Redundancy-selection trade-off in phenotype-structured populations

Realistic fitness landscapes generally display a redundancy-fitness trade-off: highly fit trait configurations are inevitably rare, while less fit trait configurations are expected to be more redundant. The resulting sub-optimal patterns in the fitness distribution are typically described by means of effective formulations, where redundancy provided by the presence of neutral contributions is modelled implicitly, e.g. with a bias of the mutation process. However, the extent to which effective formulations are compatible with explicitly redundant landscapes is yet to be understood, as well as the consequences of a potential miss-match. Here we investigate the effects of such trade-off on the evolution of phenotype-structured populations, characterised by continuous quantitative traits. We consider a typical replication-mutation dynamics, and we model redundancy by means of two dimensional landscapes displaying both selective and neutral traits. We show that asymmetries of the landscapes will generate neutral contributions to the marginalised fitness-level description, that cannot be described by effective formulations, nor disentangled by the full trait distribution. Rather, they appear as effective sources, whose magnitude depends on the geometry of the landscape. Our results highlight new important aspects on the nature of sub-optimality. We discuss practical implications for rapidly mutant populations such as pathogens and cancer cells, where the qualitative knowledge of their trait and fitness distributions can drive disease management and intervention policies

Structure and Interactions of the TPR Domain of Sgt2 with Yeast Chaperones and Ybr137wp.

Small glutamine-rich tetratricopeptide repeat-containing protein 2 (Sgt2) is a multi-module co-chaperone involved in several protein quality control pathways. The TPR domain of Sgt2 and several other proteins, including SGTA, Hop, and CHIP, is a highly conserved motif known to form transient complexes with molecular chaperones such as Hsp70 and Hsp90. In this work, we present the first high resolution crystal structures of Sgt2_TPR alone and in complex with a C-terminal peptide PTVEEVD from heat shock protein, Ssa1. Using nuclear magnetic resonance spectroscopy and isothermal titration calorimetry, we demonstrate that Sgt2_TPR interacts with peptides corresponding to the C-termini of Ssa1, Hsc82, and Ybr137wp with similar binding modes and affinities

Assessing the usefulness of a novel MRI-based breast density estimation algorithm in a cohort of women at high genetic risk of breast cancer: the UK MARIBS study

Introduction Mammographic breast density is one of the strongest known risk factors for breast cancer. We present a novel technique for estimating breast density based on 3D T1-weighted Magnetic Resonance Imaging (MRI) and evaluate its performance, including for breast cancer risk prediction, relative to two standard mammographic density-estimation methods.Methods The analyses were based on MRI (n = 655) and mammography (n = 607) images obtained in the course of the UK multicentre magnetic resonance imaging breast screening (MARIBS) study of asymptomatic women aged 31 to 49 years who were at high genetic risk of breast cancer. The MRI percent and absolute dense volumes were estimated using our novel algorithm (MRIBview) while mammographic percent and absolute dense area were estimated using the Cumulus thresholding algorithm and also using a 21-point Visual Assessment scale for one medio-lateral oblique image per woman. We assessed the relationships of the MRI and mammographic measures to one another, to standard anthropometric and hormonal factors, to BRCA1/2 genetic status, and to breast cancer risk (60 cases) using linear and Poisson regression.Results MRI percent dense volume is well correlated with mammographic percent dense area (R = 0.76) but overall gives estimates 8.1 percentage points lower (P < 0.0001). Both show strong associations with established anthropometric and hormonal factors. Mammographic percent dense area, and to a lesser extent MRI percent dense volume were lower in BRCA1 carriers (P = 0.001, P = 0.010 respectively) but there was no association with BRCA2 carrier status. The study was underpowered to detect expected associations between percent density and breast cancer, but women with absolute MRI dense volume in the upper half of the distribution had double the risk of those in the lower half (P = 0.009).Conclusions The MRIBview estimates of volumetric breast density are highly correlated with mammographic dense area but are not equivalent measures; the MRI absolute dense volume shows potential as a predictor of breast cancer risk that merits further investigation

