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Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R > 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions.

Monitoring changes in vegetation cover over time is crucial for understanding the spatial distribution of rainfall, as well as the dynamics of plants and animals in the Namib desert. Traditional vegetation indices have limitations in capturing changes in vegetation cover within water-limited ecosystems like the Namib gravel plains. Spectral emissivity derived from thermal infrared remote sensing has recently emerged as a promising tool for distinguishing between bare ground and non-green vegetation in arid environments. This study investigates the potential of satellite-derived emissivities for mapping changes in fractional vegetation cover across the Namib gravel plains. Analyzing Moderate Resolution Imaging Spectroradiometer (MODIS) band 29 (λ = 8.55 µm) emissivity time series from 2001 to 2021, our findings demonstrate the ability of both Normalized Difference Vegetation Index (NDVI) and emissivity to detect sudden vegetation growth on the gravel plains. Emissivity additionally allows monitoring the extent of desiccated grass over several years after a rainfall event. Our results support a relationship between the change in fractional vegetation cover, the amount of rainfall and emissivity change magnitude. Information from NDVI and emissivity therefore provide complementary information for assessing vegetation in arid environments.

Snow cover is an important freshwater source in many mountain ranges around the world and is heavily affected by climate change, often leading to reduced overall snow cover availability and duration as well as shifts in seasonality. To monitor these changes and long-term trends, the analysis of remote sensing is a commonly used tool, as data are available consistently and for long time series. In this study we acquired and processed the whole archive of available Landsat data between 1985 and 2024 for two catchments in the Chilean Andes, Aconcagua and Río Maipo, located in the Valparaíso and Santiago de Chile metropolitan regions, respectively. We generated monthly Snow Line Elevation (SLE) time series from the entire archive for both catchments and performed trend analyses on these time series. Strong positive long-term SLE change rates of 11.25 m per year for the Aconcagua catchment and 9.85 m to 15.65 m per year for the Río Maipo catchment were detected, indicating a decrease in snow cover as well as available freshwater from snowmelt. The projection to the year 2050 revealed a potential loss of snow covered area of up to 42% during summer months, with the SLE receding up to 231 m.

Peatlands play an important role as local carbon sinks and climate archives in natural environments. In addition to degradation by human activities, peatlands can also be affected by geomorphological processes such as fluvial erosion. This study used a collection of multi-temporal 3D point clouds to investigate such a situation in a valley of the Central Alps (Austria), where a dynamically migrating river is eroding peat. To detect time periods and locations where strong erosion occurred and to quantify the local peat erosion rate over the years 2006 to 2024, 3D point clouds from airborne laser scanning (ALS), uncrewed aerial vehicle laser scanning (ULS), and uncrewed aerial vehicle photogrammetry (UPH) were used (i) in a pair-wise Multiscale Model-to-Model Cloud Comparison (M3C2) change detection and quantification and (ii) in a time-series clustering approach. In the most dynamic sections of the river bank, the mean rate of peat erosion over the eighteen-year period was −0.12 ± 0.03 m/year. Moreover, the relationship between peatland erosion and main channel migration is investigated based on a set of surface elevation transects and multi-temporal mapping of the main channels. Overall, these methods provided detailed insights into the dynamics and functioning of local geomorphological processes, such as lateral undercutting with subsequent toppling and sliding of the peat bank.

After a period of rapidly declining U.S. COVID-19 incidence during January-March 2021, increases occurred in several jurisdictions (1,2) despite the rapid rollout of a large-scale vaccination program. This increase coincided with the spread of more transmissible variants of SARS-CoV-2, the virus that causes COVID-19, including B.1.1.7 (1,3) and relaxation of COVID-19 prevention strategies such as those for businesses, large-scale gatherings, and educational activities. To provide long-term projections of potential trends in COVID-19 cases, hospitalizations, and deaths, COVID-19 Scenario Modeling Hub teams used a multiple-model approach comprising six models to assess the potential course of COVID-19 in the United States across four scenarios with different vaccination coverage rates and effectiveness estimates and strength and implementation of nonpharmaceutical interventions (NPIs) (public health policies, such as physical distancing and masking) over a 6-month period (April-September 2021) using data available through March 27, 2021 (4). Among the four scenarios, an accelerated decline in NPI adherence (which encapsulates NPI mandates and population behavior) was shown to undermine vaccination-related gains over the subsequent 2-3 months and, in combination with increased transmissibility of new variants, could lead to surges in cases, hospitalizations, and deaths. A sharp decline in cases was projected by July 2021, with a faster decline in the high-vaccination scenarios. High vaccination rates and compliance with public health prevention measures are essential to control the COVID-19 pandemic and to prevent surges in hospitalizations and deaths in the coming months.

