Highly efficient Bayesian joint inversion for receiver-based data and its application to lithospheric structure beneath the southern Korean Peninsula

With the deployment of extensive seismic arrays, systematic and efficient parameter and uncertainty estimation is of increasing importance and can provide reliable, regional models for crustal and upper-mantle structure.We present an efficient Bayesian method for the joint inversion of surface-wave dispersion and receiver-function data that combines trans-dimensional (trans-D) model selection in an optimization phase with subsequent rigorous parameter uncertainty estimation. Parameter and uncertainty estimation depend strongly on the chosen parametrization such that meaningful regional comparison requires quantitative model selection that can be carried out efficiently at several sites. While significant progress has been made for model selection (e.g. trans-D inference) at individual sites, the lack of efficiency can prohibit application to large data volumes or cause questionable results due to lack of convergence. Studies that address large numbers of data sets have mostly ignored model selection in favour of more efficient/simple estimation techniques (i.e. focusing on uncertainty estimation but employing ad-hoc model choices). Our approach consists of a two-phase inversion that combines trans-D optimization to select the most probable parametrization with subsequent Bayesian sampling for uncertainty estimation given that parametrization. The trans-D optimization is implemented here by replacing the likelihood function with the Bayesian information criterion (BIC). The BIC provides constraints on model complexity that facilitate the search for an optimal parametrization. Parallel tempering (PT) is applied as an optimization algorithm. After optimization, the optimal model choice is identified by the minimum BIC value from all PT chains. Uncertainty estimation is then carried out in fixed dimension. Data errors are estimated as part of the inference problem by a combination of empirical and hierarchical estimation. Data covariance matrices are estimated from data residuals (the difference between prediction and observation) and periodically updated. In addition, a scaling factor for the covariance matrix magnitude is estimated as part of the inversion. The inversion is applied to both simulated and observed data that consist of phase- and group-velocity dispersion curves (Rayleigh wave), and receiver functions. The simulation results show that model complexity and important features are well estimated by the fixed dimensional posterior probability density. Observed data for stations in different tectonic regions of the southern Korean Peninsula are considered. The results are consistent with published results, but important features are better constrained than in previous regularized inversions and are more consistent across the stations. For example, resolution of crustal and Moho interfaces, and absolute values and gradients of velocities in lower crust and upper mantle are better constrained

First-time rhesus monkey mothers, and mothers of sons, preferentially engage in face-to-face interactions with infants

Face-to-face interactions between mothers and infants occur in both human and non-human primates, but there is large variability in the occurrence of these behaviors and the reason for this variability remains largely unexplored. Other types of maternal investment have been shown to be dependent on infant sex (e.g. milk production and maternal responsiveness) and maternal experience (e.g. symmetrical communication). Thus, we sought to determine whether variability in face-to-face interactions, that is, mutual gazing (MG), which are hypothesized to be important for later socio-cognitive development, could be explained by these variables. We studied 28 semi-free ranging rhesus monkey (Macaca mulatta) mother-infant dyads (6 primiparous; 12 male infants) born and reared at the Laboratory of Comparative Ethology field station at the NIH Animal Center in Poolesville, MD, across the first 90 postnatal days. Infant sex (i.e. male) was a significant predictor of maternal grooming (β ± SE = 0.359 ± 0.164, Z = 2.19, P = 0.029) whereas both parity (i.e. first time mothers) and infant sex (i.e. male) significantly predicted MG (parity: β ± SE = -0.735 ± 0.223, Z = -3.30, P < 0.001; infant sex: β ± SE = 0.436 ± 0.201, Z = 2.17, P = 0.029). Separation from the mother (outside of arm's reach) was not influenced by parity or infant sex. Together with existing literature, these findings point toward differential maternal investment for sons versus daughters. Mothers may be investing differentially in sons, behaviorally, to ensure their future social competence and thus later reproductive success. Collectively, our findings add to the literature that is beginning to identify early life experiences that may lead to sex differences in neurological and behavioral development.Division of Intramural Research, National Institute of Child Health and Human Developmen

Density correlations and dynamical Casimir emission of Bogoliubov phonons in modulated atomic Bose-Einstein condensates

