Life Cycle and Phylogeography of True Truffles

True truffle (Tuber spp.) is one group of ascomycetes with great economic importance. During the last 30 years, numerous fine-scale population genetics studies were conducted on different truffle species, aiming to answer several key questions regarding their life cycles; these questions are important for their cultivation. It is now evident that truffles are heterothallic, but with a prevalent haploid lifestyle. Strains forming ectomycorrhizas and germinating ascospores act as maternal and paternal partners respectively. At the same time, a number of large-scale studies were carried out, highlighting the influences of the last glaciation and river isolations on the genetic structure of truffles. A retreat to southern refugia during glaciation, and a northward expansion post glaciation, were revealed in all studied European truffles. The Mediterranean Sea, acting as a barrier, has led to the existence of several refugia in different peninsulas for a single species. Similarly, large rivers in southwestern China act as physical barriers to gene flow for truffles in this region. Further studies can pay special attention to population genetics of species with a wide distribution range, such as T. himalayense, and the correlation between truffle genetic structure and the community composition of truffle-associated bacteria.

Towards an Improved Large-Scale Gridded Population Dataset: A Pan-European Study on the Integration of 3D Settlement Data into Population Modelling

Large-scale gridded population datasets available at the global or continental scale have become an important source of information in applications related to sustainable development. In recent years, the emergence of new population models has leveraged the inclusion of more accurate and spatially detailed proxy layers describing the built-up environment (e.g., built-area and building footprint datasets), enhancing the quality, accuracy and spatial resolution of existing products. However, due to the consistent lack of vertical and functional information on the built-up environment, large-scale gridded population datasets that rely on existing built-up land proxies still report large errors of under- and overestimation, especially in areas with predominantly high-rise buildings or industrial/commercial areas, respectively. This research investigates, for the first time, the potential contributions of the new World Settlement Footprint—3D (WSF3D) dataset in the field of large-scale population modelling. First, we combined a Random Forest classifier with spatial metrics derived from the WSF3D to predict the industrial versus non-industrial use of settlement pixels at the Pan-European scale. We then examined the effects of including volume and settlement use information into frameworks of dasymetric population modelling. We found that the proposed classification method can predict industrial and non-industrial areas with overall accuracies and a kappa-coefficient of ~84% and 0.68, respectively. Additionally, we found that both, integrating volume and settlement use information considerably increased the accuracy of population estimates between 10% and 30% over commonly employed models (e.g., based on a binary settlement mask as input), mainly by eliminating systematic large overestimations in industrial/commercial areas. While the proposed method shows strong promise for overcoming some of the main limitations in large-scale population modelling, future research should focus on improving the quality of the WFS3D dataset and the classification method alike, to avoid the false detection of built-up settlements and to reduce misclassification errors of industrial and high-rise buildings.

Expression of OLFM4 and Lysozyme During Necrotizing Enterocolitis and Volvulus in Newborns: a Comparative Observational Research Study

Background: In neonatal patients with necrotizing enterocolitis (NEC) and volvulus the inflammatory response is mediated by a plurality of different proteins. The proteins olfactomedin 4 (OLFM4) and lysozyme (LYZ) are part of the intestinal mucosal defense and especially OLFM4 has rarely been evaluated in neonatal gastrointestinal diseases. The aim of this study was to compare the expression levels of OLFM4 and lysozyme during NEC and volvulus in neonates. Methods: Intestinal tissues of patients with NEC and patients with volvulus were examined using immunohistochemical staining of OLFM4 and lysozyme of formalin-fixed and paraffin-embedded sections of resected tissue. Staining-positive tissues were semi-quantitatively scored from 0 (no staining), 1 (weak staining), 2 (moderate staining) to 3 (highly intense staining) by two individual investigators.Results: Both applied antibodies against OLFM4 showed different staining patterns with higher staining intensity of the antibody OLFM4 (D1E4M). OLFM4 (median score of the antibody OLFM4 (D1E4M): 3.0) and lysozyme (median score: 3.0) are highly expressed in intestinal and immune cells during NEC. The expression of OLFM4 and lysozyme in tissue with intestinal volvulus was also observable (median score of the antibody OLFM4 (D1E4M): 1.25) and median score of the antibody against LYZ: 2.0), but lower levels could be seen in comparison to tissue with NEC (p=0.033 and p=0.037, respectively).Conclusions: Both proteins, OLFM4 and lysozyme, may play a role in the pathogenesis of NEC and volvulus in neonatal patients, but the exact mechanisms of OLFM4 and lysozyme function and their role in immunological responses have not yet been resolved. These observations add new insights as basis for further large-scale population research.

A Model for Simulating Emergent Patterns of Cities and Roads on Real-world Landscapes

Emergence of cities and road networks have characterised human activity and movement over millennia. However, this anthropogenic infrastructure does not develop in isolation, but is deeply embedded in the natural landscape, which strongly influences the resultant spatial patterns. Nevertheless, the precise impact that landscape has on the location, size and connectivity of cities is a long-standing, unresolved problem. To address this issue, we incorporate high-resolution topographic maps into a Turing-like pattern forming system, in which local reinforcement rules result in co-evolving centres of population and transport networks. Using Italy as a case study, we show that the model constrained solely by topography results in an emergent spatial pattern that is consistent with Zipf’s Law and comparable to the census data. Thus, we infer the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern, that is then modified by higher-level historical, socio-economic or cultural factors.

Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon—given the huge data resources that already exist for this species—the general principles developed here could be applied and extended to many other species and ecosystems.

Population coding and oscillatory subspace synchronization integrate context into actions

Contextual cues and prior evidence guide human goal-directed behavior. To date, the neurophysiological mechanisms that implement contextual priors to guide subsequent actions remain unclear. Here we demonstrate that increasing behavioral uncertainty introduces a shift from an oscillatory to a continuous processing mode in human prefrontal cortex. At the population level, we found that oscillatory and continuous dynamics reflect dissociable signatures that support distinct aspects of encoding, transmission and execution of context-dependent action plans. We show that prefrontal population activity encodes predictive context and action plans in serially unfolding orthogonal subspaces, while prefrontal-motor theta oscillations synchronize action-encoding population subspaces to mediate the hand-off of action plans. Collectively, our results reveal how two key features of large-scale population activity, namely continuous population trajectories and oscillatory synchrony, operate in concert to guide context-dependent human behavior.

COEVOLUTION WITH SPATIALLY STRUCTURED RICE LANDRACES MAINTAINS MULTIPLE GENERALIST LINEAGES IN THE RICE BLAST PATHOGEN

Traditional agrosystems, where humans, crops and microbes have coevolved over long periods, can serve as models to understand the eco-evolutionary determinants of disease dynamics and help the engineering of durably resistant agrosystems. Here, we investigated the genetic and phenotypic relationship between rice (Oryza sativa) landraces and their rice blast pathogen (Magnaporthe oryzae) in the traditional Yuanyang terraces of flooded rice paddies in China, where rice landraces have been grown and bred over centuries without significant disease outbreaks. Analyses of genetic subdivision revealed that indica rice plants clustered according to landrace names. Three new diverse lineages of rice blast specific to the Yuanyang terraces coexisted with lineages previously detected at the worldwide scale. Population subdivision in the pathogen population did not mirror pattern of population subdivision in the host. Measuring the pathogenicity of rice blast isolates on landraces revealed generalist life histories. Our results suggest that the implementation of disease control strategies based on the emergence or maintenance of a generalist lifestyle in pathogens may sustainably reduce the burden of disease in crops.