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Optimization of the GB/SA solvation model for predicting the structure of surface loops in proteins.

Implicit solvation models are commonly optimized with respect to experimental data or Poisson-Boltzmann (PB) results obtained for small molecules, where the force field is sometimes not considered. In previous studies, we have developed an optimization procedure for cyclic peptides and surface loops in proteins based on the entire system studied and the specific force field used. Thus, the loop has been modeled by the simplified solvation function E(tot) = E(FF) (epsilon = 2r) + Sigma(i) sigma(i)A(i), where E(FF) (epsilon = nr) is the AMBER force field energy with a distance-dependent dielectric function, epsilon = nr, A(i) is the solvent accessible surface area of atom i, and sigma(i) is its atomic solvation parameter. During the optimization process, the loop is free to move while the protein template is held fixed in its X-ray structure. To improve on the results of this model, in the present work we apply our optimization procedure to the physically more rigorous solvation model, the generalized Born with surface area (GB/SA) (together with the all-atom AMBER force field) as suggested by Still and co-workers (J. Phys. Chem. A 1997, 101, 3005). The six parameters of the GB/SA model, namely, P(1)-P(5) and the surface area parameter, sigma (programmed in the TINKER package) are reoptimized for a "training" group of nine loops, and a best-fit set is defined from the individual sets of optimized parameters. The best-fit set and Still's original set of parameters (where Lys, Arg, His, Glu, and Asp are charged or neutralized) were applied to the training group as well as to a "test" group of seven loops, and the energy gaps and the corresponding RMSD values were calculated. These GB/SA results based on the three sets of parameters have been found to be comparable; surprisingly, however, they are somewhat inferior (e.g, of larger energy gaps) to those obtained previously from the simplified model described above. We discuss recent results for loops obtained by other solvation models and potential directions for future studies.

Models, Biological↗

Optimization of solutions for the one plant protection problem.

Plant protection problems are simulated by a system of ordinary differential equations with given initial conditions. The sensitivity and resistance of pathogen subpopulations to fungicide mixtures, fungicide weathering, plant growth, etc. are taken into consideration. The system of equations is solved numerically for each set of initial conditions and parameters of the disease and fungicide applications. Optimization algorithms were investigated and a computer program was developed for optimization of these solutions. 14 typical cases of the disease were simulated and optimized in order to determine optimal fungicide treatments. The optimized strategy for fungicide application differs considerably from the commonly used method and seems to be an important new principle in plant protection. The approach developed in this study may be useful for a wide spectrum of purposes in the simulation of leaf diseases. It may also help the biologist to decrease or pinpoint experimental work and analyze its results and is perspective for plant disease control.

Algorithms↗

Genetic optimism: framing genes and mental illness in the news.

Over the past two decades the pace and specificity of discoveries associating genetics with mental illness has accelerated, which is reflected in an increase in news coverage about the genetics of mental disorder. The news media is a major source of public understanding of genetics and a strong influence on public discourse. This paper examines the news coverage of genetics and mental illness (i.e., bipolar illness and schizophrenia) over a 25 year period, emphasizing the peak period of 1987-1994. Using a sample of 110 news stories from 5 major American newspapers and 3 news magazines, we identify the frame of "genetic optimism" which dominated the reporting of genetics and mental illness beginning in the mid- 1980s. The structure of the frame is comprised of 3 elements: a gene for the disorder exists; it will be found; and it will be good. New discoveries of genes were announced with great fanfare, but the most promising claims could not be replicated or were retracted in short order. Despite these disconfirmations, genetic optimism persisted in subsequent news stories. While the scientific accuracy of the gene stories is high, the genetic optimism frame distorts some of the findings, misrepresents and reifies the impact of genes on mental disorder, and leaves no space for critics or an examination of potential negative impacts. The stances of reporters, scientists and editors may all in different ways contribute to the perpetuation of genetic optimism. Genetic optimism presents an overly sanguine picture of the state of genetics; as we enter the genetic age it is important to balance the extraneous "hype and hope" contained in news stories of genetics and mental illness.

Genetics↗

Do optimism and pessimism predict physical functioning?

Dispositional optimism has been shown to be related to self-report measures of health and well-being, yet little research has examined the relationship between optimism and more objective measures of functioning. The purpose of this study was to examine the relationship between optimism and pessimism and objective physical functioning. Four hundred eighty community-dwelling older adults with knee pain completed a measure of optimism and pessimism and were observed performing four daily activities (walking, lifting an object, climbing stairs, and getting into and out of a car). Results indicated that pessimism was significantly related to performance on all four tasks (p < .001), while optimism was related to performance only on the walking task (p < .05), after controlling for demographic and health variables.

Activities of Daily Living↗

Event-specific versus unitary causal accounts of optimism bias.

Optimism bias is often assumed to have a unitary cause regardless of the event, however, factors causing it may actually be event-specific. In Experiment 1 (N = 23), subjects rated the importance of various causes for individual events. The results identified consistent differences in perceptions of causal factors across events. Experiment 2 (N = 190) employed the possible causal factors absent/exempt error and degree of motivation to investigate an event-specific theory of optimism bias in a manipulation design. Participants were encouraged to view one causal factor (absent/exempt or motivation) as either important or unimportant to future risk when they estimated their risk of absent/exempt-related, motivation-related and unrelated events (as determined in Experiment 1). A hanging control group received no manipulation. The event-specific theory's prediction that these manipulations would affect particular events and not others were not supported. However, discouraging the absent/exempt error reduced optimism bias across events, generally. Hence, a unitary and not an event-specific theory of optimism bias was supported. Furthermore, for the first time, the possible role of and confounding of cognitive manipulations of optimism bias by mood were evaluated, and not supported.

Adult↗

Robust optimal design for the estimation of hyperparameters in population pharmacokinetics.

The expectation of the determinant of the inverse of the population Fisher information matrix is proposed as a criterion to evaluate and optimize designs for the estimation of population pharmacokinetic (PK) parameters. Given a PK model, a measurement error model, a parametric distribution of the parameters and a prior distribution representing the belief about the hyperparameters to be estimated, the EID criterion is minimized in order to find the optimal population design. In this approach, a group is defined as a number of subjects to whom the same sampling schedule (i.e., the number of samples and their timing) is applied. The constraints, which are defined a priori, are the number of groups, the size of each group and the number of samples per subject in each group. The goal of the optimization is to determine the optimal sampling times in each group. This criterion is applied to a one-compartment open model with first-order absorption. The error model is either homoscedastic or heteroscedastic with constant coefficient of variation. Individual parameters are assumed to arise from a lognormal distribution with mean vector M and covariance matrix C. Uncertainties about the M and C are accounted for by a prior distribution which is normal for M and Wishart for C. Sampling times are optimized by using a stochastic gradient algorithm. Influence of the number of different sampling schemes, the number of subjects per sampling schedule, the number of samples per subject in each sampling scheme, the uncertainties on M and C and the assumption about the error model and the dose have been investigated.

Humans↗

Optimal experimental design for precise estimation of the parameters of the axial dispersion model of hepatic elimination.

The axial dispersion model of hepatic drug elimination is characterized by two dimensionless parameters, the dispersion number, DN, and the efficiency number, RN, corresponding to the relative dispersion of material on transit through the organ and the relative efficiency of elimination of drug by the organ, respectively. Optimal design theory was applied to the estimation of these two parameters based on changes in availability (F) of drug at steady state for the closed boundary condition model, with particular attention to variations in the fraction of drug unbound in the perfusate (fuB). Sensitivity analysis indicates that precision in parameter estimation is greatest when F is low and that correlation between RN and DN is high, which is desirable for parameter estimation, when DN lies between 0.1 and 100. Optimal design points were obtained using D-optimization, taking into account the error variance model. If the error variance model is unknown, it is shown that choosing Poisson error model is reasonable. Furthermore, although not optimal, geometric spacing of fuB values is often reasonable and definitively superior to a uniform spacing strategy. In practice, the range of fuB available for selection may be limited by such practical considerations as assay sensitivity and acceptable concentration range of binding protein. Notwithstanding, optimal design theory provides a rational approach to precise parameter estimation.

Linear Models↗

A stochastic model for optimizing composite predictors based on gene expression profiles.

PURPOSE: This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. METHODS: The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. RESULTS: The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. CONCLUSIONS: The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Adult↗

Formulation optimization of paclitaxel carried by PEGylated emulsions based on artificial neural network.

