The influence of stomach distention on feeding in the nudibranch mollusk Melibe leonina

Although research on satiation has revealed much about the effect of sensory inputs on motivational state, we have yet to fully understand exactly how satiating signals influence the neural circuits underlying specific behaviors. One organism that is well suited for addressing this question is the nudibranch Melibe leonina, because its feeding activity is easily quantified, it has translucent skin that makes the stomach easy to observe, and it has large, identifiable neurons that are very suitable for subsequent analysis of the neural correlates of satiation. In this study our goal was to document the time course of satiation in Melibe, and determine if stomach distention contributes to satiation. When exposed to brine shrimp (Artemia), Melibe immediately commenced stereotypic oral hood movements to capture prey, and continued to do so for approximately five hours. Individuals eventually stopped, despite the continued presence of food, and the slowing and eventual termination of oral hood closures was correlated with distension of the stomach caused by the ingested Artemia. We obtained further evidence that stomach distension is one of the underlying causes of satiation by injecting artificial non-nutritive food into the stomach, and by cutting open part of the stomach wall to prevent it from filling and distending. The first treatment caused satiation to occur more rapidly, while the second treatment delayed satiation. Both results demonstrate that in Melibe stomach distention has a major impact on the motivation to feed. These findings provide the framework for subsequent studies designed to determine precisely how stomach distention influences feeding circuits.     

Solution structures of purine base analogues 9-deazaguanine and 9-deazahypoxanthine

Deaza analogues of nucleobases are potential drugs against infectious diseases caused by parasites. A caveat is that apart from binding their target parasite enzymes, they also bind and inhibit enzymes of the host. In order to design derivatives of deaza analogues which specifically bind target enzymes, knowledge of their molecular structure, protonation state, and predominant tautomers at physiological conditions is essential. We have employed resonance Raman spectroscopy at an excitation wavelength of 260 nm, to decipher solution structure of 9-deazaguanine (9DAG) and 9-deazahypoxanthine (9DAH). These are analogues of guanine and hypoxanthine, respectively, and have been exploited to study static complexes of nucleobase binding enzymes. Such enzymes are known to perturb pK_a of their ligands, and thus, we also determined solution structures of these analogues at two, acidic and alkaline, pH. Structure of each possible protonation state and tautomer was computed using density functional theoretical calculations. Species at various pHs were identified based on isotopic shifts in experimental wavenumbers and by comparing these shifts with corresponding computed isotopic shifts. Our results show that at physiological pH, N1 of pyrimidine ring in 9DAG and 9DAH bears a proton. At lower pH, N3 is place of protonation, and at higher pH, deprotonation occurs at N1 position. The proton at N7 of purine ring remains intact even at pH 12.5. We have further compared these results with naturally occurring nucleotides. Our results identify key vibrational modes which can report on hydrogen bonding interactions, protonation and deprotonation in purine rings upon binding to the active site of enzymes.     

Modelling various sculptures in the Cretaceous bivalve Inoceramus hobetsensis

The geometry of the external shell sculpture in the Late Cretaceous inoceramid bivalve Inoceramus hobetsensis Nagao & Matsumoto, 1939 was studied both empirically and theoretically. A large sample, collected from the Upper Cretaceous of Hokkaido, Japan, shows remarkably high intraspecific variation in the shell sculptural pattern. Quasi-commarginal ribs, slightly oblique to the external growth increments, occur in some specimens. These sculptures are commonly irregular in strength and spacing, and their features are successfully modelled by computer simulations when the commarginal ribs are superposed with nearly concentric divaricate rib. Computer models indicate that the divergent sculpture element, often found in other inoceramids, was present throughout the evolution of I. hobetsensis and was developing in the evolutionary lineage from I. hobetsensis nonsulcatus to I. hobetsensis hobetsensis, although it was only weakly expressed. The results also suggest that some apparently distinct sculptural patterns of I. hobetsensis are the result of minor changes in the morphogenetic program.     

Pervasive selection or is it…? why are FST outliers sometimes so frequent?

It is now common for population geneticists to estimate F_ST for a large number of loci across the genome, before testing for selected loci as being outliers to the F_ST distribution. One surprising result of such F_ST scans is the often high proportion (>1% and sometimes >10%) of outliers detected, and this is often interpreted as evidence for pervasive local adaptation. In this issue of Molecular Ecolog, Fourcade et al. ( 2013 ) observe that a particularly high rate of F_ST outliers has often been found in river organisms, such as fishes or damselflies, despite there being no obvious reason why selection should affect a larger proportion of the genomes of these organisms. Using computer simulations, Fourcade et al. ( 2013 ) show that the strong correlation in co‐ancestry produced in long one‐dimensional landscapes (such as rivers, valleys, peninsulas, oceanic ridges or coastlines) greatly increases the neutral variance in F_ST, especially when the landscape is further reticulated into fractal networks. As a consequence, outlier tests have a high rate of false positives, unless this correlation can be taken into account. Fourcade et al.'s study highlights an extreme case of the general problem, first noticed by Robertson ( 1975a , b ) and Nei & Maruyama ( 1975 ), that correlated co‐ancestry inflates the neutral variance in F_ST when compared to its expectation under an island model of population structure. Similar warnings about the validity of outlier tests have appeared regularly since then but have not been widely cited in the recent genomics literature. We further emphasize that F_ST outliers can arise in many different ways and that outlier tests are not designed for situations where the genetic architecture of local adaptation involves many loci.     

