Rapid Vector-Based Peak Fitting and Resolution Enhancement for Correlation Analyses of Raman Hyperspectra.

Spectroscopic peak parameters are important since they provide information about the analyte under study. Besides obtaining these parameters, peak fitting also resolves overlapped peaks. Thus, the obtained parameters should permit the construction of a higher-resolution version of the original spectrum. However, peak fitting is not an easy task due to computational reasons and because the true nature of the analyte is often unknown. These difficulties are major impediments when large hyperspectral data sets need to be processed rapidly, such as for manufacturing process control. We have developed a novel and relatively fast two-part algorithm to perform peak fitting and resolution enhancement on such data sets. In the first part of the algorithm, estimates of the total number of bands and their parameters were obtained from a representative spectrum in the data set, using a combination of techniques. Starting with these parameter estimates, all the spectra were then iteratively and rapidly fitted with Gaussian bands, exploiting intrinsic features of the Gaussian distribution with vector operations. The best fits for each spectrum were retained. By reducing the obtained bandwidths and commensurately increasing their amplitudes, high-resolution spectra were constructed that greatly improved correlation-based analyses. We tested the performance of the algorithm on synthetic spectra to confirm that this method could recover the ground truth correlations between highly overlapped peaks. To assess effective peak resolution, the method was applied to low-resolution spectra of glucose and compared to results from high-resolution spectra. We then processed a larger spectral data set from mammalian cells, fixed with methanol or air drying, to demonstrate the resolution enhancement of the algorithm on complex spectra and the effects of resolution-enhanced spectra on two-dimensional correlation spectroscopy and principal component analyses. The results indicated that the algorithm would allow users to obtain high-resolution spectra relatively fast and permit the recovery of important aspects of the data's intrinsic correlation structure.

Saline dry fixation for improved cell composition analysis using Raman spectroscopy.

Raman spectroscopy enables the label-free assessment of cellular composition. While live cell analysis is the most accurate approach for cellular Raman spectroscopy, the analysis of fixed cells has proved to be very useful, particularly in collaborative projects where samples need to be serially examined by different laboratories or stored and reanalyzed at a later date. However, many chemicals that are widely used for cell fixation directly affect cellular biomolecules, yielding Raman spectra with missing or altered information. In this article, we compared the suitability of dry-fixation with saline versus chemical fixatives. We compared the Raman spectroscopy of saline dry-fixed cells with the more commonly used formaldehyde and methanol fixation and found that dry-fixed cell spectra preserved more cellular information than either chemical fixative. We also assessed the stability of dry-fixed cells over time and found that they were stable for at least 5 months. Finally, a comparison of dry-fixed and live cell spectra revealed effects due to the hydration state of the cells since they were recovered upon rehydrating dry-fixed samples. Thus, for fixed cell Raman spectroscopy, we recommend dry-fixation with unbuffered saline as a superior method to formaldehyde or methanol fixation.

Two-Dimensional Clustering of Spectral Changes for the Interpretation of Raman Hyperspectra.

Two-dimensional correlation spectroscopy (2D-COS) is a technique that permits the examination of synchronous and asynchronous changes present in hyperspectral data. It produces two-dimensional correlation coefficient maps that represent the mutually correlated changes occurring at all Raman wavenumbers during an implemented perturbation. To focus our analysis on clusters of wavenumbers that tend to change together, we apply a k-means clustering to the wavenumber profiles in the perturbation domain decomposition of the two-dimensional correlation coefficient map. These profiles (or trends) reflect peak intensity changes as a function of the perturbation. We then plot the co-occurrences of cluster members two-dimensionally in a manner analogous to a two-dimensional correlation coefficient map. Because wavenumber profiles are clustered based on their similarity, two-dimensional cluster member spectra reveal which Raman peaks change in a similar manner, rather than how much they are correlated. Furthermore, clustering produces a discrete partitioning of the wavenumbers, thus a two-dimensional cluster member spectrum exhibits a discrete presentation of related Raman peaks as opposed to the more continuous representations in a two-dimensional correlation coefficient map. We demonstrate first the basic principles of the technique with the aid of synthetic data. We then apply it to Raman spectra obtained from a polystyrene perchlorate model system followed by Raman spectra from mammalian cells fixed with different percentages of methanol. Both data sets were designed to produce differential changes in sample components. In both cases, all the peaks pertaining to a given component should then change in a similar manner. We observed that component-based profile clustering did occur for polystyrene and perchlorate in the model system and lipids, nucleic acids, and proteins in the mammalian cell example. This confirmed that the method can translate to "real world" samples. We contrast these results with two-dimensional correlation spectroscopy results. To supplement interpretation, we present the cluster-segmented mean spectrum of the hyperspectral data. Overall, this technique is expected to be a valuable adjunct to two-dimensional correlation spectroscopy to further facilitate hyperspectral data interpretation and analysis.

Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra.

Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.

Non-invasive monitoring of red blood cells during cold storage using handheld Raman spectroscopy.

BACKGROUND: The current best practices allow for the red blood cells (RBCs) to be stored for prolonged periods in blood banks worldwide. However, due to the individual-related variability in donated blood and RBCs continual degradation within transfusion bags, the quality of stored blood varies considerably. There is currently no method for assessing the blood product quality without compromising the sterility of the unit. This study demonstrates the feasibility of monitoring storage lesion of RBCs in situ while maintaining sterility using an optical approach. STUDY DESIGN AND METHODS: A handheld spatially offset Raman spectroscopy (RS) device was employed to non-invasively monitor hemolysis and metabolic changes in 12 red cell concentrate (RCC) units within standard sealed transfusion bags over 7 weeks of cold storage. The donated blood was analyzed in parallel by biochemical (chemical analysis, spectrophotometry, hematology analysis) and RS measurements, which were then correlated through multisource correlation analysis. RESULTS: Raman bands of lactate (857 cm-1 ), glucose (787 cm-1 ), and hemolysis (1003 cm-1 ) were found to correlate strongly with bioanalytical data over the length of storage, with correlation values 0.98 (95% confidence interval [CI]: 0.86-1.00; p = .0001), 0.95 (95% CI: 0.71-0.99; p = .0008) and 0.97 (95% CI: 0.79-1.00; p = .0004) respectively. DISCUSSION: This study demonstrates the potential of collecting information on the clinical quality of blood units without breaching the sterility using Raman technology. This could significantly benefit quality control of RCC units, patient safety and inventory management in blood banks and hospitals.

Augmented Two-Dimensional Correlation Spectroscopy for the Joint Analysis of Correlated Changes in Spectroscopic and Disparate Sources.

Here, we present an augmented form of two-dimensional correlation spectroscopy, that integrates in a single format data from spectroscopic and multiple non-spectroscopic sources for analysis. The integration is affected by augmenting every spectrum in a hyperspectral data set with relevant non-spectroscopic data to permit two-dimensional correlation analysis(2D-COS) of the ensemble of augmented spectra. A k-means clustering is then applied to the results of the perturbation domain decomposition to determine which Raman peaks cluster with any of the non-spectroscopic data. We introduce and explain the method with the aid of synthetic spectra and synthetic non-spectroscopic data. We then demonstrate this approach with data using Raman spectra from human embryonic stem cell aggregates undergoing directed differentiation toward pancreatic endocrine cells and parallel bioassays of hormone mRNA expression and C-peptide levels in spent medium. These pancreatic endocrine cells generally contain insulin or glucagon. Insulin has disulfide bonds that produce Raman scattering near 513 cm-1, but no tryptophan. For insulin-positive cells, we found that the application of multisource correlation analysis revealed a high correlation between insulin mRNA and Raman scattering in the disulfide region. In contrast, glucagon has no disulfide bonds but does contain tryptophan. For glucagon-positive cells, we also observed a high correlation between glucagon mRNA and tryptophan Raman scattering (∼757 cm-1). We conclude with a discussion of methods to enhance spectral resolution and its effects on the performance of multisource correlation analysis.

