are destructive to the body fluids encountered at crime scenes. Raman spectroscopy has demonstrated excellent potential in forensic science as it provides direct information about the structural and molecular changes without the need for processing or extracting samples. However, its current applicability is limited to pure body fluids, as signals from the substrate underlying these fluids greatly influence the current models used for age estimation. In this study, we utilized Raman spectroscopy to identify selective spectral markers that delineate the bloodstain age in the presence of interfering signals from the substrate. The pure bloodstains and the bloodstains on the substrate were aged for two weeks at 21 ± 2 ℃ in the dark. Least absolute shrinkage and selection operator (LASSO) regression was employed to guide the feature selection in the presence of interference from substrates to accurately predict the bloodstain age. Substrate-specific regression models guided by an automated feature selection algorithm yielded low values of predictive root mean square error (0.207, 0.204, 0.222 h in logarithmic scale) and high R2 (0.924, 0.926, 0.913) on test data consisting of blood spectra on floor tile, facial tissue, and linoleum-polymer substrates, respectively. This framework for an automated feature selection algorithm relies entirely on pure bloodstain spectra to train substrate-specific models for estimating the age of composite (blood on substrate) spectra. The model can thus be easily applied to any new composite spectra and is highly scalable to new environments. This study demonstrates that Raman spectroscopy coupled with LASSO could serve as a reliable and nondestructive technique to determine the age of bloodstains on any surface while aiding forensic investigations in real-world scenarios.

Lipid nanoparticles (LNPs) are versatile structures with tunable physicochemical properties that are ideally suited as a platform for vaccine delivery and RNA therapeutics. A key barrier to LNP rational design is the inability to relate composition and structure to intracellular processing and function. Here Single Particle Automated Raman Trapping Analysis (SPARTA) is combined with small-angle X-ray and neutron scattering (SAXS/SANS) techniques to link LNP composition with internal structure and morphology and to monitor dynamic LNP-phospholipase D (PLD) interactions. This analysis demonstrates that PLD, a key intracellular trafficking mediator, can access the entire LNP lipid membrane to generate stable, anionic LNPs. PLD activity on vesicles with matched amounts of enzyme substrate is an order of magnitude lower, indicating that the LNP lipid membrane structure can be used to control enzyme interactions. This represents an opportunity to design enzyme-responsive LNP solutions for stimuli-responsive delivery and diseases where PLD is dysregulated.

Otitis media (OM) is a prevalent disease that is the most frequent cause of acute physician visits and prescription of antibiotics for children. Current methods to diagnose OM and differentiate between the two main types of OM, acute otitis media (AOM) and otitis media with effusion (OME), rely on interpreting symptoms that may overlap between them. Since AOM requires antibiotic treatment and OME does not, there is a clinical need to distinguish between AOM and OME to determine whether antibiotic treatment is necessary and guide future prescriptions. We used an optical spectroscopy technique, Raman spectroscopy (RS), to identify and characterize the biochemical features of the three main pathogens that cause AOM in vitro. A Renishaw inVia confocal Raman microscope at 785 nm was used to spectrally investigate the Raman signatures of Haemophilus influenzae, Moraxella catarrhalis, and Streptococcus pneumoniae. Biochemical features or biomarkers important for classification of each bacterial species were identified and yielded a 97% accuracy of discrimination. To test the effectiveness of Raman-based bacterial classification in a clinical sample, human middle ear effusion (MEE) from patients affected by recurrent AOM was collected, cultured, and measured using RS. The probability of bacterial involvement from each of the three main bacteria that cause AOM was determined from the clinical MEE samples. These results suggest the potential of utilizing RS to aid in accurately diagnosing AOM and providing physicians with bacterial identification to guide treatment.

Cutaneous pharmacokinetics (cPK) after topical formulation application has been a research area of particular interest for regulatory and drug development scientists to mechanistically understand topical bioavailability (BA). Semi-invasive techniques, such as tape-stripping, dermal microdialysis, or dermal open-flow microperfusion, all quantify macroscale cPK. While these techniques have provided vast cPK knowledge, the community lacks a mechanistic understanding of active pharmaceutical ingredient (API) penetration and permeation at the cellular level. One noninvasive approach to address microscale cPK is coherent Raman scattering imaging (CRI), which selectively targets intrinsic molecular vibrations without the need for extrinsic labels or chemical modification. CRI has two main methods-coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS)-that enable sensitive and selective quantification of APIs or inactive ingredients. CARS is typically utilized to derive structural skin information or visualize chemical contrast. In contrast, the SRS signal, which is linear with molecular concentration, is used to quantify APIs or inactive ingredients within skin stratifications. Although mouse tissue has commonly been utilized for cPK with CRI, topical BA and bioequivalence (BE) must ultimately be assessed in human tissue before regulatory approval. This paper presents a methodology to prepare and image ex vivo skin to be used in quantitative pharmacokinetic CRI studies in the evaluation of topical BA and BE. This methodology enables reliable and reproducible API quantification within human and mouse skin over time. The concentrations within lipid-rich and lipid-poor compartments, as well as total API concentration over time are quantified; these are utilized for estimates of micro- and macroscale BA and, potentially, BE.

