New methodology to process shifted excitation Raman difference spectroscopy data: a case study of pollen classification.

Shifted excitation Raman difference spectroscopy (SERDS) is a background correction method for Raman spectroscopy. Here, the difference spectra were directly used as input for SERDS-based classification after an optimization procedure to correct for photobleaching of the autofluorescence. Further processing included a principal component analysis to compensate for the reduced signal to noise ratio of the difference spectra and subsequent classification by linear discriminant analysis. As a case study 6,028 Raman spectra of single pollen originating from plants of eight different genera and four different growth habits were automatically recorded at excitation wavelengths 784 and 786 nm using a high-throughput screening Raman system. Different pollen were distinguished according to their growth habit, i.e. tree versus non-tree with an accuracy of 95.9%. Furthermore, all pollen were separated according to their genus, providing also insight into similarities based on their families. Classification results were compared using spectra reconstructed from the differences and raw spectra after state-of-art baseline correction as input. Similar sensitivities, specificities, accuracies and precisions were found for all spectra with moderately background. Advantages of SERDS are expected in scenarios where Raman spectra are affected by variations due to detector etaloning, ambient light, and high background.

Biochemical alterations in the Musculus triceps brachii and Musculus longissimus thoracis during early postmortem period in pigs.

Muscle-to-meat-transition is influenced by alterations of the energy metabolism. Porcine Musculus triceps brachii (MT) consisted of more fast-twitch-glycolytic muscle fibers and samples, collected 0, 10 and 20 min after slaughter (p.m.), showed higher mitochondrial respiratory activities and ATP concentrations than Musculus longissimus thoracis (LT) samples. Enzyme activities in MT were higher at 0 min (glycogen phosphorylase (GP)), 10 min (GP, citrate synthase (CS)) and at 20 min p.m. (CS). However, LT results were higher at 0 min (lactate dehydrogenase (LDH)), 10 min (phosphofructokinase (PFK), LDH) and at 20 min p.m. (PFK, F0F1-ATPase (F0F1)). Between 0 min and 10 min p.m. CS activities decreased in LT and MT samples, PFK increased in LT and GP in MT samples. Between 10 min and 20 min p.m. PFK and LDH decreased in LT and GP in MT samples, whereas F0F1 increased in LT and CS in MT samples. The data indicate that muscles with different mitochondria contents show clearly different energy metabolism characteristics.

Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients.

Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols.

Recent progress in surface-enhanced Raman spectroscopy for biological and biomedical applications: from cells to clinics.

The application of surface-enhanced Raman spectroscopy (SERS) in biological and biomedical detection schemes is feasible due to its excellent molecular specificity and high sensitivity as well as the capability of SERS to be performed in complex biological compositions. SERS-based investigation of cells, which are the basic structure and functional unit of organisms, represents the starting point of this review. It is demonstrated that SERS provides a deep understanding of living cells as well as their microenvironment which is needed to assess the development of diseases. The clinical relevance of SERS is proved by its application for the detection of cancer cells and tumour margins under in vivo conditions and examples for theranostic approaches are discussed. This review article provides a comprehensive overview of the recent progress within the last 3 years.

Surface-enhanced Raman spectroscopy and microfluidic platforms: challenges, solutions and potential applications.

The exhaustive body of literature published in the last four years on the development and application of systems based on surface-enhanced Raman spectroscopy (SERS) combined with microfluidic devices demonstrates that this research field is a current hot topic. This synergy, also referred to as lab-on-a-chip SERS (LoC-SERS) or nano/micro-optofluidics SERS, has opened the door for new opportunities where both techniques can profit. On the one hand, SERS measurements are considerably improved because the processes previously performed on a large scale in the laboratory and prone to human error can now be carried out in nanoliter volumes in an automatic and reproducible manner; on the other hand, microfluidic platforms need detection methods able to sense in small volumes and therefore, SERS is ideal for this task. The present review not only aims to provide the reader an overview of the recent developments and advancements in this field, but it also addresses the key aspects of fundamental SERS theory that influence the interpretation of SERS spectra, as well as the challenges brought about by the experimental conditions and chemometric data analysis.

Relations between personality changes and cerebrospinal fluid biomarkers of Alzheimer's disease pathology.

