Evaluation of the Surface Roughness of Cystine Stones Using a Visible Laser Diode Scattering Approach

To understand the processes of fragmentation and the chemical reactivity of solids, proper characterization of surface topography is crucial. This paper describes a non-destructive technique of quantifying the surface roughness of cystine renal stones, using visible laser diode scattering and fractal geometry. Fragments of cystine stones were mounted on microscope slides and coated by a carbon-sputtering apparatus. The slides were placed under a dynamic active-vision system, using a visible laser diode to measure three-dimensional surface coordinates. The data obtained were analyzed by fractal geometry. Surface fractal dimensions were determined by the variation method. The results showed that the surface of a compact-size sample can be evaluated quantitatively. The technique is valuable for the accurate presentation of surfaces in three dimensions

Biodiversity loss through speciation collapse: Mechanisms, warning signals, and possible rescue

Speciation is the process that generates biodiversity, but recent empirical findings show that it can also fail, leading to the collapse of two incipient species into one. Here, we elucidate the mechanisms behind speciation collapse using a stochastic individual-based model with explicit genetics. We investigate the impact of two types of environmental disturbance: deteriorated visual conditions, which reduce foraging ability and impede mate choice, and environmental homogenization, which restructures ecological niches. We find that: (1) Species pairs can collapse into a variety of forms including new species pairs, monomorphic or polymorphic generalists, or single specialists. Notably, polymorphic generalist forms may be a transient stage to a monomorphic population; (2) Environmental restoration enables species pairs to re-emerge from single generalist forms, but not from single specialist forms; (3) Speciation collapse is up to four orders of magnitude faster than speciation, while the re-emergence of species pairs can be as slow as de novo speciation; (4) While speciation collapse can be predicted from either demographic, phenotypic, or genetic signals, observations of phenotypic changes allow the most general and robust warning signal of speciation collapse. We conclude that factors altering ecological niches can reduce biodiversity by reshaping the ecosystem's evolutionary attractors

Effect of Dietary Components on Larval Life History Characteristics in the Medfly (Ceratitis capitata: Diptera, Tephritidae)

Background: The ability to respond to heterogenous nutritional resources is an important factor in the adaptive radiation of insects such as the highly polyphagous Medfly. Here we examined the breadth of the Medfly’s capacity to respond to different developmental conditions, by experimentally altering diet components as a proxy for host quality and novelty. Methodology/Principal Findings: We tested responses of larval life history to diets containing protein and carbohydrate components found in and outside the natural host range of this species. A 40% reduction in the quantity of protein caused a significant increase in egg to adult mortality by 26.5%±6% in comparison to the standard baseline diet. Proteins and carbohydrates had differential effects on larval versus pupal development and survival. Addition of a novel protein source, casein (i.e. milk protein), to the diet increased larval mortality by 19.4%±3% and also lengthened the duration of larval development by 1.93±0.5 days in comparison to the standard diet. Alteration of dietary carbohydrate, by replacing the baseline starch with simple sugars, increased mortality specifically within the pupal stage (by 28.2%±8% and 26.2%±9% for glucose and maltose diets, respectively). Development in the presence of the novel carbohydrate lactose (milk sugar) was successful, though on this diet there was a decrease of 29.8±1.6 µg in mean pupal weight in comparison to pupae reared on the baseline diet. Conclusions: The results confirm that laboratory reared Medfly retain the ability to survive development through a wide range of fluctuations in the nutritional environment. We highlight new facets of the responses of different stages of holometabolous life histories to key dietary components. The results are relevant to colonisation scenarios and key to the biology of this highly invasive species

NOMAD spectrometer on the ExoMars trace gas orbiter mission: part 2—design, manufacturing, and testing of the ultraviolet and visible channel

NOMAD is a spectrometer suite on board the ESA/Roscosmos ExoMars Trace Gas Orbiter, which launched in March 2016. NOMAD consists of two infrared channels and one ultraviolet and visible channel, allowing the instrument to perform observations quasi-constantly, by taking nadir measurements at the day- and night-side, and during solar occultations. Here, in part 2 of a linked study, we describe the design, manufacturing, and testing of the ultraviolet and visible spectrometer channel called UVIS. We focus upon the optical design and working principle where two telescopes are coupled to a single grating spectrometer using a selector mechanism

