Random Expectation Research Articles

Ambivalence, Avoidance, and Appeal: Alliterative Aspects of Anglo Anthroponyms

In several countries, one of the most pronounced trends in contemporary baby naming is selecting a comparatively uncommon name. Nevertheless, although a well-documented phenomenon, studies of uncommon name use are often limited to forenames. This study analyses approximately 22 million full names from England and 1 million from Wales, given between 1838 and 2014. It addresses the hypothesis that, consistent with the contemporary desire to choose an uncommon name, alliterative names – uncommon by definition – would become increasingly popular. More broadly, this study charts the long-term trends in alliterative naming over time. In both England and Wales, this pattern is consistent with a random expectation for much of the 19th century but declines significantly throughout the 20th century to its lowest use in the 1970s. This trend reverses towards the end of the 20th century, with alliterative naming becoming more common in contemporary records. These three aspects of alliterative name use are thematically referred to as ‘ambivalence’, ‘avoidance’ and ‘appeal’; and may reflect changing attitudes towards alliterative naming. The relatively renewed appeal of alliterative names towards the end of the 20th century complements previous research on the preponderance of uncommon names and the contemporary ‘need for uniqueness’ in naming.

Looking for Mimicry in a Snake Assemblage Using Deep Learning.

Batesian mimicry is a canonical example of evolution by natural selection, popularized by highly colorful species resembling unrelated models with astonishing precision. However, Batesian mimicry could also occur in inconspicuous species and rely on subtle resemblance. Although potentially widespread, such instances have been rarely investigated, such that the real frequency of Batesian mimicry has remained largely unknown. To fill this gap, we developed a new approach using deep learning to quantify the visual resemblance between putative mimics and models from photographs. We applied this method to Western Palearctic snakes. Potential nonvenomous mimics were revealed by an excess of resemblance to sympatric venomous snakes compared with random expectations. We found that 8% of the nonvenomous species were potential mimics, although they resembled their models imperfectly. This study is the first to quantify the frequency of Batesian mimicry in a whole community of vertebrates, and it shows that even concealed species can act as potential models. Our approach should prove useful for detecting mimicry in other communities, and more generally it highlights the benefits of deep learning for quantitative studies of phenotypic resemblance.

Termite mound vegetation patterns are largely driven by stochastic rather than deterministic processes at regional scale in Africa: A meta‐analysis

AbstractQuestionsAlthough the biogeography of plant communities has been well studied, mechanisms controlling plant community diversity are still poorly understood. Stochastic and deterministic processes are hotly debated as being key in structuring communities across taxa. Here we ask, to what extent are plant communities on termite mounds shaped by either stochastic or deterministic processes within and between regions on the African continent?MethodsWe performed a meta‐analysis on 23 studies that satisfied our selection criteria out of 369 that we initially identified. All these studies sampled woody plants that occurred on termite mounds and the surrounding matrix. In order to disentangle the relative importance of deterministic and stochastic processes in generating beta diversity between mound–mound and matrix–matrix plots, within and between regions, we applied null models. We also assessed the relationship between species richness and environmental variables for each site.ResultsOf the environmental variables assessed at each site, only altitude had a significant (negative) relationship with species richness. Within each region comparison of mound–mound, matrix–matrix and matrix–mound species composition did not significantly deviate from the null models of random expectation. Between regions, the observed pattern was significantly higher than null expectation for both mound–mound and matrix–matrix plots between East and West Africa. Surprisingly, the comparison between southern Africa and both East and West Africa did not significantly deviate from the null expectation, regardless of increased spatial separation. We attributed the within‐region pattern to homogenizing dispersal and reliance on the same species pool (γ) for matrix and mound plots. The between‐regions pattern was influenced by both deterministic and stochastic processes.ConclusionOur results suggest that the processes responsible for vegetation composition between mound–mound, matrix–matrix and mound–matrix plots are stochastic in nature due to lack of difference from the null expectation. However, regional patterns are governed by both deterministic and stochastic processes.

The Transcriptional Aftermath in Two Independently Formed Hybrids of the Opportunistic Pathogen Candida orthopsilosis.

