Remote sensing-based statistical approach for defining drained lake basins in a continuous Permafrost region, North Slope of Alaska

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered \u3e71,000 km2, including a \u3e39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2– 95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-lat-itude carbon cycling

A decade of remotely sensed observations highlight complex processes linked to coastal permafrost bluff erosion in the Arctic

Eroding permafrost coasts are likely indicators and integrators of changes in the Arctic System as they are susceptible to the combined effects of declining sea ice extent, increases in open water duration, more frequent and impactful storms, sea-level rise, and warming permafrost. However, few observation sites in the Arctic have yet to link decadal-scale erosion rates with changing environmental conditions due to temporal data gaps. This study increases the temporal fidelity of coastal permafrost bluff observations using near-annual high spatial resolution (<1 m) satellite imagery acquired between 2008–2017 for a 9 km segment of coastline at Drew Point, Beaufort Sea coast, Alaska. Our results show that mean annual erosion for the 2007–2016 decade was 17.2 m yr−1, which is 2.5 times faster than historic rates, indicating that bluff erosion at this site is likely responding to changes in the Arctic System. In spite of a sustained increase in decadal-scale mean annual erosion rates, mean open water season erosion varied from 6.7 m yr−1 in 2010 to more than 22.0 m yr−1 in 2007, 2012, and 2016. This variability provided a range of coastal responses through which we explored the different roles of potential environmental drivers. The lack of significant correlations between mean open water season erosion and the environmental variables compiled in this study indicates that we may not be adequately capturing the environmental forcing factors, that the system is conditioned by long-term transient effects or extreme weather events rather than annual variability, or that other not yet considered factors may be responsible for the increased erosion occurring at Drew Point. Our results highlight an increase in erosion at Drew Point in the 21st century as well as the complexities associated with unraveling the factors responsible for changing coastal permafrost bluffs in the Arctic

Prognostic utility of Fibrosis-4 Index for risk of subsequent liver and cardiovascular events, and all-cause mortality in individuals with obesity and/or type 2 diabetes: a longitudinal cohort studyResearch in context panel

Summary: Background: The Fibrosis-4 Index (FIB-4) is used as a non-invasive tool for the presence of advanced liver fibrosis in metabolic dysfunction-associated steatotic liver disease and type 2 diabetes. However, evidence for an association between FIB-4 and risk of mortality and/or liver-related clinical outcomes is limited. The aim of this study was to investigate the association between FIB-4 and subsequent liver events, cardiovascular events, and all-cause mortality in individuals with obesity and/or type 2 diabetes examined in routine general practice. Methods: This was a longitudinal cohort study in which eligible adults had obesity and/or type 2 diabetes and ≥1 FIB-4 score calculable from UK Clinical Practice Research Datalink GOLD after 1 January 2001. No alcohol-related disorders and/or chronic liver diseases (except non-alcoholic fatty liver disease) and/or no prescriptions of drugs inducing liver disease were permitted. Individuals were followed until time of first event, 10 years, or 1 January 2020. Analyses were conducted using Aalen-Johansen cumulative incidence functions and Cox proportional hazards models. Findings: Among 44,481 included individuals (mean age 58·8 years; 54% female), there were 979 liver, 6002 cardiovascular, and 8971 mortality events during the 10 years of follow-up. At 10 years, the cumulative incidence of liver events in the high (>2·67), indeterminate (1·30–2·67), and low (<1·30) baseline FIB-4 risk groups were 15%, 3%, and 1%, respectively. Age- and sex-adjusted hazard ratios (HRs) for liver events were elevated in high (16·46; 95% confidence interval [CI] 13·65–19·85) and indeterminate (2·45; 95% CI 2·07–2·90) versus low FIB-4 risk groups. Similar results were found for cardiovascular events and all-cause mortality. Among 20,433 individuals with ≥2 FIB-4 measurements, increase/decrease in FIB-4 12 months after baseline was directly associated with risk of liver events: compared with individuals with low baseline FIB-4 and no change in FIB-4 (reference), the adjusted HR (95% CI) for those with high baseline FIB-4 was 24·27 (16·98–34·68) with a one-unit FIB-4 increase, and 10·90 (7·90–15·05) with a one-unit decrease. Interpretation: In addition to its value as a diagnostic tool, FIB-4 has clinical utility as a prognostic biomarker. Sequential measurement provides a pragmatic, tractable monitoring biomarker that refines risk assessment for liver events, cardiovascular events, and mortality. Funding: Novo Nordisk A/S

