Multivariate modeling and prediction of breast cancer prognostic factors using MR metabolomics.

Axillary lymph node status together with estrogen and progesterone receptor status are important prognostic factors in breast cancer. In this study, the potential of using MR metabolomics for prediction of these prognostic factors was evaluated. Biopsies from breast cancer patients (n = 160) were excised during surgery and analyzed by high resolution magic angle spinning MR spectroscopy (HR MAS MRS).

Classification of wild and farmed salmon using bayesian belief networks and gas chromatography-derived fatty acid distributions.

In this study, we present the use of Bayesian Belief Networks (BBN) for the classification of wild versus farmed Atlantic salmon (Salmo salar L.). Using a data set of 131 salmon samples from several geographical origins and the gas chromatography-derived distributions of 12 fatty acids (FAs), a Bayesian Belief Network was constructed, ultimately using only the three most important FAs (16:1n-7, 18:2n-6, and 22:5n-3).

Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI.

Purpose: To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5-year survival in patients with locally advanced breast cancer.

Materials And Methods: DCE-MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC.

Characterization of bright tobaccos by multivariate analysis of 13C CPMAS NMR spectra.

Univariate and multivariate statistics were applied to characterize cured bright tobacco samples on the basis of their 13C CPMAS NMR spectra and leaf constituent analysis. NMR spectra were obtained for 55 samples selected from a set of 134 samples of graded bright tobacco leaves from crop year 1999. Historical leaf constituent analyses were available for total alkaloids, reducing sugars, total nitrogen, and insoluble ash.

Combining clinical assessment scores and in vivo MR spectroscopy neurometabolites in very low birth weight adolescents.

Objective: Very low birth weight (VLBW) survivors are at increased risk of neurological impairments that may persist into adolescence and adulthood. The aims of this study were to identify the most important clinical assessments that characterize differences between VLBW and control adolescents, and to look at the relationship between clinical assessments and the metabolites in in vivo MR spectra.

Methods: At 14-15 years of age, 54 VLBW survivors and 64 term controls were examined clinically.

(13)C NMR pattern recognition techniques for the classification of Atlantic salmon (Salmo salar L.) according to their wild, farmed, and geographical origin.

(13)C nuclear magnetic resonance (NMR) in combination with multivariate data analysis was used to (1) discriminate between farmed and wild Atlantic salmon ( Salmo salar L.), (2) discriminate between different geographical origins, and (3) verify the origin of market samples. Muscle lipids from 195 Atlantic salmon of known origin (wild and farmed salmon from Norway, Scotland, Canada, Iceland, Ireland, the Faroes, and Tasmania) in addition to market samples were analyzed by (13)C NMR spectroscopy and multivariate analysis.

Simple dual tasking recruits prefrontal cortices in chronic severe traumatic brain injury patients, but not in controls.

The ability to carry out two tasks simultaneously, dual tasking, is specifically impaired after traumatic brain injury (TBI). The aim of the present study was to investigate the neuronal correlates to this increased dual cost in chronic severe TBI patients (n = 10) compared to healthy controls (n = 11) using functional magnetic resonance imaging (fMRI) at 3 Tesla (T). The tasks were a visual search and a simple two-fingers button press motor task.

Water distribution in brine salted cod (Gadus morhua) and salmon (Salmo salar): a low-field 1H NMR study.

Low-field (LF) (1)H NMR T 2 relaxation measurements were used to study changes in water distribution in lean (Atlantic cod) and fatty (Atlantic salmon) fish during salting in 15% NaCl and 25% NaCl brines. The NMR data were treated by PCA, continuous distribution analysis, and biexponential fitting and compared with physicochemical data. Two main water pools were observed in unsalted fish, T 21, with relaxation times in the range 20-100 ms, and T 22, with relaxation times in the range 100-300 ms.

Classification of gilthead sea bream (Sparus aurata) from 1H NMR lipid profiling combined with principal component and linear discriminant analysis.

The combination of (1)H NMR fingerprinting of lipids from gilthead sea bream (Sparus aurata) with nonsupervised and supervised multivariate analysis was applied to differentiate wild and farmed fish and to classify farmed specimen according to their areas of production belonging to the Mediterranean basin. Principal component analysis (PCA) applied on processed (1)H NMR profiles made a clear distinction between wild and farmed samples. Linear discriminant analysis (LDA) allowed classification of samples according to the geographic origin, as well as for the wild and farmed status using both PCA scores and NMR data as variables.

High-resolution (13)C nuclear magnetic resonance spectroscopy pattern recognition of fish oil capsules.

13C NMR (nuclear magnetic resonance) spectroscopy, in conjunction with multivariate analysis of commercial fish oil-related health food products, have been used to provide discrimination concerning the nature, composition, refinement, and/or adulteration or authentication of the products. Supervised (probabilistic neural networks, PNN) and unsupervised (principal component analysis, PCA; Kohonen neural networks; generative topographic mapping, GTM) pattern recognition techniques were used to visualize and classify samples. Simple PCA score plots demonstrated excellent, but not totally unambiguous, class distinctions, whereas Kohonen and GTM visualization provided better results.

MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status.

The purpose of the study was to evaluate the use of metabolic phenotype, described by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS), as a tool for prediction of histological grade, hormone status, and axillary lymphatic spread in breast cancer patients. Biopsies from breast cancer (n = 91) and adjacent non-involved tissue (n = 48) were excised from patients (n = 77) during surgery. HR MAS MR spectra of intact samples were acquired.

Bioactive compounds in cod (Gadus morhua) products and suitability of 1H NMR metabolite profiling for classification of the products using multivariate data analyses.

This work investigates the suitability of (1)H NMR spectroscopy to identify the fate of some bioactive compounds in seafood submitted to several processing conditions and examines the possibility of using (1)H NMR spectroscopy profiling to classify such products. Perchloric acid extracts of cod white muscle from newly killed and (i) unprocessed, (ii) boiled, and (iii) fried fillets and from (iv) frozen fillets, (v) the frozen fillets after thawing, and (vi) their drip loss and from (vii) rehydrated cod klippfish (n = 5) were analyzed by 500 MHz (1)H NMR spectroscopy. It was possible to identify taurine, betaine, anserine, creatine, and trimethylamine oxide (TMAO) in all extracts examined, and frozen fish was recognizable by the presence of dimethylamine (DMA).