Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon

NASA's Global Ecosystem Dynamic Investigation (GEDI) mission has been designed to measure forest structure using lidar waveforms to sample the earth's vegetation while in orbit aboard the International Space Station. In this paper, we used airborne large-footprint (LF) lidar measurements to simulate GEDI observations from which we retrieved ground elevation, vegetation height, and aboveground biomass (AGB). GEDI-like product accuracy was then assessed by comparing them to similar products derived from airborne small-footprint (SF) lidar measurements. The study focused on tropical forests and used data collected during the NASA and European Space Agency (ESA) AfriSAR ground and airborne campaigns in the Lope National Park in Central Gabon. The measurements covered a gradient of successional stages of forest development with different height, canopy density, and topography. The comparison of the two sensors shows that LF lidar waveforms and simulated waveforms from SF lidar are equivalent in their ability to estimate ground elevation (RMSE = 0.5 m, bias = 0.29 m) and maximum forest height (RMSE = 2.99 m, bias = 0.24 m) over the study area. The difference in the AGB estimated from both lidar instruments at the 1-ha spatial scale is small over the entire study area (RMSE = 6.34 Mg·ha-1, bias = 11.27 Mg·ha-1) and the bias is attributed to the impact of ground slopes greater than 10–20° on the LF lidar measurements of forest height. Our results support the ability of GEDILF lidar to measure the complex structure of humid tropical forests and provide AGB estimates comparable to SF-derived ones

Planning for Sustainability in Small Municipalities: The Influence of Interest Groups, Growth Patterns, and Institutional Characteristics

How and why small municipalities promote sustainability through planning efforts is poorly understood. We analyzed ordinances in 451 Maine municipalities and tested theories of policy adoption using regression analysis.We found that smaller communities do adopt programs that contribute to sustainability relevant to their scale and context. In line with the political market theory, we found that municipalities with strong environmental interests, higher growth, and more formal governments were more likely to adopt these policies. Consideration of context and capacity in planning for sustainability will help planners better identify and benefit from collaboration, training, and outreach opportunities

Paradoxical Effects of Rapamycin on Experimental House Dust Mite-Induced Asthma

The mammalian target of rapamycin (mTOR) modulates immune responses and cellular proliferation. The objective of this study was to assess whether inhibition of mTOR with rapamycin modifies disease severity in two experimental murine models of house dust mite (HDM)-induced asthma. In an induction model, rapamycin was administered to BALB/c mice coincident with nasal HDM challenges for 3 weeks. In a treatment model, nasal HDM challenges were performed for 6 weeks and rapamycin treatment was administered during weeks 4 through 6. In the induction model, rapamycin significantly attenuated airway inflammation, airway hyperreactivity (AHR) and goblet cell hyperplasia. In contrast, treatment of established HDM-induced asthma with rapamycin exacerbated AHR and airway inflammation, whereas goblet cell hyperplasia was not modified. Phosphorylation of the S6 ribosomal protein, which is downstream of mTORC1, was increased after 3 weeks, but not 6 weeks of HDM-challenge. Rapamycin reduced S6 phosphorylation in HDM-challenged mice in both the induction and treatment models. Thus, the paradoxical effects of rapamycin on asthma severity paralleled the activation of mTOR signaling. Lastly, mediastinal lymph node re-stimulation experiments showed that treatment of rapamycin-naive T cells with ex vivo rapamycin decreased antigen-specific Th2 cytokine production, whereas prior exposure to in vivo rapamycin rendered T cells refractory to the suppressive effects of ex vivo rapamycin. We conclude that rapamycin had paradoxical effects on the pathogenesis of experimental HDM-induced asthma. Thus, consistent with the context-dependent effects of rapamycin on inflammation, the timing of mTOR inhibition may be an important determinant of efficacy and toxicity in HDM-induced asthma

MYC Cooperates with AKT in Prostate Tumorigenesis and Alters Sensitivity to mTOR Inhibitors

