Satellite-based Earth observation plays a key role for monitoring volcanoes, especially those which are located in remote areas and which very often are not observed by a terrestrial monitoring ...network. In our study we jointly analyzed data from thermal (Moderate Resolution Imaging Spectrometer MODIS and Visible Infrared Imaging Radiometer Suite VIIRS), optical (Operational Land Imager and Multispectral Instrument) and synthetic aperture radar (SAR) (Sentinel-1 and TerraSAR-X) satellite sensors to investigate the mid-October 2019 surtseyan eruption at Late'iki Volcano, located on the Tonga Volcanic Arc. During the eruption, the remains of an older volcanic island formed in 1995 collapsed and a new volcanic island, called New Late'iki was formed. After the 12 days long lasting eruption, we observed a rapid change of the island's shape and size, and an erosion of this newly formed volcanic island, which was reclaimed by the ocean two months after the eruption ceased. This fast erosion of New Late'iki Island is in strong contrast to the over 25 years long survival of the volcanic island formed in 1995.
Wildfires pose a direct threat when occurring close to populated areas. Additionally, their significant carbon and climate feedbacks represent an indirect threat on a global, long-term scale. ...Monitoring and analyzing wildfires is therefore a crucial task to increase the understanding of interconnections between fire and ecosystems, in order to improve wildfire management activities. This study investigates the suitability of 232 different red/near-infrared band combinations based on hyperspectral imagery of the DESIS sensor with regard to burnt area detection accuracy. It is shown that the selection of wavelengths greatly influences the detection quality, and that especially the utilization of lower near-infrared wavelengths increases the yielded accuracy. For burnt area analysis based on the Normalized Difference Vegetation Index (NDVI), the optimal wavelength range has been found to be 660–670 nm and 810–835 nm for the red band and near-infrared band, respectively.
In the case of ongoing wildfire events, timely information on current fire parameters is crucial for informed decision making. Satellite imagery can provide valuable information in this regard, since ...thermal sensors can detect the exact location and intensity of an active fire at the moment the satellite passes over. This information can be derived and distributed in near-real time, allowing for a picture of current fire activity. However, the derivation of the size and shape of an already affected area is more complex and therefore most often not available within a short time frame. For urgent decision making though, it would be desirable to have this information available in near-real time, and on a large scale. The approach presented here works fully automatic and provides perimeters of burnt areas within two hours after the satellite scene acquisition. It uses the red and near-infrared bands of mid-resolution imagery to facilitate continental-scale monitoring of recently occurred burnt areas. To allow for a high detection capacity independent of the affected vegetation type, segmentation thresholds are derived dynamically from contextual information. This is done by using a Morphological Active Contour approach for perimeter determination. The results are validated against semi-automatically derived burnt areas for five wildfire incidents in Europe. Furthermore, these results are compared with three widely used burnt area datasets on a country-wide scale. It is shown that a high detection quality can be reached in near real-time. The large-scale inter-comparison shows that the results coincide with 63% to 76% of the burnt area in the reference datasets. While these established datasets are only available with a time lag of several months or are created by using manual interaction, the presented approach produces results in near-real time fully automatically. This work is therefore supposed to represent a valuable improvement in wildfire related rapid damage assessment.
Abstract
Several observational studies have investigated the association between cannabis use and intraocular pressure, but its association with primary open-angle glaucoma (POAG) remains unclear. In ...this study, we leveraged human genetic data to assess through Mendelian randomization (MR) whether cannabis use affects POAG. We used five single-nucleotide polymorphisms (SNPs) associated with lifetime cannabis use (
P
-value < 5 × 10
–8
) from a genome-wide association study (GWAS) (N = 184,765) by the International Cannabis Consortium, 23andMe, and UK Biobank and eleven SNPs associated with cannabis use disorder (
P
-value < 5 × 10
–7
) from a GWAS meta-analysis of (17,068 cases and 357,219 controls of European descent) from Psychiatric Genomics Consortium Substance Use Disorders working group, Lundbeck Foundation Initiative for Integrative Psychiatric Research, and deCode. We associated the selected five SNPs from the GWAS of lifetime cannabis use and the eleven SNPs from the GWAS of cannabis use disorder, with the largest to date GWAS meta-analysis of POAG (16,677 cases and 199,580 controls). MR analysis suggested no evidence for a causal association of lifetime cannabis use and cannabis use disorder with POAG (odds ratio (OR) of outcome per doubling of the odds of exposure (95% confidence interval): 1.04 (0.88; 1.23) for lifetime cannabis use and 0.97 (0.92; 1.03) for cannabis use disorder). Sensitivity analyses to address pleiotropy and weak instrument bias yielded similar estimates to the primary analysis. In conclusion, our results do not support a causal association between cannabis use and POAG.
Background
Observational and
in-vivo
research suggested a bidirectional relationship between depression and periodontitis. We estimated the genetic correlation and examined directionality of ...causation.
Methods
The study used summary statistics from published genome wide association studies, with sample sizes ranging from 45,563 to 797,563 individuals of European ancestry. We performed linkage disequilibrium score regression (LDSC) to estimate global correlation and used Heritability Estimation from Summary Statistics (ρ-HESS) to further examine local genetic correlation. Latent Heritable Confounder Mendelian randomization (LHC-MR), Causal Analysis using Summary Effect estimates (CAUSE), and conventional MR approaches assessed bidirectional causation.
Results
LDSC observed only weak genetic correlation (r
g
= 0.06, P-Value = 0.619) between depression and periodontitis. Analysis of local genetic correlation using ρ-HESS did not reveal loci of significant local genetic covariance. LHC-MR, CAUSE and conventional MR models provided no support for bidirectional causation between depression and periodontitis, with odds ratios ranging from 1.00 to 1.06 in either direction.
Conclusions
Results do not support shared heritability or a causal connection between depression and periodontitis.
Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property. Through greenhouse gas emissions, wildfires also ...directly contribute to climate change. The monitoring of such events and the analysis of acquired data is crucial for understanding wildfire and ecosystem interactions. The FireBIRD small satellite mission, operated by the German Aerospace Center (DLR), was specifically designed for the detection of wildfires. It features a higher spatial resolution than available with other Earth-observation systems. In addition to the detection of active fire locations, the system also allows the derivation of fire intensity by means of the Fire Radiative Power (FRP). This indicator can be used as a basis to derive the amount of emitted pollutant, which makes it valuable for climate studies. With the FireBIRD mission facing its end of life in 2021, this study retrospectively evaluates the performance of the system through an inter-comparison with data from two satellite missions of the National Aeronautics and Space Administration (NASA) and discusses the potential of such a system. The comparison is performed regarding both geometrical and radiometric aspects, the latter focusing on the FRP. This study uses and compares two different methods to derive the FRP from FireBIRD data. The data are analyzed regarding six major fire incidents in different regions of the world. The FireBIRD results are in accordance with the reference data, showing a geometrical overlapping rate of 83% and 84% regarding MODIS (Moderate-resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) overpasses in close temporal proximity. Furthermore, the results show a positive bias in FRP of about 11% compared to MODIS.
Increased fire activity across the Amazon, Australia, and even the Arctic regions has received wide recognition in the global media in recent years. Large-scale, long-term analyses are required to ...postulate if these incidents are merely peaks within the natural oscillation, or rather the consequence of a linearly rising trend. While extensive datasets are available to facilitate the investigation of the extent and frequency of wildfires, no means has been available to also study the severity of the burnings on a comparable scale. This is now possible through a dataset recently published by the German Aerospace Center (DLR). This study exploits the possibilities of this new dataset by exemplarily analyzing fire severity trends on the Australian East coast for the past 20 years. The analyzed data is based on 3503 tiles of the ESA Sentinel-3 OLCI instrument, extended by 9612 granules of the NASA MODIS MOD09/MYD09 product. Rising trends in fire severity could be found for the states of New South Wales and Victoria, which could be attributed mainly to developments in the temperate climate zone featuring hot summers without a dry season (Cfa). Within this climate zone, the ecological units featuring needleleaf and evergreen forest are found to be mainly responsible for the increasing trend development. The results show a general, statistically significant shift of fire activity towards the affection of more woody, ecologically valuable vegetation.
