Explore the vast range of titles available.

1. Ecological networks have been shown to display a nested structure. To be nested, a network must consist of a core group of generalists all interacting with each other, and with extreme specialists interacting only with generalist species. 2. Studies on ecological networks are especially prone to sampling effects, as they involve entire species assemblages. However, we know of no study addressing to what extent nestedness depends on sampling effort, despite the numerous studies discussing the ecological and evolutionary implications of nested networks. 3. Here we manipulate sampling effort in time and space and show that nestedness is less sensitive to sampling effort than number of species and links within the network. 4. That a structural property of an ecological network appears less prone to sampling bias is encouraging for other studies of ecological networks. This is because it indicates that the sensitivity of ecological networks properties to effects of sampling effort might be smaller than previously expected.

Melting and glass formation of metal-organic frameworks (MOFs) allow them to be processed into bulk materials. However, two major challenges remain: only a small fraction of MOF crystals undergo melting and glass-formation, and no well-established strategies exist for tuning MOF glass structures and properties. Here, we address both challenges through co-melting of zeolitic imidazole frameworks (ZIFs), a subset of MOFs, with heterocycle-based halide salts. The salt acts as a chemical “modifier”, akin to the role of alkali modifiers in traditional silicate glasses, e.g., allowing the melting of ZIF-8 that otherwise decomposes prior to melting. Through experimental and computational analyses, we show that the salts depolymerize the ZIFs, enabling continuous tuning of the fraction of bridging to non-bridging imidazolate linkers and, thereby, the thermal and mechanical properties. The proposed strategy enables diversification of MOF glass chemistry, tunable structures and properties, and ultimately an increased number of glass-forming MOFs with improved functionalities. Mixing metal-organic frameworks (MOFs) with halide salts enable low-temperature melting and processable MOF-derived glasses with tunable properties and enhanced structural versatility.

State–space models (SSMs) are an important modeling framework for analyzing ecological time series. These hierarchical models are commonly used to model population dynamics, animal movement, and capture–recapture data, and are now increasingly being used to model other ecological processes. SSMs are popular because they are flexible and they model the natural variation in ecological processes separately from observation error. Their flexibility allows ecologists to model continuous, count, binary, and categorical data with linear or nonlinear processes that evolve in discrete or continuous time. Modeling the two sources of stochasticity separately allows researchers to differentiate between biological variation and imprecision in the sampling methodology, and generally provides better estimates of the ecological quantities of interest than if only one source of stochasticity is directly modeled. Since the introduction of SSMs, a broad range of fitting procedures have been proposed. However, the variety and complexity of these procedures can limit the ability of ecologists to formulate and fit their own SSMs. We provide the knowledge for ecologists to create SSMs that are robust to common, and often hidden, estimation problems, and the model selection and validation tools that can help them assess how well their models fit their data. We present a review of SSMs that will provide a strong foundation to ecologists interested in learning about SSMs, introduce new tools to veteran SSM users, and highlight promising research directions for statisticians interested in ecological applications. The review is accompanied by an in-depth tutorial that demonstrates how SSMs can be fitted and validated in R. Together, the review and tutorial present an introduction to SSMs that will help ecologists to formulate, fit, and validate their models.

The JmjC domain-containing protein JMJD3/KDM6B catalyses the demethylation of H3K27me3 and H3K27me2. JMJD3 appears to be highly regulated at the transcriptional level and is upregulated in response to diverse stimuli such as differentiation inducers and stress signals. Accordingly, JMJD3 has been linked to the regulation of different biological processes such as differentiation of embryonic stem cells, inflammatory responses in macrophages, and induction of cellular senescence via regulation of the INK4A-ARF locus. Here we show here that JMJD3 interacts with the tumour suppressor protein p53. We find that the interaction is dependent on the p53 tetramerization domain. Following DNA damage, JMJD3 is transcriptionally upregulated and by performing genome-wide mapping of JMJD3, we demonstrate that it binds genes involved in basic cellular processes, as well as genes regulating cell cycle, response to stress and apoptosis. Moreover, we find that JMJD3 binding sites show significant overlap with p53 bound promoters and enhancer elements. The binding of JMJD3 to p53 target sites is increased in response to DNA damage, and we demonstrate that the recruitment of JMJD3 to these sites is dependent on p53 expression. Therefore, we propose a model in which JMJD3 is recruited to p53 responsive elements via its interaction with p53 and speculate that JMJD3 could act as a fail-safe mechanism to remove low levels of H3K27me3 and H3K27me2 to allow for efficient acetylation of H3K27.

