21Ne and 131Xe NMR study of electric field gradients and multinuclear NMR study of the composition of a ferroelectric liquid crystal.

This study has two goals. First, the electric field gradient (EFG) present in the liquid-crystalline phases of ferroelectric FELIX-R&D is determined using NMR spectroscopy of noble gases 21Ne and 131Xe. The 21Ne and 131Xe NMR spectra were recorded over a temperature range, which covers all the mesophases of FELIX-R&D: nematic N*, smectic A, and smectic C*. The spin quantum number of both 21Ne and 131Xe is 3/2. Their electric quadrupole moment interacts with the EFG at the nuclear site, which in liquid-crystalline phases results in the NMR spectra of the triplet structure, instead of a singlet detectable in the isotropic phase. The total EFG experienced by the noble gas nuclei consists of two contributions; one arises from the quadrupole moments of the liquid crystal molecules (external contribution) and the other one from the deformation of the electron distribution of the atoms (deformational contribution). The total EFGs determined from the 131Xe and 21Ne quadrupole splittings are very similar in the nematic and smectic A phases but differ in the smectic C* phase, being about twice larger in the 21Ne case which stems from the larger deformation of the xenon electron cloud than that of neon. For the first time, EFG was determined also in the smectic C* phase applying noble gas NMR spectroscopy. Second, the structure of molecules which, as a mixture, compose the used ferroelectric liquid crystal, FELIX-R&D, is determined by applying a number of various NMR methods and sophisticated spectral analysis. In this part, NMR spectra were recorded from FELIX-R&D/CDCl3 solution. The NMR spectral analysis was divided into four subsystems with over 13 000 000 nonzero intensity transitions. It appeared that FELIX-R&D is composed of three phenyl pyrimidine derivatives and a chiral dopant with fluorine in the asymmetric carbon atom.

Firefly luciferase inhibitor-conjugated peptide quenches bioluminescence: a versatile tool for real time monitoring cellular uptake of biomolecules.

In this paper, novel firefly luciferase-specific inhibitor compounds (FLICs) are evaluated as potential tools for cellular trafficking of transporter conjugates. As a proof-of-concept, we designed FLICs that were suitable for solid phase peptide synthesis and could be covalently conjugated to peptides via an amide bond. The spacer between inhibitor and peptide was optimized to gain efficient inhibition of recombinant firefly luciferase (FLuc) without compromising the activity of the model peptides. The hypothesis of using FLICs as tools for cellular trafficking studies was ensured with U87Fluc glioblastoma cells expressing firefly luciferase. Results show that cell penetrating peptide (penetratin) FLIC conjugate 9 inhibited FLuc penetrated cells efficiently (IC50 = 1.6 µM) and inhibited bioluminescence, without affecting the viability of the cells. Based on these results, peptide-FLIC conjugates can be used for the analysis of cellular uptake of biomolecules in a new way that can at the same time overcome some downsides seen with other methods. Thus, FLICs can be considered as versatile tools that broaden the plethora of methods that take advantage of the bioluminescence phenomena.

Comprehensive strategy for proton chemical shift prediction: linear prediction with nonlinear corrections.

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the descriptors are computed from an ensemble of the conformers found by conformational search based on Metropolis Monte Carlo (MMC) simulation; in the 4D model the conformational space was further expanded to the fourth dimension (time) by adding molecular dynamics to the MC conformers. An illustrative case study about the application and interpretation of the 4D prediction for a conformationally flexible structure, scopolamine, is described in detail.

MetIDB: a publicly accessible database of predicted and experimental 1H NMR spectra of flavonoids.

