Implicit associations with social status: the effects of relationship involvement

The study tested the proposition that relationship involvement influences the implicit responses of women to high- and low-status professions. It was hypothesized that when a high-involvement context was primed, women would have more positive implicit associations with high-status occupations than when a low-involvement context was primed. In contrast, when a high-involvement context was primed, women would have more negative associations with low-status occupations than when a low-involvement context was primed. To test the hypothesis, 123 female participants received a high or low relationship involvement prime. Then the participants completed a single category implicit associations test designed to measure the participants' associations with either high- or low-status occupations. As predicted, the relationship involvement prime influenced the positivity of associations made with high- and low-status occupations. The study pointed to the possibility that persons possess evolutionary-based implicit associations.     

Accelerating all-atom protein folding simulations through reduced dihedral barriers

Protein folding requires extensive changes of backbone and sidechain dihedral angles, whose energy barriers constitute obstacles for the folding kinetics. Folding of small proteins is furthermore thought to be path-independent. Here, we propose that time-consuming all-atom protein folding simulations may be accelerated through a reduction of the dihedral barriers of the force field. In order to investigate this hypothesis, we performed various folding simulations of two small proteins. We report an acceleration towards smaller root-mean-square deviations from the native protein structure using our proposed method.     

Membrane adsorption,folding, insertion and translocation of synthetic trans-membrane peptides

Spontaneous membrane adsorption, folding and insertion of the synthetic WALP16 and KALP16 peptides was studied by computer simulations starting from completely extended conformations. The peptides were simulated using an unmodified all-atom force field in combination with an efficient Monte Carlo sampling algorithm. The membrane is represented implicitly as a hydrophobic zone inside a continuum solvent modelled using the generalized Born theory of solvation. The method was previously parameterized to match insertion energies of hydrophobic side chain analogs into cyclohexane and no parameters were optimized for the present simulations. Both peptides rapidly precipitate out of bulk solution and adsorb to the membrane surface. Interfacial folding into a helical conformation is followed by membrane insertion. Both the peptide conformations and their location in the membrane are strongly temperature dependent. The temperature dependent behaviour can be summarized by fitting to a four-state model, separating the system into folded and unfolded conformers, which are either inserted into the membrane or located at the interfaces. As the temperature is lowered the dominant peptide conformation of the system changes from unfolded surface bound configurations to folded surface bound states. Folded trans-membrane conformers represent the dominant configuration at low temperatures. The analysis allows direct estimates of the free energies of peptide folding and membrane insertion. In the case of WALP the quality of the fit is excellent and the thermodynamic behaviour is in good agreement with expected theoretical consideration. For KALP the fit is more problematic due to the large solvation energies of the charged lysine residues.     

An efficient protocol for obtaining accurate hydration free energies using quantum chemistry and reweighting from molecular dynamics simulations

The non-Boltzmann Bennett (NBB) free energy estimator method is applied to 21 molecules from the blind subset of the SAMPL4 challenge. When NBB is applied with the SMD implicit solvent model, and the OLYP/DZP level of quantum chemistry, highly accurate hydration free energy calculations are obtained with respect to experiment (RMSD = 0.89 kcal·mol⁻¹). Other quantum chemical methods are also tested, and the effects of solvent model, density functional, basis set are explored in this benchmarking study, providing a framework for improvements in calculating hydration free energies. We provide a practical guide for using the best QM-NBB protocols that are consistently more accurate than either pure QM or pure MM alone. In situations where high accuracy hydration free energy predictions are needed, the QM-NBB method with SMD implicit solvent should be the first choice of quantum chemists.     

军医大学学员坚毅性评价的内隐效应及脑电特征研究

目的:探寻军医大学学员内隐层面对自我和他人坚毅性评价的特点及脑电特征,为全面、客观的评估个体的坚毅性提供理论依据和客观指标。方法:使用E-Prime2.0参照经典内隐联想范式编制内隐联想-坚毅测验,对100名军医大学学员施测坚毅量表(Grit O),选取高、低坚毅水平被试(各20名)进行内隐联想-坚毅测验,并记录脑电,分析两组被试的内隐效应及主要脑电成分。结果:计算内隐效应D值,t检验显示高坚毅组(0.55±0.36)显著低于低坚毅组(0.87±0.49),t=-2.257,P0.05,Cohen'd=0.74。两组被试均诱发明显的N400和LPP,高坚毅组中N400在任务状态下主效应显著,F(1,17)=8.528,P0.05,η2=0.334,且在电极位置上主效应显著,F(10,170)=8.207,P0.001,η2=0.326。LPP在任务状态下主效应显著,F(1,17)=5.471,P0.05,η2=0.243,且在电极位置上主效应显著,F(10,170)=18.479,P0.001,η2=0.521;低坚毅组中N400在任务状态下主效应显著,F(1,17)=10.051,P0.05,η2=0.372,且在电极位置上主效应显著,F(10,170)=8.223,P0.001,η2=0.326,LPP在任务状态下主效应不显著。结论:1.军医大学学员坚毅性评价的内隐效应显著,即均倾向于认为自我的坚毅性高,他人的坚毅性低,通过问卷法评估坚毅性时应考虑坚毅评价的内隐效应。2.高、低坚毅性军医大学学员坚毅性内隐评价时的主要脑电成分N400、LPP存在差异,N400可作为坚毅性内隐评价符合程度的判断指标。3.内隐效应及N400可以作为对军医大学学员坚毅性评价时的客观指标。     

Implicit membrane treatment of buried charged groups: Application to peptide translocation across lipid bilayers