Interspecific hybridization can drive evolutionary adaptation to novel environments. The Saccharomycotina clade of budding yeasts includes many hybrid lineages, and hybridization has been proposed as a source for new pathogenic species. Candida orthopsilosis is an emerging opportunistic pathogen for which most clinical isolates are hybrids, each derived from one of at least four independent crosses between the same two parental lineages. To gain insight into the transcriptomic aftermath of hybridization in these pathogens, we analyzed allele-specific gene expression in two independently formed hybrid strains and in a homozygous strain representative of one parental lineage. Our results show that the effect of hybridization on overall gene expression is rather limited, affecting ∼4% of the genes studied. However, we identified a larger effect in terms of imbalanced allelic expression, affecting ∼9.5% of the heterozygous genes in the hybrids. This effect was larger in the hybrid with more extensive loss of heterozygosity, which may indicate a tendency to avoid loss of heterozygosity in these genes. Consistently, the number of shared genes with allele-specific expression in the two independently formed hybrids was higher than random expectation, suggesting selective retention. Some of the imbalanced genes have functions related to pathogenicity, including zinc transport and superoxide dismutase activities. While it remains unclear whether the observed imbalanced genes play a role in virulence, our results suggest that differences in allele-specific expression may add an additional layer of phenotypic plasticity to traits related to virulence in C. orthopsilosis hybrids.IMPORTANCE How new pathogens emerge is an important question that remains largely unanswered. Some emerging yeast pathogens are hybrids originated through the crossing of two different species, but how hybridization contributes to higher virulence is unclear. Here, we show that hybrids selectively retain gene regulation plasticity inherited from the two parents and that this plasticity affects genes involved in virulence.

Mapping Brazilian spotted fever: Linking etiological agent, vectors, and hosts

Brazilian spotted fever (BSF) is a highly lethal disease in southeastern Brazil. BSF is caused by the bacterium Rickettsia rickettsii and is transmitted by the bites of the tick of the genus Amblyomma. The spatial distribution of BSF risk areas is not well known in the country given the complexity of the transmission cycle. This study used the ecological niche modeling (ENM) approach to anticipate the potential distribution of the etiological agent (Rickettsia rickettsii), vectors (Amblyomma sculptum and A. dubitatum), and hosts (Hydrochoerus hydrochaeris, Didelphis aurita, and D. marsupialis) of BSF in Brazil. We compiled occurrence records for all vectors, hosts, and BSF from our own field surveillance, online repositories, and literature. ENM identified BSF risk areas in southeastern and southern Brazil, and anticipated other dispersed suitable areas in the western, central, and northeastern coast regions of Brazil. Tick vectors and mammalian hosts were confined to these same areas; however, host species showed broader suitability in northern Brazil. All species ENMs performed significantly better than random expectations. We also tested the BSF prediction based on 253 additional independent cases identified in our surveillance; the model anticipated 251 out of 253 of these independent cases. Background similarity tests comparing the ENMs of R. rickettsii, tick vectors, and mammalian hosts were unable to reject null hypotheses of niche similarity. Finally, we observed close coincidence between independent BSF cases, and areas suitable for combinations of vectors and hosts, reflecting the ability of these model pairs to anticipate the distribution of BSF cases across Brazil.

Contrasting animal movement and spatial connectivity networks in shaping transmission pathways of a genetically diverse virus

Analyses of livestock movement networks has become key to understanding an industry’s vulnerability to infectious disease spread and for identifying farms that play disproportionate roles in pathogen dissemination. In addition to animal movements, many pathogens can spread between farms via mechanisms mediated by spatial proximity. Heterogeneities in contact patterns based on spatial proximity are less commonly considered in network studies, and studies that jointly consider spatial connectivity and animal movement are rare. The objective of this study was to determine the extent to which movement versus spatial proximity networks determine the distribution of an economically important endemic virus, porcine reproductive and respiratory syndrome virus (PRRSV), within a swine-dense region of the U.S. PRRSV can be classified into numerous phylogenetic lineages. Such data can be used to better resolve between-farm infection chains and elucidate types of contact most associated with transmission. Here, we construct movement and spatial proximity networks; farms within the networks were classified as cases if a given PRRSV lineage had been recovered at least once in a year for each of three years analyzed. We evaluated six lineages and sub-lineages across three years, and evaluated the epidemiological relevance of each network by applying network k-tests to statistically evaluate whether the pattern of case occurrence within the network was consistent with transmission via network linkages. Our results indicated that animal movements, not local area spread, play a dominant role in shaping transmission pathways, though there were differences amongst lineages. The median number of case farms inter-linked via animal movements was approximately 4.1x higher than random expectations (range: 1.7–13.7; p < 0.05, network k-test), whereas this measure was only 2.7x higher than random expectations for farms linked via spatial proximity (range: 1.3–5.4; p < 0.05, network k-test). For spatial proximity networks, contact based on proximities of <5 km appeared to have greater epidemiological relevance than longer distances, likely related to diminishing probabilities of local area spread at greater distances. However, the greater overall levels of connectivity of the spatial network compared to the movement network highlights the vulnerability of pig populations to widespread transmission via this route. By combining genetic data with network analysis, this research advances our understanding of dynamics of between-farm spread of PRRSV, helps establish the relative importance of transmission via animal movements versus local area spread, and highlights the potential for targeted control strategies based upon heterogeneities in network connectivity.

Correlated Evolution of Large DNA Fragments in the 3D Genome of Arabidopsis thaliana

In eukaryotes, the three-dimensional (3D) conformation of the genome is far from random, and this nonrandom chromatin organization is strongly correlated with gene expression and protein function, which are two critical determinants of the selective constraints and evolutionary rates of genes. However, whether genes and other elements that are located close to each other in the 3D genome evolve in a coordinated way has not been investigated in any organism. To address this question, we constructed chromatin interaction networks (CINs) in Arabidopsis thaliana based on high-throughput chromosome conformation capture data and demonstrated that adjacent large DNA fragments in the CIN indeed exhibit more similar levels of polymorphism and evolutionary rates than random fragment pairs. Using simulations that account for the linear distance between fragments, we proved that the 3D chromosomal organization plays a role in the observed correlated evolution. Spatially interacting fragments also exhibit more similar mutation rates and functional constraints in both coding and noncoding regions than the random expectations, indicating that the correlated evolution between 3D neighbors is a result of combined evolutionary forces. A collection of 39 genomic and epigenomic features can explain much of the variance in genetic diversity and evolutionary rates across the genome. Moreover, features that have a greater effect on the evolution of regional sequences tend to show higher similarity between neighboring fragments in the CIN, suggesting a pivotal role of epigenetic modifications and chromatin organization in determining the correlated evolution of large DNA fragments in the 3D genome.

Using community phylogenetics to assess phylogenetic structure in the Fitzcarrald region of Western Amazonia

ABSTRACT Here we explore the use of community phylogenetics as a tool to document patterns of biodiversity in the Fitzcarrald region, a remote area in Southwestern Amazonia. For these analyses, we subdivide the region into basin-wide assemblages encompassing the headwaters of four Amazonian tributaries (Urubamba, Yuruá, Purús and Las Piedras basins), and habitat types: river channels, terra firme (non-floodplain) streams, and floodplain lakes. We present a robust, well-documented collection of fishes from the region including 272 species collected from 132 field sites over 63 field days and four years, comprising the most extensive collection of fishes from this region to date. We conduct a preliminary community phylogenetic analysis based on this collection and recover results largely statistically indistinguishable from the random expectation, with only a few instances of phylogenetic structure. Based on these results, and of those published in other recent biogeographic studies, we conclude that the Fitzcarrald fish species pool accumulated over a period of several million years, plausibly as a result of dispersal from the larger species pool of Greater Amazonia.

Late time quantum chaos of pure states in random matrices and in the Sachdev-Ye-Kitaev model

In this letter, we study the return amplitude, which is the overlap between the initial state and the time evolved state, in the Sachdev-Ye-Kitaev (SYK) model. Initial states are taken to be product states in a spin basis. We numerically study the return amplitude by exactly diagonalizing the Hamiltonian. We also derive the analytic expression for the return amplitude in random matrix theory. The SYK results agree with the random matrix expectation. We also study the time evolution under the different Hamiltonian that describes the traversable wormholes in projected black holes in the context of holography. The time evolution now depends on the choice of initial product states. The results are again explained by random matrix theory. In the symplectic ensemble cases, we observed an interesting pattern of the return amplitude where they show the second dip, ramp and plateau like behavior.

An Algorithmic Model Building Scheme Based on Dynamic Programming Algorithms

Dynamic programming algorithm is a basic tool for solving multi-level decision-making problems, which is widely used in social economy, engineering technology and optimal control. Aiming at the incommensurability of multi-objective programming indices, the relative membership degree matrix of allocation schemes for quantitative and qualitative indices is established, and the analysis method of multi-objective and multi-stage dynamic programming problems is given by using vector and matrix unification. The decision maker determines the decision coefficients of each constraint indicator according to the specific problem and performs weighting processing. The weights of different state variables for different constraint indicators are integrated, the comprehensive weights of state variables are solved, and the original static constraint indicators are transformed into dynamic variables that can influence the decision results. The research shows that the algorithm transforms the multi-stage decision problem into a single-stage decision problem, and solves the optimal value of the expected value through the mixture of random expectation models in a single stage. As long as it is used properly, dynamic planning of this traditional method can be a better way to solve complex problems.

Additive effects of connectivity provided by different habitat types drive plant assembly

How connectivity affects plant assemblages is a central issue in landscape ecology. So far, empirical studies have produced contradictory results, possibly because studies: (1) inaccurately assess connectivity by prioritizing the respective effect of the type of habitat on plant assemblages and (2) omit the range of possible plant responses to connectivity depending on dispersal vectors. We focused on three dominant habitat types in agricultural landscapes (woodland, grassland and cropland), and analysed the effect of connectivity on herbaceous plant assemblage similarity for three primary dispersal modes (animal-dispersed, wind-dispersed and unassisted). Using circuit theory, we measured connectivity provided by woodland, grassland and cropland habitats independently. The similarity of plant assemblages was evaluated relative to the random expectation based on the regional pool. Overall, plant assemblage similarity in woodlands and temporary grasslands was dependent on connectivity, but not in wheat croplands. Only animal-dispersed species responded to connectivity. The similarity of animal-dispersed assemblages in woodlands was increased by the connectivity provided by woodland habitats, but was reduced by cropland habitats, whereas in temporary grasslands, similarity was increased by the connectivity provided by cropland habitats. Our results suggest that animal-dispersed species supplement their dispersal pathways, thus improving our knowledge of plant assembly rules in fragmented landscapes.

Genomic approaches to identify hybrids and estimate admixture times in European wildcat populations

The survival of indigenous European wildcat (Felis silvestris silvestris) populations can be locally threatened by introgressive hybridization with free-ranging domestic cats. Identifying pure wildcats and investigating the ancestry of admixed individuals becomes thus a conservation priority. We analyzed 63k cat Single Nucleotide Polymorphisms (SNPs) with multivariate, Bayesian and gene-search tools to better evaluate admixture levels between domestic and wild cats collected in Europe, timing and ancestry proportions of their hybrids and backcrosses, and track the origin (wild or domestic) of the genomic blocks carried by admixed cats, also looking for possible deviations from neutrality in their inheritance patterns. Small domestic ancestry blocks were detected in the genomes of most admixed cats, which likely originated from hybridization events occurring from 6 to 22 generations in the past. We identified about 1,900 outlier coding genes with excess of wild or domestic ancestry compared to random expectations in the admixed individuals. More than 600 outlier genes were significantly enriched for Gene Ontology (GO) categories mainly related to social behavior, functional and metabolic adaptive processes (wild-like genes), involved in cognition and neural crest development (domestic-like genes), or associated with immune system functions and lipid metabolism (parental-like genes). These kinds of genomic ancestry analyses could be reliably applied to unravel the admixture dynamics in European wildcats, as well as in other hybridizing populations, in order to design more efficient conservation plans.