Correction: Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives.

Correction for 'Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives' by Shreyas Rangan et al., Analyst, 2020, DOI: 10.1039/c9an01811e.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives.

Therapies based on injecting living cells into patients offer a huge potential to cure many degenerative and deadly diseases, with hundreds of clinical trials ongoing. Due to their complex nature, a basic understanding of their biochemical and functional characteristics, how to manufacture them for safe and efficacious therapy, and how to effectively implement them in clinical settings are very challenging. Raman spectroscopy could provide an information-rich, non-invasive, non-destructive analytical method to complement the use of conventional sample-based, infrequent and destructive biochemical assays typically employed to analyze and validate the quality of therapeutic cells. This article provides an overview of the current state of emerging cell therapies, and then reviews the related Raman spectroscopic state of the art analysis of human cells. This includes spectroscopic data processing considerations, the scope offered by technical variants of Raman spectroscopy, and analytical difficulties encountered by spectroscopists working with therapeutic cells. Finally, we outline a number of salient challenges as cell therapy products are translated from the laboratory to the clinic, and propose how Raman spectroscopy-based solutions could address these challenges.

Effects of cysteine, asparagine, or glutamine limitations in Chinese hamster ovary cell batch and fed-batch cultures.

Amino acid availability is a key factor that can be controlled to optimize the productivity of fed-batch cultures. To study amino acid limitation effects, a serum-free chemically defined basal medium was formulated to exclude the amino acids that became depleted in batch culture. The effect of limiting glutamine, asparagine, and cysteine on the cell growth, metabolism, antibody productivity, and product glycosylation was investigated in three Chinese hamster ovary (CHO) cell lines (CHO-DXB11, CHO-K1SV, and CHO-S). Cysteine limitation was detrimental to both cell proliferation and productivity for all three CHO cell lines. Glutamine limitation reduced growth but not cell specific productivity, whereas asparagine limitation had no significant effect on either growth or cell specific productivity. Neither glutamine nor asparagine limitation significantly affected antibody glycosylation. Replenishing the CHO-DXB11 culture with cysteine after 1 day of cysteine limitation allowed the cells to partially recover their growth and productivity. This recovery was not observed after 2 days of cysteine limitation. Based on these findings, a fed-batch protocol was developed using single or mixed amino acid supplementation. Although cell density and antibody concentration were lower compared to a commercial feed, the feeds based on cysteine supplementation yielded comparable cell specific productivity. Overall, this study showed that different amino acid limitations have varied effects on the performance of CHO cell cultures and that maintaining cysteine availability is a critical process parameter for the three cell lines investigated.

Defocused Spatially Offset Raman Spectroscopy in Media of Different Optical Properties for Biomedical Applications Using a Commercial Spatially Offset Raman Spectroscopy Device.

In this study, we show how defocused spatially offset Raman spectroscopy (SORS) can be employed to recover chemical information from media of biomedical significance within sealed plastic transfusion and culture bags using a commercial SORS instrument. We demonstrate a simple approach to recover subsurface spectral information through a transparent barrier by optimizing the spatial offset of the defocused beam. The efficiency of the measurements is assessed in terms of the SORS ratio and signal-to-noise ratio (S/N) through a simple manual approach and an ordinary least squares model. By comparing the results for three different biological samples (red blood cell concentrate, pooled red cell supernatant and a suspension of Jurkat cells), we show that there is an optimum value of the offset parameter which yields the maximum S/N depending on the barrier material and optical properties of the ensemble contents. The approach was developed in the context of biomedical applications but is generally applicable to any three-layer system consisting of turbid content between transparent thin plastic barriers (i.e., front and back bag surfaces), particularly where the analyte of interest is dilute or not a strong scatterer.

Smoothing Raman Spectra with Contiguous Single-Channel Fitting of Voigt Distributions: An Automated, High-Quality Procedure.

