scholarly journals Plasma Protein Contents Determined by Fourier-Transform Infrared Spectrometry

2001 ◽  
Vol 47 (4) ◽  
pp. 730-738 ◽  
Author(s):  
Cyril Petibois ◽  
Georges Cazorla ◽  
André Cassaigne ◽  
Gérard Déléris
Keyword(s):  
Fourier Transform ◽  
Ir Spectra ◽  
Spectral Range ◽  
Plasma Proteins ◽  
Fourier Transform Infrared ◽  
Infrared Spectrometry ◽  
Ir Absorption ◽  
Apo B ◽  
Ir Spectrometry ◽  
Ft Ir

Abstract Background: Fourier-transform infrared (FT-IR) spectrometry has been used to measure small molecules in plasma. We wished to extend this use to measurement of plasma proteins. Methods: We analyzed plasma proteins, glucose, lactate, and urea in 49 blood samples from 35 healthy subjects and 14 patients. For determining the concentration of each biomolecule, the method used the following steps: (a) The biomolecule was sought for which the correlation between spectral range areas of plasma FT-IR spectra and concentrations determined by comparison method was greatest. (b) The IR absorption of the biomolecule at the most characteristic spectral range was calculated by analyzing pure samples of known concentrations. (c) The plasma concentration of the biomolecule was determined using the FT-IR absorption of the pure compound and the integration value obtained for the plasma FT-IR spectra. (d) The spectral contribution of the biomolecule was subtracted from the plasma FT-IR spectra, and the resulting spectra were saved for further analyses. (e) The same method was then applied to determining the concentrations of other biomolecules by sequentially comparing the resulting FT-IR spectra. Results: Results agreed with those obtained by clinical methods for the following biomolecules when analyzed in the following order: albumin, glucose, fibrinogen, IgG2, lactate, IgG1, α1-antitrypsin, α2-macroglobulin, transferrin, apolipoprotein (Apo)-A1, urea, Apo-B, IgM, Apo-C3, IgA, IgG4, IgG3, IgD, haptoglobin, and α1-acid glycoprotein. Conclusion: FT-IR spectrometry is a useful tool for determining concentrations of several plasma biomolecules.

scholarly journals Application of Fourier Transform Infrared Spectroscopy and Chemometrics for Differentiation of Salmonella enterica Serovar Enteritidis Phage Types

2010 ◽  
Vol 76 (11) ◽  
pp. 3538-3544 ◽  
Author(s):  
Ornella Preisner ◽  
Raquel Guiomar ◽  
Jorge Machado ◽  
Jos� Cardoso Menezes ◽  
Jo�o Almeida Lopes
Keyword(s):  
Fourier Transform ◽  
Ir Spectra ◽  
Salmonella Enterica ◽  
Intact Cell ◽  
Phage Type ◽  
Fourier Transform Infrared ◽  
Intact Cells ◽  
Phage Types ◽  
Ft Ir ◽  
Ir Analysis

ABSTRACT Fourier transform infrared (FT-IR) spectroscopy and chemometric techniques were used to discriminate five closely related Salmonella enterica serotype Enteritidis phage types, phage type 1 (PT1), PT1b, PT4b, PT6, and PT6a. Intact cells and outer membrane protein (OMP) extracts from bacterial cell membranes were subjected to FT-IR analysis in transmittance mode. Spectra were collected over a wavenumber range from 4,000 to 600 cm−1. Partial least-squares discriminant analysis (PLS-DA) was used to develop calibration models based on preprocessed FT-IR spectra. The analysis based on OMP extracts provided greater separation between the Salmonella Enteritidis PT1-PT1b, PT4b, and PT6-PT6a groups than the intact cell analysis. When these three phage type groups were considered, the method based on OMP extract FT-IR spectra was 100% accurate. Moreover, complementary local models that considered only the PT1-PT1b and PT6-PT6a groups were developed, and the level of discrimination increased. PT1 and PT1b isolates were differentiated successfully with the local model using the entire OMP extract spectrum (98.3% correct predictions), whereas the accuracy of discrimination between PT6 and PT6a isolates was 86.0%. Isolates belonging to different phage types (PT19, PT20, and PT21) were used with the model to test its robustness. For the first time it was demonstrated that FT-IR analysis of OMP extracts can be used for construction of robust models that allow fast and accurate discrimination of different Salmonella Enteritidis phage types.