Cutaneous pain is a common symptom of skin disease, and available therapies are inadequate. We developed a neural selective and injectable method of cryoneurolysis with ice slurry, which leads to a long-lasting decrease in mechanical pain. The aim of this study is to determine whether slurry injection reduces cutaneous pain without inducing the side effects associated with conventional cryoneurolysis. Using the rat sciatic nerve, we examined the effects of slurry on nerve structure and function in comparison with the effects of a Food and Drug Administration‒approved cryoneurolysis device (Iovera). Coherent anti-Stokes Raman scattering microscopy and immunofluorescence staining were used to investigate histological effects on the sciatic nerve and on downstream cutaneous nerve fibers. Complete Freund's Adjuvant model of cutaneous pain was used to study the effect of the slurry on reducing pain. Structural changes in myelin induced by slurry were comparable with those induced by Iovera, which uses much colder temperatures. Compared with that of Iovera, the decrease in mechanical pain due to slurry was less profound but lasted longer without signs of dysesthesia. Slurry did not cause a reduction of epidermal nerve fibers or a change in thermal pain sensitivity. Slurry-treated rats showed reduced cutaneous mechanical pain in response to Complete Freund's Adjuvant. Slurry injection can be used to successfully reduce cutaneous pain without causing dysesthesia.

Extracellular vesicles (EVs) secreted by cancer cells provide an important insight into cancer biology and could be leveraged to enhance diagnostics and disease monitoring. This paper details a high-throughput label-free extracellular vesicle analysis approach to study fundamental EV biology, toward diagnosis and monitoring of cancer in a minimally invasive manner and with the elimination of interpreter bias. We present the next generation of our single particle automated Raman trapping analysis─SPARTA─system through the development of a dedicated standalone device optimized for single particle analysis of EVs. Our visualization approach, dubbed dimensional reduction analysis (DRA), presents a convenient and comprehensive method of comparing multiple EV spectra. We demonstrate that the dedicated SPARTA system can differentiate between cancer and noncancer EVs with a high degree of sensitivity and specificity (gt;95% for both). We further show that the predictive ability of our approach is consistent across multiple EV isolations from the same cell types. Detailed modeling reveals accurate classification between EVs derived from various closely related breast cancer subtypes, further supporting the utility of our SPARTA-based approach for detailed EV profiling.

Clinical medicine continues to seek novel rapid non-invasive tools capable of providing greater insight into disease progression and management. Raman scattering based technologies constitute a set of tools under continuing development to address outstanding challenges spanning diagnostic medicine, surgical guidance, therapeutic monitoring, and histopathology. Here we review the mechanisms and clinical applications of Raman scattering, specifically focusing on high-speed imaging methods that can provide spatial context for translational biomedical applications., The technological developments of high-speed spontaneous and coherent Raman scattering based imaging for translational applications including surgical guidance, histopathology, and pathophysiological monitoring.

Understanding the delivery and diffusion of topically-applied drugs on human skin is of paramount importance in both pharmaceutical and cosmetics research. This information is critical in early stages of drug development and allows the identification of the most promising ingredients delivered at optimal concentrations to their target skin compartments. Different skin imaging methods, invasive and non-invasive, are available to characterize and quantify the spatiotemporal distribution of a drug within ex vivo and in vivo human skin. The first part of this review detailed invasive imaging methods (autoradiography, MALDI and SIMS). This second part reviews non-invasive imaging methods that can be applied in vivo: i) fluorescence (conventional, confocal, and multiphoton) and second harmonic generation microscopies and ii) vibrational spectroscopic imaging methods (infrared, confocal Raman, and coherent Raman scattering microscopies). Finally, a flow chart for the selection of imaging methods is presented to guide human skin ex vivo and in vivo drug delivery studies.

Stimulated Raman scattering (SRS) is a nondestructive and rapid technique for imaging of biological and clinical specimens with label-free chemical specificity. SRS spectral imaging is typically carried out either via broadband methods, or by tuning narrowband ultrafast light sources over narrow spectral ranges thus specifically targeting vibrational frequencies. We demonstrate a multi-window sparse spectral sampling SRS (S4RS) approach where a rapidly-tunable dual-output all-fiber optical parametric oscillator is tuned into specific vibrational modes across more than 1400 cm−1 during imaging. This approach is capable of collecting SRS hyperspectral images either by scanning a full spectrum or by rapidly tuning into select target frequencies, hands-free and automatically, across the fingerprint, silent, and high wavenumber windows of the Raman spectrum. We further apply computational techniques for spectral decomposition and feature selection to identify a sparse subset of Raman frequencies capable of sample discrimination. Here we have applied this novel method to monitor spatiotemporal dynamic changes of active pharmaceutical ingredients in skin, which has particular relevance to topical drug product delivery.