Identification of natural compounds, especially secondary metabolites, has been hampered by the lack of easy to use and accessible reference databases. Nuclear magnetic resonance (NMR) spectroscopy is the most selective technique for identification of unknown metabolites. High quality (1)H NMR (proton nuclear magnetic resonance) spectra combined with elemental composition obtained from mass spectrometry (MS) are essential for the identification process. Here, we present MetIDB, a reference database of experimental and predicted (1)H NMR spectra of 6000 flavonoids. By incorporating the stereochemistry, intramolecular interactions, and solvent effects into the prediction model, chemical shifts and couplings were predicted with great accuracy. A user-friendly web-based interface for MetIDB has been established providing various interfaces to the data and data-mining possibilities. For each compound, additional information is available comprising compound annotation, a (1)H NMR spectrum, 2D and 3D structure with correct stereochemistry, and monoisotopic mass as well as links to other web resources. The combination of chemical formula and (1)H NMR chemical shifts proved to be very efficient in metabolite identification, especially for isobaric compounds. Using this database, the process of flavonoid identification can then be significantly shortened by avoiding repetitive elucidation of already described compounds.

High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis.

AIMS: High-throughput metabolite quantification holds promise for cardiovascular risk assessment. Here, we evaluated whether metabolite quantification by nuclear magnetic resonance (NMR) improves prediction of subclinical atherosclerosis in comparison to conventional lipid testing. METHODS AND RESULTS: Circulating lipids, lipoprotein subclasses, and small molecules were assayed by NMR for 1595 individuals aged 24-39 years from the population-based Cardiovascular Risk in Young Finns Study. Carotid intima-media thickness (IMT), a marker of subclinical atherosclerosis, was measured in 2001 and 2007. Baseline conventional risk factors and systemic metabolites were used to predict 6-year incidence of high IMT (≥ 90 th percentile) or plaque. The best prediction of high intima-media thickness was achieved when total and HDL cholesterol were replaced by NMR-determined LDL cholesterol and medium HDL, docosahexaenoic acid, and tyrosine in prediction models with risk factors from the Framingham risk score. The extended prediction model improved risk stratification beyond established risk factors alone; area under the receiver operating characteristic curve 0.764 vs. 0.737, P =0.02, and net reclassification index 17.6%, P =0.0008. Higher docosahexaenoic acid levels were associated with decreased risk for incident high IMT (odds ratio: 0.74; 95% confidence interval: 0.67-0.98; P = 0.007). Tyrosine (1.33; 1.10-1.60; P = 0.003) and glutamine (1.38; 1.13-1.68; P = 0.001) levels were associated with 6-year incident high IMT independent of lipid measures. Furthermore, these amino acids were cross-sectionally associated with carotid IMT and the presence of angiographically ascertained coronary artery disease in independent populations. CONCLUSION: High-throughput metabolite quantification, with new systemic biomarkers, improved risk stratification for subclinical atherosclerosis in comparison to conventional lipids and could potentially be useful for early cardiovascular risk assessment.

¹H-NMR fingerprinting of Vaccinium vitis-idaea flavonol glycosides.

INTRODUCTION: The fruits of Vaccinium vitis-idaea L. are a valuable source of biologically active flavonoid derivatives. For studies focused on the purification of its quercetin glycosides (QGs) and related glycosides from plants and for the purpose of biological studies, the availability of numeric datasets from computer-assisted ¹H iterative full spin analysis (HiFSA), that is, ¹H-NMR fingerprinting, can replace and assist the repetitive and tedious two-dimensional NMR identification protocol required for both known and new compounds, respectively. OBJECTIVE: To fully interpret the complex ¹H-NMR fingerprints of eight QGs obtained from the berries of V. vitis-idaea and provide complete and unambiguous signal assignments. METHODS: Vaccinium vitis-idaea QGs were purified in a single run by long-bed gel permeation chromatography and identified by comparison with commercially available compounds using LC-MS combining ion-trap and time-of-flight detection and one- or two-dimensional NMR. The HiFSA analysis yielded full sets of ¹H chemical shifts and proton-proton coupling constants, allowing for field-independent spectral simulation. RESULTS: Signal assignments were achieved for the reference standards and the QGs that dominated in purified fractions. However, even mixtures of two to three QGs could be fitted using the HiFSA approach. In the case of the overlapped sugar resonances, the initial fitting of the ¹H spectra of reference compounds, together with values extracted from the two-dimensional NMR data and literature data, assisted in the process. CONCLUSION: The HiFSA method revealed for the first time the presence of Q-3-O-ß-glucopyranoside and Q-3-O-ß-glucuronopyranoside in the berries of V. vitis-idaea, and unambiguously confirmed the structures of Q-3-O-[4″-(3-hydroxy-3-methylglutaroyl)]-α-rhamnopyranoside, Q-3-O-α-rhamnopyranoside, Q-3-O-ß-galactopyranoside, Q-3-O-α-arabinofuranoside, Q-3-O-ß-xylopyranoside and Q-3-O-α-arabinopyranoside.

