I NDEPENDENT C OMPONENTS A NALYSIS I NDEPENDENT C OMPONENTS A NALYSIS Applications of ICA Douglas N. Rutledge, Delphine Jouan-Rimbaud Bouveresse
Information Hidden in MIR Spectra Source : R.Aries, D. Lidiard, R. Spragg, Spectrosc. Internat., 2(3) 41-44
ICA on 100 Mid-Infrared spectra Samples : a single polystyrene film Mid-IR spectra taken at end of production line Acquired from 4000cm -1 to 400cm -1, at 1 cm -1 Pre-treatment of spectra : - normalised between 0 and 1 - neither centred nor standardised
PC2 CO 2 & H 2 O Results of a PCA on the polystyrene MIR data
PC6 Interferogram & derivative PC5 Interferogram & derivative
PC5-PC6 Scores Plot
IC2/7 signal looks like water vapour spectrum Due to variations in moisture content of air
IC3/7 signal looks like spectrum of CO 2 Due to variations in CO 2 content of air
IC4/7 signal looks like beats of a simple interferogram Due to variations in optical path of polystyrene sample ?
IC7/7 signal looks like first derivative of average MIR spectrum Due to one spectrometer (N°61) being badly adjusted (frequency shift)
Elimination of artifacts Monitoring changes in oils during heating using 3-D Fluorescence Spectroscopy
Rayleigh scattering Raman scattering 3-D Fluorescence Spectra of Oils during Heating
IC1 = Rayleigh + Raman
IC2 = Polyphenols
IC3 = Chlorophyll…
Antioxydant influence of catechin on rats after hyperlipidic diets, monitored using a LC-MS based metabolomic approach
The data Samples Male Wistar rats (n = 8/group) fed for 6 weeks normo- (5% diet w/w) or hyper- lipidic (15 and 25%) diets (CT05 / HF15 / HF25) With or without catechin supplementation (0.2% w/w) (NP / PP) (polyphenolic antioxidant - helps prevent inflammatory and coronary diseases) Urines collected 17 and 38 days after diets were given (T17 / T38) Technique Analysed by mass spectrometry on a LC-QToF (m/z ; positive ionization) (HPLC Alliance 2695, Symmetry® RP18 column, Micromass Qtof-Micro / Waters) Pretreatment Intensities of peaks transformed to log(X+1) Variables sorted in order of decreasing variance (later as function of Retention Time)
Log(raw LC-MS data)
Independent Components Analysis Extract “pure signals” from observed mixtures - “pure signals” => “Loadings” - “proportions” of “pure signals” to mixtures = “Scores”
ICA on Log(Data)
IC2 “Loadings”
IC3 “Loadings”
IC5 “Loadings”
Mid-Infrared analysis of edible oils heated at 190° for 3 hours
ICA applied to Mid-Infrared spectra 180 spectra acquired every 3 minutes over 3 hours during flat heating at 190°C
PCA Loadings
PCA Scores
ICA Signals
ICA Scores
Mid-IR spectrum of CO 2
Scores of samples on IC9 as a function of heating time
Mid-IR spectrum cis-trans isomerisation
Scores of samples on IC2 as a function of heating time
ICA applied to Raman hyperspectral images Hyperspectral images acquired for an authentic and a suspect pharmaceutical pill M Boiret, D N Rutledge, N Gorretta, Y-M Ginot, J-M Roger Utilisation de la microscopie Raman et des methodes chimiometriques pour la detection de comprimes contrefaits, SpectrAnalyse, 2014, in press
Images collected using a PerkinElmer RS400 system Microscope coupled to spectrophotometer with 785nm 400mW laser CCD sensor (Charge-Coupled Device) Sample on a motorized stage with a pitch of 50 microns Raman spectra acquired from 3200cm -1 to 100cm -1 Spectral resolution 2 cm spectra on a surface of about 8mm * 8mm
ICA_by_Blocks applied to authentic and suspect pills
ICA Proportions ICA Signals & Reference spectra R=0.99 R=0.98 Authentic pharmaceutical pill
ICA Proportions ICA Signals Suspect pharmaceutical pill
ICA Signals & Reference spectrum (Metformine) Suspect pharmaceutical pill Compare ICA signals with spectral database ICA Signals & Reference spectrum (Avicel) R=0.96 R=0.99
ICA can be applied to data usually analysed using PCA Contributions of variables are easier to interpret CONCLUSION