Specific changes in personality profiles may represent early non-cognitive symptoms of Alzheimer's disease (AD). Evaluating the subject's personality changes may add significant clinical information, as well as help to better understand the interaction between personality change, cognitive decline, and cerebral pathology. With this study we aimed to describe the relationship between personality changes and cerebrospinal fluid (CSF) markers of AD pathology at early clinical stages of the disease. One hundred and ten subjects, of whom 66 cognitively impaired patients (57 with mild cognitive impairment (MCI), and 9 with mild dementia) and 44 healthy controls, had neuropsychological examination as well as lumbar puncture to determine concentrations of CSF biomarkers of AD pathology (amyloid beta1-42 (Aß1-42), phosphorylated tau (ptau-181), and total-tau (tau)). The Revised NEO Personality Inventory (NEO-PI-R) was administered twice, once to evaluate subjects' current personality and once to assess personality traits retrospectively 5 years before evaluation. Subjects with an AD CSF biomarker profile showed significant increase in neuroticism and decrease in conscientiousness over time as compared to non-AD CSF biomarker group. In regression analysis controlling for global cognition as measured by the MMSE score, increasing neuroticism and decreasing extraversion, openness to experience and conscientiousness were associated with lower Aß1-42 concentrations but not with tau and ptau-181 concentrations. Our findings suggest that early and specific changes in personality are associated with cerebral AD pathology. Concentrations of CSF biomarkers, additionally to severity of the cognitive impairment, significantly contribute in predicting specific personality changes.

Recognition of tumor cells by immuno-SERS-markers in a microfluidic chip at continuous flow.

SERS active nanoparticles were labeled with a reporter molecule and conjugated with anti-EpCAM antibodies. These immuno SERS markers were mixed with leukocytes, MCF-7 breast cancer cells and polystyrene beads, and the mixture was injected into a microfluidic quartz chip. Raman spectra were acquired at 785 nm excitation with 25 milliseconds exposure time in a continuous flow regime. Spectral unmixing by N-FINDR identified spectral signatures of SERS-labelled cells and polystyrene beads. This approach demonstrated rapid and reproducible SERS-assisted cell detection. Strategies are discussed to further increase the throughput for cell sorting.

Molecular self-healing mechanisms between C60-fullerene and anthracene unveiled by Raman and two-dimensional correlation spectroscopy.

The self-healing polymer P(LMA-co-MeAMMA) crosslinked with C60-fullerene has been studied by FT-Raman spectroscopy in combination with two-dimensional (2D) correlation analysis and density functional theory calculations. To unveil the molecular changes during the self-healing process mediated by the Diels-Alder equilibrium between 10-methyl-9-anthracenyl groups and C60-fullerene different anthracene-C60-fullerene adducts have been synthesized and characterized by time-, concentration- and temperature-dependent FT-Raman measurements. The self-healing process could be monitored via the C60-fullerene vibrations at 270, 432 and 1469 cm(-1). Furthermore, the detailed analysis of the concentration-dependent FT-Raman spectra point towards the formation of anthracene-C60-fullerene adducts with an unusual high amount of anthracene bound to C60-fullerene in the polymer film, while the 2D correlation analysis of the temperature-dependent Raman spectra suggests a stepwise dissociation of anthracene-C60-fullerene adducts, which are responsible for the self-healing of the polymer.

Developments in spontaneous and coherent Raman scattering microscopic imaging for biomedical applications.

First, the potential role of Raman-based techniques in biomedicine is introduced. Second, an overview about the instrumentation for spontaneous and coherent Raman scattering microscopic imaging is given with a focus of recent developments. Third, imaging strategies are summarized including sequential registration with laser scanning microscopes, line imaging and global or wide-field imaging. Finally, examples of biomedical applications are presented in the context of single cells, laser tweezers, tissue sections, biopsies and whole animals.

Combining multiset resolution and segmentation for hyperspectral image analysis of biological tissues.

Hyperspectral images can provide useful biochemical information about tissue samples. Often, Fourier transform infrared (FTIR) images have been used to distinguish different tissue elements and changes caused by pathological causes. The spectral variation between tissue types and pathological states is very small and multivariate analysis methods are required to describe adequately these subtle changes. In this work, a strategy combining multivariate curve resolution-alternating least squares (MCR-ALS), a resolution (unmixing) method, which recovers distribution maps and pure spectra of image constituents, and K-means clustering, a segmentation method, which identifies groups of similar pixels in an image, is used to provide efficient information on tissue samples. First, multiset MCR-ALS analysis is performed on the set of images related to a particular pathology status to provide basic spectral signatures and distribution maps of the biological contributions needed to describe the tissues. Later on, multiset segmentation analysis is applied to the obtained MCR scores (concentration profiles), used as compressed initial information for segmentation purposes. The multiset idea is transferred to perform image segmentation of different tissue samples. Doing so, a difference can be made between clusters associated with relevant biological parts common to all images, linked to general trends of the type of samples analyzed, and sample-specific clusters, that reflect the natural biological sample-to-sample variability. The last step consists of performing separate multiset MCR-ALS analyses on the pixels of each of the relevant segmentation clusters for the pathology studied to obtain a finer description of the related tissue parts. The potential of the strategy combining multiset resolution on complete images, multiset segmentation and multiset local resolution analysis will be shown on a study focused on FTIR images of tissue sections recorded on inflamed and non-inflamed palatine tonsils.