PURPOSE: To develop paclitaxel carried by injectable PEGylated emulsions, an artificial neural network (ANN) was used to optimize the formulation--which has a small particle size, high entrapment efficiency, and good stability--and to investigate the role of each ingredient in the emulsion. METHODS: Paclitaxel emulsions were prepared by a modified ethanol injection method. A computer optimization technique based on a spherical experimental design for three-level, three factors [soybean oil (X1), PEG-DSPE (X2) and polysorbate 80 (X3)] were used to optimize the formulation. The entrapment efficiency of paclitaxel (Y1) was quantified by HPLC; the particle size of the emulsions (Y2) was measured by dynamic laser light scattering and the stability of paclitaxel emulsions was monitored by the changes in drug concentration (Y3) and particle size (Y4) after storage at 4 degrees C. RESULTS: The entrapment efficiency, particle size and stability of paclitaxel emulsions were influenced by PEG-DSPE, polysorbate 80, and soybean oil. Paclitaxel emulsions of small size (262 nm), high entrapment efficiency (96.7%), and good stability were obtained by the optimization. CONCLUSIONS: A novel formulation for paclitaxel emulsions was optimized with ANN and prepared. The contribution indices of each component suggested that PEG-DSPE mainly contributes to the entrapment efficiency and particle size of paclitaxel emulsions, while polysorbate 80 contributes to stability.

Antineoplastic Agents, Phytogenic↗

Dispositional optimism and recovery from coronary artery bypass surgery: the beneficial effects on physical and psychological well-being.

The effect of dispositional optimism on recovery from coronary artery bypass surgery was examined in a group of 51 middle-aged men. Patients provided information at three points in time--(a) on the day before surgery, (b) 6-8 days postoperatively, and (c) 6 months postoperatively. Information was obtained relating to the patient's rate of physical recovery, mood, and postsurgical quality of life. Information was also gathered regarding the manner in which the patients attempted to cope with the stress of the surgery and its aftermath. As expected, dispositional optimism proved to be an important predictor of coping efforts and of surgical outcomes. More specifically, dispositional optimism (as assessed prior to surgery) correlated positively with manifestations of problem-focused coping and negatively with the use of denial. Dispositional optimism was also associated with a faster rate of physical recovery during the period of hospitalization and with a faster rate of return to normal life activities subsequent to discharge. Finally, there was a strong positive association between level of optimism and postsurgical quality of life at 6 months.

Adaptation, Psychological↗

Optimism, self-mastery, and symptoms of depression in women professionals.

The construct validity and predictive utility of dispositional optimism were examined in a sample of 192 women professionals. By using covariance structure modeling with latent variables, opotimism (Scheier & Carver, 1985) and self-mastery (Pearlin & Schooler, 1978) were found to be empirically distinct, although substantially correlated, constructs. Furthermore, although optimism and self-mastery were significant and negatively correlated with symptoms of depression, only self-mastery was independently associated with symptom levels. In addition, no evidence was found that optimism and self-mastery interact to influence depressive symptoms. These results suggest that the apparent predictive power of optimism may derive from its substantial overlap with self-mastery. Implications for the assessment and interpretation of optimism and self-mastery are discussed.

Adaptation, Psychological↗

Optimism, coping, psychological distress, and high-risk sexual behavior among men at risk for acquired immunodeficiency syndrome (AIDS).

In a cohort of gay men responding to the threat of acquired immunodeficiency syndrome (AIDS), dispositional optimism was associated with less distress, less avoidant coping, positive attitudes as a coping strategy, and fewer AIDS-related concerns. Men who knew they were seropositive for human immunodeficiency virus (HIV) were significantly more optimistic about not developing AIDS than men who knew they were seronegative for HIV. This AIDS-specific optimism was related to higher perceived control over AIDS and to active coping among seropositive men only and to health behaviors in both serostatus groups. There was no relation of optimism to risk-related sexual behavior. It is concluded that optimism is psychologically adaptive without necessarily compromising health behavior. It is also concluded that it is useful to distinguish between event-based optimistic expectations and dispositional optimism.

AIDS Serodiagnosis↗

Optimism is associated with mood, coping, and immune change in response to stress.

This study explored prospectively the effects of dispositional and situational optimism on mood (N = 90) and immune changes (N = 50) among law students in their first semester of study. Optimism was associated with better mood, higher numbers of helper T cells, and higher natural killer cell cytotoxicity. Avoidance coping partially accounted for the relationship between optimism and mood. Among the immune parameters, mood partially accounted for the optimism-helper T cell relationship, and perceived stress partially accounted for the optimism-cytotoxicity relationship. Individual differences in expectancies, appraisal, and mood may be important in understanding psychological and immune responses to stress.

Adaptation, Psychological↗

How does optimism suppress immunity? Evaluation of three affective pathways.

Studies have linked optimism to poorer immunity during difficult stressors. In this study, when 1st-year law students (N = 46) relocated to attend law school, reducing conflict among curricular and extracurricular goals, optimism predicted larger delayed-type hypersensitivity responses, indicating more robust in vivo cellular immunity. However, when students did not relocate, increasing goal conflict, optimism predicted smaller responses. Although this effect has been attributed to negative affect when difficult stressors violate optimistic expectancies, distress did not mediate optimism's effects on immunity. Alternative affective mediators related to engagement--engaged affect and fatigue--likewise failed to mediate optimism's effects, although all 3 types of affect independently influenced in vivo immunity. Alternative pathways include effort or self-regulatory depletion.