Studies in ecology are often describing observed variations in a certain ecological phenomenon by use of environmental explanatory variables. A common problem is that the numerical nature of the ecological phenomenon does not always fit the assumptions underlying traditional statistical tests. A text book example comes from pollination ecology where flower visits are normally reported as frequencies; number of visits per flower per unit time. Using visitation frequencies in statistical analyses comes with two major caveats: the lack of knowledge on its error distribution and that it does not include all information found in the data; 10 flower visits in 20 flowers is treated the same as recording 100 visits in 200 flowers. We simulated datasets with various \"flower visitation distributions\" over various numbers of flowers observed (exposure) and with different types of effects inducing variation in the data. The different datasets were then analyzed first with the traditional approach using number of visits per flower and then by using count data models. The analysis of count data gave a much better chance of detecting effects than the traditionally used frequency approach. We conclude that if the data structure, statistical analyses and interpretations of results are mixed up, valuable information can be lost.

There is growing recognition of urban areas as hosts for innovative ways to conserve and promote biodiversity. Parks, as one specific type of urban green space, constitute particularly important biodiversity hotspots in the cityscape. We reviewed empirical findings on the species richness in urban parks across all species groups that have been studied. The aim was to assess and discuss the overall species richness of urban parks, its community attributes and drivers. Search and subsequent selection process resulted in 62 papers from 25 different countries. For all examined species groups, the findings consistently show that parks are among the most species rich types of urban green spaces, but also that exotics constitute large shares, especially of plant species. Key ecological theories like the gradient approach and the island habitat ecological theory, and fundamental ecological relationships such as the species-area relationship are valid despite the manipulated ‘nature’ of parks and the surrounding urban matrix. Most studies surveyed large number of parks and applied ‘multi-scale’ approaches in tests of confounding variables, providing methodological strength. While matrix effects are consistently found to affect species richness negatively, the diversity of habitats and microhabitat heterogeneity contained in urban parks appears as the most decisive factor for the overall species richness. However, a constraint of research to date is the limitation of individual studies to one or a few species groups, rarely bridging between flora and fauna. Adopting ‘multi-species group’ approaches in future research is needed to further advance the understanding of the overall biodiversity of urban parks, and its drivers.

Despite increased awareness, maternal cigarette smoking during pregnancy continues to be a common habit causing risk for numerous documented negative health consequences in the exposed children. It has been proposed that epigenetic mechanisms constitute the link between prenatal exposure to maternal cigarette smoking (PEMCS) and the diverse pathologies arising in later life. We here review the current literature, focusing on DNA methylation. Alterations in the global DNA methylation patterns were observed after exposure to maternal smoking during pregnancy in placenta, cord blood and buccal epithelium tissue. Further, a number of specific genes exemplified by CYP1A1, AhRR, FOXP3, TSLP, IGF2, AXL, PTPRO, C11orf52, FRMD4A and BDNF are shown to have altered DNA methylation patterns in at least one of these tissue types due to PEMCS. Investigations showing persistence and indications of trans-generational inheritance of DNA methylation alterations induced by smoking exposure are also described. Further, smoking-induced epigenetic manifestations can be both tissue-dependent and gender-specific which show the importance of addressing the relevant sex, tissue and cell types in the future studies linking specific epigenetic alterations to disease development. Moreover, the effect of paternal cigarette smoking and second-hand smoke exposure is documented and accordingly not to be neglected in future investigations and data evaluations. We also outline possible directions for the future research to address how DNA methylation alterations induced by maternal lifestyle, exemplified by smoking, have direct consequences for fetal development and later in life health and behavior of the child.