Collagen induces maturation of human monocyte-derived dendritic cells by signaling through osteoclast-associated receptor

Osteoclast-associated receptor (OSCAR) is widely expressed on human myeloid cells. Collagen types (Col)I, II, and III have been described as OSCAR ligands, and ColII peptides can induce costimulatory signaling in receptor activator for NF-κB–dependent osteoclastogenesis. In this study, we isolated collagen as an OSCAR-interacting protein from the membranes of murine osteoblasts. We have investigated a functional outcome of the OSCAR–collagen interaction in human monocyte-derived dendritic cells (DCs). OSCAR engagement by ColI/II-induced activation/maturation of DCs is characterized by upregulation of cell surface markers and secretion of cytokines. These collagen-matured DCs (Col-DCs) were efficient drivers of allogeneic and autologous naive T cell proliferation. The T cells expanded by Col-DCs secreted cytokines with no clear T cell polarization pattern. Global RNA profiling revealed that multiple proinflammatory mediators, including cytokines and cytokine receptors, components of the stable immune synapse (namely CD40, CD86, CD80, and ICAM-1), as well as components of TNF and TLR signaling, are transcriptional targets of OSCAR in DCs. Our findings indicate the existence of a novel pathway by which extracellular matrix proteins locally drive maturation of DCs during inflammatory conditions, for example, within synovial tissue of rheumatoid arthritis patients, where collagens become exposed during tissue remodeling and are thus accessible for interaction with infiltrating precursors of DCs

Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska.

Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (\u3e25% of area) or completely drained during the 62-year period. Decadal-scale lake drainage rates progressively declined from 2.0 lakes/yr (1955-1975), to 1.6 lakes/yr (1975-2000), and to 1.2 lakes/yr (2000-2017) in the ~30,000-k

Towards panarctic mapping of drained lake basins in permafrost regions

Lakes and drained lake basins (DLBs) are dominant landforms across Arctic lowland regions. The long-term dynamics of lake formation and drainage is evident in the abundance of lakes and DLBs covering as much as 80% of the landscape in various regions of Arctic Alaska, Russia, and Canada. Lake drainage can be triggered through different mechanisms such as lake tapping by an adjacent stream, bank overflow or ice wedge degradation. Following drainage, DLBs can become valuable grazing land for caribou and reindeer as well as usable land for infrastructure development due to low ground ice content in recent DLBs. In addition, DLBs can be sites for soil organic carbon accumulation in the form of peat which also play a role for carbon cycling. Comprehensive and accurate mapping of DLB distribution, age and drainage mechanism, will further inform our understanding of their role in permafrost landscape evolution across varying timescales. DLBs differ from the surrounding terrain in vegetation structure and composition, soil moisture, elevation, size and types of ice-wedge polygons and other parameters that make them an identifiable target based on remote sensing data. Here, we present a novel approach to map DLBs in permafrost landscapes with a specific focus on the North Slope of Alaska as well as select areas in Siberia and northwestern Canada. To map DLBs, we combined multispectral satellite imagery (Landsat-8 and Sentinel-2), Synthetic Aperture Radar (SAR) acquisitions (Sentinel-1), and DEM data (ArcticDEM). To cover the entire study area in each region, we included Landsat-8 acquisitions from all available years and Sentinel-2 for 2016 and 2018 to create cloud-free mosaics. The classification combines methodologies from pixel-based and object-based image analysis. To allow for processing of these large datasets that cover more than 200.000 km2, a classification workflow was developed in Google Earth Engine. Preliminary results show good agreement of our classification with previously published data sets for subsets of our North Slope study area. This work marks the first attempt to map DLBs at the pan-Arctic scale. Our results highlight the importance of treating areas of different surficial geology and vegetation communities separately in the classification process to ensure higher classification accuracy