Automated mass spectrometric analysis of urinary and plasma serotonin

Serotonin emerges as crucial neurotransmitter and hormone in a growing number of different physiologic processes. Besides extensive serotonin production previously noted in patients with metastatic carcinoid tumors, serotonin now is implicated in liver cell regeneration and bone formation. The aim was to develop a rapid, sensitive, and highly selective automated on-line solid-phase extraction method coupled to high-performance liquid chromatography–tandem mass spectrometry (XLC-MS/MS) to quantify low serotonin concentrations in matrices such as platelet-poor plasma and urine. Fifty microliters plasma or 2.5 μL urine equivalent were pre-purified by automated on-line solid-phase extraction, using weak cation exchange. Chromatography of serotonin and its deuterated internal standard was performed with hydrophilic interaction chromatography. Mass spectrometric detection was operated in multiple reaction monitoring mode using a quadrupole tandem mass spectrometer with positive electrospray ionization. Serotonin concentrations were determined in platelet-poor plasma of metastatic carcinoid patients (n = 23) and healthy controls (n = 22). Urinary reference intervals were set by analyzing 24-h urine collections of 120 healthy subjects. Total run-time was 6 min. Intra- and inter-assay analytical variation were <10%. Linearity in the 0–7300 μmol/L calibration range was excellent (R2 > 0.99). Quantification limits were 30 and 0.9 nmol/L in urine and plasma, respectively. Platelet-poor serotonin concentrations in metastatic carcinoid patients were significantly higher than in controls. The urinary reference interval was 10–78 μmol/mol creatinine. Serotonin analysis with sensitive and specific XLC-MS/MS overcomes limitations of conventional HPLC. This enables accurate quantification of serotonin for both routine diagnostic procedures and research in serotonin-related disorders

Is disturbed clearance of apoptotic keratinocytes responsible for UVB-induced inflammatory skin lesions in systemic lupus erythematosus?

Apoptotic cells are thought to play an essential role in the pathogenesis of systemic lupus erythematosus (SLE). We hypothesise that delayed or altered clearance of apoptotic cells after UV irradiation will lead to inflammation in the skin of SLE patients. Fifteen SLE patients and 13 controls were irradiated with two minimal erythemal doses (MEDs) of ultraviolet B light (UVB). Subsequently, skin biopsies were analysed (immuno)histologically, over 10 days, for numbers of apoptotic cells, T cells, macrophages, and deposition of immunoglobulin and complement. Additionally, to compare results with cutaneous lesions of SLE patients, 20 biopsies of lupus erythematosus (LE) skin lesions were analysed morphologically for apoptotic cells and infiltrate. Clearance rate of apoptotic cells after irradiation did not differ between patients and controls. Influx of macrophages in dermal and epidermal layers was significantly increased in patients compared with controls. Five out of 15 patients developed a dermal infiltrate that was associated with increased epidermal influx of T cells and macrophages but not with numbers of apoptotic cells or epidermal deposition of immunoglobulins. Macrophages were ingesting multiple apoptotic bodies. Inflammatory lesions in these patients were localised near accumulations of apoptotic keratinocytes similar as was seen in the majority of LE skin lesions. In vivo clearance rate of apoptotic cells is comparable between SLE patients and controls. However, the presence of inflammatory lesions in the vicinity of apoptotic cells, as observed both in UVB-induced and in LE skin lesions in SLE patients, suggests that these lesions result from an inflammatory clearance of apoptotic cells

Optimization of supply diversity for the self-assembly of simple objects in two and three dimensions

The field of algorithmic self-assembly is concerned with the design and analysis of self-assembly systems from a computational perspective, that is, from the perspective of mathematical problems whose study may give insight into the natural processes through which elementary objects self-assemble into more complex ones. One of the main problems of algorithmic self-assembly is the minimum tile set problem (MTSP), which asks for a collection of types of elementary objects (called tiles) to be found for the self-assembly of an object having a pre-established shape. Such a collection is to be as concise as possible, thus minimizing supply diversity, while satisfying a set of stringent constraints having to do with the termination and other properties of the self-assembly process from its tile types. We present a study of what we think is the first practical approach to MTSP. Our study starts with the introduction of an evolutionary heuristic to tackle MTSP and includes results from extensive experimentation with the heuristic on the self-assembly of simple objects in two and three dimensions. The heuristic we introduce combines classic elements from the field of evolutionary computation with a problem-specific variant of Pareto dominance into a multi-objective approach to MTSP.Comment: Minor typos correcte

