An improved algorithm for fast resonant Mie scatter correction of infrared spectra of cells and tissues

Mie scattering effects create serious problems for the interpretation of Fourier‐transform infrared spectroscopy spectra of single cells and tissues. During recent years, different techniques were proposed to retrieve pure absorbance spectra from spectra with Mie distortions. Recently, we published an iterative algorithm for correcting Mie scattering in spectra of single cells and tissues, which we called “the fast resonant Mie scatter correction algorithm.” The algorithm is based on extended multiplicative signal correction (EMSC) and employs a meta‐model for a parameter range of refractive index and size parameters. In the present study, we suggest several improvements of the algorithm. We demonstrate that the improved algorithm reestablishes chemical features of the measured spectra, and show that it tends away from the reference spectrum employed in the EMSC. We suggest strategies for choosing parameter ranges and other model parameters such as the number of principal components of the meta‐model and the number of iterations. We demonstrate that the suggested algorithm optimizes an error function of the refractive index in a forward Mie model. We suggest a stop criterion for the iterative algorithm based on the error function of the forward model.      

Front Cover: An open‐source code for Mie extinction extended multiplicative signal correction for infrared microscopy spectra of cells and tissues (J. Biophotonics 8/2019)

Spectra from microscopic tissue sections are strongly distorted by Mie‐type scattering and require correction by the ME‐EMSC algorithm. In the upper right, Mie extinction curves, which are simulated by the ME‐EMSC algorithm, are shown. Two measured spectra are shown in the foreground, a raw spectrum which contains Mie scattering, and the spectrum corrected by the ME‐EMSC algorithm. The cover figure was designed by Dr. Boris Zimmermann. Further details can be found in the article by Johanne H. Solheim, Evgeniy Gunko, Dennis Petersen, et al. ( e201800415 ).

     

An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples

In infrared spectroscopy of thin film samples, interference introduces distortions in spectra, commonly referred to as fringes. Fringes may alter absorbance peak ratios, which hampers the spectral analysis. We have previously introduced extended multiplicative signal correction (EMSC) for fringes correction. In the current article, we provide a robust open-source algorithm for fringe correction in infrared spectroscopy and propose several improvements to the Fringe EMSC model. The suggested algorithm achieves a more precise fringe frequency estimation by mean centering of the measured spectrum and applying a window function prior to the Fourier transform. It selects two frequencies from a user defined number of maxima in the Fourier domain. The improved Fringe EMSC algorithm is validated on two experimental datasets, one of them being a hyperspectral image. Techniques for separating sample spectra from background spectra in hyperspectral images, and techniques to identify spectra affected by fringes are also provided.     

Optical properties of mice's stool in 550 to 1000 nm wavelength range

The aim of this work was to measure optical properties of stool of mice to provide this relevant wavelength‐dependent behavior for optical imaging modalities such as fluorescent molecular tomography and near‐infrared optical tomography. BALB/c nude female mice were studied and optical properties of the stool were determined by employing the inverse adding‐doubling approach. The animals were kept on chlorophyll‐free diet. Nine stool samples were measured. The wavelength‐dependent behavior of absorption and scattering in 550 to 1000 nm range is presented. The reduced scattering spectrum is fitted to the Mie scattering approximation in the near‐infrared (NIR) wavelength range and to the Mie + Rayleigh approximation in visible/NIR range with the fitting coefficients presented. The study revealed that the absorption spectrum of stool can lead to crosstalk with the spectrum of hemoglobin in the NIR range.      