Optimization of the hydrolysis of lignocellulosic residues by using radial basis functions modeling and particle swarm optimization

The concentrations of glucose and total reducing sugars obtained by chemical hydrolysis of three different lignocellulosic feedstocks were maximized. Two response surface methodologies were applied to model the amount of sugars produced: (1) classical quadratic least-squares fit (QLS), and (2) artificial neural networks based on radial basis functions (RBF). The results obtained by applying RBF were more reliable and better statistical parameters were obtained. Depending on the type of biomass, different results were obtained. Improvements in fit between 35% and 55% were obtained when comparing the coefficients of determination (R²) computed for both QLS and RBF methods. Coupling the obtained RBF models with particle swarm optimization to calculate the global desirability function, allowed to perform multiple response optimization. The predicted optimal conditions were confirmed by carrying out independent experiments.     

Core concepts of spatial prioritisation in systematic conservation planning

Systematic conservation planning (SCP) is a field of conservation biology concerned with delivering on‐the‐ground actions that achieve conservation goals. It describes a set of operational models that cover both design and implementation of conservation, with a strong focus on mobilising the collective action typically required to implement conservation. SCP, as it was originally described, was composed of six different stages: collection of data, identification of conservation goals, evaluation of the existing protected area network, design of expansions, implementation of conservation action, and long‐term maintenance of biodiversity in the network. Since then, the operational model has been expanded into several different variants. Conservation actions applied inside SCP include establishment and expansion of reserve networks and allocation of habitat restoration and management. Within the broader context of SCP, there is a fundamental biogeographic‐economic analysis frequently called spatial conservation prioritisation or conservation assessment, which is used for identifying where important areas for biodiversity are and how conservation goals might be achieved efficiently. Here, we review the usage and meaning of the 12 biogeographic‐economic core concepts of SCP: adequacy, complementarity, comprehensiveness, effectiveness, efficiency, flexibility, irreplaceability, replacement cost, representation, representativeness, threat, and vulnerability. Some of the concepts have clear definitions whereas others may have alternative and possibly conflicting definitions. With a comprehensive literature review literature, we elucidate the historical backgrounds of these concepts, the first definitions and usages, alternative later definitions, key applications, and prior reviews. This review reduces linguistic uncertainty in the application of SCP. Since SCP is a global activity with a multitude of different stakeholders involved, it is vital that those involved can speak the same language. Through these concepts, this review serves as a source of information about the historical development of SCP. It provides a comprehensive review for anyone wishing to understand the key concepts of spatial prioritisation within SCP.     

Background selection and FST: Consequences for detecting local adaptation

Background selection is a process whereby recurrent deleterious mutations cause a decrease in the effective population size and genetic diversity at linked loci. Several authors have suggested that variation in the intensity of background selection could cause variation in F_ST across the genome, which could confound signals of local adaptation in genome scans. We performed realistic simulations of DNA sequences, using recombination maps from humans and sticklebacks, to investigate how variation in the intensity of background selection affects F_ST and other statistics of population differentiation in sexual, outcrossing species. We show that, in populations connected by gene flow, Weir and Cockerham's (1984; Evolution, 38 , 1358) estimator of F_ST is largely insensitive to locus‐to‐locus variation in the intensity of background selection. Unlike F_ST, however, d_XY is negatively correlated with background selection. Moreover, background selection does not greatly affect the false‐positive rate in F_ST outlier studies in populations connected by gene flow. Overall, our study indicates that background selection will not greatly interfere with finding the variants responsible for local adaptation.     

Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low‐cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.     

Physiological dynamics,reproduction‐maintenance allocations,and life history evolution

Allocation of resources to competing processes of growth, maintenance, or reproduction is arguably a key process driving the physiology of life history trade‐offs and has been shown to affect immune defenses, the evolution of aging, and the evolutionary ecology of offspring quality. Here, we develop a framework to investigate the evolutionary consequences of physiological dynamics by developing theory linking reproductive cell dynamics and components of fitness associated with costly resource allocation decisions to broader life history consequences. We scale these reproductive cell allocation decisions to population‐level survival and fecundity using a life history approach and explore the effects of investment in reproduction or tissue‐specific repair (somatic or reproductive) on the force of selection, reproductive effort, and resource allocation decisions. At the cellular level, we show that investment in protecting reproductive cells increases fitness when reproductive cell maturation rate is high or reproductive cell death is high. At the population level, life history fitness measures show that cellular protection increases reproductive value by differential investment in somatic or reproductive cells and the optimal allocation of resources to reproduction is moulded by this level of investment. Our model provides a framework to understand the evolutionary consequences of physiological processes underlying trade‐offs and highlights the insights to be gained from considering fitness at multiple levels, from cell dynamics through to population growth.