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

<p>Abstract</p> <p>Background</p> <p>We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex <it>i </it>and all other vertices.</p> <p>Results</p> <p>We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time) that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined.</p> <p>Conclusion</p> <p>Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically significant. Simple filtering schemes substantially improve the method's predicted power. Moreover, no clear effect on performance is observed when comparing ligated and unligated structures. Similarly, the CC prediction results are robust to slight structural perturbations from molecular dynamics simulation.</p

Surface-Enhanced Nitrate Photolysis on Ice

Heterogeneous nitrates photolysis is the trigger for many chemical processes occurring in the polar boundary layer and is widely believed to occur in a quasi-liquid layer (QLL) at the surface of ice. The dipole forbidden character of the electronic transition relevant to boundary layer atmospheric chemistry and the small photolysis/photoproducts quantum yields in ice (and in water) may confer a significant enhancement and interfacial specificity to this important photochemical reaction at the surface of ice. Using amorphous solid water films at cryogenic temperatures as models for the disordered interstitial air/ice interface within the snowpack suppresses the diffusive uptake kinetics thereby prolonging the residence time of nitrate anions at the surface of ice. This approach allows their slow heterogeneous photolysis kinetics to be studied providing the first direct evidence that nitrates adsorbed onto the first molecular layer at the surface of ice are photolyzed more effectively than those dissolved within the bulk. Vibrational spectroscopy allows the ~3-fold enhancement in photolysis rates to be correlated with the nitrates’ distorted intramolecular geometry thereby hinting at the role played by the greater chemical heterogeneity in their solvation environment at the surface of ice than in the bulk. A simple 1D kinetic model suggests 1-that a 3(6)-fold enhancement in photolysis rate for nitrates adsorbed onto the ice surface could increase the photochemical NO[subscript 2] emissions from a 5(8) nm thick photochemically active interfacial layer by 30%(60)%, and 2-that 25%(40%) of the NO[subscript 2] photochemical emissions to the snowpack interstitial air are released from the top-most molecularly thin surface layer on ice. These findings may provide a new paradigm for heterogeneous (photo)chemistry at temperatures below those required for a QLL to form at the ice surface

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

Testing for Associations between Loci and Environmental Gradients Using Latent Factor Mixed Models

Adaptation to local environments often occurs through natural selection acting on a large number of loci, each having a weak phenotypic effect. One way to detect these loci is to identify genetic polymorphisms that exhibit high correlation with environmental variables used as proxies for ecological pressures. Here, we propose new algorithms based on population genetics, ecological modeling, and statistical learning techniques to screen genomes for signatures of local adaptation. Implemented in the computer program "latent factor mixed model" (LFMM), these algorithms employ an approach in which population structure is introduced using unobserved variables. These fast and computationally efficient algorithms detect correlations between environmental and genetic variation while simultaneously inferring background levels of population structure. Comparing these new algorithms with related methods provides evidence that LFMM can efficiently estimate random effects due to population history and isolation-by-distance patterns when computing gene-environment correlations, and decrease the number of false-positive associations in genome scans. We then apply these models to plant and human genetic data, identifying several genes with functions related to development that exhibit strong correlations with climatic gradients.Comment: 29 pages with 8 pages of Supplementary Material (V2 revised presentation and results part

An Indirect Cue of Predation Risk Counteracts Female Preference for Conspecifics in a Naturally Hybridizing Fish Xiphophorus birchmanni

Mate choice is context dependent, but the importance of current context to interspecific mating and hybridization is largely unexplored. An important influence on mate choice is predation risk. We investigated how variation in an indirect cue of predation risk, distance to shelter, influences mate choice in the swordtail Xiphophorus birchmanni, a species which sometimes hybridizes with X. malinche in the wild. We conducted mate choice experiments to determine whether females attend to the distance to shelter and whether this cue of predation risk can counteract female preference for conspecifics. Females were sensitive to shelter distance independent of male presence. When conspecific and heterospecific X. malinche males were in equally risky habitats (i.e., equally distant from shelter), females associated primarily with conspecifics, suggesting an innate preference for conspecifics. However, when heterospecific males were in less risky habitat (i.e., closer to shelter) than conspecific males, females no longer exhibited a preference, suggesting that females calibrate their mate choices in response to predation risk. Our findings illustrate the potential for hybridization to arise, not necessarily through reproductive “mistakes”, but as one of many potential outcomes of a context-dependent mate choice strategy