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study).

Type 1 diabetic patients with varying severity of kidney disease were investigated to create multimetabolite models of the disease process. Urinary albumin excretion rate was measured for 3358 patients with type 1 diabetes. Prospective records were available for 1051 patients, of whom 163 showed progression of albuminuria (8.3-year follow-up), and 162 were selected as stable controls. At baseline, serum lipids, lipoprotein subclasses, and low-molecular weight metabolites were quantified by NMR spectroscopy (325 samples). The data were analyzed by the self-organizing map. In cross-sectional analyses, patients with no complications had low serum lipids, less inflammation, and better glycemic control, whereas patients with advanced kidney disease had high serum cystatin-C and sphingomyelin. These phenotype extremes shared low unsaturated fatty acids (UFAs) and phospholipids. Prospectively, progressive albuminuria was associated with high UFAs, phospholipids, and IDL and LDL lipids. Progression at longer duration was associated with high HDL lipids, whereas earlier progression was associated with poor glycemic control, increased saturated fatty acids (SFAs), and inflammation. Diabetic kidney disease consists of diverse metabolic phenotypes: UFAs, phospholipids, IDL, and LDL may be important in the subclinical phase, high SFAs and low HDL suggest accelerated progression, and the sphingolipid pathway in advanced kidney injury deserves further research.

Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction.

While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein (1)H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6-17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for (1)Hα, (1)HN, (13)Cα, (13)Cß, (13)CO and backbone (15)N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspot.

Molecular dynamics simulations for human CAR inverse agonists.

Constitutive androstane receptor (CAR), along with pregnane x receptor (PXR), is an important metabolic sensor in the hepatocytes. Like all other nuclear receptors (NRs), CAR works in concert with coregulator proteins, coactivators, and corepressors which bind to the NRs. The main basis for the receptor to distinguish between coactivators and corepressors is the position of the C-terminal helix 12 (H12), which is determined by the bound NR ligand. CAR, having constitutive activity, can be repressed or further activated by its ligands. Crystal structure of human CAR bound to an agonist and a coactivator peptide is available, but no structural information on an inverse agonist-bound human CAR and a corepressor exists. In our previous molecular dynamics (MD) studies, no corepressor peptide was included. Therefore, probably due to the strong interactions which keep the relatively short H12 of CAR in the active position, the structural changes elicited by inverse agonists were very subtle, and H12 of CAR seemed to more or less retain its active conformation. Here, we have run a series of MD simulations to study the movement of H12 in the presence of both activating and repressing ligands as well as a corepressor peptide. The presence of the corepressor on the coregulator surface of CAR induced a clear shift of H12 of the inverse agonists-bound CAR. In general, H12 moved toward H10 and not away from the ligand binding domain, as seen in some other NRs. However, H12 of CAR is short enough that this movement seems to be adequate to accommodate the binding of the corepressor.

(1) H NMR spectral analysis and conformational behavior of n-alkanes in different chemical environments.

