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Cryopyrin-associated periodic syndromes (CAPS) are orphan hereditary auto-inflammatory diseases with various phenotypes, including chronic kidney disease (CKD). Current therapies inhibit interleukin-1 (IL-1) to achieve clinical and serological remission; however, the effect on kidney involvement remains unclear. The objective of this study was to investigate the long-term efficacy of anti-IL-1 treatment with special emphasis on renal outcome. We retrospectively analysed clinical, genetic and laboratory data of patients with CAPS under anti-IL-1 therapy from a single-centre university outpatient clinic. Patients with CAPS (n = 28) were followed for a median of 11 (IQR 8.5–13) years. Four patients at various ages (19%), bearing the most common CAPS mutation R260W, had significant CKD at presentation. All affected patients were related; however, other family members with the same genetic variant did not develop CKD. While anti-IL-1 therapy was effective in lowering symptom burden and inflammatory parameters in all CAPS patients, two of the four individuals with significant CKD had persistent proteinuria and worsening kidney function. None of the patients without renal affection at therapy initiation developed relevant CKD in the follow-up period. We showed that in patients with CAPS: (1) CKD is a common complication; (2) renal involvement shows familial predisposition beyond the mutational status and is independent of age; (3) anti-IL-1 therapy results in sustained improvement of inflammatory parameters and symptom load and (4) may prevent development of CAPS-associated CKD but not affect kidney involvement when already present. Overall, early therapy initiation might sufficiently prevent renal disease manifestation and attenuate progression. [ABSTRACT FROM AUTHOR]

Here, we present observations of temporal variability of sub-ice platelet layer over seasonal and diurnal timescales under Ice Shelf Water-influenced fast ice in McMurdo Sound. Electromagnetic induction (EM) sounding time-series measurements of the thicknesses of fast ice and sub-ice platelet layer were made in winter and late spring of 2018. Winter objectives were to measure the seasonal growth of fast ice and sub-ice platelet layer near the McMurdo Ice Shelf in the east, while in late spring we assessed the diurnal variability of sub-ice platelet layer with coincident EM time-series and oceanographic measurements collected in the main outflow path of supercooled Ice Shelf Water in the west. During winter, we observed when the sub-ice platelet layer formed beneath consolidated ice. Episodes of rapid sub-ice platelet layer growth (∼ 0.5–1 m) coincided with strong southerly wind events and polynya activity, suggesting wind-enhanced Ice Shelf Water circulation from the McMurdo–Ross Ice Shelf cavity. In late spring, we investigated how the tides and ocean properties influenced the sub-ice platelet layer. Over a 2-week neap–spring tidal cycle, changes in sub-ice platelet layer thickness were observed to correlate with the tides, increasing more during neap than spring tide cycles, and on diurnal timescales, more on ebb than flood tides. Neap and ebb tides correspond with stronger northward circulation out of the cavity, indicating that sub-ice platelet layer growth was driven by tidally enhanced Ice Shelf Water outflow. The observed variability indicated that wind-driven circulation and the tides influence Ice Shelf Water outflow in McMurdo Sound and, consequently, sub-ice platelet layer evolution over a range of timescales. [ABSTRACT FROM AUTHOR]

Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the 1-year drift campaign Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in describing the surface meltwater volume; it is necessary to estimate budgets and used in model parameterization to simulate pond coverage evolution. However, observational data on pond depth are spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air–pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements and the importance of such high-resolution data for new satellite retrievals, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea ice surface emerging from the increasingly available visual image data recorded from uncrewed aerial vehicles (UAVs) or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models. [ABSTRACT FROM AUTHOR]

If and how the sea ice cycle drives the methane cycle in the high Arctic is an open question and crucial to improving source/sink balances. This study presents new insights into the effects of strong and fast freezing on the physical-chemical properties of ice and offers implications for methane fluxes into and out of newly formed lead ice. During the 2019-2020 transpolar drift of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC), we took weekly samples of growing lead ice and underlying seawater at the same site between January and March 2020. We analyzed concentrations and stable carbon isotopic signatures (513C-CH4) of methane and calculated methane solubility capacities (MSC) and saturation levels in both environments. During the first month, intense cooling resulted in the growth of two-thirds of the final ice thickness. In the second month, ice growth speed decreased by 50%. Both growth phases, disentangled, exposed different freeze impacts on methane pathways. The fast freeze caused strong brine entrapment, keeping the newly formed lead ice permeable for 2 weeks. These physical conditions activated a methane pump. An increased MSC induced methane uptake at the air-ice interface, and the still-open brine channels provided top-down transport to the ocean interface with brine drainage. When the subsurface layer became impermeable, the top-down pumping stopped, but the ongoing uptake induced a methane excess on top. During the second growth phase, methane exchange exclusively continued at the ice-ocean interface. The shift in the relative abundance of the 12C and 13C isotopes between lead ice and seawater toward a 13C-enrichment in seawater reveals brine drainage as the main pathway releasing methane from aging lead ice. We conclude that in winter, refrozen leads temporarily function as active sinks for atmospheric methane and postulate that the relevance of this process may even increase when the Arctic fully transitions into a seasonally ice-covered ocean when leads may be more abundant. To highlight the relevance of methane in-gassing at the air-ice interface as a potential but still unconsidered pathway, we include estimates of the occurrence and frequency of young lead ice from satellite observations of leads during MOSAiC. [ABSTRACT FROM AUTHOR]

Automated sea ice charting from synthetic aperture radar (SAR) has been researched for more than a decade, and we are still not close to unlocking the full potential of automated solutions in terms of resolution and accuracy. The central complications arise from ground truth data not being readily available in the polar regions. In this paper, we build a data set from 20 near-coincident x-band SAR acquisitions and as many airborne laser scanner (ALS) measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), between October and May. This data set is then used to assess the accuracy and robustness of five machine-learning-based approaches by deriving classes from the freeboard, surface roughness (standard deviation at 0.5 m correlation length) and reflectance. It is shown that there is only a weak correlation between the radar backscatter and the sea ice topography. Accuracies between 44 % and 66 % and robustness between 71 % and 83 % give a realistic insight into the performance of modern convolutional neural network architectures across a range of ice conditions over 8 months. It also marks the first time algorithms have been trained entirely with labels from coincident measurements, allowing for a probabilistic class retrieval. The results show that segmentation models able to learn from the class distribution perform significantly better than pixel-wise classification approaches by nearly 20 % accuracy on average. [ABSTRACT FROM AUTHOR]

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. We estimated lead fractions from high-resolution divergence obtained from satellite synthetic aperture radar (SAR) data and evaluated them against existing lead products. We derived two new lead fraction products from divergence with a spatial resolution of 700 m calculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time instances. With those accumulated divergence-derived lead fractions, we comprehensively described the presence of up to 10 d old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of up to a few hundred meters. We presented a Lagrangian time series of the divergence-based lead fractions along the drift of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic Ocean during winter 2019–2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50–150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with six others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 order of magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application. [ABSTRACT FROM AUTHOR]

Copyright of Transfer: Zeitschrift für Kommunikation & Markenmanagement is the property of Deutsche Werbewissenschaftliche Gesellschaft and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the globally increasing awareness regarding the interconnectivity between freshwater ecosystems, projects for re-establishing connectivity with fishways as well as stock management are increasing. To ensure the quality and impact of such projects and for extending the scientific state of knowledge on this topic, a detailed monitoring of these measures is mandatory. Automatic, passive, and contactless counting devices can play a major role in these long-term monitoring projects, both for animal protection (non-invasive methods) and technical issues (comparatively low-cost systems in terms of time). Infrared fish counters can be used in a variety of fisheries applications and have proven particularly valuable in situations when long-term or continuous monitoring in lotic systems is required. Herein, we describe the function and technical capabilities of the VAKI Riverwatcher fish counter, provide information regarding its installation, and highlight some specific, practical applications of this technology. We discuss how the Riverwatcher can be used to validate the functionality of fish passage structures and to provide abundance estimates of migratory fish populations. Finally, we call attention to the challenges associated with operating monitoring equipment in variable river systems and briefly discuss potential sources of error that can influence the monitoring results and approaches to minimize or alleviate these errors. [ABSTRACT FROM AUTHOR]

