The Solar Twin Planet Search I. Fundamental parameters of the stellar sample

Context. We are carrying out a search for planets around a sample of solar twin stars using the HARPS spectrograph. The goal of this project is to exploit the advantage offered by solar twins to obtain chemical abundances of unmatched precision. This survey will enable new studies of the stellar composition - planet connection.Aims. We determine the fundamental parameters of the 88 solar twin stars that have been chosen as targets for our experiment.Methods. We used the MIKE spectrograph on the Magellan Clay Telescope to acquire high resolution, high signal-to-noise ratio spectra of our sample stars. We measured the equivalent widths of iron lines and used strict differential excitation/ionization balance analysis to determine atmospheric parameters of unprecedented internal precision: σ(Teff) = 7? K, σ(log? g) = 0.019, σ([Fe/H]) = 0.006? dex, σ(vt) = 0.016? km? s-1. Reliable relative ages and highly precise masses were then estimated using theoretical isochrones.Results. The spectroscopic parameters we derived are in good agreement with those measured using other independent techniques. There is even better agreement if the sample is restricted to those stars with the most internally precise determinations of stellar parameters in every technique involved. The root-mean-square scatter of the differences seen is fully compatible with the observational errors, demonstrating, as assumed thus far, that systematic uncertainties in the stellar parameters are negligible in the study of solar twins. We find a tight activity-age relation for our sample stars, which validates the internal precision of our dating method. Furthermore, we find that the solar cycle is perfectly consistent both with this trend and its star-to-star scatter.Conclusions. We present the largest sample of solar twins analyzed homogeneously using high quality spectra. The fundamental parameters derived from this work will be employed in subsequent work that aims to explore the connections between planet formation and stellar chemical composition

High precision abundances of the old solar twin HIP 102152: Insights on Li depletion from the oldest sun

We present the first detailed chemical abundance analysis of the old 8.2 Gyr solar twin, HIP 102152. We derive differential abundances of 21 elements relative to the Sun with precisions as high as 0.004 dex (≲1%), using ultra high-resolution (R = 110,0

Does the oxytocin receptor polymorphism (rs2254298) confer 'vulnerability' for psychopathology or 'differential susceptibility'? insights from evolution

The diathesis-stress model of psychiatric conditions has recently been challenged by the view that it might be more accurate to speak of 'differential susceptibility' or 'plasticity' genes, rather than one-sidedly focusing on individual vulnerability. That is, the same allelic variation that predisposes to a psychiatric disorder if associated with (developmentally early) environmental adversity may lead to a better-than-average functional outcome in the same domain under thriving (or favourable) environmental conditions. Studies of polymorphic variations of the serotonin transporter gene, the monoamino-oxidase-inhibitor A coding gene or the dopamine D4 receptor gene indicate that the early environment plays a crucial role in the development of favourable versus unfavourable outcomes. Current evidence is limited, however, to establishing a link between genetic variation and behavioural phenotypes. In contrast, little is known about how plasticity may be expressed at the neuroanatomical level as a 'hard-wired' correlate of observable behaviour. The present review article seeks to further strengthen the argument in favour of the differential susceptibility theory by incorporating findings from behavioural and neuroanatomical studies in relation to genetic variation of the oxytocin receptor gene. It is suggested that polymorphic variation at the oxytocin receptor gene (rs2254298) is associated with sociability, amygdala volume and differential risk for psychiatric conditions including autism, depression and anxiety disorder, depending on the quality of early environmental experiences. Seeing genetic variation at the core of developmental plasticity can explain, in contrast to the diathesis-stress perspective, why evolution by natural selection has maintained such 'risk' alleles in the gene pool of a population

Self-love and sociability: the ‘rudiments of commerce’ in the state of nature

Istvan Hont’s classic work on the theoretical links between the seventeenth-century natural jurists Hugo Grotius and Samuel Pufendorf and the eighteenth-century Scottish political economists remains a popular trope among intellectual and economic historians of various stamps. Despite this, a common criticism levelled at Hont remains his relative lack of engagement with the relationship between religion and economics in the early modern period. This paper challenges this aspect of Hont’s narrative by drawing attention to an alternative, albeit complementary, assessment of the natural jurisprudential heritage of eighteenth-century British political economy. Specifically, the article attempts to map on to Hont’s thesis the Christian Stoic interpretation of Grotius and Pufendorf which has gained greater currency in recent years. In doing so, the paper argues that Grotius and Pufendorf’s contributions to the ‘unsocial sociability’ debate do not necessarily lead directly to the Scottish school of political economists, as is commonly assumed. Instead, it contends that a reconsideration of Grotius and Pufendorf as neo-Stoic theorists, particularly via scrutiny of their respective adaptations of the traditional Stoic theory of oikeiosis, steers us towards the heart of the early English ‘clerical’ Enlightenment

Computational discovery of chemically patterned surfaces that effect unique hydration water dynamics