Alkyl chains are common structural units, for example in lipids, and their (1) H NMR spectral parameters offer valuable information about their conformational behavior in solvent environment. Even the spectra of short n-alkanes are complex, which is obviously a reason why their accurate spectral analyses have not been reported before. The present study reports the quantum mechanical analysis of (1) H NMR spectra of n-butane, n-pentane, n-hexane, and n-heptane. The spectral parameters were used to characterize the conformational behavior of n-alkanes. The temperature dependence analysis of coupling constants suggests that the enthalpy difference between the gauche (g) and trans (t) conformations (ΔH(g) ) of n-butane in chloroform is 2.55-2.85 kJ mol(-1) . The difference between the trans-gauche (tg) and all-trans (tt) conformers of n-pentane (ΔH(tg) ) seems to be 0.1-0.2 kJ mol(-1) higher. The coupling constant information shows that the t(n) conformations become more favored with longer chains, although not only for energetic reasons but also partly because the g(+) g(-) arrangements become sterically unfavorable, which decreases the number of favorable g(n) -type conformations. The analysis of the (1) H NMR spectra of n-pentane and n-hexane in solvents representing different chemical environments indicates that polar and spherical dimethyl sulfoxide favors clearly the g conformations, whereas n-hexane-d(14) favors slightly the extended t(n) conformation. In addition to the intrinsic scientific importance for NMR spectral parameter prediction and molecular modeling in solution, the results provide some insights to behavior of hydrocarbon chains and their spectra in different chemical environments.

Synthesis and biological evaluation of phenolic 4,5-dihydroisoxazoles and 3-hydroxy ketones as estrogen receptor alpha and beta agonists.

In this work, 52 diphenyl-4,5-dihydroisoxazoles and -3-hydroxy ketones were prepared and their estrogen receptor alpha (ERalpha) and estrogen receptor beta (ERbeta) activities were explored in order to systematize and maximize their biological activity. The biological activity was firstly screened by using ERE reporter assay to find out how aromatic hydroxylation and methylation of the chiral centers of the compounds affect the ability of ER to mediate biological responses. For selected 19 compounds, the relative binding affinities (RBA, relative to 3,17beta-estradiol) and ability to induce transcription of primary E2 target gene pS2 in human MCF-7 breast cancer cells were determined. In the reporter assay, many compounds showed even stronger activity than E2 and some of them showed RBA larger than 1%. The highest RBAs were determined for the enantiomers of 1-hydroxy-6-(4-hydroxy-phenyl)-1-phenyl-hexan-3-one (50a and 50b). Isomer 50a showed high binding affinity both to ERalpha (with RBA approximately 200%) and ERbeta (with RBA approximately 60%), while the RBAs of 50b were ca. 40% of those. Some of the other compounds (with RBA approximately 1-16%) showed also notable ERalpha binding selectivity. When four most promising ligands (50a, 50b, 45a, and 45b) were studied with respect to their ability to induce the transcription of primary E2 target gene pS2, the compounds acted as agonists or partial agonists. Computer modeling was used to predict receptor binding conformations and to rationalize the RBA differences of the compounds.

13C isotope effects on 1H chemical shifts: NMR spectral analysis of 13C-labelled D-glucose and some 13C-labelled amino acids.

The one- and two-bond (13)C isotope shifts, typically -1.5 to -2.5 ppb and -0.7 ppb respectively, in non-cyclic aliphatic systems and up to -4.4 ppb and -1.0 ppb in glucose cause effects that need to be taken into account in the adaptive NMR spectral library-based quantification of the isotopomer mixtures. In this work, NMR spectral analyses of some (13)C-labelled amino acids, D-glucose and other small compounds were performed in order to obtain rules for prediction of the (13)C isotope effects on (1)H chemical shifts. It is proposed that using the additivity rules, the isotope effects can be predicted with a sufficient accuracy for amino acid isotopomer applications. For glucose the effects were found strongly non-additive. The complete spectral analysis of fully (13)C-labelled D-glucose made it also possible to assign the exocyclic proton signals of the glucose.

Screening of binding activity of Streptococcus pneumoniae, Streptococcus agalactiae and Streptococcus suis to berries and juices.

Antiadhesion therapy is a promising approach to the fight against pathogens. Antibiotic resistance and the lack of effective vaccines have increased the search for new methods to prevent infectious diseases. Previous studies have shown the antiadhesion activity of juice from cultivated cranberries (Vaccinium macrocarpon Ait.) against bacteria, especially E. coli. In this study, the binding of two streptococcal strains, Streptococcus pneumoniae and Streptococcus agalactiae, to molecular size fractions (FI, FII and FIII, <10 kDa, 10-100 kDa, and >100 kDa, respectively) of berries and berry and fruit juices from 12 plant species were studied using a microtiter well assay. For Streptococcus suis a hemagglutination inhibition assay was used. In general, binding activity was detected especially to wild cranberry (Vaccinium oxycoccos L.) and to other Vaccinium species. S. pneumoniae cells bound most to cranberry juice fraction FI and S. agalactiae cells to cranberry fraction FIII. Hemagglutination induced by S. suis was most effectively inhibited by cranberry fraction FII. NMR spectra of some characteristic active and non-active fractions were also measured. They indicate that fractions FII and FIII contained proanthocyanidins and/or other phenolic compounds. The results suggest Vaccinium berries as possible sources of antiadhesives against bacterial infections.