Two-dimensional Raman correlation spectroscopy reveals molecular structural changes during temperature-induced self-healing in polymers based on the Diels-Alder reaction.

The thermally healable polymer P(LMA-co-FMA-co-MIMA) has been studied by temperature-dependent FT-Raman spectroscopy, two-dimensional Raman correlation analysis and density functional theory (DFT) calculations. To the best of our knowledge this study reports for the first time on the investigation of a self-healing polymer by means of two-dimensional correlation techniques. The synchronous correlation spectrum reveals that the spectrally overlapping C[double bond, length as m-dash]C stretching vibrations at 1501, 1575, 1585 and 1600 cm(-1) are perfect marker bands to monitor the healing process which is based on a Diels-Alder reaction of furan and maleimide. The comparison between experimental and calculated Raman spectra as well as their correlation spectra showed a good agreement between experiment and theory. The data presented within this study nicely demonstrate that Raman correlation analysis combined with a band assignment based on DFT calculations presents a powerful tool to study the healing process of self-healing polymers.

Spectrometer calibration protocol for Raman spectra recorded with different excitation wavelengths.

The combination of Raman spectroscopy with chemometrics has gained significant importance within the last years to address a broad variety of biomedical and life science questions. However, the routine application of chemometric models to analyze Raman spectra recorded with Raman devices different from the device used to establish the model is extremely challenging due to Raman device specific influences on the recorded Raman spectra. Here we report on the influence of different non-resonant excitation wavelengths on Raman spectra and propose a calibration routine, which corrects for the main part of the spectral differences between Raman spectra recorded with different (non-resonant) excitation wavelengths. The calibration routine introduced within this contribution is an improvement to the known 'standard' calibration routines and is a starting point for the development of a calibration protocol to generate spectrometer independent Raman spectra. The presented routine ensures that a chemometric model utilizes only Raman information of the sample and not artifacts from small shifts in the excitation wavelength. This is crucial for the application of Raman-spectroscopy in real-world-settings, such as diagnostics of diseases or identification of bacteria.

Seamless stitching of tile scan microscope images.

For diagnostic purposes, optical imaging techniques need to obtain high-resolution images of extended biological specimens in reasonable time. The field of view of an objective lens, however, is often smaller than the sample size. To image the whole sample, laser scanning microscopes acquire tile scans that are stitched into larger mosaics. The appearance of such image mosaics is affected by visible edge artefacts that arise from various optical aberrations which manifest in grey level jumps across tile boundaries. In this contribution, a technique for stitching tiles into a seamless mosaic is presented. The stitching algorithm operates by equilibrating neighbouring edges and forcing the brightness at corners to a common value. The corrected image mosaics appear to be free from stitching artefacts and are, therefore, suited for further image analysis procedures. The contribution presents a novel method to seamlessly stitch tiles captured by a laser scanning microscope into a large mosaic. The motivation for the work is the failure of currently existing methods for stitching nonlinear, multimodal images captured by our microscopic setups. Our method eliminates the visible edge artefacts that appear between neighbouring tiles by taking into account the overall illumination differences among tiles in such mosaics. The algorithm first corrects the nonuniform brightness that exists within each of the tiles. It then compensates for grey level differences across tile boundaries by equilibrating neighbouring edges and forcing the brightness at the corners to a common value. After these artefacts have been removed further image analysis procedures can be applied on the microscopic images. Even though the solution presented here is tailored for the aforementioned specific case, it could be easily adapted to other contexts where image tiles are assembled into mosaics such as in astronomical or satellite photos.

Detection of vancomycin resistances in enterococci within 3 ½ hours.

Vancomycin resistant enterococci (VRE) constitute a challenging problem in health care institutions worldwide. Novel methods to rapidly identify resistances are highly required to ensure an early start of tailored therapy and to prevent further spread of the bacteria. Here, a spectroscopy-based rapid test is presented that reveals resistances of enterococci towards vancomycin within 3.5 hours. Without any specific knowledge on the strain, VRE can be recognized with high accuracy in two different enterococci species. By means of dielectrophoresis, bacteria are directly captured from dilute suspensions, making sample preparation very easy. Raman spectroscopic analysis of the trapped bacteria over a time span of two hours in absence and presence of antibiotics reveals characteristic differences in the molecular response of sensitive as well as resistant Enterococcus faecalis and Enterococcus faecium. Furthermore, the spectroscopic fingerprints provide an indication on the mechanisms of induced resistance in VRE.