The biodistribution and pharmacokinetics of drugs are vital to the mechanistic understanding of their efficacy. Measuring antimicrobial drug efficacy has been challenging as plasma drug concentration is used as a surrogate for tissue drug concentration, yet typically does not reflect that at the intended site(s) of action. Utilizing an image-guided approach, it is feasible to accurately quantify the biodistribution and pharmacokinetics within the desired site(s) of action. We outline imaging modalities used in visualizing drug distribution with examples ranging from in vitro cellular drug uptake to clinical treatment of microbial infections. The imaging modalities of interest are: radio-labeling, magnetic resonance, mass spectrometry imaging, computed tomography, fluorescence, and Raman spectroscopy. We outline the progress, limitations, and future outlook for each methodology. Further advances in these optical approaches would benefit patients and researchers alike, as non-invasive imaging could yield more profound insights with a lower clinical burden than invasive measurement approaches used today.

A common approach to tailoring synthetic hydrogels for regenerative medicine applications involves incorporating RGD cell adhesion peptides, yet assessing the cellular response to engineered microenvironments at the nanoscale remains challenging. To date, no study has demonstrated how RGD concentration in hydrogels affects the presentation of individual cell surface receptors. Here we studied the interaction between human mesenchymal stem cells (hMSCs) and RGD-functionalized poly(ethylene glycol) hydrogels, by correlating macro- and nanoscale single-cell interfacial quantification techniques. We quantified RGD unbinding forces on a synthetic hydrogel using single cell atomic force spectroscopy, revealing that short-term binding of hMSCs was sensitive to RGD concentration. We also performed direct stochastic optical reconstruction microscopy (dSTORM) to quantify the molecular interactions between integrin α5β1 and a biomaterial, unexpectedly revealing that increased integrin clustering at the hydrogel-cell interface correlated with fewer available RGD binding sites. Our complementary, quantitative approach uncovered mechanistic insights into specific stem cell-hydrogel interactions, where dSTORM provides nanoscale sensitivity to RGD-dependent differences in cell surface localization of integrin α5β1. Our findings reveal that it is possible to precisely determine how peptide-functionalized hydrogels interact with cells at the molecular scale, thus providing a basis to fine-tune the spatial presentation of bioactive ligands.

Traditional in vitro bioengineering approaches whereby only individual biophysical cues are manipulated at any one time are highly inefficient, falling short when recapitulating the complexity of the cardiac environment. Multiple biophysical cues are present in the native myocardial niche and are essential during development, as well as in maintenance of adult cardiomyocyte (CM) phenotype in both health and disease. This study establishes a novel biofabrication workflow to study and manipulate hiPSC-CMs and to understand how these cells respond to a multiplexed biophysical environment, namely microscopic topography (3D shape resembling that of adult CM) and substrate stiffness, at a single cell level. Silicon masters were fabricated and developed to generate pillars of the desired 3D shapes, which would be used to mould the designed microwell arrays into a hydrogel. Polyacrylamide was modified with the incorporation of acrylic acid to provide a carboxylic group conjugation site for adhesion motifs, without comprising its capacity to modulate the stiffness. In this manner, individual parameters can be finely tuned independently within the hydrogel: the dimension of 3D shaped microwell and its stiffness. The design allows the platform to isolate single hiPSC-CMs to study solely biophysical cues in an absence of cell-cell physical interaction. Under physiologic-like physical conditions (3D shape resembling that of adult CM and 9.83 kPa substrate stiffness), isolated single hiPSC-CMs exhibit increased Cx-43 density, cell Peer reviewed version of the manuscript published in final form at Biofabrication (2020). membrane stiffness and calcium transient amplitude; co-expression of the subpopulation-related MYL2- MYL7 proteins; while displaying higher anisotropism in comparison to pathologic-like conditions (flat surface and 112 kPa substrate stiffness). This demonstrates that supplying a physiological or pathological microenvironment to an isolated single hiPSC-CM in absence of any physical cell-to-cell communication in this biofabricated platform leads to a significantly different set of cellular features, thus presenting a differential phenotype. Importantly, this demonstrates the high plasticity of hiPSC-CMs even in isolation. The ability of multiple biophysical cues to significantly influence isolated single hiPSC-CM phenotype and functionality highlights the importance of fine-tuning such cues for specific applications. This has the potential to produce more fit-for purpose hiPSC-CMs. Further understanding of human cardiac development is enabled by the robust, versatile and reproducible biofabrication techniques applied here. We envision this system to be easily applied to other tissues and cell types where the influence of stiffness and cellular shape plays also an important role in its physiology. Keywords: microfabrication, cardiomyocyte, physical interaction, cell shape, calcium handling, human induced pluripotent stem cells