Examinations of the Matrix Isolation Fourier Transform Infrared Spectra of Organic Compounds: Part XVII

1989 ◽  
Vol 43 (8) ◽  
pp. 1424-1427 ◽  
Author(s):  
W. M. Coleman ◽  
Bert M. Gordon
Keyword(s):  
Fourier Transform ◽  
Quantitative Analysis ◽  
Matrix Isolation ◽  
Complex Mixture ◽  
Fourier Transform Infrared ◽  
Mass Range ◽  
Infrared Spectrometry ◽  
Flame Ionization ◽  
The Matrix ◽  
Ft Ir

Qualitative and quantitative analysis of compounds in a complex mixture by gas chromatography/matrix isolation/Fourier transform infrared spectrometry (GC/MI/FT-IR) is described. The carbon-deuterium stretching mode was characterized and used for analysis since it has a unique position in the infrared spectrum. Compounds of varying functionalities were examined over a concentration range from 6 to 50 ng. Linear responses over this mass range were obtained. Flame ionization detection was used for collaborative detection in establishing the linearity of the responses. These results represent the first use of GC/MI/FT-IR for quantitative analysis of compounds in a complex mixture using deuterium-labeled analogues.

Advantages of Dual-Beam Interferometry in Fourier Transform Infrared Spectrometry

1986 ◽  
Vol 40 (5) ◽  
pp. 628-632 ◽  
Author(s):  
Donald L. Beduhn ◽  
Robert L. White
Keyword(s):  
Fourier Transform ◽  
Fourier Transform Infrared ◽  
Infrared Spectrometry ◽  
Single Beam ◽  
Fiber Analysis ◽  
Dual Beam ◽  
Infrared Microscope ◽  
Order Of Magnitude ◽  
Infrared Spectrometer ◽  
Ft Ir

A dual-beam Fourier transform infrared spectrometer (FT-IR) is described. Sensitivity improvement, photometric accuracy, and instrument stability are evaluated by comparing dual-beam spectra with conventional single-beam spectra. Dual-beam FT-IR data acquisitions require an order of magnitude less measurement time than single-beam acquisitions for spectra of comparable signal-to-noise ratios. Application of dual-beam FT-IR for analysis of a highly transmitting sample is discussed. Single fiber analysis without masking and without an infrared microscope is described.

Multiple Filtering Strategy for the Automated Detection of Ethanol by Passive Fourier Transform Infrared Spectrometry

2001 ◽  
Vol 55 (11) ◽  
pp. 1544-1552 ◽  
Author(s):  
Patrick O. Idwasi ◽  
Gary W. Small ◽  
Roger J. Combs ◽  
Robert B. Knapp ◽  
Robert T. Kroutil
Keyword(s):  
Remote Sensing ◽  
Fourier Transform ◽  
Digital Filters ◽  
Laboratory Data ◽  
Fourier Transform Infrared ◽  
Automated Detection ◽  
Infrared Spectrometry ◽  
Linear Discriminant ◽  
Detection Strategy ◽  
Ft Ir

Digital filtering methods are evaluated for use in the automated detection of ethanol from passive Fourier transform infrared (FT-IR) data collected during laboratory and open-air remote sensing experiments. In applications in which analyte signals are overwhelmed by the overlapping signals of an interference, the use of multiple digital filters is observed to improve the sensitivity of the analyte detection. The detection strategy is based on the application of bandpass digital filters to short segments of the interferogram data collected by the FT-IR spectrometer. To implement the automated detection of a target analyte, the filtered interferogram segments are supplied as input to piecewise linear discriminant analysis. Through the use of a set of training data, discriminants are computed that can subsequently be applied to detect the presence of the analyte in an automated manner. This research focuses on the detection of ethanol vapor in the presence of an ammonia interference. A two-filter detection strategy based on the use of separate ethanol and ammonia filters is compared to an approach based on a single ethanol filter. Bandpass parameters of the digital filters and the interferogram segment location are optimized through the use of laboratory data in which ethanol and ammonia vapors are generated in a gas cell and viewed against various infrared background radiances. The filter and segment parameters obtained through this optimization are subsequently tested with field remote sensing data collected when the spectrometer is allowed to view ethanol and ammonia plumes generated from a heated stack. The two-filter strategy is found to outperform the single-filter approach with both the laboratory and field data in situations in which the ammonia interference dominates the ethanol signature.

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