An X-ray spectrum estimation method from transmission measurement combined with scatter correction

PurposeConventional x-ray spectrum estimation methods from transmission measurement often lead to inaccurate results when extensive x-ray scatter is present in the measured projection. This study aims to apply the weighted L1-norm scatter correction algorithm in spectrum estimation for reducing residual differences between the estimated and true spectrum.MethodThe scatter correction algorithm is based on a simple radiographic scattering model where the intensity of scattered x-ray is directly estimated from a transmission measurement. Then, the scatter-corrected measurement is used for the spectrum estimation method that consists of deciding the weights of predefined spectra and representing the spectrum as a linear combination of the predefined spectra with the weights. The performances of the estimation method combined with scatter correction are evaluated on both simulated and experimental data.ResultsThe results show that the estimated spectra using the scatter-corrected projection nearly match the true spectra. The normalized-root-mean-square-error and the mean energy difference between the estimated spectra and corresponding true spectra are reduced from 5.8% and 1.33 keV without the scatter correction to 3.2% and 0.73 keV with the scatter correction for both simulation and experimental data, respectively.ConclusionsThe proposed method is more accurate for the acquisition of x-ray spectrum than the estimation method without scatter correction and the spectrum can be successfully estimated even the materials of the filters and their thicknesses are unknown. The proposed method has the potential to be used in several diagnostic x-ray imaging applications.     

Analysis of the circular dichroism spectrum of proteins using the convex constraint algorithm: a practical guide.

Due to the time scale of circular dichroism (CD) measurements, it is theoretically possible to deconvolute such a spectrum if the pure CD spectra differ significantly from one another. In the last decade several methods have been published aiming at obtaining the conformational weights, or percentages (which are the coefficients for a linear combination) of the so-called typical secondary structural elements making up the three-dimensional structure of proteins. Two methods that can be used to determine the secondary structures of proteins are described here. The first method, called LINCOMB, is a simple algorithm based on a least-squares fit with a set of reference spectra representing the known secondary structures and yielding an estimation of weights attributed to alpha-helix, beta-pleated sheet (mainly antiparallel), beta-turns, unordered form, and aromatic/disulfide (or nonpeptide) contributions of the protein being analyzed. This method requires a "template" or reference curve set, which was obtained from the second method. The second method, "convex constraint analysis," is a general deconvolution method for a CD spectra set of any variety of conformational type. The algorithm, based on a set of three constraints, is able to deconvolute a set of CD curves to its common "pure"-component curves and conformational weights. To analyze a single CD spectrum with this method, the spectrum is appended to the data set used as a reference data set. As a way to determine the reliability of the algorithm and provide a guideline to its usage, some applications are presented.     

Optical properties of some freshwater phytoplanktonic algae

Measurements of absorption and scattering of light by pure cultures of some New Zealand freshwater phytoplankters have been made with a spectrophotometer. An integrating sphere accessory was used to capture most of the light scattered by an algal cell suspension and thus give an indication of the true absorption coefficient, with only a small correction required for residual scattering. The purpose of this study was to investigate the factors affecting the relationships of chlorophyll-a concentration to absorption and scattering by a diverse selection of algae. Qualitative differences in absorption spectra of the different phytoplankton studied here can be related to differences in pigment composition. Quantitative differences in the specific absorption coefficients (absorption coefficient divided by Chl-a concentration) at the Chl-a red peak (676 nm in vivo) are explained in terms of different extents of packaging of pigment in cells or cell aggregates in the different cultures. Qualitative differences in scattering spectra are explained in terms of optical size of the particulates comprising the pure cultures. The green and diatom cultures displayed a complex-shaped but non-trending scattering spectrum with minima (troughs) in scattering associated with maxima (peaks) in absorption. The blue-green cultures behaved as optically small particles and displayed a pattern of decreasing scattering with increasing wavelength. Quantitative differences in specific scattering coefficients (scattering coefficient divided by Chl-a concentration) were related mainly to differences in the effective ratio of surface areas to Chl-a content of scattering centres in the different cultures. Overall, however, the specific absorption and scattering coefficients at any given wavelength were less variable between cultures than expected suggesting that the common assumption that absorption and scattering by the algal component of a lake water depends only on the Chl-a concentration may be a justifiable first approximation in field studies.     