In vivo Raman spectroscopy has been utilized for the non-invasive, non-destructive assessment of tissue pathophysiology for a variety of applications largely through the use of fiber optic probes to interface with samples of interest. Fiber optic probes can be designed to optimize the collection of Raman-scattered photons from application-dependent depths, and this critical consideration should be addressed when planning a study. Herein we investigate four distinct probe geometries for sensitivity to superficial and deep signals through a Monte Carlo model that incorporates Raman scattering and fluorescence. Experimental validation using biological tissues was performed to accurately recapitulate in vivo scenarios. Testing in biological tissues agreed with modeled results and revealed that microlens designs had slightly enhanced performance at shallow depths (< 1 mm), whereas all of the beampath-modified designs yielded more signal from deep within tissue. Simulation based on fluence maps generated using ray-tracing in the absence of optical scattering had drastically different results as a function of depth for each probe compared to the biological simulation. The contrast in simulation results between the non-scattering and biological tissue phantoms underscores the importance of considering the optical properties of a given application when designing a fiber optic probe. The model presented here can be easily extended for optimization of entirely novel probe designs prior to fabrication, reducing time and cost while improving data quality.

Breast conserving surgery is the preferred treatment for women diagnosed with early stage invasive breast cancer. To ensure successful breast conserving surgeries, efficient tumour margin resection is required for minimizing tumour recurrence. Currently surgeons rely on touch preparation cytology or frozen section analysis to assess tumour margin status intraoperatively. These techniques have suboptimal accuracy and are time-consuming. Tumour margin status is eventually confirmed using postoperative histopathology that takes several days. Thus, there is a need for a real-time, accurate, automated guidance tool that can be used during tumour resection intraoperatively to assure complete tumour removal in a single procedure. In this paper, we evaluate feasibility of a 3-dimensional scanner that relies on Raman Spectroscopy to assess the entire margins of a resected specimen within clinically feasible time. We initially tested this device on a phantom sample that simulated positive tumour margins. This device first scans the margins of the sample and then depicts the margin status in relation to an automatically reconstructed image of the phantom sample. The device was further investigated on breast tissues excised from prophylactic mastectomy specimens. Our findings demonstrate immense potential of this device for automated breast tumour margin assessment to minimise repeat invasive surgeries.

Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components’ unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices., Label-free surface-enhanced Raman spectroscopy is an emergent method for the detection and discrimination of biological analytes. Here, the authors describe SERS sensors with arrayed mildly-selective surface chemistries to give a fingerprint based on different interactions for analysing biological samples.

In this two-part review we present an up-to-date description of different imaging methods available to map the localization of drugs on skin as a complement of established ex-vivo absorption studies. This first part deals with invasive methods which are grouped in two classes according to their underlying principles: i) methods using radioactivity such as autoradiography and ii) mass spectrometry methods such as MALDI and SIMS. For each method, a description of the principle is given along with example applications of imaging and quantifying drug delivery in human skin. Thanks to these techniques a better assessment of the fate of drugs is obtained: its localization on a particular skin structure, its potential accumulation, etc. A critical comparison in terms of capabilities, sensitivity and practical applicability is included that will help the reader to select the most appropriate technique depending on the particular problem to be solved.

The interactions of programmed death protein-1 (PD-1) on T cells with its ligand, PD-L1, strongly contributes to an immunosuppressive microenvironment. Blockades of PD-L1 have shown long-term survival in patients. However

Background and objective Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue. Materials and methods In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation. Results With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively. Conclusion These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc.

Acoustic patterning using ultrasound standing waves has recently emerged as a potent biotechnology enabling the remote generation of ordered cell systems. This capability has opened up exciting opportunities, for example, in guiding the development of organoid cultures or the organization of complex tissues. The success of these studies is often contingent on the formation of tightly-packed and uniform cell arrays; however, a number of factors can act to disrupt or prevent acoustic patterning. Yet, to the best of our knowledge, there has been no comprehensive assessment of the quality of acoustically-patterned cell populations. In this report we use a mathematical approach, known as Voronoï tessellation, to generate a series of metrics that can be used to measure the effect of cell concentration, pressure amplitude, ultrasound frequency and biomaterial viscosity upon the quality of acoustically-patterned cell systems. Moreover, we extend this approach towards the characterization of spatiotemporal processes, namely, the acoustic patterning of cell suspensions and the migration of patterned, adherent cell clusters. This strategy is simple, unbiased and highly informative, and we anticipate that the methods described here will provide a systematic framework for all stages of acoustic patterning, including the robust quality control of devices, statistical comparison of patterning conditions, the quantitative exploration of parameter limits and the ability to track patterned tissue formation over time.

