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