Theoretical probability distributions are often fitted to the individual peaks of Raman spectra to decompose them and facilitate further analyses. Fitting has the additional advantage of eliminating noise. We have exploited this noise-eliminating attribute of fitting procedures in an automated algorithm to smooth Raman spectra. An initial smoothing was performed by fitting Voigt distributions to every channel in a spectrum. The Voigt distribution characters used were strongly Gaussian, the distribution widths equal to the spectral resolution, and their initial amplitudes equal to the spectral intensities at the channels where they were located. The smoothed spectrum was then subtracted from the original noisy spectrum to obtain a residual. For channels where the residual exceeded a limit-of-detection threshold, the distribution width was decreased. The fitting was then repeated until a secondary, lower limit distribution width was reached. The residual was then smoothed repeatedly in the same manner until the minimum distribution width was reached. After each repetition, the smoothed residual was added to the smoothed spectrum. The process was continued until a combined limit of detection and chi-squared stopping criterion was reached. Although slower in comparison to spline- and Savitzky-Golay-based methods, the smoothing quality was significantly better allowing the majority of smoothed spectra, in contrast to these methods, to pass a stringent smoothing quality test.

Deposits in the lungs of Kwäday Dän Ts'ìnchi man: Characterization by a combination of analytical microscopical methods.

OBJECTIVES: The approximately 250 years old remains of the Kwäday Dän Ts'ìnchi man were found in a glacier in Canada. Studying the state of preservation of the corpse, we observed black deposits in his lung. Following this observation we wanted to determine: (1) location of the deposits in the lung tissue, (2) composition and origins of the deposits. METHODS: By light microscopy (LM) and transmission electron microscopy (TEM), we studied the deposits in the Kwäday Dän Ts'ìnchi man' s lung and compared it with distribution of anthracotic deposits in contemporary samples from the David Harwick Pathology Centre (DHPC). To determine chemical composition of the inclusions we used Raman spectroscopy. Scanning electron microscopy and elemental mapping was used for determine the chemical elements. RESULTS: The histopathological identification of anthracosis in the Kwäday Dän Ts'ìnchi man's lung allowed us to distinguish crushed parenchyma from conducting airway tissue and identification of particles using LM and TEM. Crystal particles were found using TEM. Ordered carbonaceous material (graphene and graphite), disordered carbonaceous material (soot) and what might be minerals (likely conglomerates) were found with Raman spectrometry. Gold and lead particles in the lung were discovered with scanning electron microscopy and elemental mapping. CONCLUSIONS: Presence of soot particles in anthracotic areas in the Kwäday Dän Ts'ìnchi man's lung probably were due to an inhalation of particles in open fires. Gold and lead particles are most likely of an environmental origin and may have been inhaled and could have impacted his health and his Champagne and Aishihik First Nations (CAFN) contemporaries.

Developing Fully Automated Quality Control Methods for Preprocessing Raman Spectra of Biomedical and Biological Samples.

Spectral preprocessing is frequently required to render Raman spectra useful for further processing and analyses. The various preprocessing steps, individually and sequentially, are increasingly being automated to cope with large volumes of data from, for example, hyperspectral imaging studies. Full automation of preprocessing is especially desirable when it produces consistent results and requires minimal user input. It is therefore essential to evaluate the "quality" of such preprocessed spectra. However, relatively few methods exist to evaluate preprocessing quality, and fully automated methods for doing so are virtually non-existent. Here we provide a brief overview of fully automated spectral preprocessing and fully automated quality assessment of preprocessed spectra. We follow this with the introduction of fully automated methods to establish figures-of-merit that encapsulate preprocessing quality. By way of illustration, these quantitative methods are applied to simulated and real Raman spectra. Quality factor and quality parameter figures-of-merit resulting from individual preprocessing step quality tests, as well as overall figures-of-merit, were found to be consistent with the quality of preprocessed spectra.

Pressure-assisted capillary electrophoresis frontal analysis for faster binding constant determination.