Thin-section Computed Tomography findings before and after azithromycin treatment of neutrophilic reversible lung allograft dysfunction

Recently a novel subgroup of bronchiolitis obliterans syndrome (BOS) has been described in patients after lung transplantation with high neutrophil counts in broncho-alveolar lavage and recovery of lung functional decline with azithromycin treatment. We aimed to describe the thin-section computed tomography (CT) findings of these neutrophilic reversible allograft dysfunction (NRAD) patients before and after azithromycin.status: publishe

Detecting the orientation of magnetic fields in galaxy clusters

Clusters of galaxies, filled with hot magnetized plasma, are the largest bound objects in existence and an important touchstone in understanding the formation of structures in our Universe. In such clusters, thermal conduction follows field lines, so magnetic fields strongly shape the cluster's thermal history; that some have not since cooled and collapsed is a mystery. In a seemingly unrelated puzzle, recent observations of Virgo cluster spiral galaxies imply ridges of strong, coherent magnetic fields offset from their centre. Here we demonstrate, using three-dimensional magnetohydrodynamical simulations, that such ridges are easily explained by galaxies sweeping up field lines as they orbit inside the cluster. This magnetic drape is then lit up with cosmic rays from the galaxies' stars, generating coherent polarized emission at the galaxies' leading edges. This immediately presents a technique for probing local orientations and characteristic length scales of cluster magnetic fields. The first application of this technique, mapping the field of the Virgo cluster, gives a startling result: outside a central region, the magnetic field is preferentially oriented radially as predicted by the magnetothermal instability. Our results strongly suggest a mechanism for maintaining some clusters in a 'non-cooling-core' state.Comment: 48 pages, 21 figures, revised version to match published article in Nature Physics, high-resolution version available at http://www.cita.utoronto.ca/~pfrommer/Publications/pfrommer-dursi.pd

A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report

<p>Abstract</p> <p>Background</p> <p>Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21^stcentury. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.</p> <p>Methods</p> <p>The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.</p> <p>Results</p> <p>(1) Feature selection: CAP has a more effective "modelling" focus than DA.</p> <p>(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.</p> <p>Conclusion</p> <p>Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.</p

Constraints on the opacity of spiral disks from near-infrared observations

In this paper I review how near-infrared (NIR) observations can constrain the opacity of spiral disks. Basic considerations show that NIR photometry provides a powerful probe of the optical depths in spiral galaxy disks in the regime of interest, where the optical depth in the V-band is near unity. I review the existing opacity constraints from the analysis of dust lanes in edge-on and face-on galaxies. The ``internal extinction correction" in the NIR-Tully-Fisher relation deserves particular attention as the most powerful constraint on the impact of dust on the total luminosity of spiral galaxies. All observations for luminous spirals point towards an effective, face-on optical depth of tau_V=0.5-1

Attitude toward contraception and abortion among Curaçao women. Ineffective contraception due to limited sexual education?

Background In Curaçao is a high incidence of unintended pregnancies and induced abortions. Most of the induced abortions in Curaçao are on request of the woman and performed by general practitioners. In Curaçao, induced abortion is strictly prohibited, but since 1999 there has been a policy of connivance. We present data on the relevance of economic and socio-cultural factors for the high abortion-rates and the ineffective use of contraception. Methods Structured interviews to investigate knowledge and attitudes toward sexuality, contraception and abortion and reasons for ineffective use of contraceptives among women, visiting general practitioners. Results Of 158 women, 146 (92%) participated and 82% reported that their education on sexuality and about contraception was of good quality. However 'knowledge of reliable contraceptive methods' appeared to be - in almost 50% of the cases - false information, misjudgements or erroneous views on the chance of getting pregnant using coitus interruptus and about the reliability and health effects of oral contraceptive pills. Almost half of the interviewed women had incorrect or no knowledge about reliability of condom use and IUD. 42% of the respondents risked by their behavior an unplanned pregnancy. Most respondents considered abortion as an emergency procedure, not as contraception. Almost two third experienced emotional, physical or social problems after the abortion. Conclusions Respondents had a negative attitude toward reliable contraceptives due to socio-cultural determined ideas about health consequences and limited sexual education. Main economic factors were costs of contraceptive methods, because most health insurances in Curaçao do not cover contraceptives. To improve the effective use of reliable contraceptives, more adequate information should be given, targeting the wrong beliefs and false information. The government should encourage health insurance companies to reimburse contraceptives. Furthermore, improvement of counseling during the abortion procedure is important

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.Comment: Accepted for the Shape in Medical Imaging (ShapeMI) workshop at MICCAI International Conference 202

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure