State Policy Report - Disaster Resilience: 2022 Session Recap

This report identifies trends in state disaster resilience policy among enacted legislation from the 2021-2022 legislative session. Legislative trends are presented by state and region and by 12 categories: Funding, Energy, Communications, Transportation, Safety and Security, Health and Medical, Food and Water, Housing, Hazardous Materials, Land Use, Governance, and Equity. The report discusses and contextualizes findings in greater detail across funding, governance, critical infrastructure, health and human services, and equity. With recent policy emphasis on disaster mitigation, equity, and climate change at the federal level, the report aims to shed light on state-level policy priorities via enacted legislation

State Policy Report - Disaster Resilience: 2023 Session Recap

This report identifies trends in state disaster resilience policy among legislation enacted in 2023. Legislative trends are presented by state and region and by 12 categories: Funding, Energy, Communications, Transportation, Safety and Security, Health and Medical, Food and Water, Housing, Hazardous Materials, Land Use, Governance, and Equity. The report discusses and contextualizes findings in greater detail across funding, governance, critical infrastructure, health and human services, and equity. With recent policy emphasis on disaster mitigation, equity, and climate change at the federal level, the report aims to shed light on state-level policy priorities via enacted legislation

Burping wetlands : quantifying greenhouse gas ebullition rates across a range of sediment types and characteristics, water quality variables, and land use

Aquatic ecosystems are a source of greenhouse gases (GHG) to the atmosphere. One pathway of this GHG release is ebullition, or bubbling, from aquatic sediments. The contribution of ebullition is often underestimated in global GHG budgets, as it is rarely included in GHG emission measurements. The ebullition pathway can account for up to 67 percent of methane emissions from water bodies. We aim to determine the factors that influence ebullition of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O), including sediment characteristics, water quality characteristics, and land use. Our study ponds are in urban, agricultural, and woodland areas. We found that N2O flux rates are significantly lower than CH4 and CO2 flux rates across all study ponds. We also found that urban areas have higher GHG flux rates, which is correlated with low organic matter content. Understanding the factors influencing GHG ebullition from aquatic ecosystems will give us a broader understanding of the significance of their contribution to global GHG budgets in a changing climate.Jannice Newson, Jaylen Bragg, Hamza Amjad, Lauren Dyck, Selena Komarevich, Colin Whitfield, Helen Baulch, Jason Venkiteswaran, Nora Casson, Richard Helmle, and Rebecca L. North (University of Missouri, University of Winnipeg, University of Saskatchewan, Wilfred Laurier University

ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition

Sign languages are used as a primary language by approximately 70 million D/deaf people world-wide. However, most communication technologies operate in spoken and written languages, creating inequities in access. To help tackle this problem, we release ASL Citizen, the first crowdsourced Isolated Sign Language Recognition (ISLR) dataset, collected with consent and containing 83,399 videos for 2,731 distinct signs filmed by 52 signers in a variety of environments. We propose that this dataset be used for sign language dictionary retrieval for American Sign Language (ASL), where a user demonstrates a sign to their webcam to retrieve matching signs from a dictionary. We show that training supervised machine learning classifiers with our dataset advances the state-of-the-art on metrics relevant for dictionary retrieval, achieving 63% accuracy and a recall-at-10 of 91%, evaluated entirely on videos of users who are not present in the training or validation sets. An accessible PDF of this article is available at the following link: https://aashakadesai.github.io/research/ASLCitizen_arxiv_updated.pd

Collaboration and contestation in further and higher education partnerships in England: a Bourdieusian field analysis

Internationally, ‘College for All’ policies are creating new forms of vocational higher education (HE), and shifting relationships between HE and further education (FE) institutions. In this paper, we consider the way in which this is being implemented in England, drawing on a detailed qualitative case study of a regional HE–FE partnership to widen participation. We focus on the complex mix of collaboration and contestation that arose within it, and how these affected socially differentiated groups of students following high- and low-status routes through its provision. We outline Bourdieu’s concept of ‘field’ as a framework for our analysis and interpretation, including its theoretical ambiguities regarding the definition and scale of fields. Through hermeneutic dialogue between data and theory, we tentatively suggest that such partnerships represent bridges between HE and FE. These bridges are strong between higher-status institutions, but highly contested between lower-status institutions competing closely for distinction. We conclude that the trajectories and outcomes for socially disadvantaged students require attention and collective action to address the inequalities they face, and that our theoretical approach may have wider international relevance beyond the English case

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P&lt;5×10 - 8 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care. </p

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Phage Encoded H-NS: A Potential Achilles Heel in the Bacterial Defence System

The relationship between phage and their microbial hosts is difficult to elucidate in complex natural ecosystems. Engineered systems performing enhanced biological phosphorus removal (EBPR), offer stable, lower complexity communities for studying phage-host interactions. Here, metagenomic data from an EBPR reactor dominated by Candidatus Accumulibacter phosphatis (CAP), led to the recovery of three complete and six partial phage genomes. Heat-stable nucleoid structuring (H-NS) protein, a global transcriptional repressor in bacteria, was identified in one of the complete phage genomes (EPV1), and was most similar to a homolog in CAP. We infer that EPV1 is a CAP-specific phage and has the potential to repress up to 6% of host genes based on the presence of putative H-NS binding sites in the CAP genome. These genes include CRISPR associated proteins and a Type III restriction-modification system, which are key host defense mechanisms against phage infection. Further, EPV1 was the only member of the phage community found in an EBPR microbial metagenome collected seven months prior. We propose that EPV1 laterally acquired H-NS from CAP providing it with a means to reduce bacterial defenses, a selective advantage over other phage in the EBPR system. Phage encoded H-NS could constitute a previously unrecognized weapon in the phage-host arms race

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care