Infrared absorbance spectroscopy of aqueous proteins: Comparison of transmission and ATR data collection and analysis for secondary structure fitting

Attenuated total reflectance (ATR) infrared absorbance spectroscopy of proteins in aqueous solution is much easier to perform than transmission spectroscopy, where short path‐length cells need to be assembled reproducibly. However, the shape of the resulting ATR infrared spectrum varies with the refractive index of the sample and the instrument configuration. Refractive index in turn depends on the absorbance of the sample. In this work, it is shown that a room temperature triglycine sulfate detector and a ZnSe ATR unit can be used to collect reproducible spectra of proteins. A simple method for transforming the protein ATR spectrum into the shape of the transmission spectrum is also given, which proceeds by approximating a Kramers‐Krönig–determined refractive index of water as a sum of four linear components across the amide I and II regions. The light intensity at the crystal surface (with 45° incidence) and its rate of decay away from the surface is determined as a function of the wave number–dependent refractive index as well as the decay of the evanescent wave from the surface. The result is a single correction factor at each wave number. The spectra were normalized to a maximum of 1 between 1600 cm^?1 and 1700 cm^?1 and a self‐organizing map secondary structure fitting algorithm, SOMSpec, applied using the BioTools reference set. The resulting secondary structure estimates are encouraging for the future of ATR spectroscopy for biopharmaceutical characterization and quality control applications.     

A representation learning approach for recovering scatter-corrected spectra from Fourier-transform infrared spectra of tissue samples

Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of scattering effects, often Mie scattering, which probably overshadows biochemically relevant spectral information by a nonlinear, nonadditive spectral component in Fourier transform infrared (FTIR) spectroscopic measurements. Correspondingly, many successful machine learning approaches for FTIR spectra have relied on preprocessing procedures that computationally remove the scattering components from an infrared spectrum. We propose an approach to approximate this complex preprocessing function using deep neural networks. As we demonstrate, the resulting model is not just several orders of magnitudes faster, which is important for real-time clinical applications, but also generalizes strongly across different tissue types. Using Bayesian machine learning approaches, our approach unveils model uncertainty that coincides with a band shift in the amide I region that occurs when scattering is removed computationally based on an established physical model. Furthermore, our proposed method overcomes the trade-off between computation time and the corrected spectrum being biased towards an artificial reference spectrum.     

Fluorescence spectroscopy of H‐ras transfected murine fibroblasts: A comparison with Monte Carlo simulations

Autofluorescence properties of tissues have been widely used to diagnose various types of malignancies. In this study, we measured the autofluorescence properties of H‐ras transfected murine fibroblasts and the counterpart control cells. The pair of cells is genetically identical except for the transfected H‐ras gene. We applied Monte Carlo simulations to evaluate the relative contributions of Rayleigh and Mie scattering effects towards fluorescence in an in vitro model system of normal and H‐ras transfected fibroblasts. The experimental results showed that fluorescence emission intensity was higher for normal cells than the malignant counterpart cells by about 30%. In normal cells, linearity in emission intensity was observed for cell densities of up to 1.0 × 10⁶ cells/ml whereas for transformed cells it was up to 1.4 × 10⁶ cells/ml. Nuclear volume changes give good account for the differences in the intrinsic fluorescence between normal and malignant cells. The Monte Carlo (MC) code, newly developed for this study, explains both predominant experimental features: the large fluorescence intensity differences between the transfected and the corresponding control cells as well as the phenomena of the red shift in the excitation spectra as a function of cell density. The contribution of Rayleigh scattering was found to be predominant compared to Mie scattering. © 2009 Wiley Periodicals, Inc. Biopolymers 93: 132–140, 2010. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com     

组织模型偏振散射光谱特性研究

结合偏振门技术和米氏散射理论,建立了组织模型的偏振散射差分光谱理论模型.计算分析了粒子群的平均尺寸、相对折射率变化时后向偏振散射差分光谱的特征.结果表明,利用偏振门技术测量的差分光谱主要是来自表层粒子的光信号,偏振散射差分光谱对粒子平均尺寸及相对折射率的变化比较敏感,随着粒子平均尺寸的增加,光谱振荡频率将增加,而随着相对折射率的减小,光谱的振幅减小,且差分光强值减小.该方法对于早期癌症检测具有潜在应用意义.     