Adult↗

Optimal shapes of compact strings.

Optimal geometrical arrangements, such as the stacking of atoms, are of relevance in diverse disciplines. A classic problem is the determination of the optimal arrangement of spheres in three dimensions in order to achieve the highest packing fraction; only recently has it been proved that the answer for infinite systems is a face-centred-cubic lattice. This simply stated problem has had a profound impact in many areas, ranging from the crystallization and melting of atomic systems, to optimal packing of objects and the sub-division of space. Here we study an analogous problem--that of determining the optimal shapes of closely packed compact strings. This problem is a mathematical idealization of situations commonly encountered in biology, chemistry and physics, involving the optimal structure of folded polymeric chains. We find that, in cases where boundary effects are not dominant, helices with a particular pitch-radius ratio are selected. Interestingly, the same geometry is observed in helices in naturally occurring proteins.

Collagen↗

A prospective evaluation of optimal sampling theory in the determination of the steady-state pharmacokinetics of piperacillin in febrile neutropenic cancer patients.

We examined the use of optimal sampling theory in the determination of the pharmacokinetics of piperacillin in febrile, neutropenic cancer patients. Patients were studied prospectively as part of a randomized, double-blind clinical trial of piperacillin and amikacin versus imipenem and placebo. The results from the analysis of 5 optimal samples were compared with those derived from 15 concentration determinations (10 samples, with the 5 optimal samples assayed in duplicate). The use of a standard least-squares estimator as opposed to a bayesian estimator, with normal prior distributions placed on beta and serum clearance, was also examined. Finally, the use of duplicate determinations in improving the precision of parameter estimation was studied. Plasma concentrations obtained at time points determined by optimal sampling theory, when analyzed with a bayesian estimator, produced estimates of pharmacokinetic parameter values that were in good agreement with those derived from the 15-determination set. Duplicate assay did not improve the precision of parameter estimation. Estimation of plasma clearance was quite robust, irrespective of the estimator used, probably because this evaluation was performed at steady state. Optimal sampling theory is a promising technique that can be employed to determine patient-specific estimates of pharmacokinetic parameter values in target populations.

Adolescent↗

Optimality and evolutionary tuning of the expression level of a protein.

Different proteins have different expression levels. It is unclear to what extent these expression levels are optimized to their environment. Evolutionary theories suggest that protein expression levels maximize fitness, but the fitness as a function of protein level has seldom been directly measured. To address this, we studied the lac system of Escherichia coli, which allows the cell to use the sugar lactose for growth. We experimentally measured the growth burden due to production and maintenance of the Lac proteins (cost), as well as the growth advantage (benefit) conferred by the Lac proteins when lactose is present. The fitness function, given by the difference between the benefit and the cost, predicts that for each lactose environment there exists an optimal Lac expression level that maximizes growth rate. We then performed serial dilution evolution experiments at different lactose concentrations. In a few hundred generations, cells evolved to reach the predicted optimal expression levels. Thus, protein expression from the lac operon seems to be a solution of a cost-benefit optimization problem, and can be rapidly tuned by evolution to function optimally in new environments.

Adaptation, Physiological↗

Optimal reactive vaccination strategies for a foot-and-mouth outbreak in the UK.

Foot-and-mouth disease (FMD) in the UK provides an ideal opportunity to explore optimal control measures for an infectious disease. The presence of fine-scale spatio-temporal data for the 2001 epidemic has allowed the development of epidemiological models that are more accurate than those generally created for other epidemics and provide the opportunity to explore a variety of alternative control measures. Vaccination was not used during the 2001 epidemic; however, the recent DEFRA (Department for Environment Food and Rural Affairs) contingency plan details how reactive vaccination would be considered in future. Here, using the data from the 2001 epidemic, we consider the optimal deployment of limited vaccination capacity in a complex heterogeneous environment. We use a model of FMD spread to investigate the optimal deployment of reactive ring vaccination of cattle constrained by logistical resources. The predicted optimal ring size is highly dependent upon logistical constraints but is more robust to epidemiological parameters. Other ways of targeting reactive vaccination can significantly reduce the epidemic size; in particular, ignoring the order in which infections are reported and vaccinating those farms closest to any previously reported case can substantially reduce the epidemic. This strategy has the advantage that it rapidly targets new foci of infection and that determining an optimal ring size is unnecessary.

Animals↗