Acute hunger does not always undermine prosociality

This is the final version. Available on open access from Nature Research via the DOI in this recordData Availability: The data that support the findings of this paper are available on the OSF website (https://osf.io/zexd7/?view_only=480593713c904397a033e751a6da7a69).It has been argued that, when they are acutely hungry, people act in self-protective ways by keeping resources to themselves rather than sharing them. In four studies, using experimental, quasi-experimental, and correlational designs (total N = 795), we examine the effects of acute hunger on prosociality in a wide variety of non-interdependent tasks (e.g. dictator game) and interdependent tasks (e.g. public goods games). While our procedures successfully increase subjective hunger and decrease blood glucose, we do not find significant effects of hunger on prosociality. This is true for both decisions incentivized with money and with food. Metaanalysis across all tasks reveals a very small effect of hunger on prosociality in noninterdependent tasks (d = .108), and a non-significant effect in interdependent tasks (d = -0.076). In study five (N = 197), we show that, in stark contrast to our empirical findings, people hold strong lay theories that hunger undermines prosociality.Volkswagen Foundatio

Measuring local volume fraction, long-wavelength correlations, and fractionation in a phase-separating polydisperse fluid

We dynamically simulate fractionation (partitioning of particle species) during spinodal gas-liquid separation of a size-polydisperse colloid, using polydispersity up to ∼40% and a skewed parent size distribution. We introduce a novel coarse-grained Voronoi method to minimise size bias in measuring local volume fraction, along with a variety of spatial correlation functions which detect fractionation without requiring a clear distinction between the phases. These can be applied whether or not a system is phase separated, to determine structural correlations in particle size, and generalise easily to other kinds of polydispersity (charge, shape, etc.). We measure fractionation in both mean size and polydispersity between the phases, its direction differing between model interaction potentials which are identical in the monodisperse case. These qualitative features are predicted by a perturbative theory requiring only a monodisperse reference as input. The results show that intricate fractionation takes place almost from the start of phase separation, so can play a role even in nonequilibrium arrested states. The methods for characterisation of inhomogeneous polydisperse systems could in principle be applied to experiment as well as modelling

Numerical comparison of a constrained path ensemble and a driven quasisteady state

We investigate the correspondence between a nonequilibrium ensemble defined via the distribution of phase-space paths of a Hamiltonian system and a system driven into a steady state by nonequilibrium boundary conditions. To discover whether the nonequilibrium path ensemble adequately describes the physics of a driven system, we measure transition rates in a simple one-dimensional model of rotors with Newtonian dynamics and purely conservative interactions. We compare those rates with known properties of the nonequilibrium path ensemble. In doing so, we establish effective protocols for the analysis of transition rates in nonequilibrium quasisteady states. Transition rates between potential wells and also between phase-space elements are studied and found to exhibit distinct properties, the more coarse-grained potential wells being effectively further from equilibrium. In all cases the results from the boundary-driven system are close to the path-ensemble predictions, but the question of equivalence of the two remains open

Effects of orientational order on modulated cylindrical interfaces

Cylindrical interfaces occur in sheared or deformed emulsions and as biological or technological lipid monolayer or bilayer tubules. Like the corresponding spherical droplets and vesicles, these cylinderlike surfaces may host orientational order with n -fold rotational symmetry, for example in the positions of lipid molecules or of spherical nanoparticles. We examine how that order interacts with and induces shape modulations of cylindrical interfaces. While on spherical droplets 2 n topological defects necessarily exist and can induce icosahedral droplet shapes, the cylindrical topology is compatible with a defect-free patterning. Nevertheless, once a modulation is introduced by a mechanism such as spontaneous curvature, nontrivial patterns of order, including ones with excess defects, emerge and have nonlinear effects on the shape of the tube. By examining the equilibrium energetics of the system analytically and with a lattice-based Markov chain Monte Carlo simulation, we predict low-temperature morphologies of modulated cylindrical interfaces hosting orientational order. A shape modulation induces a banded pattern of alternatingly isotropic and ordered interfacial material. Furthermore, cylindrical systems can be divided into type I, without defects, and type II, which go through a spectrum of defect states with up to 4 n excess defects. The character of the curvature-induced shape transition from unmodulated to modulated cylinders is continuous or discontinuous accordingly