The energetic cost of burying charged groups in the hydrophobic core of lipid bilayers has been controversial, with simulations giving higher estimates than certain experiments. Implicit membrane approaches are usually deemed too simplistic for this problem. Here we challenge this view. The free energy of transfer of amino acid side chains from water to the membrane center predicted by IMM1 is reasonably close to all-atom free energy calculations. The shape of the free energy profile, however, for the charged side chains needs to be modified to reflect the all-atom simulation findings (IMM1-LF). Membrane thinning is treated by combining simulations at different membrane widths with an estimate of membrane deformation free energy from elasticity theory. This approach is first tested on the voltage sensor and the isolated S4 helix of potassium channels. The voltage sensor is stably inserted in a transmembrane orientation for both the original and the modified model. The transmembrane orientation of the isolated S4 helix is unstable in the original model, but a stable local minimum in IMM1-LF, slightly higher in energy than the interfacial orientation. Peptide translocation is addressed by mapping the effective energy of the peptide as a function of vertical position and tilt angle, which allows identification of minimum energy pathways and transition states. The barriers computed for the S4 helix and other experimentally studied peptides are low enough for an observable rate. Thus, computational results and experimental studies on the membrane burial of peptide charged groups appear to be consistent. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova.     

Positive implicit attitudes toward odor words

Associations between certain odors and for instance health effects may lead to positive or negative attitudes toward these odors. However, in experiments we conducted using the Implicit Association Test (IAT), we encountered attitudes even to odor "words." The IAT is based on the principle that reaction times measuring the association between words from a target dimension (in this case, odor vs. a neutral reference category) and an attribute dimension (i.e., positive or negative words) reflect the attitude to the target, where attitude-congruent associations between target and attribute are reflected by shorter reaction times. In a first experiment, we found distinctly positive attitudes to the concept odor in a student sample, which was replicated in a second experiment. In the main experiment, subjects in the aromatherapy group, who prefer using scented consumer products for relaxation purposes, showed a significantly more positive attitude toward odor words in the IAT than a control group, who did not have such a preference. The fact that results from the implicit test were not always associated with explicitly stated attitudes toward the odor words attests to the fact that the IAT measures the attitude of interest in a different way. As such, the IAT has added value in circumstances where explicit tests can be biased.     

Causal inference in biomolecular pathways using a Bayesian network approach and an Implicit method

We introduce here the concept of Implicit networks which provide, like Bayesian networks, a graphical modelling framework that encodes the joint probability distribution for a set of random variables within a directed acyclic graph. We show that Implicit networks, when used in conjunction with appropriate statistical techniques, are very attractive for their ability to understand and analyze biological data. Particularly, we consider here the use of Implicit networks for causal inference in biomolecular pathways. In such pathways, an Implicit network encodes dependencies among variables (proteins, genes), can be trained to learn causal relationships (regulation, interaction) between them and then used to predict the biological response given the status of some key proteins or genes in the network. We show that Implicit networks offer efficient methodologies for learning from observations without prior knowledge and thus provide a good alternative to classical inference in Bayesian networks when priors are missing. We illustrate our approach by an application to simulated data for a simplified signal transduction pathway of the epidermal growth factor receptor (EGFR) protein.     

Discovering implicit protein–protein interactions in the <Emphasis Type="Italic">Cell Cycle</Emphasis> using bioinformatics approaches

The cell division control protein (Cdc2) kinase is a catalytic subunit of a protein kinase complex, called the M phase promoting factor, which induces entry into mitosis and is universal among eukaryotes. This protein is believed to play a major role in cell division and control. The lives of biological cells are controlled by proteins interacting in metabolic and signaling pathways, in complexes that replicate genes and regulate gene activity, and in the assembly of the cytoskeletal infrastructure. Our knowledge of protein–protein (P–P) interactions has been accumulated from biochemical and genetic experiments, including the widely used yeast two-hybrid test. In this paper we examine if P–P interactions in regenerating tissues and cells of the anuran Xenopus laevis can be discovered from biomedical literature using computational and literature mining techniques. Using literature mining techniques, we have identified a set of implicitly interacting proteins in regenerating tissues and cells of Xenopus laevis that may interact with Cdc2 to control cell division. Genome sequence based bioinformatics tools were then applied to validate a set of proteins that appear to interact with the Cdc2 protein. Pathway analysis of these proteins suggests that Myc proteins function as the regulator of M phase initiation by controlling expression of the Akt1 molecule that ultimately inhibits the Cdc2-cyclin B complex in cells. P–P interactions that are implicitly appearing in literature can be effectively discovered using literature mining techniques. By applying evolutionary principles on the P–P interacting pairs, it is possible to quantitatively analyze the significance of the associations with biological relevance. The developed BioMap system allows discovering implicit P–P interactions from large quantity of biomedical literature data. The unique similarities and differences observed within the interacting proteins can lead to the development of the new hypotheses that can be used to design further laboratory experiments.     

Leap-dynamics: efficient sampling of conformational space of proteins and peptides in solution

A molecular simulation scheme, called Leap-dynamics, that provides efficient sampling of protein conformational space in solution is presented. The scheme is a combined approach using a fast sampling method, imposing conformational 'leaps' to force the system over energy barriers, and molecular dynamics (MD) for refinement. The presence of solvent is approximated by a potential of mean force depending on the solvent accessible surface area. The method has been successfully applied to N-acetyl-L-alanine-N-methylamide (alanine dipeptide), sampling experimentally observed conformations inaccessible to MD alone under the chosen conditions. The method predicts correctly the increased partial flexibility of the mutant Y35G compared to native bovine pancreatic trypsin inhibitor. In particular, the improvement over MD consists of the detection of conformational flexibility that corresponds closely to slow motions identified by nuclear magnetic resonance techniques.