For the analysis of the spectra of complex biofluids, preprocessing methods play a crucial role in rendering the subsequent data analyses more robust and accurate. Normalization is a preprocessing method, which accounts for different dilutions of samples by scaling the spectra to the same virtual overall concentration. In the field of 1H NMR metabonomics integral normalization, which scales spectra to the same total integral, is the de facto standard. In this work, it is shown that integral normalization is a suboptimal method for normalizing spectra from metabonomic studies. Especially strong metabonomic changes, evident as massive amounts of single metabolites in samples, significantly hamper the integral normalization resulting in incorrectly scaled spectra. The probabilistic quotient normalization is introduced in this work. This method is based on the calculation of a most probable dilution factor by looking at the distribution of the quotients of the amplitudes of a test spectrum by those of a reference spectrum. Simulated spectra, spectra of urine samples from a metabonomic study with cyclosporin-A as the active compound, and spectra of more than 4000 samples of control animals demonstrate that the probabilistic quotient normalization is by far more robust and more accurate than the widespread integral normalization and vector length normalization.

Bose-Einstein condensation has been achieved in a magnetic surface microtrap with 4 x 10(5) (87)Rb atoms. The strongly anisotropic trapping potential is generated by a microstructure which consists of microfabricated linear copper conductor of widths ranging from 3 to 30 microm. After loading a high number of atoms from a pulsed thermal source directly into a magneto-optical trap the magnetically stored atoms are transferred into the microtrap by adiabatic transformation of the trapping potential. In the microtrap the atoms are cooled to condensation using forced rf-evaporation. The complete in vacuo trap design is compatible with ultrahigh vacuum below 2 x 10(-11) mbar.

Metabonomic analysis of biofluids and tissues utilizing high-resolution NMR spectroscopy and chemometric techniques has proven valuable in characterizing the biochemical response to toxicity for many xenobiotics. To assess the analytical reproducibility of metabonomic protocols, sample preparation and NMR data acquisition were performed at two sites (one using a 500 MHz and the other using a 600 MHz system) using two identical (split) sets of urine samples from an 8-day acute study of hydrazine toxicity in the rat. Despite the difference in spectrometer operating frequency, both datasets were extremely similar when analyzed using principal components analysis (PCA) and gave near-identical descriptions of the metabolic responses to hydrazine treatment. The main consistent difference between the datasets was related to the efficiency of water resonance suppression in the spectra. In a 4-PC model of both datasets combined, describing all systematic dose- and time-related variation (88% of the total variation), differences between the two datasets accounted for only 3% of the total modeled variance compared to ca. 15% for normal physiological (pre-dose) variation. Furthermore, <3% of spectra displayed distinct inter-site differences, and these were clearly identified as outliers in their respective dose-group PCA models. No samples produced clear outliers in both datasets, suggesting that the outliers observed did not reflect an unusual sample composition, but rather sporadic differences in sample preparation leading to, for example, very dilute samples. Estimations of the relative concentrations of citrate, hippurate, and taurine were in >95% correlation (r(2)) between sites, with an analytical error comparable to normal physiological variation in concentration (4-8%). The excellent analytical reproducibility and robustness of metabonomic techniques demonstrated here are highly competitive compared to the best proteomic analyses and are in significant contrast to genomic microarray platforms, both of which are complementary techniques for predictive and mechanistic toxicology. These results have implications for the quantitative interpretation of metabonomic data, and the establishment of quality control criteria for both regulatory agencies and for integrating data obtained at different sites.

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A new triple-resonance (TXI) (1H, 13C, 15N) high-resolution nuclear magnetic resonance (NMR) capillary probe with 2.5-microL NMR-active sample volume (V(obs)) was built and tested for applications with mass- and volume-limited samples and for coupling of microbore liquid chromatography to NMR. This is the first microliter probe with optimized coil geometry for use with individual capillary tubes with an outer diameter of 1 mm. The 90 degree pulse lengths of the 1-mm microliter probe were below 2 micros for proton, below 8 micros for carbon, and below 20 micros for nitrogen, and a spectral line width at signal half-height below 1 Hz was obtained. Compared to a conventional 5-mm probe, the new 600-MHz 1-mm TXI microliter probe with z-gradient shows an increase in mass sensitivity by a factor of 5, corresponding to a 25-fold reduction in measuring time. The consumption of costly deuterated solvent is reduced by at least 2 orders of magnitude. The 1-mm TXI microliter probe with z-gradient allows the measurement of one-dimensional 1H NMR and two-dimensional heteronuclear NMR spectra with a few nanomoles (micrograms) of compound with high sensitivity, speed, and quality. This is a breakthrough for discrete sample NMR spectroscopy with paramount importance for structure elucidation in natural compound chemistry and metabolic research. It offers also advantages for linking chromatographic methods to NMR in a nindustrial environment. Capillary tube NMR may find new applications in areas where high sample throughput is essential, e.g., in the quality control of large sample arrays from parallel chemistry, screening, and compound depositories. It has the potential to increase the sample throughput by 1 order of magnitude or more if new hardware for fast sample handling and exchange becomes available.

A 24-year-old man known to consume illegal drugs was found dead in his apartment. A reclosable plastic zipper bag containing several hundred milligrams of a brown powder was found close to the dead body and the first assumption of the investigators was death due to heroin intoxication. Therefore, a legal autopsy was ordered. The following toxicological analysis revealed ocfentanil in urine and in the brown powder. Four different approaches for the determination of the ocfentanil concentrations in peripheral whole blood are described. Enrichment of ocfentanil from the powder was realized. With this reference, it was possible to determine the ocfentanil concentration in the seized powder to be 0.91%. Concentrations of ocfentanil were also determined in the sampled body fluids using the standard addition procedure. In peripheral blood 9.1 µg/L, in heart blood 27.9 µg/L and in urine 480 µg/L were measured. In addition, the antidepressant citalopram, the neuroleptic quetiapine and cannabinoids were found in urine and subsequently quantified in peripheral blood.

Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

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