Analysis and classification of proton NMR spectra of lipoprotein fractionsfrom healthy volunteers and patients with cancer or CHD

Citation
Tf. Bathen et al., Analysis and classification of proton NMR spectra of lipoprotein fractionsfrom healthy volunteers and patients with cancer or CHD, ANTICANC R, 20(4), 2000, pp. 2393-2408
Citations number
73
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Onconogenesis & Cancer Research
Journal title
ANTICANCER RESEARCH
ISSN journal
0250-7005 → ACNP
Volume
20
Issue
4
Year of publication
2000
Pages
2393 - 2408
Database
ISI
SICI code
0250-7005(200007/08)20:4<2393:AACOPN>2.0.ZU;2-L
Abstract
Human blood plasma samples from 52 subjects were collected and the very low density lipoprotein (VLDL) intermediate density lipoprotein (IDL) low dens ity lipoprotein (LDL) and high density lipoprotein were isolated by serial ultra centrifugation. 600 MHz H-1 NMR spectra of the lipoprotein fractions were acquired. The methyl and methylene regions in the spectra of VLDL, LDL and HDL were utilised in further analyses via Kohonen neural networks (KNN ) and generative topographic mapping (GTM) two related examples of (unsuper vised learning) self-organising feature mapping techniques. Systematic vari ations in lipoprotein profiles can be substantially visualised through the use of KNN and GTM. The relationship between the sample positions in the Ko honen plot was visualised by surface plots of the corresponding VLDL and HD L cholesterol and VLDL triglyceride contents. The GTM maps of the VLDL and HDL fractions were used to investigate the individual properties of selecte d samples. A large number of the cancer patients were found clustered in th e VLDL GTM map, and GTM map positions of samples in relation to CHD, diabet es and renal failure could be found. Although the study group here consider ed is heterogeneous in respect to age, sex, type of disease and medications within each defined class, classification of VLDL and HDL data with probab ilistic neural network (PNN) was quite successful with respect to the group ings: cancer, CHD, volunteers and other (comprising patients with other dis eases). Statistics based on 15 independent sets of PNN calculations gave tr ue positive fractions usually higher than 0.83 and false positive fractions lower than 0.088. Attempts to use the corresponding LDL data and four clas ses were uniformly poor although some classifications (e.g, volunteer versu s CHD) were easily performed.