Literature DB >> 24992094

Using Fourier transform IR spectroscopy to analyze biological materials.

Matthew J Baker1, Júlio Trevisan2, Paul Bassan3, Rohit Bhargava4, Holly J Butler5, Konrad M Dorling6, Peter R Fielden7, Simon W Fogarty8, Nigel J Fullwood9, Kelly A Heys5, Caryn Hughes3, Peter Lasch10, Pierre L Martin-Hirsch5, Blessing Obinaju5, Ganesh D Sockalingum11, Josep Sulé-Suso12, Rebecca J Strong5, Michael J Walsh13, Bayden R Wood14, Peter Gardner3, Francis L Martin5.   

Abstract

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

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Year:  2014        PMID: 24992094      PMCID: PMC4480339          DOI: 10.1038/nprot.2014.110

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  106 in total

1.  Fourier transform infrared imaging: theory and practice.

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2.  Analysis of variance in spectroscopic imaging data from human tissues.

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Journal:  Cancer Lett       Date:  2006-05-19       Impact factor: 8.679

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Authors:  Jayakrupakar Nallala; Olivier Piot; Marie-Danièle Diebold; Cyril Gobinet; Olivier Bouché; Michel Manfait; Ganesh D Sockalingum
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Review 9.  The Syrian hamster embryo (SHE) assay (pH 6.7): mechanisms of cell transformation and application of vibrational spectroscopy to objectively score endpoint alterations.

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10.  Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis.

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3.  Renal Graft Fibrosis and Inflammation Quantification by an Automated Fourier-Transform Infrared Imaging Technique.

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