Adding external pressure during the process of capillary electrophoresis usually add to the band broadening, especially if the pressure induced flow is significant. The resolution is normally negatively affected in pressure-assisted capillary electrophoresis (PACE). Frontal analysis (FA), however, can potentially benefit from using an external pressure while avoiding the drawbacks in other modes of CE. In this work, possible impact from the external pressure was simulated by COMSOL Multiphysics®. Under a typical CE-FA set-up, it was found that the detected concentrations of analyte will not be significantly affected by an external pressure less than 5 psi. Besides, the measured ligand concentration in PACE-FA was also not affected by common variables (molecular diffusion coefficient (10-8 to 10-11 m2 /s), capillary length etc). To provide an experimental proof, PACE-FA is used to study the binding interactions between hydroxypropyl ß-cyclodextrin (HP-ß-CD) and small ligand molecules. Taking the HP-ß-CD /benzoate pair as an example, the binding constants determined by CE-FA (18.3 ± 0.8 M-1 ) and PACE-FA (16.5 ± 0.5 M-1 ) are found to be similar. Based on the experimental results, it is concluded that PACE-FA can reduce the time of binding analysis while maintaining the accuracy of the measurements.

Types of cell death and apoptotic stages in Chinese Hamster Ovary cells distinguished by Raman spectroscopy.

Cell death is the ultimate cause of productivity loss in bioreactors that are used to produce therapeutic proteins. We investigated the ability of Raman spectroscopy to detect the onset and types of cell death for Chinese Hamster Ovary (CHO) cells-the most widely used cell type for therapeutic protein production. Raman spectroscopy was used to compare apoptotic, necrotic, autophagic, and control CHO cells. Several specific nucleic acid-, protein-, and lipid-associated marker bands within the 650-850 cm-1 spectral region were identified that distinguished among cells undergoing different modes of cell death; supporting evidence was provided by principal component analysis (PCA) of the full spectral data. In addition to comparing the different modes of cell death, normal cells were compared to cells sorted at several stages of apoptosis, in order to explore the potential for early detection of apoptosis. Different stages of apoptosis could be distinguished via Raman spectroscopy, with multiple changes observed in nucleic acid peaks at early stages whereas an increase in lipid signals was a feature of late apoptosis/secondary necrosis.

Empirical Factors Affecting the Quality of Non-Negative Matrix Factorization of Mammalian Cell Raman Spectra.

Mammalian cells contain various macromolecules that can be investigated non-invasively with Raman spectroscopy. The particular mixture of major macromolecules present in a cell being probed are reflected in the measured Raman spectra. Determining macromolecular identities and estimating their concentrations from these mixture Raman spectra can distinguish cell types and otherwise enable biological research. However, the application of canonical multivariate methods, such as principal component analysis (PCA), to perform spectral unmixing yields mathematical solutions that can be difficult to interpret. Non-negative matrix factorization (NNMF) improves the interpretability of unmixed macromolecular components, but can be difficult to apply because ambiguities produced by overlapping Raman bands permit multiple solutions. Furthermore, theoretically sound methods can be difficult to implement in practice. Here we examined the effects of a number of empirical approaches on the quality of NNMF results. These approaches were evaluated on simulated mammalian cell Raman hyperspectra and the results were used to develop an enhanced procedure for implementing NNMF. We demonstrated the utility of this procedure using a Raman hyperspectral data set measured from human islet cells to recover the spectra of insulin and glucagon. This was compared to the relatively inferior PCA of these data.

Using Raman spectroscopy to assess hemoglobin oxygenation in red blood cell concentrate: an objective proxy for morphological index to gauge the quality of stored blood?