Angular range,sampling and noise considerations for inverse light scattering analysis of nuclear morphology

In recent years, significant work has been devoted to the use of angle‐resolved elastic scattering for the extraction of nuclear morphology in tissue. By treating the nucleus as a Mie scattering object, techniques such as angle‐resolved low‐coherence interferometry (a/LCI) have demonstrated substantial success in identifying nuclear alterations associated with dysplasia. Because optical biopsies are inherently noninvasive, only a small, discretized portion of the 4π scattering field can be collected from tissue, limiting the amount of information available for diagnostic purposes. In this work, we comprehensively characterize the diagnostic impact of variations in angular sampling, range and noise for inverse light scattering analysis of nuclear morphology, using a previously reported dataset from 40 patients undergoing a/LCI optical biopsy for cervical dysplasia. The results from this analysis are applied to a benchtop scanning a/LCI system which compromises angular range for wide‐area scanning capability. This work will inform the design of next‐generation optical biopsy probes by directing optical design towards parameters which offer the most diagnostic utility.      

Extended multiplicative signal correction for FTIR spectral quality test and pre‐processing of infrared imaging data

Spectral quality control is an important step in the analysis of infrared spectral data, however, often neglected in scientific literature. A frequently used quality test that was originally developed for infrared spectra of bacteria is provided by OPUS software from Bruker Optik GmbH. In this study, the OPUS quality test is applied to a large number of spectra of bacteria, yeasts and moulds and hyperspectral images of microorganisms. It is shown that the use of strict thresholds for parameters of the OPUS quality test leads to discarding too many spectra. A strategy for optimizing parameters thresholds of the OPUS quality test is provided and a novel approach for spectral quality testing based on extended multiplicative signal correction (EMSC) is suggested. For all the data sets considered in our study, the EMSC quality test is shown to be the best among different alternatives of OPUS quality test provided.     

Time-Resolved Spectroscopy of mitochondria,cells and tissues under normal and pathological conditions

In this study, the detailed dependence of light scattering on tissue architecture and intracellular composition has been investigated. Firstly, we simulated the reduced scattering coefficient (_s) of the rat liver using the Mie theory, the Rayleigh-Debye-Gans approximation and electron microscopy data. Then, the reduced scattering coefficient of isolated rat liver mitochondria, isolated hepatocytes and various rat tissues (i.e. perfused liver, brain, muscle, tumors) was measured at 780 nm by using time-resolved spectroscopy and a sample-substitution protocol. The comparison of the isolated mitochondria data with the isolated hepatocyte and whole liver measurements suggests that the mitochondrial compartment is the primary factor for light propagation in hepatic tissue, thus strengthening the relevance of the preliminary theoretical study. Nevertheless, the possibility that other intracellular components, such as peroxisomes and lysosomes, interfere with light propagation in rat liver is discussed. Finally, we demonstrate that light scattering in normal rat tissues and tumors is roughly proportional to the mitochondrial content, according to estimates of the mitochondrial protein content of the tissues.     

Interpretation and Optimization of Absorbance and Fluorescence Signals from Voltage-sensitive Dyes