Viability in Multiplex Lexical Networks and Machine Learning Characterizes Human Creativity

Previous studies have shown how individual differences in creativity relate to differences in the structure of semantic memory. However, the latter is only one aspect of the whole mental lexicon, a repository of conceptual knowledge that is considered to simultaneously include multiple types of conceptual similarities. In the current study, we apply a multiplex network approach to compute a representation of the mental lexicon combining semantics and phonology and examine how it relates to individual differences in creativity. This multiplex combination of 150,000 phonological and semantic associations identifies a core of words in the mental lexicon known as viable cluster, a kernel containing simpler to parse, more general, concrete words acquired early during language learning. We focus on low (N = 47) and high (N = 47) creative individuals’ performance in generating animal names during a semantic fluency task. We model this performance as the outcome of a mental navigation on the multiplex lexical network, going within, outside, and in-between the viable cluster. We find that low and high creative individuals differ substantially in their access to the viable cluster during the semantic fluency task. Higher creative individuals tend to access the viable cluster less frequently, with a lower uncertainty/entropy, reaching out to more peripheral words and covering longer multiplex network distances between concepts in comparison to lower creative individuals. We use these differences for constructing a machine learning classifier of creativity levels, which leads to an accuracy of 65.0 ± 0.9 % and an area under the curve of 68.0 ± 0.8 % , which are both higher than the random expectation of 50%. These results highlight the potential relevance of combining psycholinguistic measures with multiplex network models of the mental lexicon for modelling mental navigation and, consequently, classifying people automatically according to their creativity levels.

Differences Between the Raw Material and the Products of de Novo Gene Birth Can Result from Mutational Biases.

Proteins are among the most important constituents of biological systems. Because all protein-coding genes have a noncoding ancestral form, the properties of noncoding sequences and how they shape the birth of novel proteins may influence the structure and function of all proteins. Differences between the properties of young proteins and random expectations from noncoding sequences have previously been interpreted as the result of natural selection. However, interpreting such deviations requires a yet-unattained understanding of the raw material of de novo gene birth and its relation to novel functional proteins. We mathematically show that the average properties and selective filtering of the “junk” polypeptides of which this raw material is composed are not the only factors influencing the properties of novel functional proteins. We find that in some biological scenarios, they also depend on the variance of the properties of junk polypeptides and their correlation with the rate of allelic turnover, which may itself depend on mutational biases. This suggests for instance that any property of polypeptides that accelerates their exploration of the sequence space could be overrepresented in novel functional proteins, even if it has a limited effect on adaptive value. To exemplify the use of our general theoretical results, we build a simple model that predicts the mean length and mean intrinsic disorder of novel functional proteins from the genomic GC content and a single evolutionary parameter. This work provides a theoretical framework that can guide the prediction and interpretation of results when studying the de novo emergence of protein-coding genes.

Influence of the Structural Accuracy of Homology Models on Their Applicability to Docking-Based Virtual Screening: The β2 Adrenergic Receptor as a Case Study.

How accurate do structures of the β2 adrenergic receptor (β2AR) need to be to effectively serve as platforms for docking-based virtual screening campaigns? To answer this research question, here, we targeted through controlled virtual screening experiments 23 homology models of the β2AR endowed with different levels of structural accuracy. Subsequently, we studied the correlation between virtual screening performance and structural accuracy of the targeted models. Moreover, we studied the correlation between virtual screening performance and template/target receptor sequence identity. Our study demonstrates that docking-based virtual screening campaigns targeting homology models of the β2AR, in the majority of the cases, yielded results that exceeded random expectations in terms of area under the receiver operating characteristic curve (ROC AUC). Moreover, with the most effective scoring method, over one-third and one-quarter of the models yielded results that exceeded random expectation also in terms of enrichment factors (EF1, EF5, and EF10) and BEDROC (α = 160.9), respectively. Not surprisingly, we found a detectable linear correlation between virtual screening performance and structural accuracy of the ligand-binding cavity. We also found a detectable linear correlation between virtual screening performance and structural accuracy of the second extracellular loop (EL2). Finally, our data indicate that, although there is no detectable linear correlation between virtual screening performance and template/β2AR sequence identity, models built on the basis of templates that show high sequence identity with the β2AR, especially within the ligand-biding cavity, performed consistently well. Conversely, models with lower sequence identity displayed performance levels that ranged from very good to random, with no apparent correlation with the sequence identity itself.

