Day occupation is associated with psychopathology for adolescents and young adults with Down syndrome

Background: Young adults with Down syndrome experience increased rates of emotional and behavioural problems compared with the general population. Most adolescents with Down syndrome living in Western Australia participate in sheltered employment as their main day occupation. Relationship between day occupation and changes in behaviour has not been examined. Therefore, the aim of this research was to explore any relationship between post school day occupations and changes in the young person’s behaviour. Methods: The Down syndrome Needs Opinion Wishes database was used for case ascertainment of young adults aged 15 to 32 years with Down syndrome. Families of 118 young people in this population-based database completed questionnaires in 2004, 2009 and 2011. The questionnaires addressed both young person characteristics such as age, gender, presence of impairments, behaviour, functioning in activities of daily living, and family characteristics such as income and family functioning. Post-school day occupations in which the young people were participating included open and sheltered employment, training and day recreation programs. Change in behaviour of young adults who remained in the same post-school day occupation from 2009 to 2011 (n = 103) were examined in a linear regression model adjusting for confounding variables including age, gender, prior functioning and behaviour in 2004 and family income.Results: In comparison to those young adults attending open employment from 2009 to 2011, those attending day recreation programs were reported to experience worsening in behaviour both in the unadjusted (effect size -0.14, 95% CI -0.24, -0.05) and adjusted models (effect size -0.15, 95% CI -0.29, -0.01). Conclusions: We found that the behaviour of those participating in open employment improved compared to those attending other day occupations. Further examination of the direction of this association is required

Gating of a pH-Sensitive K2P Potassium Channel by an Electrostatic Effect of Basic Sensor Residues on the Selectivity Filter

K+ channels share common selectivity characteristics but exhibit a wide diversity in how they are gated open. Leak K2P K+ channels TASK-2, TALK-1 and TALK-2 are gated open by extracellular alkalinization. The mechanism for this alkalinization-dependent gating has been proposed to be the neutralization of the side chain of a single arginine (lysine in TALK-2) residue near the pore of TASK-2, which occurs with the unusual pKa of 8.0. We now corroborate this hypothesis by transplanting the TASK-2 extracellular pH (pHo) sensor in the background of a pHo-insensitive TASK-3 channel, which leads to the restitution of pHo-gating. Using a concatenated channel approach, we also demonstrate that for TASK-2 to open, pHo sensors must be neutralized in each of the two subunits forming these dimeric channels with no apparent cross-talk between the sensors. These results are consistent with adaptive biasing force analysis of K+ permeation using a model selectivity filter in wild-type and mutated channels. The underlying free-energy profiles confirm that either a doubly or a singly charged pHo sensor is sufficient to abolish ion flow. Atomic detail of the associated mechanism reveals that, rather than a collapse of the pore, as proposed for other K2P channels gated at the selectivity filter, an increased height of the energetic barriers for ion translocation accounts for channel blockade at acid pHo. Our data, therefore, strongly suggest that a cycle of protonation/deprotonation of pHo-sensing arginine 224 side chain gates the TASK-2 channel by electrostatically tuning the conformational stability of its selectivity filter

Using metadynamics to explore complex free-energy landscapes

Metadynamics is an atomistic simulation technique that allows, within the same framework, acceleration of rare events and estimation of the free energy of complex molecular systems. It is based on iteratively \u2018filling\u2019 the potential energy of the system by a sum of Gaussians centred along the trajectory followed by a suitably chosen set of collective variables (CVs), thereby forcing the system to migrate from one minimum to the next. The power of metadynamics is demonstrated by the large number of extensions and variants that have been developed. The first scope of this Technical Review is to present a critical comparison of these variants, discussing their advantages and disadvantages. The effectiveness of metadynamics, and that of the numerous alternative methods, is strongly influenced by the choice of the CVs. If an important variable is neglected, the resulting estimate of the free energy is unreliable, and predicted transition mechanisms may be qualitatively wrong. The second scope of this Technical Review is to discuss how the CVs should be selected, how to verify whether the chosen CVs are sufficient or redundant, and how to iteratively improve the CVs using machine learning approaches

Quantum simulation of low-temperature metallic liquid hydrogen

The melting temperature of solid hydrogen drops with pressure above ~65 GPa, suggesting that a liquid state might exist at low temperatures. It has also been suggested that this low-temperature liquid state might be non-molecular and metallic, although evidence for such behaviour is lacking. Here we report results for hydrogen at high pressures using ab initio methods, which include a description of the quantum motion of the protons. We determine the melting temperature as a function of pressure and find an atomic solid phase from 500 to 800 GPa, which melts at <200 K. Beyond this and up to 1,200 GPa, a metallic atomic liquid is stable at temperatures as low as 50 K. The quantum motion of the protons is critical to the low melting temperature reported, as simulations with classical nuclei lead to considerably higher melting temperatures of ~300 K across the entire pressure range considered

Exploring high-dimensional free energy landscapes of chemical reactions

Molecular dynamics (MD) techniques are widely used in computing free energy changes for conformational transitions and chemical reactions, mainly in condensed matter systems. Most of the MD‐based approaches employ biased sampling of a priori selected coarse‐grained coordinates or collective variables (CVs) and thereby accelerate otherwise infrequent transitions from one free energy basin to the other. A quick convergence in free energy estimations can be achieved by enhanced sampling of large number of CVs. Conventional enhanced sampling approaches become exponentially slower with increasing dimensionality of the CV space, and thus they turn out to be highly inefficient in sampling high‐dimensional free energy landscapes. Here, we focus on some of the novel methods that are designed to overcome this limitation. In particular, we discuss four methods: bias‐exchange metadynamics, parallel‐bias metadynamics, adiabatic free energy dynamics/temperature‐accelerated MD, and temperature‐accelerated sliced sampling. The basic idea behind these techniques is presented and applications using these techniques are illustrated. Advantages and disadvantages of these techniques are also delineated

Dynamical spatial warping: A novel method for the conformational sampling of biophysical structure

The difficulties encountered in sampling of systems with rough energy landscapes using present methodology significantly limit the impact of simulation on molecular biology, in particular protein folding and design. Here, we present a major methodological development based on a promising new technique, the reference potential spatial warping algorithm (REPSWA) [Z. Zhu et al., Phys. Rev. Lett., 88 (2002), pp. 100201-100204], and present applications to several realistic systems. REPSWA works by introducing a variable transformation in the classical partition function that reduces the volume of phase space associated with a priori known barrier regions while increasing that associated with attractive basins. In this way, the partition function is preserved so that enhanced sampling is achieved without the need for reweighting phase-space averages. Here, a new class of transformations, designed to overcome the barriers induced by intermolecular/nonbonded interactions, whose locations are not known a priori, is introduced. The new transformations are designed to work in synergy with transformations originally introduced for overcoming intramolecular barriers. The new transformation adapts to the fluctuating local environment and is able to handle barriers that arise "on the fly." Thus, the new method is referred to as dynamic contact REPSWA (DC-REPSWA). In addition, combining hybrid Monte Carlo (HMC) with DC-REPSWA allows more aggressive sampling to take place. The combined DC-REPSWA-HMC method and its variants are shown to substantially enhance conformational sampling in long molecular chains composed of interacting single beads and beads with branches. The latter topologies characterize the united residue and united side chain representation of protein structures. © 2008 Society for Industrial and Applied Mathematics