Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Designing business models of cloud platforms

Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution.

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a "covarion-like" pattern of correlated changes in evolutionary rates, and switches in conserved residues ("conserved but different"). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than "constant but different," but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Sulfur speciation and stable isotope trends of water-soluble sulfates in mine tailings profiles

Sulfur speciation and the sources of water-soluble sulfate in three oxidizing sulfidic mine tailings impoundments were investigated by selective dissolution and stable isotopes. The studied tailings impoundments-Piuquenes, Cauquenes, and Salvador No. 1-formed from the exploitation of the Rio Blanco/La Andina, El Teniente, and El Salvador Chilean porphyry copper deposits, which are located in Alpine, Mediterranean, and hyperarid climates, respectively. The water-soluble sulfate may originate from dissolution of primary ore sulfates (e.g., gypsum, anhydrite, jarosite) or from oxidation of sulfide minerals exposed to aerobic conditions during mining activity. With increasing aridity and decreasing pyrite content of the tailings, the sulfur speciation in the unsaturated oxidation zones showed a trend from dominantly Fe(Ill) oxyhydroxide fixed sulfate (e.g., jarosite and schwertmannite) in Piuquenes toward increasing presence of water-soluble sulfate at Cauquenes and Salvador No. 1. In the saturated primary zones, sulfate is predominantly present in water-soluble form (mainly as anhydrite and/or gypsum). In the unsaturated zone at Piuquenes and Cauquenes,the delta(34)S(S04) values ranged from +0.5 parts per thousand to +2.0 parts per thousand and from -0.4 parts per thousand to +1.4 parts per thousand Vienna Canyon Diablo Troilite (V-CDT), respectively, indicating a major sulfate source from pyrite oxidation (delta(34)S(pyrite) -1.1 parts per thousand and -0.9 parts per thousand). In the saturated zone at Piuquenes and Cauquenes, the values ranged from -0.8%. to +0.3 parts per thousand and from +2.2 parts per thousand to +3.9 parts per thousand, respectively. At Cauquenes the 34 S enrichment in the saturated zone toward depth indicates the increasing contribution of isotopically heavy dissolved sulfate from primary anhydrite (similar to+10.9%o). At El Salvador No. 1, the delta(34)S(SO4) average value is -0.9 parts per thousand, suggesting dissolution of supergene sulfate minerals (jarosite, alunite, gypsum) with a delta(34)S similar to -0.7 parts per thousand as the most probable sulfate source. The gradual decrease Of delta(18)O(S04) values from the surface to the oxidation front in the tailings impoundments at Piuquenes (from -4.5 parts per thousand to -8.6 parts per thousand Vienna Standard Mean Ocean Water, V-SMOW) and at Cauquenes (from -1.3 parts per thousand to -3.5 parts per thousand) indicates the increasing importance of ferric iron as the main electron acceptor in the oxidation of pyrite. The different delta(18)O(SO4) values between the tailings impoundments studied here reflect the local climates.

Ever-young sex chromosomes in European tree frogs.

Non-recombining sex chromosomes are expected to undergo evolutionary decay, ending up genetically degenerated, as has happened in birds and mammals. Why are then sex chromosomes so often homomorphic in cold-blooded vertebrates? One possible explanation is a high rate of turnover events, replacing master sex-determining genes by new ones on other chromosomes. An alternative is that X-Y similarity is maintained by occasional recombination events, occurring in sex-reversed XY females. Based on mitochondrial and nuclear gene sequences, we estimated the divergence times between European tree frogs (Hyla arborea, H. intermedia, and H. molleri) to the upper Miocene, about 5.4-7.1 million years ago. Sibship analyses of microsatellite polymorphisms revealed that all three species have the same pair of sex chromosomes, with complete absence of X-Y recombination in males. Despite this, sequences of sex-linked loci show no divergence between the X and Y chromosomes. In the phylogeny, the X and Y alleles cluster according to species, not in groups of gametologs. We conclude that sex-chromosome homomorphy in these tree frogs does not result from a recent turnover but is maintained over evolutionary timescales by occasional X-Y recombination. Seemingly young sex chromosomes may thus carry old-established sex-determining genes, a result at odds with the view that sex chromosomes necessarily decay until they are replaced. This raises intriguing perspectives regarding the evolutionary dynamics of sexually antagonistic genes and the mechanisms that control X-Y recombination.