Wildfire spread models are an essential tool for mitigating catastrophic effects associated with wildfires. However, current operational models suffer from significant limitations regarding accuracy ...and transferability. Recent advances in the availability and capability of Earth observation data and artificial intelligence offer new perspectives for data-driven modeling approaches with the potential to overcome the existing limitations. Therefore, this study developed a data-driven Deep Learning wildfire spread modeling approach based on a comprehensive dataset of European wildfires and a Spatiotemporal Graph Neural Network, which was applied to this modeling problem for the first time. A country-scale model was developed on an individual wildfire time series in Portugal while a second continental-scale model was developed with wildfires from the entire Mediterranean region. While neither model was able to predict the daily spread of European wildfires with sufficient accuracy (weighted macro-mean IoU: Portugal model 0.37; Mediterranean model 0.36), the continental model was able to learn the generalized patterns of wildfire spread, achieving similar performances in various fire-prone Mediterranean countries, indicating an increased capacity in terms of transferability. Furthermore, we found that the spatial and temporal dimensions of wildfires significantly influence model performance. Inadequate reference data quality most likely contributed to the low overall performances, highlighting the current limitations of data-driven wildfire spread models.
To investigate the effect of genetically proxied inhibition of tumor necrosis factor receptor 1 (TNFR1) on the risk of periodontitis.
Genetic instruments were selected from the vicinity of TNFR ...superfamily member 1A (TNFRSF1A) gene (chromosome 12; base pairs 6,437,923-6,451,280 as per GRCh37 assembly) based on their association with C-reactive protein (N= 575,531). Summary statistics of these variants were obtained from a genome-wide association study (GWAS) of 17,353 periodontitis cases and 28,210 controls to estimate the effect of TNFR1 inhibition on periodontitis using a fixed-effects inverse method.
Considering rs1800693 as an instrument, we found no effect of TNFR1 inhibition on periodontitis risk (Odds ratio (OR) scaled per standard deviation increment in CRP: 1.57, 95% confidence interval (CI): 0.38;6.46). Similar results were derived from a secondary analysis that used three variants (rs767455, rs4149570, and rs4149577) to index TNFR1 inhibition.
We found no evidence of a potential efficacy of TNFR1 inhibition on periodontitis risk.
Interleukin 6 (IL-6) is considered to play a role in the dysbiotic host response in the development of periodontitis. While the inhibition of the IL-6 receptor using monoclonal antibodies is a ...well-established therapy for some diseases, so far, its potential benefit in patients with periodontitis has not been examined. We tested the association of genetically proxied downregulation of IL-6 signaling with periodontitis to explore whether downregulation of IL-6 signaling could represent a viable treatment target for periodontitis.
As proxies for IL-6 signaling downregulation, we selected 52 genetic variants in close vicinity of the gene encoding IL-6 receptor that were associated with lower circulating C-reactive protein (CRP) levels in a genome-wide association study (GWAS) of 575 531 participants of European ancestry from the UK Biobank and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Associations with periodontitis were tested with inverse-variance weighted Mendelian randomization in a study of 17 353 cases and 28 210 controls of European descent in the Gene-Lifestyle Interactions in Dental Endpoints (GLIDE) consortium. In addition, the effect of CRP reduction independent of the IL-6 pathway was assessed.
Genetically proxied downregulation of IL-6 signaling was associated with lower odds of periodontitis (odds ratio (OR) = 0.81 per 1-unit decrement in log-CRP levels; 95% confidence interval (CI): 0.66;0.99; P = 0.0497). Genetically proxied reduction of CRP independent of the IL-6 pathway had a similar effect (OR = 0.81; 95% CI: 0.68; 0.98; P = 0.0296).
In conclusion, genetically proxied downregulation of IL-6 signaling was associated with lower odds of periodontitis and CRP might be a causal target for the effect of IL-6 on the risk of periodontitis.
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