The molecular biogeography of the Indo‐Pacific: Testing hypotheses with multispecies genetic patterns

AbstractAimTo test hypothesized biogeographic partitions of the tropical Indo‐Pacific Ocean with phylogeographic data from 56 taxa, and to evaluate the strength and nature of barriers emerging from this test.LocationThe Indo‐Pacific Ocean.Time periodPliocene through the Holocene.Major taxa studiedFifty‐six marine species.MethodsWe tested eight biogeographic hypotheses for partitioning of the Indo‐Pacific using a novel modification to analysis of molecular variance. Putative barriers to gene flow emerging from this analysis were evaluated for pairwise ΦST, and these ΦST distributions were compared to distributions from randomized datasets and simple coalescent simulations of vicariance arising from the Last Glacial Maximum. We then weighed the relative contribution of distance versus environmental or geographic barriers to pairwise ΦST with a distance‐based redundancy analysis (dbRDA).ResultsWe observed a diversity of outcomes, although the majority of species fit a few broad biogeographic regions. Repeated coalescent simulation of a simple vicariance model yielded a wide distribution of pairwise ΦST that was very similar to empirical distributions observed across five putative barriers to gene flow. Three of these barriers had median ΦST that were significantly larger than random expectation. Only 21 of 52 species analysed with dbRDA rejected the null model. Among these, 15 had overwater distance as a significant predictor of pairwise ΦST, while 11 were significant for geographic or environmental barriers other than distance.Main conclusionsAlthough there is support for three previously described barriers, phylogeographic discordance in the Indo‐Pacific Ocean indicates incongruity between processes shaping the distributions of diversity at the species and population levels. Among the many possible causes of this incongruity, genetic drift provides the most compelling explanation: given massive effective population sizes of Indo‐Pacific species, even hard vicariance for tens of thousands of years can yield ΦST values that range from 0 to nearly 0.5.

Niche-structured assemblages of exotic earthworms in headwater streambanks in eastern New York State, USA

In eastern North America, most Lumbricid earthworms found today above the post-Wisconsin Glacial boundary are non-indigenous, some with marked potential as invasive and ecologically disruptive species. These earthworms tend to appear as assemblages, not solitary species. Among potential explanations are successional facilitation among taxa, anthropogenic dispersal mechanisms that promote multi-species introductions, or simply shared habitat determinants that lead to accumulations through various dispersal pathways. We examined headwater streambanks in higher elevation forests of eastern New York State, and found up to 15 lumbricid earthworm species per 50 m-long reach among 14 sites divided between two montane regions, the northern Catskill Mountains and the Helderberg Plateau of eastern New York State.After pooling six surveys per site taken over two years, we found consistent differences between the two regions. Although most species (14/18) were found in both regions, their relative abundances and assortment patterns differed. Eisenoides lonnbergi and Bimastos rubidus, two native species were more prevalent in the Catskills, and represented new records for both regions. Ordination (CCA) on a set of measured environmental parameters revealed that most species were distributed along a soil pH-tree composition gradient. At the site level, clustering was strongly regional, despite a relatively small distance (<25 km) separating the regions. In all, several determinants may be at work in shaping observed earthworm assemblages. However, we did not detect evidence for interspecific interactions as a structuring element. When tested with a null model simulation, observed pairwise species associations did not depart significantly from random expectations (z-tests, p > 0.30 for both regions). Furthermore, the riparian zones we surveyed are relatively dynamic settings, so the stability of these novel assemblages is uncertain. With other invasive earthworm species now spreading throughout New York State, that uncertainty may grow.

Identification of novel targets in non-muscle invasive bladder cancer: A systems biology approach.