From deep seated slope deformation to rock avalanche: Destabilization and transportation models of the Sierre landslide (Switzerland)

Sackung is a widespread post-glacial morphological feature affecting Alpine mountains and creating characteristic geomorphological expression that can be detected from topography. Over long time evolution, internal deformation can lead to the formation of rapidly moving phenomena such as a rock-slide or rock avalanche. In this study, a detailed description of the Sierre rock-avalanche (SW Switzerland) is presented. This convex-shaped postglacial instability is one of the larger rock-avalanche in the Alps, involving more than 1.5 billion m3 with a run-out distance of about 14 km and extremely low Fahrböschung angle. This study presents comprehensive analyses of the structural and geological characteristics leading to the development of the Sierre rock-avalanche. In particular, by combining field observations, digital elevation model analyses and numerical modelling, the strong influence of both ductile and brittle tectonic structures on the failure mechanism and on the failure surface geometry is highlighted. The detection of pre-failure deformation indicates that the development of the rock avalanche corresponds to the last evolutionary stage of a pre-existing deep seated gravitational slope instability. These analyses accompanied by the dating and the characterization of rock avalanche deposits, allow the proposal of a destabilization model that clarifies the different phases leading to the development of the Sierre rock avalanche.

Redox dysregulation and oxidative stress in schizophrenia: genetic and functional anomalies of glutathione synthesis in patients and experimental models involving GABA interneurons and NMDA receptors

Objective: Converging evidence speak in favor of an abnormal susceptibility to oxidative stress in schizophrenia. A decreased level of glutathione (GSH), the principal non-protein antioxidant and redox regulator, was observed both in cerebrospinal-fluid and prefrontal cortex of schizophrenia patients (Do et al., 2000). Results: Schizophrenia patients have an abnormal GSH synthesis most likely of genetic origin: Two independent case-control studies showed a significant association between schizophrenia and a GAG trinucleotide repeat (TNR) polymorphism in the GSH key synthesizing enzyme glutamate-cysteine-ligase (GCL) catalytic subunit (GCLC) gene. The most common TNR genotype 7/7 was more frequent in controls, whereas the rarest TNR genotype 8/8 was three times more frequent in patients. The disease-associated genotypes correlated with a decrease in GCLC protein expression, GCL activity and GSH content. Such a redox dysregulation during development could underlie the structural and functional anomalies in connectivity: In experimental models, GSH deficit induced anomalies similar to those observed in patients. (a) morphology: In animal models with GSH deficit during the development we observed in prefrontal cortex a decreased dendritic spines density in pyramidal cells and an abnormal development of parvalbumine (but not of calretinine) immunoreactive GABA interneurones in anterior cingulate cortex. (b) physiology: GSH depletion in hippocampal slices induces NMDA receptors hypofunction and an impairment of long term potentiation. In addition, GSH deficit affected the modulation of dopamine on NMDA-induced Ca 2+ response in cultured cortical neurons. While dopamine enhanced NMDA responses in control neurons, it depressed NMDA responses in GSH-depleted neurons. Antagonist of D2-, but not D1-receptors, prevented this depression, a mechanism contributing to the efficacy of antipsychotics. The redox sensitive ryanodine receptors and L-type calcium channels underlie these observations. (c) cognition: Developing rats with low [GSH] and high dopamine lead deficit in olfactory integration and in object recognition which appears earlier in males that females, in analogy to the delay of the psychosis onset between man and woman. Conclusion: These clinical and experimental evidence, combined with the favorable outcome of a clinical trial with N-Acetyl Cysteine, a GSH precursor, on both the negative symptoms (Berk et al., submitted) and the mismatch negativity in an auditory oddball paradigm supported the proposal that a GSH synthesis impairment of genetic origin represent, among other factors, one major risk factor in schizophrenia.

Hybrid speciation in birds: allopatry more important than ecology?

Hybrid speciation was once thought to be rare in animals, but over the past decade, improved molecular analysis techniques and increased research attention have allowed scientists to uncover many examples. In this issue, two papers (Elgvin et al. 2011; Hermansen et al. 2011) present compelling evidence for the hybrid origin of the Italian sparrow based on nuclear and mitochondrial DNA sequences, microsatellites, and plumage coloration. These studies point to an important role for geographic isolation in the process of hybrid speciation, and provide a starting point for closer examination of the genetic and behavioural mechanisms involved.