Blood banking is an essential aspect of modern medical care. When red blood cells (RBCs) are stored, they become damaged by various chemical processes, such as accumulation of their own waste products and oxidative injury, among others. These processes lead to the development of the RBC storage lesion, a complex condition where the severity is reflected through the morphology of the stored cells. It was hypothesized that Raman spectroscopy could be used to monitor certain structural and compositional changes associated with such ageing effects and that a relationship between these features and traditional morphology (as measured using a morphology index) could be observed. The hypothesis was tested by measuring spectral features associated with hemoglobin oxygenation from dry-fixed smears and liquid RBCs for twenty-nine different donors (combined), and comparing the trends with morphological scoring from seven of these donors. After appropriately fitting the two data sets to either power or linear curves, the oxygenation state was shown to change in a manner that was donor-dependent and that closely tracked morphological changes. This study suggests Raman analysis has promise for providing a rapid and objective measure of the cell quality of stored RBCs through measurements of hemoglobin oxygenation that is comparable to traditional morphological assessment.

Raman Spectroscopy of Blood and Blood Components.

Blood is a bodily fluid that is vital for a number of life functions in animals. To a first approximation, blood is a mildly alkaline aqueous fluid (plasma) in which a large number of free-floating red cells (erythrocytes), white cells (leucocytes), and platelets are suspended. The primary function of blood is to transport oxygen from the lungs to all the cells of the body and move carbon dioxide in the return direction after it is produced by the cells' metabolism. Blood also carries nutrients to the cells and brings waste products to the liver and kidneys. Measured levels of oxygen, nutrients, waste, and electrolytes in blood are often used for clinical assessment of human health. Raman spectroscopy is a non-destructive analytical technique that uses the inelastic scattering of light to provide information on chemical composition, and hence has a potential role in this clinical assessment process. Raman spectroscopic probing of blood components and of whole blood has been on-going for more than four decades and has proven useful in applications ranging from the understanding of hemoglobin oxygenation, to the discrimination of cancerous cells from healthy lymphocytes, and the forensic investigation of crime scenes. In this paper, we review the literature in the field, collate the published Raman spectroscopy studies of erythrocytes, leucocytes, platelets, plasma, and whole blood, and attempt to draw general conclusions on the state of the field.

Measuring and Remediating Nonspecific Modifications of Gold Surfaces Using a Coupled in Situ Electrochemical Fluorescence Microscopic Methodology.

In surface-based biosensors, the nonspecific or undesired adsorption of the probe is an important characteristic that is typically difficult to measure and therefore to control or eliminate. A methodology for measuring and then minimizing or eliminating this problem on gold surfaces, readily applicable to many common surface modifications is presented. Combining electrochemical perturbation and fluorescence microscopy, we show that the potential at which the adsorbed species is removed can be used as an estimate of the strength of the adsorbate-surface interaction. This desorption potential can be easily measured through an increase in fluorescence intensity as the potential is manipulated. Furthermore, this method can be used to evaluate strategies for preventing or removing nonspecific adsorption. This is demonstrated for a wide variety of surface modifications, from strongly chemisorbed monolayers such as thiol self-assembled monolayers (SAMs) to physisorbed monolayers as well as for complex surface structures like peptide and DNA mixed-component SAMs. The use of a coadsorption strategy or small magnitude potential-step cycles was shown to significantly decrease the amount of nonspecifically or noncovalently bound probe, creating better defined surfaces.

Raman spectroscopy as a novel tool for monitoring biochemical changes and inter-donor variability in stored red blood cell units.

Individual units of donated red blood cells (RBCs) do not ordinarily undergo analytical testing prior to transfusion. This study establishes the utility of Raman spectroscopy for analyzing the biochemistry of stored RBC supernatant and reveals interesting storage-related changes about the accumulation of lactate, a chemical species that may be harmful to certain patients. The data show measurable variations in supernatant composition and demonstrate that some units of donated RBCs accumulate lactate much more readily than others. The spectra also indicate a higher relative concentration of lactate in units collected from male donors than female donors (p = 0.004) and imply that there is a greater degree of variability at later stages of storage in units from older male donors (>45 years). The study proves that Raman analysis has promise for elucidating the relationship between the metabolism of stored RBCs and donor characteristics. It also suggests that there may be benefit in developing a Raman instrument for the rapid non-invasive assessment of blood-bag biochemistry by measuring through plastic over-layers.