A fiber optic probe-based Raman spectroscopy system using a single laser module with two excitation wavelengths, at 680 and 785 nm, has been developed for measuring the fingerprint and high wavenumber regions using a single detector. This system is simpler and less expensive than previously reported configurations of combined fingerprint and high wavenumber Raman systems, and its probe-based implementation facilitates numerous in vivo applications. The high wavenumber region of the Raman spectrum ranges from 2800–3800 cm(−1) and contains valuable information corresponding to the molecular vibrations of proteins, lipids, and water, which is complimentary to the biochemical signatures found in the fingerprint region (800–1800 cm(−1)), which probes DNA, lipids, and proteins. The efficacy of the system is demonstrated by tracking changes in water content in tissue-mimicking phantoms, where Voigtian decomposition of the high wavenumber water peak revealed a correlation between the water content and type of water-tissue interactions in the samples. This dual wavelength system was then used for in vivo assessment of cervical remodeling during mouse pregnancy, a physiologic process with known changes in tissue hydration. The system shows that Raman spectroscopy is sensitive to changes in collagen content in the fingerprint region and hydration state in the high wavenumber region, which was verified using an ex vivo comparison of wet and dry weight. Simultaneous fingerprint and high wavenumber Raman spectroscopy will allow precise in vivo quantification of tissue water content in the high wavenumber region, paired with the high biochemical specificity of the fingerprint region.

In this work, we demonstrate the targeted diagnosis of immunomarker programmed death ligand 1 (PD-L1) and simultaneous detection of epidermal growth factor receptor (EGFR) in breast cancer tumors in vivo using gold nanostars (AuNS) with multiplexed surface enhanced Raman spectroscopy (SERS). Real-time longitudinal tracking with SERS demonstrated maximum accumulation of AuNS occurred 6 h post intravenous (IV) delivery, enabling detection of both biomarkers simultaneously. Raman signal correlating to both PD-L1 and EGFR decreased by ∼30% in control tumors where receptors were pre-blocked prior to AuNS delivery, indicating both the sensitivity and specificity of SERS in distinguishing tumors with different levels of PD-L1 and EGFR expression. Our in vivo study was combined with the first demonstration of ex vivo SERS spatial maps of whole tumor lesions that provided both a qualitative and quantitative assessment of biomarker status with near cellular-level resolution. High resolution SERS maps also provided an overview of AuNS distribution in tumors which correlated well with the vascular density. Mass spectrometry showed AuNS accumulation in tumor and liver, and clearance via spleen, and electron microscopy revealed AuNS were endocytosed in tumors, Kupffer cells in the liver, and macrophages in the spleen. This study demonstrates that SERS-based diagnosis mediated by AuNS provides an accurate measure of multiple biomarkers both in vivo and ex vivo, which will ultimately enable a clinically-translatable platform for patient-tailored immunotherapies and combination treatments.

Staphylococcus aureus ( S. aureus) is a leading cause of hospital-acquired infections, such as bacteremia, pneumonia, and endocarditis. Treatment of these infections can be challenging since strains of S. aureus, such as methicillin-resistant S. aureus (MRSA), have evolved resistance to antimicrobials. Current methods to identify infectious agents in hospital environments often rely on time-consuming, multistep culturing techniques to distinguish problematic strains (i.e., antimicrobial resistant variants) of a particular bacterial species. Therefore, a need exists for a rapid, label-free technique to identify drug-resistant bacterial strains to guide proper antibiotic treatment. Here, our findings demonstrate the ability to characterize and identify microbes at the subspecies level using Raman microspectroscopy, which probes the vibrational modes of molecules to provide a biochemical "fingerprint". This technique can distinguish between different isolates of species such as Streptococcus agalactiae and S. aureus. To determine the ability of this analytical approach to detect drug-resistant bacteria, isogenic variants of S. aureus including the comparison of strains lacking or expressing antibiotic resistance determinants were evaluated. Spectral variations observed may be associated with biochemical components such as amino acids, carotenoids, and lipids. Mutants lacking carotenoid production were distinguished from wild-type S. aureus and other strain variants. Furthermore, spectral biomarkers of S. aureus isogenic bacterial strains were identified. These results demonstrate the feasibility of Raman microspectroscopy for distinguishing between various genetically distinct forms of a single bacterial species in situ. This is important for detecting antibiotic-resistant strains of bacteria and indicates the potential for future identification of other multidrug resistant pathogens with this technique.

Advances in nanotechnology have provided new opportunities for the design of next-generation nucleic acid biosensors and diagnostics. Indeed, combining advances in functional nanoparticles, DNA nanotechnology, and nuclease-enzyme-based amplification can give rise to new assays with advantageous properties. In this work, we developed a microRNA (miRNA) assay using bright fluorescent quantum dots (QDs), simple DNA probes, and the enzyme duplex-specific nuclease. We employed an isothermal target-recycling mechanism, where a single miRNA target triggers the cleavage of many DNA signal probes. The incorporation of DNA-functionalized QDs enabled a quantitative fluorescent readout, mediated by Förster resonance energy transfer (FRET)-based interaction with the DNA signal probes. Our approach splits the reaction in two, performing the enzyme-mediated amplification and QD-based detection steps separately such that each reaction could be optimized for performance of the active components. Target recycling gave ca. 3 orders of magnitude amplification, yielding highly sensitive detection with a limit of 42 fM (or 1.2 amol) of miR-148, with excellent selectivity versus mismatched sequences and other miRNAs. Furthermore, we used an alternative target (miR-21) and FRET pair for direct and absolute quantification of miR-21 in RNA extracts from human cancer and normal cell lines., ACS Applied Materials & Interfaces, 10 (34), ISSN:1944-8244, ISSN:1944-8252