The P2X3 receptor (P2X3R), an ATP-gated non-selective cation channel of the P2X receptor family, is expressed in sensory neurons and involved in nociception. P2X3R inhibition was shown to reduce chronic and neuropathic pain. In a previous screening of 2000 approved drugs, natural products and bioactive substances, various non-steroidal anti-inflammatory drugs (NSAIDs) were found to inhibit P2X3R-mediated currents. To investigate whether the inhibition of P2X receptors contributes to the analgesic effect of NSAIDs, we characterized the potency and selectivity of various NSAIDs at P2X3R and other P2XR subtypes using two-electrode voltage clamp electrophysiology. We identified diclofenac as a hP2X3R and hP2X2/3R antagonist with micromolar potency (with IC50 values of 138.2 µM and 76.7 µM, respectively). A weaker inhibition of hP2X1R, hP2X4R and hP2X7R by diclofenac was determined. Flufenamic acid (FFA) proved to inhibit hP2X3R, rP2X3R and hP2X7R (IC50 values of 221µM, 264.1µM and ∼ 900µM, respectively), questioning its widespread use as a nonselective ion channel blocker, when P2XR-mediated currents are under study. Inhibition of the hP2X3R or hP2X2/3R by diclofenac could be overcome by prolonged ATP-application or increasing concentrations of the agonist α,β-meATP, respectively, indicating competition of diclofenac and the agonists. Molecular dynamics simulation showed that diclofenac largely overlaps with ATP bound to the open state of the hP2X3R. Our results strongly support a competitive antagonism through which diclofenac, by interacting with residues of the ATP-binding site, left flipper, and dorsal fin domains inhibits gating of P2X3R by conformational fixation of the left flipper and dorsal fin domains. In summary, we demonstrate the inhibition of the human P2X3 receptor by various NSAIDs. Diclofenac proved to be the most effective antagonist with a strong inhibition of hP2X3R and hP2X2/3R and a weaker inhibition of hP2X1R, hP2X4R and hP2X7R. Considering their involvement in nociception, inhibition of hP2X3R and hP2X2/3R by micromolar concentrations of diclofenac may contribute to the analgesic effect as well as the side effect of taste disturbances of diclofenac and represent an additional mode of action besides the well-known high potency COX inhibition.

Background & Aims: The Rspo–Lgr4/5–Znrf3/Rnf43 module is a master regulator of hepatic Wnt/β–catenin signaling and metabolic zonation, but its impact on nonalcoholic fatty liver disease (NAFLD) remains unclear. We studied whether liver–specific loss of the Wnt/β–catenin modulators Leucine–Rich Repeat–Containing G Protein–Coupled Receptor 4/5 (Lgr4/5) promotes nonalcoholic fatty liver disease (NAFLD). Methods: Mice with liver–specific deletion of both receptors Lgr4/5 (Lgr4/5dLKO) were fed with normal diet (ND) or high fat diet (HFD). Livers of these mice were analyzed for lipid and fibrotic content by tissue staining and immunohistochemistry (IHC), and lipoproteins, inflammation and liver enzyme markers were measured in blood. Mechanistic insights into hepatic lipid accumulation were obtained by using ex vivo primary hepatocyte cultures derived from the Lgr4/5dLKO mice. Lipid analysis of mouse livers was performed by mass spectrometry (MS)–based untargeted lipidomic analysis. Results: We demonstrated that liver-specific ablation of Lgr4/5–mediated Wnt signaling resulted in hepatic steatosis, impaired bile acid (BA) secretion and predisposition to liver fibrosis. Under HFD conditions, we observed progressive intrahepatic fat accumulation, developing into macro–vesicular steatosis. Serum lipoprotein levels in HFD–fed Lgr4/5dLKO mice were decreased, rather than increased, suggesting that accumulation of fat in the liver was due to impaired lipid secretion by hepatocytes. Our lipidome analysis revealed a severe alteration of several lipid species in livers of Lgr4/5dLKO mice, including triacylglycerol estolides (TG–EST), a storage form of bioactive free fatty acid (FA) esters of hydroxy FAs (FAHFAs). Conclusions: Loss of hepatic Wnt/β–catenin activity by Lgr4/5 deletion led to deregulation of lipoprotein pathways, loss of BA secretion, intrinsic alterations of lipid homeostasis and the onset of NAFLD. Competing Interest Statement All authors except M.L.M.G, A.G.M, C.G. and L.T. are or have been employed by and/or shareholders of Novartis Pharma AG.