We present a theory of the density correlations that appear in an atomic Bose-Einstein condensate as a consequence of the dynamical Casimir emission of pairs of Bogoliubov phonons when the atom-atom scattering length is modulated in time. Different regimes as a function of the temporal shape of the modulation are identified and a simple physical picture of the phenomenon is discussed. Analytical expressions for the density correlation function are provided for the most significant limiting cases. This theory is able to explain some unexpected features recently observed in numerical calculations of Hawking radiation from analog black holes

Parkinson-causing α-synuclein missense mutations shift native tetramers to monomers as a mechanism for disease initiation

β-Sheet-rich α-synuclein (αS) aggregates characterize Parkinson's disease (PD). αS was long believed to be a natively unfolded monomer, but recent work suggests it also occurs in α-helix-rich tetramers. Crosslinking traps principally tetrameric αS in intact normal neurons, but not after cell lysis, suggesting a dynamic equilibrium. Here we show that freshly biopsied normal human brain contains abundant αS tetramers. The PD-causing mutation A53T decreases tetramers in mouse brain. Neurons derived from an A53T patient have decreased tetramers. Neurons expressing E46K do also, and adding 1-2 E46K-like mutations into the canonical αS repeat motifs (KTKEGV) further reduces tetramers, decreases αS solubility and induces neurotoxicity and round inclusions. The other three fPD missense mutations likewise decrease tetramer:monomer ratios. The destabilization of physiological tetramers by PD-causing missense mutations and the neurotoxicity and inclusions induced by markedly decreasing tetramers suggest that decreased α-helical tetramers and increased unfolded monomers initiate pathogenesis. Tetramer-stabilizing compounds should prevent this

The Promise of Stochastic Resonance in Falls Prevention

Multisensory integration is essential for maintenance of motor and cognitive abilities, thereby ensuring normal function and personal autonomy. Balance control is challenged during senescence or in motor disorders, leading to potential falls. Increased uncertainty in sensory signals is caused by a number of factors including noise, defined as a random and persistent disturbance that reduces the clarity of information. Counter-intuitively, noise can be beneficial in some conditions. Stochastic resonance is a mechanism whereby a particular level of noise actually enhances the response of non-linear systems to weak sensory signals. Here we review the effects of stochastic resonance on sensory modalities and systems directly involved in balance control. We highlight its potential for improving sensorimotor performance as well as cognitive and autonomic functions. These promising results demonstrate that stochastic resonance represents a flexible and non-invasive technique that can be applied to different modalities simultaneously. Finally we point out its benefits for a variety of scenarios including in ambulant elderly, skilled movements, sports and to patients with sensorimotor or autonomic dysfunctions.Multisensory integration is essential for maintenance of motor and cognitive abilities, thereby ensuring normal function and personal autonomy. Balance control is challenged during senescence or in motor disorders, leading to potential falls. Increased uncertainty in sensory signals is caused by a number of factors including noise, defined as a random and persistent disturbance that reduces the clarity of information. Counter-intuitively, noise can be beneficial in some conditions. Stochastic resonance is a mechanism whereby a particular level of noise actually enhances the response of non-linear systems to weak sensory signals. Here we review the effects of stochastic resonance on sensory modalities and systems directly involved in balance control. We highlight its potential for improving sensorimotor performance as well as cognitive and autonomic functions. These promising results demonstrate that stochastic resonance represents a flexible and non-invasive technique that can be applied to different modalities simultaneously. Finally we point out its benefits for a variety of scenarios including in ambulant elderly, skilled movements, sports and to patients with sensorimotor or autonomic dysfunctions

Brain region-specific susceptibility of Lewy body pathology in synucleinopathies is governed by α-synuclein conformations

The protein α-synuclein, a key player in Parkinson's disease (PD) and other synucleinopathies, exists in different physiological conformations: cytosolic unfolded aggregation-prone monomers and helical aggregation-resistant multimers. It has been shown that familial PD-associated missense mutations within the α-synuclein gene destabilize the conformer equilibrium of physiologic α-synuclein in favor of unfolded monomers. Here, we characterized the relative levels of unfolded and helical forms of cytosolic α-synuclein in post-mortem human brain tissue and showed that the equilibrium of α-synuclein conformations is destabilized in sporadic PD and DLB patients. This disturbed equilibrium is decreased in a brain region-specific manner in patient samples pointing toward a possible "prion-like" propagation of the underlying pathology and forms distinct disease-specific patterns in the two different synucleinopathies. We are also able to show that a destabilization of multimers mechanistically leads to increased levels of insoluble, pathological α-synuclein, while pharmacological stabilization of multimers leads to a "prion-like" aggregation resistance. Together, our findings suggest that these disease-specific patterns of α-synuclein multimer destabilization in sporadic PD and DLB are caused by both regional neuronal vulnerability and "prion-like" aggregation transmission enabled by the destabilization of local endogenous α-synuclein protein

