Toward objective selection of representative microscope images

Scientists wishing to communicate the essential characteristics of a pattern (such as an immunofluorescence distribution) currently must make a subjective choice of one or two images to publish. We therefore developed methods for objectively choosing a typical image from a set, with emphasis on images from cell biology. The methods involve calculation of numerical features to describe each image, calculation of similarity between images as a distance in feature space, and ranking of images by distance from the center of the feature distribution. Two types of features were explored, image texture measures and Zernike polynomial moments, and various distance measures were utilized. Criteria for evaluating methods for assigning typicality were proposed and applied to sets of images containing more than one pattern. The results indicate the importance of using distance measures that are insensitive to the presence of outliers. For collections of images of the distributions of a lysosomal protein, a Golgi protein, and nuclear DNA, the images chosen as most typical were in good agreement with the conventional understanding of organelle morphologies. The methods described here have been implemented in a web server (http://murphylab.web.cmu.edu/services/TyplC).     

The objective structured interview for medical student selection

An objective structured interview is an integral part of the process of selecting and admitting applicants to study medicine at this university. During the nine years (to the end of 1986) that the interview has been used 1600 candidates were interviewed out of roughly 13 000 applicants, and from these, 584 students were admitted to the course. Analysis of the interview data was carried out based on two aspects of student progress: graduation with honours and failure to complete the course of study.The interview as a whole, and especially some of the subscales, appears to identify students who may fail to complete the course: it may also help to predict which students are likely to graduate with honours.     

Conserved metabolic regulatory functions of sirtuins

Silent information regulator 2 (Sir2) proteins, or sirtuins, are protein deacetylases/mono-ADP-ribosyltransferases found in organisms ranging from bacteria to humans. Their dependence on nicotinamide adenine dinucleotide (NAD+) links their activity to cellular metabolic status. In bacteria, the sirtuin CobB regulates the metabolic enzyme acetyl-coenzyme A (acetyl-CoA) synthetase. The earliest function of sirtuins therefore may have been regulation of cellular metabolism in response to nutrient availability. Recent findings support the idea that sirtuins play a pivotal role in metabolic control in higher organisms, including mammals. This review surveys evidence for an emerging role of sirtuins as regulators of metabolism in mammals.     

Physiological and metabolic functions of melatonin

Melatonin is a lipophilic hormone, mainly produced and secreted at night by the pineal gland. Melatonin synthesis is under the control of postganglionic sympathetic fibers that innervates the pineal gland. Melatonin acts via high affinity G protein-coupled membrane receptors. To date, three different receptor subtypes have been identified in mammals: MT1 (Mel 1a) and MT2 (Mel 1b) and a putative binding site called MT3. The chronobiotic properties of the hormone for resynchronization of sleep and circadian rhythms disturbances has been demonstrated both in animal models or in clinical trials. Several other physiological effects of melatonin in different peripheral tissues have been described in the past years. In this way, it has been demonstrated that the hormone is involved in the regulation of seasonal reproduction, body weight and energy balance. This contribution has been focused to review some of the physiological functions of melatonin as well as the role of the hormone in the regulation of energy balance and its possible involvement in the development of obesity.     

Scale for resource selection functions

Resource selection functions (RSFs) are statistical models defined to be proportional to the probability of use of a resource unit. My objective with this review is to identify how RSFs can be used to unravel the influence of scale in habitat selection. In wildlife habitat studies, including radiotelemetry, RSFs can be estimated using a variety of statistical methods, all of which can be used to explore the role of scale. All RSFs are bounded by the resolution of data and the spatial extent of the study area, but also allow predictor covariates to be measured at a variety of scales. Conditional logistic regression permits designs (e.g. matched case) that relate the process of habitat selection to a limited domain of resource units that might better characterize what is truly ‘available’ to the animal. Scale influences the process of habitat selection, e.g. food resources are often selected at fine spatial scales, whereas landscape patterns at much larger scales typically influence the location of home ranges. Scale also influences appropriate sampling in many ways: (1) heterogeneity might be obliterated (transmutation) if resolution or grain size is too large, (2) variance of habitat characteristics might be undersampled if extent or domain is too small, (3) timing and duration of observations can influence RSF models, and (d) both spatial and temporal autocorrelations can vary directly with the intensity of sampling. Using RSFs, researchers can examine habitat selection at multiple scales, and predictive models that bridge scales can be estimated. Using Geographical Information Systems, predictor covariates in RSF models can be measured at different scales easily so that the predictive ability of models at alternative spatial and temporal domains can be explored by the investigator. Identification of the scale that best explains the data can be evaluated by comparing alternative models using information‐theoretic metrics such as Akaike Information Criteria, and predictive capability of the models can be assessed using k‐fold cross validation.     

Fluctuating selection on basal metabolic rate

BMR (Basal metabolic rate) is an important trait in animal life history as it represents a significant part of animal energy budgets. BMR has also been shown to be positively related to sustainable work rate and maximal thermoregulatory capacity. To this date, most of the studies have focused on the causes of interspecific and intraspecific variation in BMR, and fairly little is known about the fitness consequences of different metabolic strategies. In this study, we show that winter BMR affects local survival in a population of wild blue tits (Cyanistes caeruleus), but that the selection direction differs between years. We argue that this fluctuating selection is probably a consequence of varying winter climate with a positive relation between survival and BMR during cold and harsh conditions, but a negative relation during mild winters. This fluctuating selection can not only explain the pronounced variation in BMR in wild populations, but will also give us new insights into how energy turnover rates can shape the life‐history strategies of animals. Furthermore, the study shows that the process of global warming may cause directional selection for a general reduction in BMR, affecting the general life‐history strategy on the population level.     

Peroxisomal beta-oxidation--a metabolic pathway with multiple functions

Fatty acid degradation in most organisms occurs primarily via the beta-oxidation cycle. In mammals, beta-oxidation occurs in both mitochondria and peroxisomes, whereas plants and most fungi harbor the beta-oxidation cycle only in the peroxisomes. Although several of the enzymes participating in this pathway in both organelles are similar, some distinct physiological roles have been uncovered. Recent advances in the structural elucidation of numerous mammalian and yeast enzymes involved in beta-oxidation have shed light on the basis of the substrate specificity for several of them. Of particular interest is the structural organization and function of the type 1 and 2 multifunctional enzyme (MFE-1 and MFE-2), two enzymes evolutionarily distant yet catalyzing the same overall enzymatic reactions but via opposite stereochemistry. New data on the physiological roles of the various enzymes participating in beta-oxidation have been gathered through the analysis of knockout mutants in plants, yeast and animals, as well as by the use of polyhydroxyalkanoate synthesis from beta-oxidation intermediates as a tool to study carbon flux through the pathway. In plants, both forward and reverse genetics performed on the model plant Arabidopsis thaliana have revealed novel roles for beta-oxidation in the germination process that is independent of the generation of carbohydrates for growth, as well as in embryo and flower development, and the generation of the phytohormone indole-3-acetic acid and the signal molecule jasmonic acid.     

Observing metabolic functions at the genome scale

Background  

High-throughput techniques have multiplied the amount and the types of available biological data, and for the first time achieving a global comprehension of the physiology of biological cells has become an achievable goal. This aim requires the integration of large amounts of heterogeneous data at different scales. It is notably necessary to extend the traditional focus on genomic data towards a truly functional focus, where the activity of cells is described in terms of actual metabolic processes performing the functions necessary for cells to live.     

Considering ecological dynamics in resource selection functions

1.  Describing distribution and abundance is requisite to exploring interactions between organisms and their environment. Recently, the resource selection function (RSF) has emerged to replace many of the statistical procedures used to quantify resource selection by animals.
2.  A RSF is defined by characteristics measured on resource units such that its value for a unit is proportional to the probability of that unit being used by an organism. It is solved using a variety of techniques, particularly the binomial generalized linear model.
3.  Observing dynamics in a RSF – obtaining substantially different functions at different times or places for the same species – alerts us to the varying ecological processes that underlie resource selection.
4.  We believe that there is a need for us to reacquaint ourselves with ecological theory when interpreting RSF models. We outline a suite of factors likely to govern ecologically based variation in a RSF. In particular, we draw attention to competition and density-dependent habitat selection, the role of predation, longitudinal changes in resource availability and functional responses in resource use.
5.  How best to incorporate governing factors in a RSF is currently in a state of development; however, we see promise in the inclusion of random as well as fixed effects in resource selection models, and matched case–control logistic regression.
6.  Investigating the basis of ecological dynamics in a RSF will allow us to develop more robust models when applied to forecasting the spatial distribution of animals. It may also further our understanding of the relative importance of ecological interactions on the distribution and abundance of species.     

Linear selection indices for non-linear profit functions

Summary Two methods of deriving linear selection indices for non-linear profit functions have been proposed. One is by linear approximation of profit, and another is the graphical method of Moav and Hill (1966). When profit is defined as the function of population means, the graphical method is optimal. In this paper, profit is defined as the function of the phenotypic values of individual animals; it is then shown that the graphical method is not generally optimal. We propose new methods for constructing selection indices. First, a numerical method equivalent to the graphical method is proposed. Furthermore, we propose two other methods using quadratic approximation of profit: one is based on Taylor series about means before selection, and the other is based on Tayler series about means after selection. Among these different methods, it is shown that the method using quadratic approximation based on Taylor series about means after selection is the most efficient.     

布朗葡萄藻的培养基选择及其产物代谢规律

通过对布朗葡萄藻分别在Chu13、Chu13×2和BG-11培养基中培养结果的比较,发现在气升式光照生物反应器中Chu13培养基最有利于布朗葡萄藻的生长和烃的合成,培养15d后,其生物量和粗烃质量分数分别为1.82g/L和58.7%;棕榈酸、油酸和亚麻酸是布朗葡萄藻的主要脂肪酸组成,Chu13培养获得的藻体不饱和脂肪酸比例最高。Chu13培养基中布朗葡萄藻代谢规律的研究表明:粗烃含量随着生物量的增加而逐渐增大,15d后粗烃产量达到最大值1.07g/L,不同生长周期烃的组成保持一致,布朗葡萄藻的烃主要由C33H56和C34H58组成;在布朗葡萄藻生长周期中,不饱和脂肪酸的比例显著上升,培养15d达到64%以上。     

Peroxisomes of alkane-utilizing yeasts metabolic functions and practical aspects

One of the most striking features of alkane-grown yeast cells is conspicuous appearance of peroxisomes in harmony with a high level of catalase. This unique phenomenon was first demonstrated in the authors′ laboratory, and the metabolic functions of peroxisomes in yeasts utilizing alkanes has been estabilished with intact peroxisomes isolated by density gradient centrifugation. The organelles participate in the degradation of fatty acids derived from alkanes to C²-units and the synthesis of gluconeogenic intermediates from C²-units. The abundant appearance of peroxisomes in alkane-utilizing cells has allowed successful production of several useful enzymes including catalase, D-amino acid oxidase, uricase, acyl-CoA oxidase etc. Yeast cells will be an excellent system for investigation the functions and development of peroxisomes because biogenesis of the organelles is induced only by transferring the cells into alkane medium from glucose or ethanol medium.     

Biological functions and metabolic fate of vitamin E revisited

Information accumulated lately has confirmed the essentiality of vitamin E for humans and provided a better understanding of its biological function and metabolic fate. The discovery of -tocopherol transfer protein, which preferentially binds to RRR--tocopherol, not only provides conclusive evidence of the essentiality of vitamin E for humans, but also sheds light on the superiority of RRR--tocopherol biologically over other isomers. The presence of tocopherol regeneration systems and multiple interdependent antioxidant systems is largely responsible for the lack of a widespread deficiency in humans and the difficulty to deplete vitamin E in the adult. The bulk of excess tocopherols consumed is excreted to feces unchanged or to urine with the side chain shortened but the chroman ring intact. The ability of dietary vitamin E to mediate mitochondrial superoxide generation affords a possible mode of action of vitamin E at the tissue levels. By decreasing the generation and/or the levels of reactive oxygen/nitrogen species, dietary vitamin E not only protects against oxidative damage, but also modulates the expression and/or activation of redox-sensitive biological response modifiers that regulate important cellular events.     

Improved protein structure selection using decoy-dependent discriminatory functions

Background  

A key component in protein structure prediction is a scoring or discriminatory function that can distinguish near-native conformations from misfolded ones. Various types of scoring functions have been developed to accomplish this goal, but their performance is not adequate to solve the structure selection problem. In addition, there is poor correlation between the scores and the accuracy of the generated conformations.     

Density-dependent selection migration model with non-monotone fitness functions

This paper studies the classical single locus, diallelic selection model with diffusion for a continuously reproducing population. The phase variables are population density and allele frequency (or allele density). The genotype fitness depend only on population density but include one-hump functions of the density variable. With mild assumptions on genotype fitnesses, we study the geometry of the nullclines and the asymptotic behavior of solutions of the selection model without diffusion. For the diffusion model with zero Neumann boundary conditions, we use this geometric information to show that if the initial data satisfy certain conditions then the corresponding solution to the reaction-diffusion equation converges to the spatially constant stable equilibrium which is closest to the initial data.Research partially supported by NSF grant DMS-8920597Research supported by funds provided by the USDA-Forest Service, Southeastern Forest Experiment Station, Pioneering (Population Genetics of Forest Trees) Research Unit, Raleigh, North Carolina     

A network-based method for target selection in metabolic networks

MOTIVATION: The lack of new antimicrobials, combined with increasing microbial resistance to old ones, poses a serious threat to public health. With hundreds of genomes sequenced, systems biology promises to help in solving this problem by uncovering new drug targets. RESULTS: Here, we propose an approach that is based on the mapping of the interactions between biochemical agents, such as proteins and metabolites, onto complex networks. We report that nodes and links in complex biochemical networks can be grouped into a small number of classes, based on their role in connecting different functional modules. Specifically, for metabolic networks, in which nodes represent metabolites and links represent enzymes, we demonstrate that some enzyme classes are more likely to be essential, some are more likely to be species-specific and some are likely to be both essential and specific. Our network-based enzyme classification scheme is thus a promising tool for the identification of drug targets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.