基于遗传算法特征选择的HBV再激活分类预测模型

探讨原发性肝癌患者精确放疗后乙型肝炎病毒(hepatitis b virus,HBV)再激活的危险特征和分类预测模型。提出基于遗传算法的特征选择方法,从原发性肝癌数据的初始特征集中选择HBV再激活的最优特征子集。建立贝叶斯和支持向量机的HBV再激活分类预测模型,并预测最优特征子集和初始特征集的分类性能。实验结果表明,基于遗传算法的特征选择提高了HBV再激活分类性能,最优特征子集的分类性能明显优于初始特征子集的分类性能。影响HBV再激活的最优特征子集包括:HBV DNA水平,肿瘤分期TNM,Child-Pugh,外放边界和全肝最大剂量。贝叶斯的分类准确性最高可达82.89%,支持向量机的分类准确性最高可达83.34%。     

Screening for peptide affinity ligands on CIM monoliths

Screening of peptide ligands for affinity chromatography usually involves incubation with the target protein in a batch system. In an additional step, peptides with fast binding kinetics have to be selected in respect to satisfactory performance under flow conditions on a support ensuring optimal three-dimensional presentation of the peptide. We have developed a rapid screening system based on peptide synthesis and screening on CIM((R)) disks. The disk size was minimized to fit into microplates usually applied for solid-phase extraction. In combination with a vacuum manifold, semi-automated peptide synthesis and screening for binding to a target protein under simulated chromatography conditions are possible. Various analytical methods can be applied for parallel and automated determination of the quantity, integrity, or activity of the target protein in the flow through or bound to the affinity support. This system also allows parallel screening for suitable chromatographic conditions like running buffer, washing, and elution conditions.     

Guidelines for medical practice: 1. The reasons why.

Various external special interest groups are promoting attempts to better measure and control the performance of the medical profession, primarily to restrain costs. We can neither afford to ignore the rising costs nor reject efforts by provincial licensing authorities to improve supervision of the quality of care. Furthermore, there is increasing public interest in the outcome of medical treatment and a suspicion that some care may be unnecessary or inappropriate. Much of what physicians do is not based on impeccable or complete scientific evidence, and we have not established a method whereby science can consistently be translated into practice. Optimal practice patterns must be defined to improve the quality of care and to maximize the efficiency with which scarce resources are used. Careful scientific evaluation of data is particularly necessary with the arrival of new drugs and technology. Sensible, flexible guidelines produced by appropriate panels will help promote improved practice. Rigid standards must be avoided to allow for individual consideration and scientific innovation. The recognized difficulties of influencing clinical practice by precept or education and the problems imposed by rapidly changing scientific knowledge are two hurdles to be overcome. Licensing bodies must identify and enforce minimal standards, but optimal practice patterns are better devised by a broader segment of the profession. Intervention by third-party payers, as is prevalent in the United States, intrudes upon physician autonomy and reduces access to care. Physicians must support the development of guidelines for optimal medical practice based on the best existing data and focused on improving the quality of care.     

Phylogeny of the nominotypical subgenus of Culex (Diptera: Culicidae): insights from analyses of anatomical data into interspecific relationships and species groups in an unresolved tree

The aim of this study was to produce the first objective and comprehensive phylogenetic analysis of the speciose subgenus Culex based on morphological data. We used implied and equally weighted parsimony methods to analyse a dataset comprised of 286 characters of the larval, pupal, and adult stages of 150 species of the subgenus and an outgroup of 17 species. We determined the optimal support by summing the GC supports for each MPC, selecting the cladograms with the highest supports to generate a strict consensus tree. We then collapsed the branches with GC support < 1 to obtain the ‘best’ topography of relationships. The analyses largely failed to resolve relationships among the species and the informal groups in which they are currently placed based on morphological similarities and differences. All analyses, however, support the monophyly of genus Culex. With the exception of the Atriceps Group, the analyses failed to find positive support for any of the informal species groups (monophyly of the Duttoni Group could not be established because only one of the two species of the group was included in the analyses). Since the analyses would seem to include sufficient data for phylogenetic reconstruction, lack of resolution appears to be the result of inadequate or conflicting character data, and perhaps incorrect homology assessments. Molecular and other biological data are needed to gain insights into the evolution of subgenus Culex. Nevertheless, we discuss the placement of several taxa in the current morphology-based classification of the subgenus based on insights realized during the study.

     

Predicting trophic relations in ecological networks: A test of the Allometric Diet Breadth Model

Few food web theory hypotheses/predictions can be readily tested using likelihoods of reproducing the data. Simple probabilistic models for food web structure, however, are an exception as their likelihoods were recently derived. Here I test the performance of a more complex model for food web structure that is grounded in the allometric scaling of interactions with body size and the theory of optimal foraging (Allometric Diet Breadth Model—ADBM). This deterministic model has been evaluated by measuring the fraction of trophic relations it correctly predicts. I contrasted this value with that produced by simpler models based on body sizes and found that the quantitative information on allometric scaling and optimal foraging does not significantly increase model fit. Also, I present a method to compute the p-value for the fraction of trophic interactions correctly predicted by the ADBM, or any other model, with respect to three probabilistic models. I find that the ADBM predicts significantly more links than random graphs, but other models can outperform it. Although optimal foraging and allometric scaling may improve our understanding of food webs, the ADBM needs to be modified or replaced to find support in the data.     

A diffusion model and optimal cell loading for immobilized cell biocatalysts

A diffusion model based on the random pore model is derived for immobilized cell biocatalysts and verified with 19 sets of experimental diffusion data. The predicted effective diffusivity relative to that for the support matrix reflects a quadratic dependence on the cell loading and contains a single parameter that depends on the intracellular diffusivity and the chemical partitioning coefficient. The model is used to predict optimal cell loadings that maximize the total reaction rate in an immobilized cell biocatalyst. A rule of thumb based on the diffusion model is obtained to the effect that the cell loading should be at least (1/3) for single reactions regardless of the kinetics and diffusional resistances. A means of calculating improved lower bounds is provided for cases where the cellular diffusional resistance is known but the kinetics are not. The optimal cell loadings for reversible first-order and for Michaelis-Menten kinetics are presented and demonstrated to be within the range of conditions of practical interest.     

The IGF-1 network in lung carcinoma therapeutics

Elucidation of the molecular events that underlie respiratory epithelium carcinogenesis still remains a largely unresolved issue. Various new therapeutic interventions are in advanced clinical testing or in daily clinical practice based on available preclinical findings. However, the complex molecular interplay that characterizes carcinogenesis requires further investigation to identify the pivotal factors and their interactions that might render the treatment of these malignancies more effective. Insulin-like growth factor-1 (IGF-1) network is a new important signalling cascade in lung carcinogenesis. Here, we integrate updated results that further support the significance of IGF-1 molecular circuitry in respiratory epithelium tumourigenesis, and pose future perspectives regarding its optimal use in the therapeutic field.     

Spurious 99% bootstrap and jackknife support for unsupported clades

Quantifying branch support using the bootstrap and/or jackknife is generally considered to be an essential component of rigorous parsimony and maximum likelihood phylogenetic analyses. Previous authors have described how application of the frequency-within-replicates approach to treating multiple equally optimal trees found in a given bootstrap pseudoreplicate can provide apparent support for otherwise unsupported clades. We demonstrate how a similar problem may occur when a non-representative subset of equally optimal trees are held per pseudoreplicate, which we term the undersampling-within-replicates artifact. We illustrate the frequency-within-replicates and undersampling-within-replicates bootstrap and jackknife artifacts using both contrived and empirical examples, demonstrate that the artifacts can occur in both parsimony and likelihood analyses, and show that the artifacts occur in outputs from multiple different phylogenetic-inference programs. Based on our results, we make the following five recommendations, which are particularly relevant to supermatrix analyses, but apply to all phylogenetic analyses. First, when two or more optimal trees are found in a given pseudoreplicate they should be summarized using the strict-consensus rather than frequency-within-replicates approach. Second jackknife resampling should be used rather than bootstrap resampling. Third, multiple tree searches while holding multiple trees per search should be conducted in each pseudoreplicate rather than conducting only a single search and holding only a single tree. Fourth, branches with a minimum possible optimized length of zero should be collapsed within each tree search rather than collapsing branches only if their maximum possible optimized length is zero. Fifth, resampling values should be mapped onto the strict consensus of all optimal trees found rather than simply presenting the ≥ 50% bootstrap or jackknife tree or mapping the resampling values onto a single optimal tree.     

The basal ganglia: learning new tricks and loving it

The field of basal ganglia research is exploding on every level - from discoveries at the molecular level to those based on human brain imaging. A remarkable series of new findings support the view that the basal ganglia are essential for some forms of learning-related plasticity. Other new findings are challenging some of the basic tenets of the field as it now stands. Combined with the new evidence on learning-related functions of the basal ganglia, these studies suggest that the basal ganglia are parts of a brain-wide set of adaptive neural systems promoting optimal motor and cognitive control.     

Insular carnivore biogeography: island area and mammalian optimal body size

Patterns of size variation in insular mammals have been used to support the claim that mammals have a single optimal body size. This hypothesis enjoys wide support, despite having been questioned on both theoretical and empirical grounds. It is claimed that species of optimal size maintain the highest population densities. Therefore these species are thought to inhabit the smallest islands, where larger and smaller species are generally absent. We sought such a pattern by testing how area affects the body sizes of the largest and smallest carnivore species on islands. Using data on carnivores from 322 islands, we found that the sizes of carnivores on small islands tend to be close to the order's mode. Furthermore, we found that the size distribution of carnivore species that inhabit islands resembles that of those whose range is entirely continental. We conclude that insular carnivores provide no support for theories proposing a single optimal size, and we suspect such theories are also flawed on theoretical grounds.     

Using highly efficient nonlinear experimental design methods for optimization of Lactococcus lactis fermentation in chemically defined media

Optimization of fermentation media and processes is a difficult task due to the potential for high dimensionality and nonlinearity. Here we develop and evaluate variations on two novel and highly efficient methods for experimental fermentation optimization. The first approach is based on using a truncated genetic algorithm with a developing neural network model to choose the best experiments to run. The second approach uses information theory, along with Bayesian regularized neural network models, for experiment selection. To evaluate these methods experimentally, we used them to develop a new chemically defined medium for Lactococcus lactis IL1403, along with an optimal temperature and initial pH, to achieve maximum cell growth. The media consisted of 19 defined components or groups of components. The optimization results show that the maximum cell growth from the optimal process of each novel method is generally comparable to or higher than that achieved using a traditional statistical experimental design method, but these optima are reached in about half of the experiments (73–94 vs. 161, depending on the variants of methods). The optimal chemically defined media developed in this work are rich media that can support high cell density growth 3.5–4 times higher than the best reported synthetic medium and 72% higher than a commonly used complex medium (M17) at optimization scale. The best chemically defined medium found using the method was evaluated and compared with other defined or complex media at flask‐ and fermentor‐scales. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Phylogeny of the Avian Family Ciconiidae (Storks) Based on CytochromebSequences and DNA–DNA Hybridization Distances

This study is a phylogenetic analysis of the avian family Ciconiidae, the storks, based on two molecular data sets: 1065 base pairs of sequence from the mitochondrial cytochromebgene and a complete matrix of single-copy nuclear DNA–DNA hybridization distances. Sixteen of the nineteen stork species were included in the cytochromebdata matrix, and fifteen in the DNA–DNA hybridization matrix. Both matrices included outgroups from the families Cathartidae (New World vultures) and Threskiornithidae (ibises, spoonbills). Optimal trees based on the two data sets were congruent in those nodes with strong bootstrap support. In the best-fit tree based on DNA–DNA hybridization distances, nodes defining relationships among very recently diverged species had low bootstrap support, while nodes defining more distant relationships had strong bootstrap support. In the optimal trees based on the sequence data, nodes defining relationships among recently diverged species had strong bootstrap support, while nodes defining basal relationships in the family had weak support and were incongruent among analyses. A combinable-component consensus of the best-fit DNA–DNA hybridization tree and a consensus tree based on different analyses of the cytochromebsequences provide the best estimate of relationships among stork species based on the two data sets.     

Direct and indirect effects of environmental temperature on the evolution of reproductive strategies: an information-theoretic approach

For ectotherms, environmental temperature affects the optimal size and number of offspring via multiple mechanisms. First, temperature influences the performance of offspring, which directly affects the optimal size of offspring. Second, temperature influences maternal body size, which indirectly affects the optimal size and/or number of offspring when larger females acquire more energetic resources or provide better parental care. Although traditional statistical approaches might distinguish the relative importance of these effects, an information-theoretic approach enables one to estimate effects more accurately by identifying the best evolutionary model in a set of candidate models. Here, we use the Akaike Information Criterion to calculate the likelihoods of seven path models, each derived from one or more optimality models of reproduction. Variation in reproductive traits among populations of lizards (Sceloporus undulatus) was used to quantify support for the models. Our results overwhelmingly supported a model based on an indirect effect of temperature that is mediated by maternal size. Path coefficients of this model were consistent with the hypotheses that, first, larger females can acquire more energy for reproduction and, second, the survival of offspring depends on both their size and their density. Our analyses exemplify how information theory can identify evolutionary hypotheses that merit experimental testing.     

Divergence and support among slightly suboptimal likelihood gene trees

Contemporary phylogenomic studies frequently incorporate two-step coalescent analyses wherein the first step is to infer individual-gene trees, generally using maximum-likelihood implemented in the popular programs PhyML or RAxML . Four concerns with this approach are that these programs only present a single fully resolved gene tree to the user despite potential for ambiguous support, insufficient phylogenetic signal to fully resolve each gene tree, inexact computer arithmetic affecting the reported likelihood of gene trees, and an exclusive focus on the most likely tree while ignoring trees that are only slightly suboptimal or within the error tolerance. Taken together, these four concerns are sufficient for RAxML and Phy ML users to be suspicious of the resulting (perhaps over-resolved) gene-tree topologies and (perhaps unjustifiably high) bootstrap support for individual clades. In this study, we sought to determine how frequently these concerns apply in practice to contemporary phylogenomic studies that use RAxML for gene-tree inference. We did so by re-analyzing 100 genes from each of ten studies that, taken together, are representative of many empirical phylogenomic studies. Our seven findings are as follows. First, the few search replicates that are frequently applied in phylogenomic studies are generally insufficient to find the optimal gene-tree topology. Second, there is often more topological variation among slightly suboptimal gene trees relative to the best-reported tree than can be safely ignored. Third, the Shimodaira–Hasegawa-like approximate likelihood ratio test is highly effective at identifying dubiously supported clades and outperforms the alternative approaches of relying on bootstrap support or collapsing minimum-length branches. Fourth, the bootstrap can, but rarely does, indicate high support for clades that are not supported amongst slightly suboptimal trees. Fifth, increasing the accuracy by which RA xML optimizes model-parameter values generally has a nominal effect on selection of optimal trees. Sixth, tree searches using the GTRCAT model were generally less effective at finding optimal known trees than those using the GTRGAMMA model. Seventh, choice of gene-tree sampling strategy can affect inferred coalescent branch lengths, species-tree topology and branch support.     

Optimal Sensor Placement in Smart Home Using Building Information Modeling: A Home Support Application

ObjectivesIn this paper, we present a plugin for the optimal placement of sensors in a smart home. Our approach includes the Building Information Modeling (BIM) which is a plan that describes the building layout.Material and methodsThis plugin uses the CSTB EveBim viewer for loading IFC file representing the digital building's model. We use then, a mathematical model based on a mixed integer linear program, to determine the optimal sensor placement according to building and sensors characteristics.ResultsThe results show the efficiency of the proposed algorithm and the developed plugin. We obtain an optimal solution after few seconds, and we show the sensor placement on the building digital model.ConclusionWe show the relevance of the proposed plugin to equip room of retirement home or ambient assisted living in order to identify occupant activity for home support application.     

The theory of tree bole and branch form

Summary Working from the general postulate that natural selection of plant form operates so as to maximize the survival potential of a species, this paper examines the hypothesis that the mechanical support of tree foliage must approach optimality in the use of wood, i.e., that tree stems and branches will have optimal form with respect to the amount of support tissue. Mathematical models of bole and branch form are presented, based on the proposition that either wind or gravity are the primary limiting factors for tree size and shape. Predictions of trunk and branch diameter as a function of tree size were tested with dimensional measurements ofPopulus tremuloides. The individual stems were selected from close-grown stands of differing ages. For small and intermediate trees, trunk diameter is such that stems have only 1.6 times as much wood as the minimum required to keep the tree from buckling under its own weight due to elastic instability. Branch diameters are shown to be close to the minimum required to maintain the spatial position of growing branches, as well as withstand wind forces. This minimal branch cost not only reduces the load which the stem must support against elastic instability, but allows the crown to flex in high winds. The flexing, in turn, reduces the drag force exerted by the wind on the trunk. Thus, the hypothesis that the observed tree form is an optimal design cannot be rejected on the basis of these results. Additional studies are planned with respect to optimal foliage distribution.     

Optimal control for selected cancer chemotherapy ODE models: a view on the potential of optimal schedules and choice of objective function

In this article, four different mathematical models of chemotherapy from the literature are investigated with respect to optimal control of drug treatment schedules. The various models are based on two different sets of ordinary differential equations and contain either chemotherapy, immunotherapy, anti-angiogenic therapy or combinations of these. Optimal control problem formulations based on these models are proposed, discussed and compared. For different parameter sets, scenarios, and objective functions optimal control problems are solved numerically with Bock’s direct multiple shooting method.In particular, we show that an optimally controlled therapy can be the reason for the difference between a growing and a totally vanishing tumor in comparison to standard treatment schemes and untreated or wrongly treated tumors. Furthermore, we compare different objective functions. Eventually, we propose an optimization-driven indicator for the potential gain of optimal controls. Based on this indicator, we show that there is a high potential for optimization of chemotherapy schedules, although the currently available models are not yet appropriate for transferring the optimal therapies into medical practice due to patient-, cancer-, and therapy-specific components.     

The efficiency of different search strategies in estimating parsimony jackknife,bootstrap, and Bremer support

Background  

For parsimony analyses, the most common way to estimate confidence is by resampling plans (nonparametric bootstrap, jackknife), and Bremer support (Decay indices). The recent literature reveals that parameter settings that are quite commonly employed are not those that are recommended by theoretical considerations and by previous empirical studies. The optimal search strategy to be applied during resampling was previously addressed solely via standard search strategies available in PAUP*. The question of a compromise between search extensiveness and improved support accuracy for Bremer support received even less attention. A set of experiments was conducted on different datasets to find an empirical cut-off point at which increased search extensiveness does not significantly change Bremer support and jackknife or bootstrap proportions any more.     

How to best support sit to stand transfers of geriatric patients: Motion optimization under external forces for the design of physical assistive devices

Sit to stand (STS) transfers form a challenging type of motion, in particular for geriatric patients. Physical assistive devices that are built to enhance the mobility of this class of patients therefore must especially be able to support STS transfers. This paper presents a method to predict geriatric STS movements and compute the best possible actions by external devices to support these movements. We treat three types of active devices that act on different parts of the patient’s body and provide different levels of support. Our approach is based on the solution of optimal control problems for a whole-body multi-phase model of humans standing up from sitting to upright position. Computations are performed for percentiles 20/50/80 of male and female geriatric population. The actions of the external devices are simulated by external forces at moving contact points, which are all determined by the optimization, simultaneously with the expected movements and joint torques of the patients. The results serve as inputs for design optimizations of the different device types.