Ultra high performance supercritical fluid chromatography coupled with tandem mass spectrometry for screening of doping agents. II: Analysis of biological samples.

The potential and applicability of UHPSFC-MS/MS for anti-doping screening in urine samples were tested for the first time. For this purpose, a group of 110 doping agents with diverse physicochemical properties was analyzed using two separation techniques, namely UHPLC-MS/MS and UHPSFC-MS/MS in both ESI+ and ESI- modes. The two approaches were compared in terms of selectivity, sensitivity, linearity and matrix effects. As expected, very diverse retentions and selectivities were obtained in UHPLC and UHPSFC, proving a good complementarity of these analytical strategies. In both conditions, acceptable peak shapes and MS detection capabilities were obtained within 7min analysis time, enabling the application of these two methods for screening purposes. Method sensitivity was found comparable for 46% of tested compounds, while higher sensitivity was observed for 21% of tested compounds in UHPLC-MS/MS and for 32% in UHPSFC-MS/MS. The latter demonstrated a lower susceptibility to matrix effects, which were mostly observed as signal suppression. In the case of UHPLC-MS/MS, more serious matrix effects were observed, leading typically to signal enhancement and the matrix effect was also concentration dependent, i.e., more significant matrix effects occurred at the lowest concentrations.

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.

In vivo enzymatic activity of acetylCoA synthetase in skeletal muscle revealed by 13C turnover from hyperpolarized [1-13C]acetate to [1-13C]acetylcarnitine

BACKGROUND: Acetate metabolism in skeletal muscle is regulated by acetylCoA synthetase (ACS). The main function of ACS is to provide cells with acetylCoA, a key molecule for numerous metabolic pathways including fatty acid and cholesterol synthesis and the Krebs cycle. METHODS: Hyperpolarized [1-(13)C]acetate prepared via dissolution dynamic nuclear polarization was injected intravenously at different concentrations into rats. The (13)C magnetic resonance signals of [1-(13)C]acetate and [1-(13)C]acetylcarnitine were recorded in vivo for 1min. The kinetic rate constants related to the transformation of acetate into acetylcarnitine were deduced from the 3s time resolution measurements using two approaches, either mathematical modeling or relative metabolite ratios. RESULTS: Although separated by two biochemical transformations, a kinetic analysis of the (13)C label flow from [1-(13)C]acetate to [1-(13)C]acetylcarnitine led to a unique determination of the activity of ACS. The in vivo Michaelis constants for ACS were KM=0.35±0.13mM and Vmax=0.199±0.031μmol/g/min. CONCLUSIONS: The conversion rates from hyperpolarized acetate into acetylcarnitine were quantified in vivo and, although separated by two enzymatic reactions, these rates uniquely defined the activity of ACS. The conversion rates associated with ACS were obtained using two analytical approaches, both methods yielding similar results. GENERAL SIGNIFICANCE: This study demonstrates the feasibility of directly measuring ACS activity in vivo and, since the activity of ACS can be affected by various pathological states such as cancer or diabetes, the proposed method could be used to non-invasively probe metabolic signatures of ACS in diseased tissue.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Potential approaches for more successful dendritic cell-based immunotherapy.

INTRODUCTION: Dendritic cells (DCs) are the most important antigen-presenting cell population for activating antitumor T-cell responses; therefore, they offer a unique opportunity for specific targeting of tumors. AREAS COVERED: We will discuss the critical factors for the enhancement of DC vaccine efficacy: different DC subsets, types of in vitro DC manufacturing protocol, types of tumor antigen to be loaded and finally different adjuvants for activating them. We will cover potential combinatorial strategies with immunomodulatory therapies: depleting T-regulatory (Treg) cells, blocking VEGF and blocking inhibitory signals. Furthermore, recommendations to incorporate these criteria into DC-based tumor immunotherapy will be suggested. EXPERT OPINION: Monocyte-derived DCs are the most widely used DC subset in the clinic, whereas Langerhans cells and plasmacytoid DCs are two emerging DC subsets that are highly effective in eliciting cytotoxic T lymphocyte responses. Depending on the type of tumor antigens selected for loading DCs, it is important to optimize a protocol that will generate highly potent DCs. The future aim of DC-based immunotherapy is to combine it with one or more immunomodulatory therapies, for example, Treg cell depletion, VEGF blockage and T-cell checkpoint blockage, to elicit the most optimal antitumor immunity to induce long-term remission or even cure cancer patients.