Droplet based microfluidics: spectroscopic characterization of levofloxacin and its SERS detection.

Levofloxacin (Levo), a second generation fluoroquinolone, has both clinical and environmental relevance. Therefore, the implementation of fast, robust and cost effective techniques for its monitoring is required. Here, its spectroscopic characterization and its detection in aqueous environment were carried out using surface enhanced Raman spectroscopy combined with droplet based microfluidics. The Levo molecule interacts with the silver nanoparticles via the carboxylate group and it adopts an upright or slightly tilted orientation. Furthermore, it is shown that the presence of Cl(-) ions has a strong influence on the enhancement efficiency of the Raman signal of the target molecule. Thus, for the determination of the limit of detection (LOD) the measurements were carried out in the absence of any electrolytes. The estimated LOD is ∼0.8 µM and the linear dynamic window ranges between 1-15 µM. These results were achieved after the normalization of the SERS signal to the Raman mode at 230 cm(-1). This band was attributed to the ν(Ag-O) stretching and it accounts for the Levo molecules in the first layer on the Ag nanoparticles.

Aqueous black colloids of reticular nanostructured gold.

Since ancient times, noble gold has continuously contributed to several aspects of life from medicine to electronics. It perpetually reveals its new features. We report the finding of a unique form of gold, reticular nanostructured gold (RNG), as an aqueous black colloid, for which we present a one-step synthesis. The reticules consist of gold crystals that interconnect to form compact strands. RNG exhibits high conductivity and low reflection, and these features, coupled with the high specific surface area of the material, could prove valuable for applications in electronics and catalysis. Due to high absorption throughout the visible and infrared domain, RNG has the potential to be applied in the construction of sensitive solar cells or as a substrate for Raman spectroscopy.

Classification and prediction of HCC tissues by Raman imaging with identification of fatty acids as potential lipid biomarkers.

PURPOSE: Patients with hepatocellular carcinoma (HCC) can only be treated curatively at early stages and then have a favorable prognosis of this often fatal disease. For this reason, an early detection and diagnostic confirmation are crucial. Raman imaging spectroscopy is a promising technology for high-resolution visualization of the spatial distribution of molecular composition in tissue sections. The aim of this study was to investigate molecular information of liver tissue by Raman imaging for classification and diagnostic prediction. METHODS: Unstained cryosections of human hepatic tissues (23 patients) were measured by Raman spectroscope in the regions of HCC (n = 12) and fibrosis (n = 17). The acquired data set was used to generate a random forest classification model with 101 iterations of sevenfold cross-validation. The models obtained during cross-validation were also used to predict regions of tumor margin (n = 8) aside from independent testing. RESULTS: Raman spectra differed between malignant and non-malignant tissue regions. Based on these spectral data, a random forest classification model calculated a prediction accuracy of 86 % (76 % sensitivity and 93 % specificity). The ten most important variables were identified at 2895, 2856, 1439, 1298, 1080, 1063, 1023, 937, 920, and 719 cm(-1). CONCLUSIONS: In this study, Raman imaging spectroscopy was applied successfully for liver tissue to differentiate, classify, and predict with high accuracy malignant and non-malignant tissue regions. Furthermore, the most important differences were identified as the Raman signature of fatty acids. The demonstrated results highlight the enormous potential which vibrational spectroscopy techniques have for the future diagnostics and prognosis estimation of HCC.

The relationship of pork longissimus muscle pH to mitochondrial respiratory activities, meat quality and muscle structure.

The way the pH falls post-slaughter has an impact on meat quality. Pork longissimus muscles (n=48) were sorted in fast- (FG) (n=15) and normal glycolysing (NG) (n=33) muscles according to the post-slaughter pH 45 min values (FG<6.0; NG>6.0). FG muscles (5.84±0.04) compared with NG muscles (6.27±0.04) were accompanied with higher temperature, electrical conductivity, lightness and yellowness, and reduced grill loss and shear force values (P<0.05), but there were no pH-dependent changes of the drip loss and redness results. FG muscles had higher (P<0.05) percentages of fast-twitch glycolytic and lower proportions of fast-twitch oxidative and slow-twitch oxidative (P<0.05) muscle fibres. The study confirms the relationship of pH value to meat quality and muscle fibre characteristics also showing that pH values have no impact on intrinsic mitochondrial respiratory function.