Chemical Ubiquitination for Decrypting a Cellular Code

The modification of proteins with ubiquitin (Ub) is an important regulator of eukaryotic biology and deleterious perturbation of this process is widely linked to the onset of various diseases. The regulatory capacity of the Ub signal is high and, in part, arises from the capability of Ub to be enzymatically polymerised to form polyubiquitin (polyUb) chains of eight different linkage types. These distinct polyUb topologies can then be site-specifically conjugated to substrate proteins to elicit a number of cellular outcomes. Therefore, to further elucidate the biological significance of substrate ubiquitination, methodologies that allow the production of defined polyUb species, and substrate proteins that are site-specifically modified with them, are essential to progress our understanding. Many chemically inspired methods have recently emerged which fulfil many of the criteria necessary for achieving deeper insight into Ub biology. With a view to providing immediate impact in traditional biology research labs, the aim of this review is to provide an overview of the techniques that are available for preparing Ub conjugates and polyUb chains with focus on approaches that use recombinant protein building blocks. These approaches either produce a native isopeptide, or analogue thereof, that can be hydrolysable or non-hydrolysable by deubiquitinases. The most significant biological insights that have already been garnered using such approaches will also be summarized

Unified one-fluid formulation for incompressible flexible solids and multiphase flows: Application to hydrodynamics using the immersed structural potential method (ISPM)

In this paper, we present a two-dimensional computational framework for the simulation of fluid-structure interaction problems involving incompressible flexible solids and multiphase flows, further extending the application range of classical immersed computational approaches to the context of hydrodynamics. The proposed method aims to overcome shortcomings such as the restriction of having to deal with similar density ratios among different phases or the restriction to solve single-phase flows. First, a variation of classical immersed techniques, pioneered with the immersed boundary method (IBM), is presented by rearranging the governing equations, which define the behaviour of the multiple physics involved. The formulation is compatible with the “one-fluid” formulation for two-phase flows and can deal with large density ratios with the help of an anisotropic Poisson solver. Second, immersed deformable structures and fluid phases are modelled in an identical manner except for the computation of the deviatoric stresses. The numerical technique followed in this paper builds upon the immersed structural potential method developed by the authors, by adding a level set–based method for the capturing of the fluid-fluid interfaces and an interface Lagrangian-based meshless technique for the tracking of the fluid-structure interface. The spatial discretisation is based on the standard marker-and-cell method used in conjunction with a fractional step approach for the pressure/velocity decoupling, a second-order time integrator, and a fixed-point iterative scheme. The paper presents a wide d range of two-dimensional applications involving multiphase flows interacting with immersed deformable solids, including benchmarking against both experimental and alternative numerical schemes

Resolving the homology-function relationship through comparative genomics of membrane-trafficking machinery and parasite cell biology

With advances in DNA sequencing technology, it is increasingly common and tractable to informatically look for genes of interest in the genomic databases of parasitic organisms and infer cellular states. Assignment of a putative gene function based on homology to functionally characterized genes in other organisms, though powerful, relies on the implicit assumption of functional homology, i.e. that orthology indicates conserved function. Eukaryotes reveal a dazzling array of cellular features and structural organization, suggesting a concomitant diversity in their underlying molecular machinery. Significantly, examples of novel functions for pre-existing or new paralogues are not uncommon. Do these examples undermine the basic assumption of functional homology, especially in parasitic protists, which are often highly derived? Here we examine the extent to which functional homology exists between organisms spanning the eukaryotic lineage. By comparing membrane trafficking proteins between parasitic protists and traditional model organisms, where direct functional evidence is available, we find that function is indeed largely conserved between orthologues, albeit with significant adaptation arising from the unique biological features within each lineage