HOIL1 regulates group 2 innate lymphoid cell numbers and type 2 inflammation in the small intestine

Patients with mutations in HOIL1 experience a complex immune disorder including intestinal inflammation. To investigate the role of HOIL1 in regulating intestinal inflammation, we employed a mouse model of partial HOIL1 deficiency. The ileum of HOIL1-deficient mice displayed features of type 2 inflammation including tuft cell and goblet cell hyperplasia, and elevated expression of Il13, Il5 and Il25 mRNA. Inflammation persisted in the absence of T and B cells, and bone marrow chimeric mice revealed a requirement for HOIL1 expression in radiation-resistant cells to regulate inflammation. Although disruption of IL-4 receptor alpha (IL4Rα) signaling on intestinal epithelial cells ameliorated tuft and goblet cell hyperplasia, expression of Il5 and Il13 mRNA remained elevated. KLRG

Parks Canada’s adaptation framework and workshop approach: Lessons learned across a diverse series of adaptation workshops

In 2017, the Canadian Parks Council Climate Change Working Group, a team of federal, provincial, and territorial representatives, developed a Climate Change Adaptation Framework for Parks and Protected Areas, guiding practitioners through a simple, effective five-step adaptation process. This framework was adapted by Parks Canada into a two-day adaptation workshop approach, with 11 workshops subsequently held from September 2017 to May 2019 at Parks Canada sites in the Yukon, Quebec, Manitoba, Alberta, Nova Scotia, British Columbia, Newfoundland, and Ontario. Lessons learned from each workshop have been integrated into the approach, with the development of tools and guidance for each phase of the process, and a shareable, visual “placemat” that describes each step of the framework, acting as a map for those navigating the process

Towards outperforming conventional sensor arrays with fabricated individual photonic vapour sensors inspired by Morpho butterflies.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Combining vapour sensors into arrays is an accepted compromise to mitigate poor selectivity of conventional sensors. Here we show individual nanofabricated sensors that not only selectively detect separate vapours in pristine conditions but also quantify these vapours in mixtures, and when blended with a variable moisture background. Our sensor design is inspired by the iridescent nanostructure and gradient surface chemistry of Morpho butterflies and involves physical and chemical design criteria. The physical design involves optical interference and diffraction on the fabricated periodic nanostructures and uses optical loss in the nanostructure to enhance the spectral diversity of reflectance. The chemical design uses spatially controlled nanostructure functionalization. Thus, while quantitation of analytes in the presence of variable backgrounds is challenging for most sensor arrays, we achieve this goal using individual multivariable sensors. These colorimetric sensors can be tuned for numerous vapour sensing scenarios in confined areas or as individual nodes for distributed monitoring.We would like to acknowledge H. Ghiradella (University at Albany), M. Blohm and S. Duclos (GE) and V. Greanya, J. Abo-Shaeer, C. Nehl and M. Sandrock (DARPA) for fruitful discussions. This work has been supported in part from DARPA contract W911NF-10-C-0069 ‘Bio Inspired Photonics’ and from General Electric’s Advanced Technology research funds. The content of the information does not necessarily reflect the position or the policy of the US Government

Contrasting rhizosphere soil nutrient economy of plants associated with arbuscular mycorrhizal and ectomycorrhizal fungi in karst forests

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordData availability: Requests for data or other materials should be directed to Xinyu Zhang ([email protected]).Purpose Plants growing in the soils of karst forests associate with arbuscular mycorrhizae (AM) or ectomycorrhizae (ECM) to acquire nutrients. We researched how these different mycorrhizal associations affect rhizosphere soil nutrient economy in these calcareous soils. Methods Bulk and rhizosphere soils were sampled beneath 25 AM and 9 ECM plants growing in primary forests at the Puding Karst Critical Zone Observatory. Nutrient contents and potential enzyme activities were analyzed to test the effect of different types of mycorrhizal association on rhizosphere soil nitrogen (N) and phosphorus (P) economies. Results The contents of nitrate-N and available-P were markedly lower in the rhizospheres of ECM plants compared to AM plants. Ectomycorrhizal plants promoted relatively greater investment in N-acquisition enzymes, in contrast, AM plants caused relatively greater investment in P-acquisition enzymes. The decreased pH in the rhizospheres of AM plants likely promoted the greater P availability. Conclusion Our results revealed how plants that form contrasting mycorrhizal associations have fundamentally different effects on rhizospheric nutrient economies in the low fertility karst soils of southwest China. Differentiation in N- and P-acquisition capacity of these plants have implications for species coexistence and the high levels of plant biodiversity observed in these forests.National Natural Science Foundation of ChinaNational Key Research and Development ProgramNatural Environment Research Council (NERC

Unraveling trade‐offs among reforestation, urbanization and food security in the South China Karst Region: How can a hinterland province achieve SDGs?

This is the author accepted manuscript. Available on open access from Wiley via the DOI in this recordWhether the world can achieve the United Nations Sustainable Development Goals (SDGs) largely depends on the ability of less-developed areas to cope with multiple socio-economic changes. The challenges that hinterland areas would face during the realization of SDGs has not yet received enough attentions. In this study, a context-based assessment of regional food balances was conducted, considering key challenges related to socio-economic development as well as land use competition under the framework of the shared socioeconomic pathways (SSPs) and the implementation of reforestation. We examined one of the poorest hinterland provinces in China as a case study, projecting its food deficit and exploring the potential threats to and opportunities for SDG realization by 2030, including population growth, urbanization, urban land expansion and reforestation. The projections revealed a crop deficit of 4.9-9.8 million tonnes, corresponding to the food demands of 10.2-20.6 million people. Approximately 76-81% of this deficit was expected to be caused by increased food demand, rather than reforestation policies. Therefore, for this less-developed area with low agricultural productivity and large groups of vulnerable people, population growth and urbanization are likely to result in demands for food that cannot be met locally. In addition, large-scale reforestation projects, while enhancing a number of key ecosystem services, will increase the local food deficit by promoting the abandonment of cropland. This will result in greater reliance on food imports, with potential impacts on SDG realization in other regions. These findings highlight the need for integrated governance across multiple scales to ensure hinterland sustainability.Natural Environment Research Council (NERC)National Natural Science Foundation of Chin

Elevation and cholera: an epidemiological spatial analysis of the cholera epidemic in Harare, Zimbabwe, 2008-2009

BACKGROUND: In highly populated African urban areas where access to clean water is a challenge, water source contamination is one of the most cited risk factors in a cholera epidemic. During the rainy season, where there is either no sewage disposal or working sewer system, runoff of rains follows the slopes and gets into the lower parts of towns where shallow wells could easily become contaminated by excretes. In cholera endemic areas, spatial information about topographical elevation could help to guide preventive interventions. This study aims to analyze the association between topographic elevation and the distribution of cholera cases in Harare during the cholera epidemic in 2008 and 2009. METHODS: We developed an ecological study using secondary data. First, we described attack rates by suburb and then calculated rate ratios using whole Harare as reference. We illustrated the average elevation and cholera cases by suburbs using geographical information. Finally, we estimated a generalized linear mixed model (under the assumption of a Poisson distribution) with an Empirical Bayesian approach to model the relation between the risk of cholera and the elevation in meters in Harare. We used a random intercept to allow for spatial correlation of neighboring suburbs. RESULTS: This study identifies a spatial pattern of the distribution of cholera cases in the Harare epidemic, characterized by a lower cholera risk in the highest elevation suburbs of Harare. The generalized linear mixed model showed that for each 100 meters of increase in the topographical elevation, the cholera risk was 30% lower with a rate ratio of 0.70 (95% confidence interval=0.66-0.76). Sensitivity analysis confirmed the risk reduction with an overall estimate of the rate ratio between 20% and 40%. CONCLUSION: This study highlights the importance of considering topographical elevation as a geographical and environmental risk factor in order to plan cholera preventive activities linked with water and sanitation in endemic areas. Furthermore, elevation information, among other risk factors, could help to spatially orientate cholera control interventions during an epidemic