Voltage-sensitive dyes produce absorbance and fluorescence changes that can be used to image voltage. The present study develops a systematic approach to the optimization of these signals. A mathematical analysis assesses the dye optical density (OD) that optimizes the signal-to-noise ratio in absorbance and fluorescence measurements. The signal-to-noise ratio is maximal for a dye OD of 2 (natural logarithm) in absorbance and ~1 in fluorescence. The fluorescence result is approximate because, in contrast to absorbance, the optimal dye OD varies with the amount of scattering and intrinsic absorbance of the tissue. The signal-to-noise ratio of absorbance is higher in thick preparations such as brain slices; fluorescence is superior in thin preparations such as cell culture. The optimal OD for absorbance and fluorescence, as well as the superiority of absorbance, were confirmed experimentally on hippocampal slices. This analysis also provided insight into the interpretation of signals normalized to resting light intensities. With both absorbance and fluorescence, the normalized signal (I/I) varies with OD, and does not reflect the change in dye absorbance. In absorbance this problem is remedied by dividing I/I by the dye OD to obtain the absorbance change. For fluorescence a correction is possible, but is more complicated. Because this analysis indicates that high levels of stain optimize the signal-to-noise, dyes were tested for pharmacological actions and phototoxicity. The absorbance dye RH155 was found to have pharmacological action at high staining levels. The fluorescent dye RH414 was phototoxic. Adverse effects could not be detected with the absorbance dye RH482.     

Convex constraint analysis: a natural deconvolution of circular dichroism curves of proteins

A new algorithm, called convex constraint analysis, has been developed to deduce the chiral contribution of the common secondary structures directly from experimental CD curves of a large number of proteins. The analysis is based on CD data reported by Yang, J.T., Wu, C.-S.C. and Martinez, H.M. [Methods Enzymol., 130, 208-269 (1986)]. Application of the decomposition algorithm for simulated protein data sets resulted in component spectra [B (lambda, i)] identical to the originals and weights [C (i, k)] with excellent Pearson correlation coefficients (R) [Chang, C.T., Wu, C.-S.C. and Yang, J.T. (1978) Anal. Biochem., 91, 12-31]. Test runs were performed on sets of simulated protein spectra created by the Monte Carlo technique using poly-L-lysine-based pure component spectra. The significant correlational coefficients (R greater than 0.9) demonstrated the high power of the algorithm. The algorithm, applied to globular protein data, independent of X-ray data, revealed that the CD spectrum of a given protein is composed of at least four independent sources of chirality. Three of the computed component curves show remarkable resemblance to the CD spectra of known protein secondary structures. This approach yields a significant improvement in secondary structural evaluations when compared with previous methods, as compared with X-ray data, and yields a realistic set of pure component spectra. The new method is a useful tool not only in analyzing CD spectra of globular proteins but also has the potential for the analysis of integral membrane proteins.     

The molecular force field of guanine and its deuterated species as determined from neutron inelastic scattering and resonance Raman measurements

Neutron inelastic scattering (NIS) spectra from polycrystalline samples and ultraviolet resonance Raman scattering (RRS) spectra from aqueous solutions of guanine and CS-deuterated and (N9, NI, C2-amino)-deuterated guanine are reported. These measurements allowed theoretical simulations of the vibrational wavenumbers and intensities of the NIS and RRS bands to be performed. Å valence force field enabled the normal mode wavenumbers, as well as the atomic displacements, to be calculated. The NIS intensities were simulated by considering multi-phonon interactions arising from the lattice mode couplings with the internal molecular vibrational modes. The RRS intensities were simulated within the framework of the so-called small shift approximation, by using the molecular bond-order changes induced by the electronic transition from the ground to the first electronic excited state. It is shown that NIS spectroscopy mainly provides information on the guanine out-of-plane modes of vibration, while RRS allows the in-plane stretching vibrational motions to be analyzed.     

Label‐free optical detection of cyclosporine in biological fluids

In this paper, a spectroscopic method for determination of cyclosporine concentrations in biological fluids is presented. Blood plasma and hemoglobin solutions are chosen for the experiment. For various cyclosporine concentrations in blood plasma and hemoglobin, absorbance measurements in spectra range from 600 to 1100 nm are performed. The measurement results are analyzed by the use of a dedicated algorithm. The obtained data are characterized by a high coefficient of correlation R², which is equal to 0.9461 and 0.9808 for blood plasma and hemoglobin, respectively. The proposed method enables the selective detection of cyclosporine level and could be applied in medicine and laboratory diagnostics. The obtained result can be the base to build the point‐of‐care CsA level detection optical sensor.