Consanguinity and rare mutations outside of MCCC genes underlie nonspecific phenotypes of MCCD

Purpose: 3-Methylcrotonyl-CoA carboxylase deficiency (MCCD) is an autosomal recessive disorder of leucine catabolism that has a highly variable clinical phenotype, ranging from acute metabolic acidosis to nonspecific symptoms such as developmental delay, failure to thrive, hemiparesis, muscular hypotonia, and multiple sclerosis. Implementation of newborn screening for MCCD has resulted in broadening the range of phenotypic expression to include asymptomatic adults. The purpose of this study was to identify factors underlying the varying phenotypes of MCCD. Methods: We performed exome sequencing on DNA from 33 cases and 108 healthy controls. We examined these data for associations between either MCC mutational status, genetic ancestry, or consanguinity and the absence or presence/specificity of clinical symptoms in MCCD cases. Results: We determined that individuals with nonspecific clinical phenotypes are highly inbred compared with cases that are asymptomatic and healthy controls. For 5 of these 10 individuals, we discovered a homozygous damaging mutation in a disease gene that is likely to underlie their nonspecific clinical phenotypes previously attributed to MCCD. Conclusion: Our study shows that nonspecific phenotypes attributed to MCCD are associated with consanguinity and are likely not due to mutations in the MCC enzyme but result from rare homozygous mutations in other disease genes

A comprehensive evaluation of colonic mucosal isolates of Sutterella wadsworthensis from inflammatory bowel disease

Peer reviewedPublisher PD

Chemotactic response and adaptation dynamics in Escherichia coli

Adaptation of the chemotaxis sensory pathway of the bacterium Escherichia coli is integral for detecting chemicals over a wide range of background concentrations, ultimately allowing cells to swim towards sources of attractant and away from repellents. Its biochemical mechanism based on methylation and demethylation of chemoreceptors has long been known. Despite the importance of adaptation for cell memory and behavior, the dynamics of adaptation are difficult to reconcile with current models of precise adaptation. Here, we follow time courses of signaling in response to concentration step changes of attractant using in vivo fluorescence resonance energy transfer measurements. Specifically, we use a condensed representation of adaptation time courses for efficient evaluation of different adaptation models. To quantitatively explain the data, we finally develop a dynamic model for signaling and adaptation based on the attractant flow in the experiment, signaling by cooperative receptor complexes, and multiple layers of feedback regulation for adaptation. We experimentally confirm the predicted effects of changing the enzyme-expression level and bypassing the negative feedback for demethylation. Our data analysis suggests significant imprecision in adaptation for large additions. Furthermore, our model predicts highly regulated, ultrafast adaptation in response to removal of attractant, which may be useful for fast reorientation of the cell and noise reduction in adaptation.Comment: accepted for publication in PLoS Computational Biology; manuscript (19 pages, 5 figures) and supplementary information; added additional clarification on alternative adaptation models in supplementary informatio

Radiating Shear-Free Gravitational Collapse with Charge

We present a new shear free model for the gravitational collapse of a spherically symmetric charged body. We propose a dissipative contraction with radiation emitted outwards. The Einstein field equations, using the junction conditions and an ansatz, are integrated numerically. A check of the energy conditions is also performed. We obtain that the charge delays the black hole formation and it can even halt the collapse.Comment: 22 pages, 9 figures. It has been corrected several typos and included several references. Accepted for publication in GR

Cross validation of bi-modal health-related stress assessment

This study explores the feasibility of objective and ubiquitous stress assessment. 25 post-traumatic stress disorder patients participated in a controlled storytelling (ST) study and an ecologically valid reliving (RL) study. The two studies were meant to represent an early and a late therapy session, and each consisted of a "happy" and a "stress triggering" part. Two instruments were chosen to assess the stress level of the patients at various point in time during therapy: (i) speech, used as an objective and ubiquitous stress indicator and (ii) the subjective unit of distress (SUD), a clinically validated Likert scale. In total, 13 statistical parameters were derived from each of five speech features: amplitude, zero-crossings, power, high-frequency power, and pitch. To model the emotional state of the patients, 28 parameters were selected from this set by means of a linear regression model and, subsequently, compressed into 11 principal components. The SUD and speech model were cross-validated, using 3 machine learning algorithms. Between 90% (2 SUD levels) and 39% (10 SUD levels) correct classification was achieved. The two sessions could be discriminated in 89% (for ST) and 77% (for RL) of the cases. This report fills a gap between laboratory and clinical studies, and its results emphasize the usefulness of Computer Aided Diagnostics (CAD) for mental health care

ARPES: A probe of electronic correlations

Angle-resolved photoemission spectroscopy (ARPES) is one of the most direct methods of studying the electronic structure of solids. By measuring the kinetic energy and angular distribution of the electrons photoemitted from a sample illuminated with sufficiently high-energy radiation, one can gain information on both the energy and momentum of the electrons propagating inside a material. This is of vital importance in elucidating the connection between electronic, magnetic, and chemical structure of solids, in particular for those complex systems which cannot be appropriately described within the independent-particle picture. Among the various classes of complex systems, of great interest are the transition metal oxides, which have been at the center stage in condensed matter physics for the last four decades. Following a general introduction to the topic, we will lay the theoretical basis needed to understand the pivotal role of ARPES in the study of such systems. After a brief overview on the state-of-the-art capabilities of the technique, we will review some of the most interesting and relevant case studies of the novel physics revealed by ARPES in 3d-, 4d- and 5d-based oxides.Comment: Chapter to appear in "Strongly Correlated Systems: Experimental Techniques", edited by A. Avella and F. Mancini, Springer Series in Solid-State Sciences (2013). A high-resolution version can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Reviews/ARPES_Springer.pdf. arXiv admin note: text overlap with arXiv:cond-mat/0307085, arXiv:cond-mat/020850

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie