Use Of Second Derivative Spectra Research Articles

Characterisation of Intervertebral Discs Using MID-IR Spectroscopic Imaging

Introduction Lower back pain affects millions of people worldwide, and has been linked to degenerative changes in the intervertebral disc (IVD) of the spine. In the “NPmimetic” project, a multidisciplinary team has come together to create a biomimetic nanopolymer based implant and develop a minimally invasive therapy to reconstruct and regenerate diseased nucleus pulposus (NP). The biodegradable nanofibers of the implant can also be designed to carry anti-inflammatory drugs, which can be released in situ promoting healing and preventing inflammation (http://npmimetic.com/). An IVD consists primarily of a proteoglycan-water gel embedded in a randomly arranged collagen network in the NP, and highly ordered collagen lamella in the annulus fibrosus (AF). Disc cells in the AF are elongated parallel to the collagen fibers and produce predominantly collagen I in the outer AF in response to deformation. NP cells are responsive to hydrostatic pressure and synthesize mostly proteoglycan and collagen II. In adults, the cell density in an IVD is very low and cell phenotypes can change in response to altered matrix and stress distribution.1 For successful regeneration, tissue integrity together with the right mechanical environment is essential for normal cell function. To develop suitable biomimetic implants a thorough characterization profile, that can be used as an aspirational target is important. In this study, we use Fourier transform infrared (FTIR) microscopic imaging to obtain chemical maps of control and in-vivo CABC-degenerated goat IVDs.2,3 Materials and Methods Goat IVDs were kindly provided from VU University Medical Centre (VUMC), Amsterdam. The IVDs were formalin fixed (10%, overnight), paraffin embedded, and 4 µm sections were mounted on custom- made reflective steel slides. FTIR microscopy in transflection mode was used to generate chemical distribution maps from unstained paraffin sections. One microscopic image covers only a very small area (350 × 350 µm) of an IVD sample (∼2.8 × 2.3 cm, transverse section). Bigger areas are measured by sequential sample movement and image acquisition covering a user-defined mosaic image area. In this example, an area of 80 × 64 images was measured resulting in a total of 10,720 IR spectra per IVD section. FTIR mosaic imaging generally generates many thousands of data points. A major challenge is handling and analyzing such large and chemically complex datasets to extract meaningful information. However, using iterative multivariate curve resolution (MCR) techniques on the reduced data matrix from principal component analysis analysis of second derivative spectra it is possible to deconvolute highly overlapping infrared peaks into single contributions of different molecular species. Results The chemical identity of the extracted component using an iterative MCR algorithm is determined by comparing the extracted spectral profiles with the spectral profiles of reference materials for proteoglycan and collagen. Spectral features matching typical proteoglycan and collagen spectral characteristics are observed. The distribution of the extracted MCR factors for collagen and proteoglycan are compared with consecutive IVD sections, which were stained using traditional histological methods; Masson trichrome staining for collagen and Alcian blue staining for proteoglycan. A good match can be observed between the distribution maps of collagen and proteoglycans derived from FTIR microscopic imaging measurements and the traditionally stained sections. Conclusion FTIR microscopic imaging in transflection mode has been successfully used to generate molecular images of the collagen and proteoglycan distribution of natural IVD material without the use of contrast-enhancing agents. The use of second derivative spectra together with the application of iterative MCR algorithms shows great potential to enhance the chemical specificity of FTIR mosaic imaging and opens up the possibility to distinguish between different proteclycans and proteins as well as their secondary structure, which usually are expressed only through minor peak shifts. Acknowledgments We thank the European Union (NPMIMETIC ref 246351) for 7th Framework Program funding. Disclosure of Interest None declared References Adams MA, Roughley PJ. What is intervertebral disc degeneration, and what causes it? Spine 2006;31(18):2151–2161 Hoogendoorn RJW, Wuisman PIJM, Smit TH, Everts VE, Helder MN. Experimental intervertebral disc degeneration induced by chondroitinase ABC in the goat. Spine 2007;32(17):1816–1825 Hoogendoorn RJW, Helder MN, Kroeze RJ, Bank RA, Smit TH, Wuisman PI. Reproducible long-term disc degeneration in a large animal model. Spine 2008;33(9):949–954

Quantitation of Mixtures of Diprotic Organic Acids by FT-IR Flow Titrations and Multivariate Curve Resolution

The combination of FT-IR flow titrations and second-order calibration methods is assessed for the first time as a potential method for quantifying mixtures of organic acids. FT-IR spectral information is richer and more specific than that provided by other spectrometric techniques. Also, the flow titration of the sample allows the use of second-order data analysis methods, such as multivariate curve resolution, which can quantify multianalyte systems using pure analyte standards in the presence of unknown interferents. Problems linked to FT-IR flow titrations, such as the impossibility of using buffer substances and the presence of major baseline contributions in the measurements due to changes in the water structureless absorption, have been overcome through the design of an adapted experimental setup and the use of second derivative spectra. Malic and/or tartaric acid are the model substances chosen to be quantified in the presence or absence of interferents. Both substances are diprotic acids with similar p Ka values and, therefore, similar pH-dependent evolution. Samples with one or both acids with their related standards in the presence or absence of an inert interferent (sugar) are successfully resolved and quantified for a wide range of [analyte]: [interferent] ratios with no need for pH control in the process. These results suggest this methodology as an optimal and robust alternative for routine analysis.

Investigation of infrared calibration methods for application to the study of methyl methacrylate polymerization.

Infrared spectroscopy has been used to monitor the polymerization of methyl methacrylate. Concentrations of methyl methacrylate in the reaction mixture were determined by use of three calibration methods. Classical quantitative analysis was used to measure the height of the stretching vibration bands of the vinyl group at 1639 cm(-1). A calibration procedure using the considerably higher intensity of the C = O stretching vibration band of the carbonyl ester group at 1725 cm(-1) seemed useful only for high concentrations of methyl methacrylate, i.e. at the beginning of reaction, because this band overlaps that of poly(methyl methacrylate). Use of second-derivative spectra and measuring their values at 1725 cm(-1) enabled estimation of ten times lower concentrations of methyl methacrylate the calibration using the band from the vinyl group.

Study of the absorption spectra of the 4f electron transition of the Nd and Er complexes with 2-isobutylformyl-1,3-dione-indane in the presence of TX-100 and its analytical application.

The absorption spectra of 4f electron transitions of the systems of neodymium and erbium with 2-isobutylformyl-1,3-dione-indane and TX-100 have been studied by normal and derivative spectrophotometry. Their molar absorptivities at the maximum absorption bands are about 7.2 (at 571 nm) times greater for neodymium and 13.1 (at 519 nm) times greater for erbium than those in the absence of the complexing agents. Use of second derivative spectra both eliminates the interference from other rare earths and increases the sensitivity from neodymium and erbium. Beer's law is obeyed from 0 approximately 20 microg/ml for neodymium and 0 approximately 25 microg/ml for erbium. The relative standard deviations are 1.2% and 1.6% for 5.0 microg/ml of neodymium and 8.0 microg/ml of erbium, respectively. The detection limits (signal-to-noise ratio=2) are 0.14 microg/ml and 0.20 microg/ml. A method for the direct determination of neodymium and erbium in rare earth mixtures with good accuracy and selectivity is proposed.

Selective determination of holmium in rare earth mixtures by second-derivative spectrophotometry with benzoylindan-1,3-dione and cetylpyridinium chloride

The absorption spectra of 4f electron transitions of the holmium complex with benzoylindan-1,3-dione and cetylpyridinium chloride were studied by conventional and derivative spectrophotometry. The molar absorptivity of the complex at the maximum absorption band was about 22 times greater (at 450 nm) than that in the absence of the complexing agent. The use of second-derivative spectra both eliminates the interference from other rare earths and improves the sensitivity for holmium. The calibration graph showed that the complex obeys Beer's law up to 25 µg cm–3 of holmium. The corresponding value of Sandell's sensitivity is 0.36 µg cm–2. The RSD evaluated from 11 independent determinations of 10 µg of holmium is 0.96%. The detection limit, obtained from the sensitivity of the calibration graph and for 3sb(sb= standard deviation of a blank without holmium, n= 11), was found to be 0.43 mg dm–3 of holmium. The quantification limit, obtained for 10sb, was 1.43 µg cm–3 of holmium. A method for the direct determination of holmium in rare earth mixtures with good selectivity and accuracy is described.

The use of second-derivative spectra for pure-variable based self-modeling mixture analysis techniques

Recently, the use of second-derivative spectra was introduced as an intermediate step in self-modeling mixture analysis. Since special problems arise using second-derivative spectra, a follow-up study was needed to evaluate the calculation of second-derivative spectra with respect to self-modeling mixture analysis techniques. A critical parameter is the size of the smoothing window, which should be large enough to reduce noise, but small enough to avoid distortion of the spectra. This paper will discuss this follow-up study and show methods to obtain the optimal smoothing, using a near-IR spectral data set of solvents, and an FTIR-microscopy data set of polymer laminate spectra. The results are obtained using the SIMPLISMA approach, but can also be applied to other pure-variable methods.