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

Protein Microarray On-Demand: A Novel Protein Microarray System

We describe a novel, simple and low-cost protein microarray strategy wherein the microarrays are generated by printing expression ready plasmid DNAs onto slides that can be converted into protein arrays on-demand. The printed expression plasmids serve dual purposes as they not only direct the synthesis of the protein of interest; they also serve to capture the newly synthesized proteins through a high affinity DNA-protein interaction. To accomplish this we have exploited the high-affinity binding (∼3–7×10 −13 M) of E. coli Tus protein to Ter, a 20 bp DNA sequence involved in the regulation of E. coli DNA replication. In our system, each protein of interest is synthesized as a Tus fusion protein and each expression construct directing the protein synthesis contains embedded Ter DNA sequence. The embedded Ter sequence functions as a capture reagent for the newly synthesized Tus fusion protein. This “all DNA” microarray can be converted to a protein microarray on-demand without need for any additional capture reagent.

Analysing and simulating spatial patterns of crop yield in Guizhou Province based on artificial neural networks

Supplemental material for this article is available online.This is the author accepted manuscript, the final version is available from SAGE via the DOI in this record.The area of karst terrain in China covers 3.63×106 km2, with more than 40% in the southwestern region over the Guizhou Plateau. Karst comprises exposed carbonate bedrock over approximately 1.30×106 km2 of this area, which suffers from soil degradation and poor crop yield. This paper aims to gain a better understanding of the environmental controls on crop yield in order to enable more sustainable use of natural resources for food production and development. More precisely, four kinds of artificial neural network were used to analyse and simulate the spatial patterns of crop yield for seven crop species grown in Guizhou Province, exploring the relationships with meteorological, soil, irrigation and fertilization factors. The results of spatial classification showed that most regions of high-level crop yield per area and total crop yield are located in the central-north area of Guizhou. Moreover, the three artificial neural networks used to simulate the spatial patterns of crop yield all demonstrated a good correlation coefficient between simulated and true yield. However, the Back Propagation network had the best performance based on both accuracy and runtime. Among the 13 influencing factors investigated, temperature (16.4%), radiation (15.3%), soil moisture (13.5%), fertilization of N (13.5%) and P (12.4%) had the largest contribution to crop yield spatial distribution. These results suggest that neural networks have potential application in identifying environmental controls on crop yield and in modelling spatial patterns of crop yield, which could enable local stakeholders to realize sustainable development and crop production goals.Natural Environment Research Council (NERC)National Natural Science Foundation of ChinaChina Scholarship Counci

Effectiveness of an implementation optimisation intervention aimed at increasing parent engagement in HENRY, a childhood obesity prevention programme - the Optimising Family Engagement in HENRY (OFTEN) trial: study protocol for a randomised controlled trial

Background: Family-based interventions to prevent childhood obesity depend upon parents’ taking action to improve diet and other lifestyle behaviours in their families. Programmes that attract and retain high numbers of parents provide an enhanced opportunity to improve public health and are also likely to be more cost-effective than those that do not. We have developed a theory-informed optimisation intervention to promote parent engagement within an existing childhood obesity prevention group programme, HENRY (Health Exercise Nutrition for the Really Young). Here, we describe a proposal to evaluate the effectiveness of this optimisation intervention in regard to the engagement of parents and cost-effectiveness. Methods/design: The Optimising Family Engagement in HENRY (OFTEN) trial is a cluster randomised controlled trial being conducted across 24 local authorities (approximately 144 children’s centres) which currently deliver HENRY programmes. The primary outcome will be parental enrolment and attendance at the HENRY programme, assessed using routinely collected process data. Cost-effectiveness will be presented in terms of primary outcomes using acceptability curves and through eliciting the willingness to pay for the optimisation from HENRY commissioners. Secondary outcomes include the longitudinal impact of the optimisation, parent-reported infant intake of fruits and vegetables (as a proxy to compliance) and other parent-reported family habits and lifestyle. Discussion: This innovative trial will provide evidence on the implementation of a theory-informed optimisation intervention to promote parent engagement in HENRY, a community-based childhood obesity prevention programme. The findings will be generalisable to other interventions delivered to parents in other community-based environments. This research meets the expressed needs of commissioners, children’s centres and parents to optimise the potential impact that HENRY has on obesity prevention. A subsequent cluster randomised controlled pilot trial is planned to determine the practicality of undertaking a definitive trial to robustly evaluate the effectiveness and cost-effectiveness of the optimised intervention on childhood obesity prevention