Monitoring cervical structure and composition during pregnancy has high potential for prediction of preterm birth (PTB), a problem affecting 15 million newborns annually. We use in vivo Raman spectroscopy, a label-free, light-based method that provides a molecular fingerprint to non-invasively investigate normal and impaired cervical remodeling. Prostaglandins stimulate uterine contractions and are clinically used for cervical ripening during pregnancy. Deletion of cyclooxygenase-1 (Cox-1), an enzyme involved in production of these prostaglandins, results in delayed parturition in mice. Contrary to expectation, Cox-1 null mice displayed normal uterine contractility; therefore, this study sought to determine whether cervical changes could explain the parturition differences in Cox-1 null mice and gestation-matched wild type (WT) controls. Raman spectral changes related to extracellular matrix proteins, lipids, and nucleic acids were tracked over pregnancy and found to be significantly delayed in Cox-1 null mice at term. A cervical basis for the parturition delay was confirmed by other ex vivo tests including decreased tissue distensibility, hydration, and elevated progesterone levels in the Cox-1 null mice at term. In conclusion, in vivo Raman spectroscopy non-invasively detected abnormal remodeling in the Cox-1 null mouse, and clearly demonstrated that the cervix plays a key role in their delayed parturition.

Renal mass biopsy is still controversial due to imperfect accuracy. Raman spectroscopy (RS) demonstrated promise as an in vivo real-time, nondestructive diagnostic tool in many malignancies. Short wave infrared (SWIR) RS has the potential to improve on previous RS systems for renal mass diagnosis. The aim of this study is to evaluate a SWIR RS system in differentiating normal and malignant renal samples. Measurements were acquired using a benchtop RS system with excitation wavelength at 1064 nm and an InGaAs array detector. Processed spectra were classified with a Bayesian machine learning algorithm, sparse multinomial logistic regression. Sensitivity and receiver operating characteristic curve analyses evaluated the classifier accuracy. Accuracy of the classifier was 92.5% with sensitivity and specificity of 95.8% and 88.8%, respectively. For posterior probability of malignant class assignment, the area under the ROC curve is 0.94 (95% confidence interval: 0.89-0.99, P < .001). SWIR RS accurately differentiated normal and malignant kidney tumors. RS has the potential to be used as a diagnostic tool in kidney cancer.

Kidney cancer affects 65,000 new patients every. As computerized tomography became ubiquitous, the number of small, incidentally detected renal masses increased. About 6,000 benign cases are misclassified radiographically as malignant and removed surgically. Raman spectroscopy (RS) has been widely demonstrated for disease discrimination, however intense near-infrared auto-fluorescence of certain tissues (e.g kidney) can present serious challenges to bulk tissue diagnosis. A 1064nm excitation dispersive detection RS system demonstrated the ability to collect spectra with superior quality in tissues with strong auto-fluorescence. Our objective is to develop a 1064 nm dispersive detection RS system capable of differentiating normal and malignant renal tissue. We will report on the design and development of a clinical system for use in nephron sparing surgeries. We will present pilot data that has been collected from normal and malignant ex vivo kidney specimens using a benchtop RS system. A total of 93 measurements were collected from 12 specimens (6 Renal Cell Carcinoma, 6 Normal ). Spectral classification was performed using sparse multinomial logistic regression (SMLR). Correct classification by SMLR was obtained in 78% of the trials with sensitivity and specificity of 82% and 75% respectively. We will present the association of spectral features with biological indicators of healthy and diseased kidney tissue. Our findings indicate that 1064nm RS is a promising technique for differentiation of normal and malignant renal tissue. This indicates the potential for accurately separating healthy and cancerous tissues and suggests implications for utilizing RS for optical biopsy and surgical guidance in nephron sparing surgery.

We present a rapidly tunable dual-output all-fiber light source for coherent Raman imaging, based on a dispersively matched mode-locked laser pumping a parametric oscillator. Output pump and Stokes pulses with a maximal power of 170 and 400 mW, respectively, and equal durations of 7 ps could be generated. The tuning mechanism required no mechanical delay line, enabling all-electronic arbitrary wavelength switching across more than 2700 cm−1 in less than 5 ms. The compact setup showed a reliable operation despite mechanical shocks of more than 25 m/s2 and is, thus, well suited for operation in a mobile cart. Imaging mouse and human skin tissue with both the portable light source and a commercial laboratory-bound reference system yielded qualitatively equal results and verified the portable light source being well suited for coherent Raman microscopy.