4D prediction of protein (1)H chemical shifts.

A 4D approach for protein (1)H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6-7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Halpha and HN shifts, respectively. However, for individual proteins the RMS errors were 0.17-0.34 and 0.34-0.65 ppm for the Halpha and HN shifts, respectively. X-ray structures gave better predictions than the corresponding NMR structures, indicating that chemical shifts contain invaluable information about local structures. The (1)H chemical shift prediction tool 4DSPOT is available from http://www.uku.fi/kemia/4dspot .

High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism.

A high-throughput proton (1H) nuclear magnetic resonance (NMR) metabonomics approach is introduced to characterise systemic metabolic phenotypes. The methodology combines two molecular windows that contain the majority of the metabolic information available by 1H NMR from native serum, e.g. serum lipids, lipoprotein subclasses as well as various low-molecular-weight metabolites. The experimentation is robotics-controlled and fully automated with a capacity of about 150-180 samples in 24 h. To the best of our knowledge, the presented set-up is unique in the sense of experimental high-throughput, cost-effectiveness, and automated multi-metabolic data analyses. As an example, we demonstrate that the NMR data as such reveal associations between systemic metabolic phenotypes and the metabolic syndrome (n = 4407). The high-throughput of up to 50,000 serum samples per year is also paving the way for this technology in large-scale clinical and epidemiological studies. In contradiction to single 'biomarkers', the application of this holistic NMR approach and the integrated computational methods provides a data-driven systems biology approach to biomedical research.

NMR and UPLC-qTOF-MS/MS characterisation of novel phenylethanol derivatives of phenylpropanoid glucosides from the leaves of strawberry (Fragaria x ananassa cv. Jonsok).

INTRODUCTION: Strawberry (Fragaria x ananassa) is rich in polyphenols, particularly anthocyanins, flavonols, condensed tannins and ellagic tannins. In addition to the fruits, the leaves of strawberry also contain a wide range of phenolic compound classes, but have not been investigated to the same extent as the fruit. OBJECTIVE: To characterise a metabolite group present in the leaves of strawberry, that was not amenable for identification based on earlier information available in the literature. METHODOLOGY: Methanolic extracts of strawberry leaves were analysed by UPLC-qTOF-MS/MS and iterative quantum mechanical NMR spectral analysis. RESULTS: The structures of phenylethanol derivatives of phenylpropanoid glucosides Eutigoside A ( F4) and its two isomeric forms 2-(4-hydroxyphenyl)ethyl-[6-O-(Z)-coumaroyl]-beta-D-glucopyranoside (F6) and 4-(2-hydroxyethyl)phenyl-[6-O-(E)-coumaroyl]-beta-D-glucopyranoside (F1) were resolved by NMR and UPLC-qTOF-MS/MS. In addition, two other derivatives of phenylpropanoid glucosides similar to Eutigoside A but possessing different phenolic acid moieties, namely Grayanoside A ( F5) and 2-(4-hydroxyphenyl)ethyl-[6-O-(E)-caffeoyl]-beta-D-glucopyranoside (F14), were similarly identified. Also, accurate characteristic coupling constants for the subunits are reported and their usefulness in structural analysis is highlighted. CONCLUSION: Chemical analysis of the leaves of strawberry (Fragaria x ananassa cv. Jonsok) resulted in the identification of a compound class, phenylethanol derivatives of phenylpropanoid glycosides, not previously found in strawberry.

A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer's disease.