Myostatin is a secreted growth factor expressed in skeletal muscle tissue, which negatively regulates skeletal muscle mass. Recent animal studies suggest a role for myostatin in insulin resistance. We evaluated the possible metabolic role of myostatin in patients with type 2 diabetes and healthy controls. 76 patients with type 2 diabetes and 92 control subjects were included in the study. They were matched for age, gender and BMI. Plasma samples and biopsies from the vastus lateralis muscle were obtained to assess plasma myostatin and expression of myostatin in skeletal muscle. Patients with type 2 diabetes had higher fasting glucose (8.9 versus 5.1 mmol/L, P<0.001), plasma insulin (68.2 versus 47.2 pmol/L, P<0.002) and HOMA2-IR (1.6 versus 0.9, P<0.0001) when compared to controls. Patients with type 2 diabetes had 1.4 (P<0.01) higher levels of muscle myostatin mRNA content than the control subjects. Plasma myostatin concentrations did not differ between patients with type 2 diabetes and controls. In healthy controls, muscle myostatin mRNA correlated with HOMA2-IR (r = 0.30, P<0.01), plasma IL-6 (r = 0.34, P<0.05) and VO2 max (r = -0.26, P<0.05), however, no correlations were observed in patients with type 2 diabetes. This study supports the idea that myostatin may have a negative effect on metabolism. However, the metabolic effect of myostatin appears to be overruled by other factors in patients with type 2 diabetes.

In recent years, considerable efforts have been made to restore turbid, phytoplankton-dominated shallow lakes to a clear-water state with high coverage of submerged macrophytes. Various dynamic lake models with simplified physical representations of vertical gradients, such as PCLake, have been used to predict external nutrient load thresholds for such nonlinear regime shifts. However, recent observational studies have questioned the concept of regime shifts by emphasizing that gradual changes are more common than sudden shifts. We investigated if regime shifts would be more gradual if the models account for depth-dependent heterogeneity of the system by including the possibility of vertical gradients in the water column and sediment layers for the entire depth. Hence, bifurcation analysis was undertaken using the 1D hydrodynamic model GOTM, accounting for vertical gradients, coupled to the aquatic ecosystem model PCLake, which is implemented in the framework for aquatic biogeochemical modeling (FABM). First, the model was calibrated and validated against a comprehensive data set covering two consecutive 7-yr periods from Lake Hinge, a shallow, eutrophic Danish lake. The autocalibration program Auto-Calibration Python (ACPy) was applied to achieve a more comprehensive adjustment of model parameters. The model simulations showed excellent agreement with observed data for water temperature, total nitrogen, and nitrate and good agreement for ammonium, total phosphorus, phosphate, and chlorophyll a concentrations. Zooplankton and macrophyte coverage were adequately simulated for the purpose of this study, and in general the GOTM-FABM-PCLake model simulations performed well compared with other model studies. In contrast to previous model studies ignoring depth heterogeneity, our bifurcation analysis revealed that the spatial extent and depth limitation of macrophytes as well as phytoplankton chlorophyll-a responded more gradually over time to a reduction in the external phosphorus load, albeit some hysteresis effects still appeared. In a management perspective, our study emphasizes the need to include depth heterogeneity in the model structure to more correctly determine at which external nutrient load a given lake changes ecosystem state to a clear-water condition.

We have investigated the role of human endogenous retroviruses in multiple sclerosis by analyzing the DNA of patients and controls in 4 cohorts for associations between multiple sclerosis and polymorphisms near viral restriction genes or near endogenous retroviral loci with one or more intact or almost-intact genes. We found that SNPs in the gene TRIM5 were inversely correlated with disease. Conversely, SNPs around one retroviral locus, HERV-Fc1, showed a highly significant association with disease. The latter association was limited to a narrow region that contains no other known genes. We conclude that HERV-Fc1 and TRIM5 play a role in the etiology of multiple sclerosis. If these results are confirmed, they point to new modes of treatment for multiple sclerosis.