The interactions of water with solid surfaces govern their apparent hydrophobicity/hydrophilicity, influenced at the molecular scale by surface coverage of chemical groups of varied nonpolar/polar character. Recently, it has become clear that the precise patterning of surface groups, and not simply average surface coverage, has a significant impact on the structure and thermodynamics of hydration layer water, and, in turn, on macroscopic interfacial properties. Here we show that patterning also controls the dynamics of hydration water, a behavior frequently thought to be leveraged by biomolecules to influence functional dynamics, but yet to be generalized. To uncover the role of surface heterogeneities, we couple a genetic algorithm to iterative molecular dynamics simulations to design the patterning of surface functional groups, at fixed coverage, to either minimize or maximize proximal water diffusivity. Optimized surface configurations reveal that clustering of hydrophilic groups increases hydration water mobility, while dispersing them decreases it, but only if hydrophilic moieties interact with water through directional, hydrogen-bonding interactions. Remarkably, we find that, across different surfaces, coverages, and patterns, both the chemical potential for inserting a methane-sized hydrophobe near the interface and, in particular, the hydration water orientational entropy serve as strong predictors for hydration water diffusivity, suggesting that these simple thermodynamic quantities encode the way surfaces control water dynamics. These results suggest a deep and intriguing connection between hydration water thermodynamics and dynamics, demonstrating that subnanometer chemical surface patterning is an important design parameter for engineering solid-water interfaces with applications spanning separations to catalysis

Are AMBER Force Fields and Implicit Solvation Models Additive? A Folding Study with a Balanced Peptide Test Set

Implicit solvation models have long been sought as routes to significantly increase the speed and capabilities of biomolecular simulations. However, it has not always been clear that force fields developed independently of solvation models can together accurately predict secondary structure and folding, and whether the separate influences of the solvation and force field models can be described as independent and additive (versus synergistic). Here, we test two implicit solvation models with several recently developed protein force fields, within the AMBER simulation package. We create a representative set of five helical and five hairpin peptides, 11–20 amino acid residues in length, and calculate folded structures using replica exchange molecular dynamics simulations for all force field/solvent/peptide combinations, each with two instances using distinct starting configurations. In general, we find that no force field/solvent combination successfully folds all peptides and that the hairpin peptides are more difficult to capture. That being said, the older ff96/igb5* combination does a reasonable job in folding multiple secondary structures, while ff14SB/igb5* and ff14ipq/igb8 work well for helical and hairpin motifs, respectively. All combinations give rise to similar numbers of salt bridges, except for solvent models paired with ff14ipq, which slightly enhances them. Interestingly, we are unable statistically to decouple the effects of force field, solvent model, and peptide secondary structure on performance, such that particular combinations can have specific effects. These results suggest that future efforts might benefit from codevelopment of implicit models with force fields or from the use of emerging coarse-graining strategies that extract solvation effects in a bottom-up manner

Affinity of small-molecule solutes to hydrophobic, hydrophilic, and chemically patterned interfaces in aqueous solution

Performance of membranes for water purification is highly influenced by the interactions of solvated species with membrane surfaces, including surface adsorption of solutes upon fouling. Current efforts toward fouling-resistant membranes often pursue surface hydrophilization, frequently motivated by macroscopic measures of hydrophilicity, because hydrophobicity is thought to increase solute-surface affinity. While this heuristic has driven diverse membrane functionalization strategies, here we build on advances in the theory of hydrophobicity to critically examine the relevance of macroscopic characterizations of solute-surface affinity. Specifically, we use molecular simulations to quantify the affinities to model hydroxyl- and methyl-functionalized surfaces of small, chemically diverse, charge-neutral solutes represented in produced water. We show that surface affinities correlate poorly with two conventional measures of solute hydrophobicity, gas-phase water solubility and oil-water partitioning. Moreover, we find that all solutes show attraction to the hydrophobic surface and most to the hydrophilic one, in contrast to macroscopically based hydrophobicity heuristics. We explain these results by decomposing affinities into direct solute interaction energies (which dominate on hydroxyl surfaces) and water restructuring penalties (which dominate on methyl surfaces). Finally, we use an inverse design algorithm to show how heterogeneous surfaces, with multiple functional groups, can be patterned to manipulate solute affinity and selectivity. These findings, importantly based on a range of solute and surface chemistries, illustrate that conventional macroscopic hydrophobicity metrics can fail to predict solute-surface affinity, and that molecular-scale surface chemical patterning significantly influences affinity-suggesting design opportunities for water purification membranes and other engineered interfaces involving aqueous solute-surface interactions

Best Practices for Foundations in Molecular Simulations [Article v1.0].

This document provides a starting point for approaching molecular simulations, guiding beginning practitioners to what issues they need to know about before and while starting their first simulations, and why those issues are so critical. This document makes no claims to provide an adequate introduction to the subject on its own. Instead, our goal is to help people know what issues are critical before beginning, and to provide references to good resources on those topics. We also provide a checklist of key issues to consider before and while setting up molecular simulations which may serve as a foundation for other best practices documents