A three-molecular-window approach for (1)H NMR spectroscopy of serum is presented to obtain specific molecular data on lipoproteins, various low-molecular-weight metabolites, and individual lipid molecules together with their degree of (poly)(un)saturation. The multiple data were analysed with self-organising maps, illustrating the strength of the approach as a holistic metabonomics framework in solely data-driven metabolic phenotyping. We studied 180 serum samples of which 30% were related to mild cognitive impairment (MCI), a neuropsychological diagnosis with severely increased risk for Alzheimer's disease (AD). The results underline the association between MCI and the metabolic syndrome (MetS). Additionally, the low relativeamount of omega-3 fatty acids appears more indicative of MCI than low serum omega-3 or polyunsaturated fatty acid concentration as such. The analyses also feature the role of elevated glycoproteins in the risk for AD, supporting the view that coexistence of inflammation and the MetS forms a high risk condition for cognitive decline.

Synthesis and evaluation of estrogen agonism of diaryl 4,5-dihydroisoxazoles, 3-hydroxyketones, 3-methoxyketones, and 1,3-diketones: a compound set forming a 4D molecular library.

In this paper, the preparation and systematic evaluation of estrogen receptor alpha (ER alpha) and estrogen receptor beta (ER beta) activities of some diaryl-1,3-diones and their synthetic intermediates, diaryl-4,5-dihydroisoxazoles, diaryl-3-hydroxyketones, diaryl-3-methoxyketones, and diaryl-2-(dimethyl-lambda 4-sulfanylidene)-1,3-diones, is described. The set of 72 compounds constitutes a general schematic structure aryl1-linker1-spacer-linker2-aryl2, where the linker1-spacer-linker2 length varies between 4 and 8 carbons. The set of compounds was applied here to map and explore the active sites of subtypes ER alpha and ER beta. The highest activities were obtained with dihydroisoxazole and hydroxyketone spacers, but even the most flexible diones with unsubstituted aryl groups showed some agonism. Most compounds were found to be ER alpha selective or to activate both receptors, but in some cases we saw also clearly stronger ER beta activation.

Spectral analysis of 1H coupled 13C spectra of the amino acids: adaptive spectral library of amino acid 13C isotopomers and positional fractional 13C enrichments.

The natural abundance 1H-coupled 13C NMR spectra of all proteogenic amino acids were measured in D2O at pH* 1. The accurate 1H,13C spin-spin coupling constants were analyzed using total-line-shape fitting. The obtained spectral parameters can be used to establish a spectral library of amino acid 13C isotopomers. The adaptive spectral library principle is introduced and discussed in this article. The simulated spectra can be applied to quantification of 13C isotopomer mixtures of amino acids and, thus, for exploring metabolic pathways. Also a protocol for amino acid 13C isotopomer metabolomic profiling in 13C labeled glucose feeding experiments is outlined. The approach is suggested to give invaluable information about positional fractional 13C enrichments, which are not easily available by any other method.

The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependent.

Proton NMR spectroscopy as a means to quantify lipoprotein subclasses has received wide clinical interest. The experimental part is a fast routine procedure that contrasts favourably to other lipoprotein measurement protocols. The difficulties in using (1)H NMR, however, are in uncovering the subclass specific information from the overlapping data. The NMR-based quantification has been evaluated only in relation to biochemical measures, thereby leaving the inherent capability of NMR rather vague due to biological variation and diversity among the biochemical experiments. Here we will assess the use of (1)H NMR spectroscopy of plasma per se. This necessitates data for which the inherent parameters, namely the shapes and areas of the (1)H NMR signals of the subclasses are available. This was achieved through isolation and (1)H NMR experiments of 11 subclasses--VLDL1, VLDL2, IDL, LDL1, LDL2, LDL3, HDL(2b), HDL(2a), HDL(3a), HDL(3b) and HDL(3c)--and the subsequent modelling of the spectra. The subclass models were used to simulate biochemically representative sets of spectra with known subclass concentrations. The spectral analyses revealed 10-fold differences in the quantification accuracy of different subclasses by (1)H NMR. This finding has critical significance since the usage of (1)H NMR methodology in the clinical arena is rapidly increasing.