396 Background: Most bladder cancers are diagnosed as non-muscle invasive bladder cancer (NMIBC). Because of the high rate of recurrence and limited treatment options for recurrent disease, there is an urgent need to identify new treatment options. In this study, a network-based drug discovery approach was applied to identify novel targets in NMIBC. Methods: A computational systems-biology framework integrating genomic, transcriptomic, protein-protein, and protein-drug interactions was applied to identify and prioritize potential NMIBC targets and pathways. First, a NMIBC disease network module was constructed from genetic associations augmented with known protein-protein interactions. Independent NMIBC case/control expression data sets were leveraged to develop a phenotypic network module comprising genes differentially expressed in NMIBC. Proteins and pathways linking the disease model with the phenotypic module were identified, ranked, and benchmarked against known NMIBC pathways and drug targets from the literature. Results: NMIBC seed genes cluster significantly within the human interactome, reflecting an underlying disease module. The expanded disease module comprises 103 genes that show functional and literature-based enrichment. Genes differentially expressed in NMIBC were significantly connected to disease module genes compared with random expectation (z = 23.3), and are enriched in several biologically relevant pathways. Based on similarity to disease biology and network topology, 11 NMIBC pathways were identified as bridging genetic predisposition for and phenotypic expression of NMIBC. Within these overlapping pathways, known and novel drug targets were identified. Of these in silico targets, 19 are currently under development for treatment of bladder cancer, validating the approach. To further validate the approach, we observed overlap between in silico targets and hits from a chemogenomic library phenotypic screen. Conclusions: A network-driven systems biology approach identified both known NMIBC targets and novel proteins/pathways that are potential targets for the treatment of NMIBC. Further target validation is required.

Niches within a niche: ecological differentiation of subterranean amphipods across Europe's interstitial waters

Species that successfully colonized subterranean environments are subject to two opposing selection processes. Stringent abiotic factors select for convergent adaptations, such as loss of eyes and pigments, while interspecific competition drives between‐species divergence. Subterranean species can resolve opposing selection by adaptation to physically different microhabitats. Yet, species frequently co‐occur in physically homogeneous subterranean habitats, like interstitial. These co‐occurrences in such a narrow ecological context can be explained either by equalizing mechanisms, in which neither of the co‐occurring species has a competitive advantage, or by more complex niche models that include species’ differentiation along a trophic niche axis. We tested these hypotheses using the amphipod genus Niphargus. We analysed Europe‐wide co‐occurrence records of Niphargus species from interstitial habitats, split into six independent large‐scale regions. Firstly, we addressed whether species’ pairwise co‐occurrences are random using a probabilistic model. Secondly, we tested whether species cluster into distinct functional–morphological groups and whether ecologically or phylogenetically distinct species are more likely to co‐occur. We found that 68% of species co‐occurrences were not different from random expectation, indicating that most species had access to most sites within each region. The remaining 32% co‐occurred either significantly more or less often than expected by chance. Cluster analysis of functional morphological characters showed that interstitial species belong to two feeding types, micro‐ and macrofeeders, likely representing two peaks of the interstitial adaptive landscape, and hinting that niche divergence, as a mechanism allowing coexistence, is favoured. Finally, we found that the number of co‐occurrences increases with increasing differentiation of functional morphology, but not phylogenetic differences. We conclude that ecological differentiation may be important in shaping such interstitial communities.

Species turnover reveals hidden effects of decreasing nitrogen deposition in mountain hay meadows.

Nitrogen (N) deposition is a major threat to biodiversity in many habitats. The recent introduction of cleaner technologies in Switzerland has led to a reduction in the emissions of nitrogen oxides, with a consequent decrease in N deposition. We examined different drivers of plant community change, that is, N deposition, climate warming, and land-use change, in Swiss mountain hay meadows, using data from the Swiss biodiversity monitoring program. We compared indicator values of species that disappeared from or colonized a site (species turnover) with the indicator values of randomly chosen species from the same site. While oligotrophic plant species were more likely to colonize, compared to random expectation, we found only weak shifts in plant community composition. In particular, the average nutrient value of plant communities remained stable over time (2003–2017). We found the largest deviations from random expectation in the nutrient values of colonizing species, suggesting that N deposition or other factors that change the nutrient content of soils were important drivers of the species composition change over the last 15 years in Swiss mountain hay meadows. In addition, we observed an overall replacement of species with lower indicator values for temperature with species with higher values. Apparently, the community effects of the replacement of eutrophic species with oligotrophic species was outweighed by climate warming. Our results add to the increasing evidence that plant communities in changing environments may be relatively stable regarding average species richness or average indicator values, but that this apparent stability is often accompanied by a marked turnover of species.