Raman spectroscopy (RS) has received increasing attention as a potential tool for clinical diagnostics. However, the unknown comparability of multiple tissue RS systems remains a major issue for technique standardization and future multisystem trials. In this study, we evaluated potential factors affecting data collection and interpretation, utilizing the skin as an example tissue. The effects of contact pressure and probe angle were characterized as potential user-induced variability sources. Similarly, instrumentation-induced variability sources of system stability and system-dependent response were also analyzed on skin and a nonvolatile biological tissue analog. Physiologically induced variations were studied on multiple tissue locations and patients. The effect of variability sources on spectral line shape and dispersion was analyzed with analysis-of-variance methods, and a new metric for comparing spectral dispersion was defined. In this study, in vivo measurements were made on multiple sites of skin from five healthy volunteers, with four stand-alone fiber optic probe–based tissue RS systems. System stability and controlled user-induced variables had no effects on obtained spectra. By contrast, instrumentation and anatomical location of measurement were significant sources of variability. These findings establish the comparability of tissue Raman spectra obtained by unique systems. Furthermore, we suggest steps for further procedural and instrumentation standardization prior to broad clinical applications of the technique.

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn’s disease (CD), affects over 1 million Americans and 2 million Europeans, and the incidence is increasing worldwide. While these diseases require unique medical care, the differentiation between UC and CD lacks a gold standard, and therefore relies on long term follow up, success or failure of existing treatment, and recurrence of the disease. Here, we present colonoscopy-coupled fiber optic probe-based Raman spectroscopy as a minimally-invasive diagnostic tool for IBD of the colon (UC and Crohn’s colitis). This pilot in vivo study of subjects with existing IBD diagnoses of UC (n = 8), CD (n = 15), and normal control (n = 8) aimed to characterize spectral signatures of UC and CD. Samples were correlated with tissue pathology markers and endoscopic evaluation. The collected spectra were processed and analyzed using multivariate statistical techniques to identify spectral markers and discriminate IBD and disease classes. Confounding factors including the presence of active inflammation and the particular colon segment measured were investigated and integrated into the devised prediction algorithm, reaching 90% sensitivity and 75% specificity to CD from this in vivo data set. These results represent significant progress towards improved real-time classification for accurate and automated in vivo detection and discrimination of IBD during colonoscopy procedures.

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue.In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation.With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively.These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc.

Clinical diagnostic devices provide new sources of information that give insight about the state of health which can then be used to manage patient care. These tools can be as simple as an otoscope to better visualize the ear canal or as complex as a wireless capsule endoscope to monitor the gastrointestinal tract. It is with tools such as these that medical practitioners can determine when a patient is healthy and to make an appropriate diagnosis when he/she is not. The goal of diagnostic medicine then is to efficiently determine the presence and cause of disease in order to provide the most appropriate intervention. The earliest form of medical diagnostics relied on the eye - direct visual observation of the interaction of light with the sample. This technique was espoused by Hippocrates in his 5th century BCE work Epidemics, in which the pallor of a patient's skin and the coloring of the bodily fluids could be indicative of health. In the last hundred years, medical diagnosis has moved from relying on visual inspection to relying on numerous technological tools that are based on various types of interaction of the sample with different types of energy - light, ultrasound, radio waves, X-rays etc. Modern advances in science and technology have depended on enhancing technologies for the detection of these interactions for improved visualization of human health. Optical methods have been focused on providing this information in the micron to millimeter scale while ultrasound, X-ray, and radio waves have been key in aiding in the millimeter to centimeter scale. While a few optical technologies have achieved the status of medical instruments, many remain in the research and development phase despite persistent efforts by many researchers in the translation of these methods for clinical care. Of these, Raman spectroscopy has been described as a sensitive method that can provide biochemical information about tissue state while maintaining the capability of delivering this information in real-time, non-invasively, and in an automated manner. This review presents the various instrumentation considerations relevant to the clinical implementation of Raman spectroscopy and reviews a subset of interesting applications that have successfully demonstrated the efficacy of this technique for clinical diagnostics and monitoring in large (n ≥ 50) in vivo human studies.

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.

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated via surgical resection. Inadequate resection can lead to local recurrence and decreased survival rates. In this study, we investigate the hypothesis that near-infrared (NIR) autofluorescence can be utilized for tumor margin analysis by differentiating STS from the surrounding normal tissue. Intraoperative in vivo measurements were acquired from 30 patients undergoing STS resection and were characterized to differentiate between normal tissue and STS. Overall, normal muscle and fat were observed to have the highest and lowest autofluorescence intensities, respectively, with STS falling in between. With the exclusion of well-differentiated liposarcomas, the algorithm's accuracy for classifying muscle, fat, and STS was 93%, 92%, and 88%, respectively. These findings suggest that NIR autofluorescence spectroscopy has potential as a rapid and nondestructive surgical guidance tool that can inform surgeons of suspicious margins in need of immediate re-excision.