MYC and phosphoinositide 3-kinase (PI3K)-pathway deregulation are common in human prostate cancer. Through examination of 194 human prostate tumors, we observed statistically significant co-occurrence of MYC amplification and PI3K-pathway alteration, raising the possibility that these two lesions cooperate in prostate cancer progression. To investigate this, we generated bigenic mice in which both activated human AKT1 and human MYC are expressed in the prostate (MPAKT/Hi-MYC model). In contrast to mice expressing AKT1 alone (MPAKT model) or MYC alone (Hi-MYC model), the bigenic phenotype demonstrates accelerated progression of mouse prostate intraepithelial neoplasia (mPIN) to microinvasive disease with disruption of basement membrane, significant stromal remodeling and infiltration of macrophages, B- and T-lymphocytes, similar to inflammation observed in human prostate tumors. In contrast to the reversibility of mPIN lesions in young MPAKT mice after treatment with mTOR inhibitors, Hi-MYC and bigenic MPAKT/Hi-MYC mice were resistant. Additionally, older MPAKT mice showed reduced sensitivity to mTOR inhibition, suggesting that additional genetic events may dampen mTOR dependence. Since increased MYC expression is an early feature of many human prostate cancers, these data have implications for treatment of human prostate cancers with PI3K-pathway alterations using mTOR inhibitors

Stakeholder analysis for a maternal and newborn health project in Eastern Uganda

Background Based on the realization that Uganda is not on track to achieving Millennium Development Goals 4 and 5, Makerere University School of Public Health in collaboration with other partners proposed to conduct two community based maternal/newborn care interventions aimed at increasing access to health facility care through transport vouchers and use of community health workers to promote ideal family care practices. Prior to the implementation, a stakeholder analysis was undertaken to assess and map stakeholders’ interests, influence/power and position in relation to the interventions; their views regarding the success and sustainability; and how this research can influence policy formulation in the country. Methods A stakeholder analysis was carried out in March 2011 at national level and in four districts of Eastern Uganda where the proposed interventions would be conducted. At the national level, four key informant interviews were conducted with the ministry of health representative, Member of Parliament, and development partners. District health team members were interviewed and also engaged in a workshop; and at community level, twelve focus group discussions were conducted among women, men and motorcycle transporters. Results This analysis revealed that district and community level stakeholders were high level supporters of the proposed interventions but not drivers. At community level the mothers, their spouses and transporters were of low influence due to the limited funds they possessed. National level and district stakeholders believed that the intervention is costly and cannot be affordably scaled up. They advised the study team to mobilize and sensitize the communities to contribute financially from the start in order to enhance sustainability beyond the study period. Stakeholders believed that the proposed interventions will influence policy through modeling on how to improve the quality of maternal/newborn health services, male involvement, and improved accessibility of services. Conclusion Most of the stakeholders interviewed were supporters of the proposed maternal and newborn care intervention because of the positive benefits of the intervention. The analysis highlighted stakeholder concerns that will be included in the final project design and that could also be useful in countries of similar setting that are planning to set up programmes geared at increasing access to maternal and new born interventions. Key among these concerns was the need to use both human and financial resources that are locally available in the community, to address supply side barriers that influence access to maternal and child healthcare. Research to policy translation, therefore, will require mutual trust, continued dialogue and engagement of the researchers, implementers and policy makers to enable scale up.UKai

Research priorities for climate mobility

The escalating impacts of climate change on the movement and immobility of people, coupled with false but influential narratives of mobility, highlight an urgent need for nuanced and synthetic research around climate mobility. Synthesis of evidence and gaps across the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report highlight a need to clarify the understanding of what conditions make human mobility an effective adaptation option and its nuanced outcomes, including simultaneous losses, damages, and benefits. Priorities include integration of adaptation and development planning; involuntary immobility and vulnerability; gender; data for cities; risk from responses and maladaptation; public understanding of climate risk; transboundary, compound, and cascading risks; nature-based approaches; and planned retreat, relocation, and heritage. Cutting across these priorities, research modalities need to better position climate mobility as type of mobility, as process, and as praxis. Policies and practices need to reflect the diverse needs, priorities, and experiences of climate mobility, emphasizing capability, choice, and freedom of movement

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10(-8)), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.Please refer to the manuscript or visit the publisher's website for funding infomation

Proceedings of the 13th annual conference of INEBRIA

CITATION: Watson, R., et al. 2016. Proceedings of the 13th annual conference of INEBRIA. Addiction Science & Clinical Practice, 11:13, doi:10.1186/s13722-016-0062-9.The original publication is available at https://ascpjournal.biomedcentral.comENGLISH SUMMARY : Meeting abstracts.https://ascpjournal.biomedcentral.com/articles/10.1186/s13722-016-0062-9Publisher's versio