Probing EWSB Naturalness in Unified SUSY Models with Dark Matter

We have studied Electroweak Symmetry Breaking (EWSB) fine-tuning in the context of two unified Supersymmetry scenarios: the Constrained Minimal Supersymmetric Model (CMSSM) and models with Non-Universal Higgs Masses (NUHM), in light of current and upcoming direct detection dark matter experiments. We consider both those models that satisfy a one-sided bound on the relic density of neutralinos, $\Omega_{\chi} h^2 < 0.12$, and also the subset that satisfy the two-sided bound in which the relic density is within the 2 sigma best fit of WMAP7 + BAO + H0 data. We find that current direct detection searches for dark matter probe the least fine-tuned regions of parameter-space, or equivalently those of lowest Higgs mass parameter $\mu$, and will tend to probe progressively more and more fine-tuned models, though the trend is more pronounced in the CMSSM than in the NUHM. Additionally, we examine several subsets of model points, categorized by common mass hierarchies; M_{\chi_0} \sim M_{\chi^\pm}, M_{\chi_0} \sim M_{\stau}, M_{\chi_0} \sim M_{\stop_1}, the light and heavy Higgs poles, and any additional models classified as "other"; the relevance of these mass hierarchies is their connection to the preferred neutralino annihilation channel that determines the relic abundance. For each of these subsets of models we investigated the degree of fine-tuning and discoverability in current and next generation direct detection experiments.Comment: 26 pages, 10 figures. v2: references added. v3: matches published versio

Expanding the Understanding of Biases in Development of Clinical-Grade Molecular Signatures: A Case Study in Acute Respiratory Viral Infections

The promise of modern personalized medicine is to use molecular and clinical information to better diagnose, manage, and treat disease, on an individual patient basis. These functions are predominantly enabled by molecular signatures, which are computational models for predicting phenotypes and other responses of interest from high-throughput assay data. Data-analytics is a central component of molecular signature development and can jeopardize the entire process if conducted incorrectly. While exploratory data analysis may tolerate suboptimal protocols, clinical-grade molecular signatures are subject to vastly stricter requirements. Closing the gap between standards for exploratory versus clinically successful molecular signatures entails a thorough understanding of possible biases in the data analysis phase and developing strategies to avoid them.Using a recently introduced data-analytic protocol as a case study, we provide an in-depth examination of the poorly studied biases of the data-analytic protocols related to signature multiplicity, biomarker redundancy, data preprocessing, and validation of signature reproducibility. The methodology and results presented in this work are aimed at expanding the understanding of these data-analytic biases that affect development of clinically robust molecular signatures.Several recommendations follow from the current study. First, all molecular signatures of a phenotype should be extracted to the extent possible, in order to provide comprehensive and accurate grounds for understanding disease pathogenesis. Second, redundant genes should generally be removed from final signatures to facilitate reproducibility and decrease manufacturing costs. Third, data preprocessing procedures should be designed so as not to bias biomarker selection. Finally, molecular signatures developed and applied on different phenotypes and populations of patients should be treated with great caution

Reversal to air-driven sound production revealed by a molecular phylogeny of tongueless frogs, family Pipidae

<p>Abstract</p> <p>Background</p> <p>Evolutionary novelties often appear by conferring completely new functions to pre-existing structures or by innovating the mechanism through which a particular function is performed. Sound production plays a central role in the behavior of frogs, which use their calls to delimit territories and attract mates. Therefore, frogs have evolved complex vocal structures capable of producing a wide variety of advertising sounds. It is generally acknowledged that most frogs call by moving an air column from the lungs through the glottis with the remarkable exception of the family Pipidae, whose members share a highly specialized sound production mechanism independent of air movement.</p> <p>Results</p> <p>Here, we performed behavioral observations in the poorly known African pipid genus <it>Pseudhymenochirus </it>and document that the sound production in this aquatic frog is almost certainly air-driven. However, morphological comparisons revealed an indisputable pipid nature of <it>Pseudhymenochirus </it>larynx. To place this paradoxical pattern into an evolutionary framework, we reconstructed robust molecular phylogenies of pipids based on complete mitochondrial genomes and nine nuclear protein-coding genes that coincided in placing <it>Pseudhymenochirus </it>nested among other pipids.</p> <p>Conclusions</p> <p>We conclude that although <it>Pseudhymenochirus </it>probably has evolved a reversal to the ancestral non-pipid condition of air-driven sound production, the mechanism through which it occurs is an evolutionary innovation based on the derived larynx of pipids. This strengthens the idea that evolutionary solutions to functional problems often emerge based on previous structures, and for this reason, innovations largely depend on possibilities and constraints predefined by the particular history of each lineage.</p

Dynamic Effective Connectivity of Inter-Areal Brain Circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference