Profiling Auspicious Butyrylcholinesterase Inhibitory Activity of Two Herbal Molecules: Hyperforin and Hyuganin C

Cholinergic therapy based on cholinesterase (ChE) inhibitory drugs is the mainstay for the treatment of Alzheimer's disease. Therefore, an extensive research has been continuing for the discovery of drug candidates as inhibitors of acetyl‐ and butyrylcholinesterase. In this study, two natural molecules, e. g. hyperforin and hyuganin C were tested in vitro for their AChE and BChE inhibitory activity. Both of the compounds were ineffective against AChE, whereas hyperforin (IC₅₀=141.60±3.39 μm ) and hyuganin C (IC₅₀=38.86±1.69 μm ) were found to be the highly active inhibitors of BChE as compared to galantamine (IC₅₀=46.58±0.91 μm ) which was used as the reference. Then, these molecules were further proceeded to molecular docking experiments in order to establish their interactions at the active site of BChE. The molecular docking results indicated that both of them are able to block the access to key residues in the catalytic triad of the enzyme, while they complement some of the hydrophobic residues of the cavity, what is consistent with our in vitro data. While both compounds were predicted as mutagenic, only hyuganin C showed hepatotoxicity in in silico analysis. According to whole outcomes that we obtained, particularly hyuganin C besides hyperforin are the promising BChE inhibitors, which can be the promising compounds for AD therapy.     

Spatial scaling of population synchrony in marine fish depends on their life history

The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship between spatial scaling in population dynamics and species position along the slow‐fast continuum of life history variation. Specifically, we explored how generation time, growth rate and mortality rate predicted the spatial scaling of abundance and yearly changes in abundance of eight marine fish species. Our results show that population dynamics of species' with ‘slow’ life histories are synchronised over greater distances than those of species with ‘fast’ life histories. These findings provide evidence for a relationship between the position of the species along the life history continuum and population dynamics in space, showing that the spatial distribution of abundance may be related to life history characteristics.     

Accounting for interspecific competition and age structure in demographic analyses of density dependence improves predictions of fluctuations in population size

Understanding species coexistence has long been a major goal of ecology. Coexistence theory for two competing species posits that intraspecific density dependence should be stronger than interspecific density dependence. Great tits and blue tits are two bird species that compete for food resources and nesting cavities. On the basis of long‐term monitoring of these two competing species at sites across Europe, combining observational and manipulative approaches, we show that the strength of density regulation is similar for both species, and that individuals have contrasting abilities to compete depending on their age. For great tits, density regulation is driven mainly by intraspecific competition. In contrast, for blue tits, interspecific competition contributes as much as intraspecific competition, consistent with asymmetric competition between the two species. In addition, including age‐specific effects of intra‐ and interspecific competition in density‐dependence models improves predictions of fluctuations in population size by up to three times.     

An integrated population model for a long‐lived ungulate: more efficient data use with Bayesian methods

We develop an integrated population model for Svalbard reindeer Rangifer tarandus platyrhynchus, and demonstrate how this type of model can be used to extract more information from the data and separate different sources of variability in population estimates. Our model combines individual mark–recapture data with population counts and harvesting data within a Bayesian model framework, and accounts for observation error, environmental and demographic stochasticity, and age structure. From this model we obtain annual estimates of age‐specific population size, survival and fecundity. The model provides estimates of age structure at a finer scale than that found in the census data, and enables us to estimate survival for the period before calves are first caught and marked, i.e. before they enter the individual mark–recapture data. The modeling framework provides an improved approach to studying age‐structured populations that are imperfectly censused and where the demography of only a sample of individuals is known. We use data from independent censuses of the same population to evaluate population estimates obtained from the model, and show that it is successful at correcting for different types of observation error. Based on our model results, we suggest that allocating resources to the collection of supplementary mark–recapture data could improve the reliability of population projections more than making regular population censuses as exhaustive as possible. Our work demonstrates how integrated Bayesian population modeling can be used to increase the amount of information extracted from collections of data, identifying and disentangling sources of variation in individual performance and population size. This represents an important step towards increasing the predictive ability of population growth models for long‐lived species experiencing changes in environmental conditions and harvesting regimes.     

EVOLUTION IN FLUCTUATING ENVIRONMENTS: DECOMPOSING SELECTION INTO ADDITIVE COMPONENTS OF THE ROBERTSON–PRICE EQUATION

We analyze the stochastic components of the Robertson–Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity.     

Uukuniemi Phlebovirus Assembly and Secretion Leave a Functional Imprint on the Virion Glycome

Uukuniemi virus (UUKV) is a model system for investigating the genus Phlebovirus of the Bunyaviridae. We report the UUKV glycome, revealing differential processing of the Gn and Gc virion glycoproteins. Both glycoproteins display poly-N-acetyllactosamines, consistent with virion assembly in the medial Golgi apparatus, whereas oligomannose-type glycans required for DC-SIGN-dependent cellular attachment are predominant on Gc. Local virion structure and the route of viral egress from the cell leave a functional imprint on the phleboviral glycome.     

Comparative analysis of amplified fragment length polymorphism and pulsed field gel electrophoresis in a hospital outbreak and subsequent endemicity of ampicillin-resistant Enterococcus faecium

Reliable molecular methods for determination of relatedness between bacterial isolates have become increasingly important to evaluate outbreaks and endemic situations with nosocomial pathogens. In the present study Simpson's index of diversity with calculated confidence intervals was used to compare amplified fragment length polymorphism (AFLP) and pulsed field gel electrophoresis (PFGE) analysis of a hospital outbreak of ampicillin-resistant Enterococcus faecium and subsequent endemicity. The outbreak, in a Norwegian tertiary hospital, of infections caused by these enterococci started in 1995 and increased in 1996 after which the situation turned endemic. The purpose of this study was to compare the two methods in this setting and to determine the length of time during an outbreak that these methods are sufficiently valid to be of value for hospital infection control efforts. One hundred and sixty clinical isolates from urine specimens collected during the period 1995-1999 were included. The findings indicate that PFGE and AFLP are equally discriminative and could in this setting be used for typing purposes over the whole 5-year period.     

Effects of speech clarity on recognition memory for spoken sentences

Extensive research shows that inter-talker variability (i.e., changing the talker) affects recognition memory for speech signals. However, relatively little is known about the consequences of intra-talker variability (i.e. changes in speaking style within a talker) on the encoding of speech signals in memory. It is well established that speakers can modulate the characteristics of their own speech and produce a listener-oriented, intelligibility-enhancing speaking style in response to communication demands (e.g., when speaking to listeners with hearing impairment or non-native speakers of the language). Here we conducted two experiments to examine the role of speaking style variation in spoken language processing. First, we examined the extent to which clear speech provided benefits in challenging listening environments (i.e. speech-in-noise). Second, we compared recognition memory for sentences produced in conversational and clear speaking styles. In both experiments, semantically normal and anomalous sentences were included to investigate the role of higher-level linguistic information in the processing of speaking style variability. The results show that acoustic-phonetic modifications implemented in listener-oriented speech lead to improved speech recognition in challenging listening conditions and, crucially, to a substantial enhancement in recognition memory for sentences.     

An efficient multivariate approach for estimating preference when individual observations are dependent

1. We discuss aspects of resource selection based on observing a given vector of resource variables for different individuals at discrete time steps. A new technique for estimating preference of habitat characteristics, applicable when there are multiple individual observations, is proposed. 2. We first show how to estimate preference on the population and individual level when only a single site- or resource component is observed. A variance component model based on normal scores in used to estimate mean preference for the population as well as the heterogeneity among individuals defined by the intra-class correlation. 3. Next, a general technique is proposed for time series of observations of a vector with several components, correcting for the effect of correlations between these. The preference of each single component is analyzed under the assumption of arbitrarily complex selection of the other components. This approach is based on the theory for conditional distributions in the multi-normal model. 4. The method is demonstrated using a data set of radio-tagged dispersing juvenile goshawks and their site characteristics, and can be used as a general tool in resource or habitat selection analysis.     

Assessment of species diversity from species abundance distributions at different localities

We show how the spatial structure of species diversity can be analyzed using the correlation between the log abundances of the species in the communities, assuming that two communities at different localities can be described by a bivariate lognormal species abundance distribution. A useful property of this approach is that the log abundances of the species at two localities can be considered as samples from a bivariate normal distribution defined by only five parameters. The variances and the correlation can be estimated by maximum likelihood methods even if there is no information about the sampling intensity and the number of unobserved species. This method also enables estimation of over-dispersion in the sampling relative to a Poisson distribution that allows sampling adjustment of the estimate of β-diversity. Furthermore, we also obtain a partitioning of species diversity into additive components of α-, β- and γ-diversity. For instance, if the correlation between the log abundances of the species is close to one, the same species will be common and rare in the two communities and the β-diversity will be low. We illustrate this approach by analysing similarities of communities of rare and endangered species of oak-living beetles in south-eastern Norway. The number of recorded species was estimated to be only 48.1% of the total number of species actually present in these communities. The correlations among communities dropped rather quickly with distance with a scaling of order 200 km. This illustrates large spatial heterogeneity in species composition, which should be accounted for in the design of schemes of such devices for assessing species diversity in these habitat-types.