Raman spectroscopy has been widely demonstrated for tissue characterization and disease discrimination, however current implementations with either 785 or 830 nm near-infrared (NIR) excitation have been ineffectual in tissues with intense autofluorescence such as the liver. Here we report the use of a dispersive 1064 nm Raman system using a low-noise Indium-Gallium-Arsenide (InGaAs) array to discriminate highly autofluorescent bulk tissue ex vivo specimens from healthy liver, adenocarcinoma, and hepatocellular carcinoma (N = 5 per group). The resulting spectra have been combined with a multivariate discrimination algorithm, sparse multinomial logistic regression (SMLR), to predict class membership of healthy and diseased tissues, and spectral bands selected for robust classification have been extracted. A quantitative metric called feature importance is defined based on classification outputs and is used to guide the association of spectral features with biological indicators of healthy and diseased liver tissue. Spectral bands with high feature importance for healthy and liver tumor specimens include retinol, heme, biliverdin, or quinones (1595 cm(-1)); lactic acid (838 cm(-1)); collagen (873 cm(-1)); and nucleic acids (1485 cm(-1)). Classification performance in both binary (normal versus tumor, 100% sensitivity and 89% specificity) and three-group cases (classification accuracy: normal 89%, adenocarcinoma 74%, hepatocellular carcinoma 64%) indicates the potential for accurately separating healthy and cancerous tissues and suggests implications for utilizing Raman techniques during surgical guidance in liver resection.

We present a study to evaluate and compare three near-infrared (NIR) fluorescence imaging systems designed to provide intraoperative guidance around anatomical structures. The three systems adapted specifically for the application of endogenous NIR fluorescence detection were (1) a photomultiplier tube based NIR viewer, (2) a thermoelectrically cooled electron-multiplying charge-coupled device (CCD) camera, and (3) a clinical endoscope CCD camera system. Each system was evaluated on the basis of ease-of-use, cost, and system performance. The cooled CCD camera showed the highest contrast ratio, but is limited in utility by its bulk interface and high cost. The clinical endoscope camera showed flexibility in its field-of-view and provides the benefit of being sterilized to allow easy integration into the surgical suite; however, it exhibits signal nonlinearity that would distort quantitative analysis. The NIR viewer shows optimal performance, exhibiting high spatial resolution, linearity, and sufficient contrast to differentiate between tissue types. This low-cost design proves to be the optimal system for parathyroid detection, offering ease-of-use in a surgical setting while meeting system performance requirements.

Light can interact with tissue in dierent ways and probing this interaction can yield information about the state of tissue with respect to its physiology as well as pathology. e use of ber optics allows applications of optical techniques in tissue to be performed remotely and with minimal damage. Since tissue response is virtually instantaneous, the results are obtained in real time, and the use of data processing techniques allows for automated detection of disease. ese properties have resulted in a variety of applications where optical techniques have been used for tissue diagnosis.

Raman spectroscopy (RS) has been extensively used to characterize bone composition. However, the link between bone biomechanics and RS measures is not well established. Here, we leveraged the sensitivity of RS polarization to organization, thereby assessing whether RS can explain differences in bone toughness in genetic mouse models for which traditional RS peak ratios are not informative. In the selected mutant mice - activating transcription factor 4 (ATF4) or matrix metalloproteinase 9 (MMP9) knock-outs - toughness is reduced but differences in bone strength do not exist between knock-out and corresponding wild-type controls. To incorporate differences in the RS of bone occurring at peak shoulders, a multivariate approach was used. Full spectrum principal components analysis of two paired, orthogonal bone orientations (relative to laser polarization) improved genotype classification and correlation to bone toughness when compared to traditional peak ratios. When applied to femurs from wild-type mice at 8 and 20 weeks of age, the principal components of orthogonal bone orientations improved age classification but not the explanation of the maturation-related increase in strength. Overall, increasing polarization information by collecting spectra from two bone orientations improves the ability of multivariate RS to explain variance in bone toughness, likely due to polarization sensitivity to organizational changes in both mineral and collagen.

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn’s colitis (CC), affects nearly 2 million Americans, and the incidence is increasing worldwide. It has been established that UC and CC are distinct forms of IBD and require different medical care, however the distinction made between UC and CC is based upon inexact clinical, radiological, endoscopic, and pathologic features. A diagnosis of indeterminate colitis occurs in up to 15% of patients when UC and CC features overlap and cannot be differentiated; in these patients, diagnosis relies on long term followup, success or failure of existing treatment, and recurrence of the disease. Thus, there is need for a tool that can improve the sensitivity and specificity for fast, accurate and automated diagnosis of IBD. Here we present colonoscopy-coupled fiber probe-based Raman spectroscopy as a novel in vivo diagnostic tool for IBD. This in vivo study of both healthy control (NC, N=10) and diagnosed IBD patients with UC (N=15) and CC (N=26) aims to characterize spectral signatures of NC, UC, and CC. Samples are correlated with tissue pathology markers and endoscopic evaluation. Optimal collection parameters for detection have been identified based upon the new, application specific instrument design. The collected spectra are processed and analyzed using multivariate statistical techniques to identify spectral markers and discriminate NC, UC, and CC. Development of spectral markers to discriminate disease type is a necessary first step in the development of real-time, accurate and automated in vivo detection of IBD during colonoscopy procedures.