Biomedical subjects

C Ruckebusch

Publications and source records attributed to C Ruckebusch.

5 recordsLinked to original sources

PubMed2007

Multivariate curve resolution of rapid-scan FTIR difference spectra of quinone photoreduction in bacterial photosynthetic membranes.

Photosynthetic reaction centres and membranes are systems of particular interest and are often taken as models to investigate the molecular mechanisms of selected bioenergetic reactions. In this work, a multivariate curve resolution by alternating least squares procedure is detailed for resolution of time-resolved difference FTIR spectra probing the evolution of quinone reduction in photosynthetic membranes from Rhodobacter sphaeroides under photoexcitation. For this purpose, different data sets were acquired in the same time range and spectroscopic domain under slightly different experimental conditions. To enable resolution and provide meaningful results the different data sets were arranged in an augmented matrix. This strategy enabled recovery of three different species despite rank-deficiency conditions. It also results in better definition (identity and evolution) of the contributions. From the resolved spectra, the species have been attributed to: 1. the formation of ubiquinol, more precisely the disappearance of Q/appearance of QH(2); 2. conformational change of the protein in the surrounding biological medium; 3. oxidation of diaminodurene, a redox mediator. Because, moreover, results obtained from augmented data sets strategies enable quantitative and qualitative interpretation of concentration profiles, other effects, for example the consequence of repeated light excitation of the same sample, choice of illumination power, or the number of spectra accumulated could be compared and discussed.

Algorithms↗

PubMed2006

Quantitative analysis of cotton-polyester textile blends from near-infrared spectra.

Quantitative analysis of textile blends and textile fabrics is currently of particular interest in the industrial context. In this frame, this work investigates whether the use of Fourier transform (FT) near-infrared (NIR) spectroscopy and chemometrics is powerful for rapid and accurate quantitative analysis of cotton-polyester content in blend products. As samples of the same composition have many sources of variability that affect NIR spectra, indirect prediction is particularly challenging and a large sample population is required to design robust calibration models. Thus, a total of more than three-hundred cotton-polyester samples were selected covering the range from the 0% to 100% cotton and the corresponding NIR reflectance spectra were measured on raw fabrics. The data set obtained was used to develop multivariate models for quantitative prediction from reference measurements. A successful approach was found to rely on partial least squares (PLS) regression combined with genetic algorithms (GAs) for wavelength selection. It involved evaluating a set of calibration models considering different spectral regions. The results obtained considering 27.5% of the original variables yielded a prediction error (RMSEP) of 2.3 in percent cotton content. It demonstrates that FT-NIR spectroscopy has the potential to be used in the textile industry for the prediction of the composition of cotton-polyester blends. As a further consequence, it was observed that the spectral preprocessing and the complexity of the model are simplified compared to the full-spectrum approach. Also, the relevancy of the spectral intervals retained after variable selection can be discussed.

Journal Article↗

PubMed2001

Antibacterial activity of a pepsin-derived bovine hemoglobin fragment.

Peptic digestion of bovine hemoglobin yields a fragment with antibacterial activity. This peptide was purified to homogeneity by a two-step procedure including anion exchange chromatography and preparative reversed-phase HPLC. Mass determination and fragmentation indicated that this peptide corresponded to the 1-23 fragment of the alpha chain of hemoglobin. The minimum inhibitory concentration and mode of action of this peptide towards Micrococcus luteus strain A270 were determined. Hemolytic assay, interaction with liposomes, and study of its structure in solution were also performed.

Amino Acid Sequence↗

PubMedDate not supplied

Time-resolved step-scan FT-IR spectroscopy: focus on multivariate curve resolution.

The present paper describes the application of step-scan FT-IR spectroscopy in combination with chemometric analysis of the spectral data for the study of the photocycle of bacteriorhodopsin. The focus is on the performance of this instrumentation for time-resolved experiments. Three-dimensional data-spectra recorded over time-are studied using various factor analysis techniques, e.g., singular values decomposition, evolving factor analysis, and multivariate curve resolution based on alternating least squares. Transient intermediates formed in the time domain ranging from 1 micros to 6.6 ms are clearly detected through reliable pure time evolving profiles. At the same time, pure difference absorbance spectra are provided. As a result, valuable information about transitions and dynamics of the protein can be extracted. We conclude first that step-scan FT-IR spectroscopy is a useful technique for the direct study of difficult photochemical systems. Second, and this is the essential motivation of this paper, chemometrics provide a step forward in the description of the photointermediates.

Journal Article↗

PubMedDate not supplied

Multivariate curve resolution methods in imaging spectroscopy: influence of extraction methods and instrumental perturbations.

Imaging spectroscopy is becoming a key field of analytical chemistry. In the face of more and more complex samples, we actually need accurate microscopic insight. Nowadays, the methods used to produce concentration maps of the pure compounds from spectral data sets are based on the classical univariate approach although multivariate approaches are sometimes investigated. But in any case, the analytical quality of the chemical images thus provided cannot be discussed since no reference methods are at our disposal. Thus the proposed research focuses on the application of multivariate methods such as Orthogonal Projection Approach (OPA), SIMPLE-to-use Self-modeling Mixture Analysis (SIMPLISMA), Multivariate Curve Resolution - Alterning Least Squares (MCR-ALS), and Positive Matrix Factorization (PMF) for imaging spectroscopy. A systematic and quantitative characterization of the accuracy of spectra and images extraction is investigated on mid-infrared spectral data sets. Of special interest is the influence of instrumental perturbations such as noise and spectral shift on the extraction ability to access the algorithm's robustness.

Journal Article↗