Optimal Vaccination Policies for an SIR Model with Limited Resources

The purpose of the paper is to use analytical method and optimization tool to suggest a vaccination program intensity for a basic SIR epidemic model with limited resources for vaccination. We show that there are two different scenarios for optimal vaccination strategies, and obtain analytical solutions for the optimal control problem that minimizes the total cost of disease under the assumption of daily vaccine supply being limited. These solutions and their corresponding optimal control policies are derived explicitly in terms of initial conditions, model parameters and resources for vaccination. With sufficient resources, the optimal control strategy is the normal Bang–Bang control. However, with limited resources, the optimal control strategy requires to switch to time-variant vaccination.     

Optimal Superpositioning of Flexible Molecule Ensembles

Analysis of the internal dynamics of a biological molecule requires the successful removal of overall translation and rotation. Particularly for flexible or intrinsically disordered peptides, this is a challenging task due to the absence of a well-defined reference structure that could be used for superpositioning. In this work, we started the analysis with a widely known formulation of an objective for the problem of superimposing a set of multiple molecules as variance minimization over an ensemble. A negative effect of this superpositioning method is the introduction of ambiguous rotations, where different rotation matrices may be applied to structurally similar molecules. We developed two algorithms to resolve the suboptimal rotations. The first approach minimizes the variance together with the distance of a structure to a preceding molecule in the ensemble. The second algorithm seeks for minimal variance together with the distance to the nearest neighbors of each structure. The newly developed methods were applied to molecular-dynamics trajectories and normal-mode ensembles of the Aβ peptide, RS peptide, and lysozyme. These new (to our knowledge) superpositioning methods combine the benefits of variance and distance between nearest-neighbor(s) minimization, providing a solution for the analysis of intrinsic motions of flexible molecules and resolving ambiguous rotations.     

Optimal Bioreactor Operational Policies for the Enzymatic Hydrolysis of Sugarcane Bagasse

The consolidation of the industrial production of second-generation (2G) bioethanol relies on the improvement of the economics of the process. Within this general scope, this paper addresses one aspect that impacts the costs of the biochemical route for producing 2G bioethanol: defining optimal operational policies for the reactor running the enzymatic hydrolysis of the C6 biomass fraction. The use of fed-batch reactors is one common choice for this process, aiming at maximum yields and productivities. The optimization problem for fed-batch reactors usually consists in determining substrate feeding profiles, in order to maximize some performance index. In the present control problem, the performance index and the system dynamics are both linear with respect to the control variable (the trajectory of substrate feed flow). Simple Michaelis–Menten pseudo-homogeneous kinetic models with product inhibition were used in the dynamic modeling of a fed-bath reactor, and two feeding policies were implemented and validated in bench-scale reactors processing pre-treated sugarcane bagasse. The first approach applied classical optimal control theory. The second policy was defined with the purpose of sustaining high rates of glucose production, adding enzyme (Accellerase® 1500) and substrate simultaneously during the reaction course. A methodology is described, which used economical criteria for comparing the performance of the reactor operating in successive batches and in fed-batch modes. Fed-batch mode was less sensitive to enzyme prices than successive batches. Process intensification in the fed-batch reactor led to glucose final concentrations around 200 g/L.     

Optimal Immunization and Isolation Policies for the GREENWOOD Chain-Binomial Epidemic Model

Optimal control for the GREENWOOD chain-binomial epidemic model is examined when control action is effected by immunization of susceptibles, isolation of infectives, or a combination of immunization and isolation in a way which minimizes the social cost of the epidemic and the cost of control over a given planning horizon. Optimal policies can be easily found for the deterministic version of the model. For the stochastic version, optimal policies are of much more complicated form and are only described in the situation when the probability of a given susceptible being infected is either small or large. This paper continues and corrects the work of DAYANANDA and HOGARTH (1977, 1978).     

Germination as an Unreliable Indicator of the Effectiveness of Cryopreservative Procedures for Imbibed Seeds

Tomato seeds of 49 per cent moisture content have been thawedfrom liquid nitrogen (—196 °C) with no loss of germinationfollowing both slow (12 °C min^–1) and rapid (850 °Cmin^–1) cooling, using 35 per cent dimethyl sulphoxide(DMSO) as a cryoprotectant. Lower concentrations of DMSO resultedin reduced germination. High proportions of seedlings from frozen/thawedseed failed to survive transplanting into soil, especially ifthey had been cooled rapidly. Seedlings grown to maturity afterthe slow cooling treatment showed a greater proportion of morphologicalabnormalities than a control population or those that had beenrapidly cooled. It is suggested that if cryopreservative techniques are to beevaluated for the storage of recalcitrant seeds, false impressionsof efficacy might be gained by reliance solely on germinationtesting. Cryopreservation, germination, recalcitrant seed     

EcoR II is an Unreliable Enzyme for Studies of CpNpG Methylation in shape Arabidopsis thaliana

Methylation patterns from cold-inducible and embryo-specific Arabidopsis thaliana gene promoter regions were investigated. Pairs of restriction enzymes sensitive and insensitive to methylation in the same recognition sequence were used to digest genomic DNA, and the methylation status was visualized by Southern hybridization. The pair BstN I/ EcoR II should detect CpNpG methylation due to the sensitivity of EcoR II to 5-methylcytosine in the second position in the recognition sequence (5-CC(A/T)GG-3). The pair Msp I/Hpa II will detect both CpNpG methylation and CpG methylation, since Msp I does not digest the recognition sequence (5-CCGG-3) when the first C residue is methylated, while Hpa II restriction is inhibited by methylation of either of the two C residues. EcoR II digestion studies suggested CpNpG methylation in all genes tested and demethylation after cold stress in all genes (including two control embryo-specific Lea genes not induced by low temperature). Control experiments indicated an unexpected pattern of methylation and low temperature demethylation in chloroplast genes. Additional control experiments, using the methylation sensitive enzyme, ScrF I (recognizing the sequence 5-CCNGG-3), disproved the presence of 5-methylcytosine in common sites not digested by EcoR II. (CpNpG-methylation was revealed in one ScrF I site in one gene and in Msp I/Hpa II sites in two genes. CpG methylation was not found in any gene tested.) Our study indicates that results obtained using EcoR II for DNA methylation studies should be interpreted with caution. The peculiarities of the EcoR II enzyme are further discussed.     

Pseudohypoglycemia: a Cause for Unreliable Finger-Stick Glucose Measurements

ObjectiveTo identify patients with an inaccurate diagnosis of hypoglycemia and discuss predisposing factors.MethodsWe describe our patient’s clinical presentation, laboratory work-up, hospital course, and follow-up and review similar cases from the literature.ResultsA 27-year-old woman with Raynaud phenomenon was admitted because of symptomatic hypoglycemia. Physical examination showed tremulousness, sweating, and the classic Raynaud color changes of the hands during episodic symptoms. A 72-hour fast revealed finger-stick capillary glucose values ranging from 32 to 45 mg/dL on multiple occasions, while concurrent plasma glucose values were consistently 1.5 to 2 times higher. Capillary measurements of glucose performed in the arms and legs at room temperature and after warming of each extremity disclosed an increase in glucose levels from a range of 35 to 52 mg/dL at room temperature to a range of 82 to 100 mg/dL after warming, confirming a discordance between capillary and venous blood results. The diagnosis of pseudohypoglycemia was made. Pseudohypoglycemia has been reported in patients with Raynaud phenomenon, peripheral vascular disease, and shock and may result from increased glucose extraction by the tissues because of low capillary flow and increased glucose transit time.ConclusionPseudohypoglycemia should be suspected in the setting of impaired microcirculation and can be confirmed by readily available means. (Endocr Pract. 2008;14:337-339)     

Optimal alphabets for an RNA world

Experiments have shown that the canonical AUCG genetic alphabet is not the only possible nucleotide alphabet. In this work we address the question ''is the canonical alphabet optimal?'' We make the assumption that the genetic alphabet was determined in the RNA world. Computational tools are used to infer the RNA secondary structure (shape) from a given RNA sequence, and statistics from RNA shapes are gathered with respect to alphabet size. Then, simulations based upon the replication and selection of fixed-sized RNA populations are used to investigate the effect of alternative alphabets upon RNA''s ability to step through a fitness landscape. These results show that for a low copy fidelity the canonical alphabet is fitter than two-, six- and eight-letter alphabets. In higher copy-fidelity experiments, six-letter alphabets outperform the four-letter alphabets, suggesting that the canonical alphabet is indeed a relic of the RNA world.     

Optimal Sequencing Rules for Some Large-Scale Flexible Manufacturing Problems Under the Manhattan and Chebychev Metrics

The purpose of this paper is to develop optimal tool partitioning policies and strip sequencing strategies for a class of flexible manufacturing problems. The problems under consideration involve a large number of operations to be performed by a series of tools on a two-dimensional object. For example, these operations could consist of drilling holes in a metallic sheet. Tools are arranged in a carousel or along a toolbar according to a predetermined sequence. Operations are performed by repeatedly moving the sheet to bring the hole locations under the tool. During each pass, as all operations involving a series of consecutive tools are executed, two main problems are to be solved: (1) how to move the sheet during each pass, (2) how to partition the tools into blocks of consecutive tools. A strip strategy is used to move the sheet. Given this policy, optimal strip widths and tool partitioning policies are determined jointly. Analytical solutions are derived under two metrics corresponding to different operating modes. A numerical example is provided.     

Optimal intervention for an epidemic model under parameter uncertainty

We will be concerned with optimal intervention policies for a continuous-time stochastic SIR (susceptible-->infective-->removed) model for the spread of infection through a closed population. In previous work on such optimal policies, it is common to assume that model parameter values are known; in reality, uncertainty over parameter values exists. We shall consider the effect upon the optimal policy of changes in parameter estimates, and of explicitly taking into account parameter uncertainty via a Bayesian decision-theoretic framework. We consider policies allowing for (i) the isolation of any number of infectives, or (ii) the immunisation of all susceptibles (total immunisation). Numerical examples are given to illustrate our results.     

Optimal foraging for multiple nutrients in an unpredictable environment

Foraging theory has typically been concerned with the acquisition of a single resource even though organisms from mammals to protozoa are capable of balancing their requirements for multiple resources. Existing theory concerning multiple nutrients from multiple foods does not predict the sequence of food selection. We constructed an optimisation model of the simplest case of two foods containing differing amounts of two nutrients. We begin with the well-supported assumption that reproductive value declines with the distance from target nutrient intake. We show that nutrient space divides into two distinct areas where the animal should exclusively consume one food or the other. The organism thus initially concentrates on one food type until the border between the areas is reached and then moves as closely as possible along the border to approach the target. This strategy is commonly observed in a range of organisms, suggesting that the assumed fitness function is common.     

Kinesin as an Electrostatic Machine

Kinesin and related motor proteins utilize ATP fuel to propel themselves along the external surface of microtubules in a processive and directional fashion. We show that the observed step-like motion is possible through time-varying charge distributions furnished by the ATP hydrolysis cycle while the static charge configuration on the microtubule provides the guide for motion. Thus, while the chemical hydrolysis energy induces appropriate local conformational changes, the motor translational energy is fundamentally electrostatic. Numerical simulations of the mechanical equations of motion show that processivity and directionality are direct consequences of the ATP-dependent electrostatic interaction between the different charge distributions of kinesin and the microtubule.     

Flexible cloglog links for binomial regression models as an alternative for imbalanced medical data

The complementary log-log link was originally introduced in 1922 to R. A. Fisher, long before the logit and probit links. While the last two links are symmetric, the complementary log-log link is an asymmetrical link without a parameter associated with it. Several asymmetrical links with an extra parameter were proposed in the literature over last few years to deal with imbalanced data in binomial regression (when one of the classes is much smaller than the other); however, these do not necessarily have the cloglog link as a special case, with the exception of the link based on the generalized extreme value distribution. In this paper, we introduce flexible cloglog links for modeling binomial regression models that include an extra parameter associated with the link that explains some unbalancing for binomial outcomes. For all cases, the cloglog is a special case or the reciprocal version loglog link is obtained. A Bayesian Markov chain Monte Carlo inference approach is developed. Simulations study to evaluate the performance of the proposed algorithm is conducted and prior sensitivity analysis for the extra parameter shows that a uniform prior is the most convenient for all models. Additionally, two applications in medical data (age at menarche and pulmonary infection) illustrate the advantages of the proposed models.     

Optimal conditions for levan formation by an overexpressed recombinant levansucrase

Summary A genetically modified levansucrase, which contained His-affinity tag in its C-terminal, was constructed by PCR reaction using two synthetic primers. This modified protein was produced up to 30 % in total cell protein of E. coli, and was purified by a one-step affinity chromatography. The optimum pH for levan production was pH 5 and the optimum temperature was 0 °C. The higher velocity of levan formation within shorter enzyme reaction times was achieved by increasing the levels of enzyme concentration. The optimal sucrose concentration for levan production was around 20 %. Under these conditions, more than 50 g levan/l was produced.     

Flexible mating patterns in an obligate brood parasite

Polygamous mating is expected to occur in obligate avian brood parasites because the lack of parental care reduces the need for a stable reproductive bond. Unlike nesting species, an absence of the constraints resulting from raising offspring might also favour a flexible mating system that adjusts to changing ecological conditions. Information on brood parasites' mating systems and their spatio‐temporal variation is, however, still scant. Here we analysed the genetic mating patterns of Great Spotted Cuckoos Clamator glandarius in two populations in northern and southern Spain and compared the results with those of previous studies. Parentage analyses showed high levels of polygamy in both populations that contrast with a prevalence of monogamy previously reported in the southern population. We suggest that the differences arise from an increase in population density, which in turn increases the probability of intraspecific encounters and therefore opportunities for mating. We also found that a greater number of mates increased the number of offspring produced, both in males and in females. The increase in offspring production in females might be the result of enhanced fertilization success during the lengthy laying period. Our data, combined with previous reports, demonstrate plasticity in the genetic mating patterns of the Great Spotted Cuckoo that may be associated with large fluctuations in population density.     

Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible,Robust and Optimal Decision-making

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.