Melt ponds are a core component of the summer sea ice system in the Arctic, increasing the uptake of solar energy and impacting the ice-associated ecosystem. They were thus one of the key topics during the one-year drift campaign MOSAiC in the Transpolar Drift 2019/2020. Pond depth is a dominating factor in the description of the surface meltwater volume, necessary to estimate budgets, and used in model parametrization to simulate pond coverage evolution. However, observational data on pond depth is spatially and temporally strongly limited to a few in situ measurements. Pond bathymetry, which is pond depth spatially fully resolved, remains entirely unexplored. Here, we present a newly developed method to derive pond bathymetry from aerial images. We determine it from a photogrammetric multi-view reconstruction of the summer ice surface topography. Based on images recorded on dedicated grid flights and facilitated assumptions, we were able to obtain pond depth with a mean deviation of 3.5 cm compared to manual in situ observations. The method is independent of pond color and sky conditions, which is an advantage over recently developed radiometric airborne retrieval methods. It can furthermore be implemented in any typical photogrammetry workflow. We present the retrieval algorithm, including requirements for the data recording and survey planning, and a correction method for refraction at the air—pond interface. In addition, we show how the retrieved surface topography model synergizes with the initial image data to retrieve the water level of individual ponds from the visually determined pond margins. We use the method to give a profound overview of the pond coverage on the MOSAiC floe, on which we found unexpected steady pond coverage and volume. We were able to derive individual pond properties of more than 1600 ponds on the floe, including their size, bathymetry, volume, surface elevation above sea level, and temporal evolution. We present a scaling factor for single in situ depth measurements, discuss the representativeness of in situ pond measurements, and show indications for non-rigid pond bottoms. The study points out the great potential to derive geometric properties of the summer sea-ice surface emerging from the increasingly available visual image data recorded from UAVs or aircraft, allowing for an integrated understanding and improved formulation of the thermodynamic and hydrological pond system in models. [ABSTRACT FROM AUTHOR]

Here, we present observations of temporal variability of sub-ice platelet layer over seasonal and diurnal timescales under Ice Shelf Water-influenced fast ice in McMurdo Sound. Electromagnetic induction (EM) sounding time-series measurements of the thicknesses of fast ice and sub-ice platelet layer were made in winter and late spring of 2018. Winter objectives were to measure the seasonal growth of fast ice and sub-ice platelet layer near the McMurdo Ice Shelf in the east, while in late spring we assessed the diurnal variability of sub-ice platelet layer with coincident EM time-series and oceanographic measurements collected in the main outflow path of supercooled Ice Shelf Water in the west. During winter, we observed when the sub-ice platelet layer formed beneath consolidated ice. Episodes of rapid sub-ice platelet layer growth (~0.5–1 m) coincided with strong southerly-wind-events and polynya activity, suggesting wind-enhanced Ice Shelf Water circulation from the McMurdo-Ross Ice Shelf cavity. In late spring, we investigated how the tides and ocean properties influenced the sub-ice platelet layer. Over a two-week neap-spring tidal cycle, changes in sub-ice platelet layer thickness were observed to correlate with the tides, increasing more during neap than spring tide cycles, and on diurnal timescales, more on ebb than flood tides. Neap and ebb tides correspond with stronger northward circulation out of the cavity, indicating that sub-ice platelet layer growth was driven by tidally-enhanced Ice Shelf Water outflow. The observed variability indicated that wind-driven circulation and the tides influence Ice Shelf Water outflow in McMurdo Sound, and consequently, sub-ice platelet layer evolution over a range of timescales. [ABSTRACT FROM AUTHOR]

Here, we present observations of temporal variability of sub-ice platelet layer over seasonal and diurnal timescales under Ice Shelf Water-influenced fast ice in McMurdo Sound. Electromagnetic induction (EM) sounding time-series measurements of the thicknesses of fast ice and sub-ice platelet layer were made in winter and late spring of 2018. Winter objectives were to measure the seasonal growth of fast ice and sub-ice platelet layer near the McMurdo Ice Shelf in the east, while in late spring we assessed the diurnal variability of sub-ice platelet layer with coincident EM time-series and oceanographic measurements collected in the main outflow path of supercooled Ice Shelf Water in the west. During winter, we observed when the sub-ice platelet layer formed beneath consolidated ice. Episodes of rapid sub-ice platelet layer growth (～0.5-1 m) coincided with strong southerly-wind-events and polynya activity, suggesting wind-enhanced Ice Shelf Water circulation from the McMurdo-Ross Ice Shelf cavity. In late spring, we investigated how the tides and ocean properties influenced the sub-ice platelet layer. Over a two-week neap-spring tidal cycle, changes in sub-ice platelet layer thickness were observed to correlate with the tides, increasing more during neap than spring tide cycles, and on diurnal timescales, more on ebb than flood tides. Neap and ebb tides correspond with stronger northward circulation out of the cavity, indicating that sub-ice platelet layer growth was driven by tidally-enhanced Ice Shelf Water outflow. The observed variability indicated that wind-driven circulation and the tides influence Ice Shelf Water outflow in McMurdo Sound, and consequently, sub-ice platelet layer evolution over a range of timescales. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leads and fractures in sea ice play a crucial role in the heat and gas exchange between the ocean and atmosphere, impacting atmospheric, ecological, and oceanic processes. Our aim was to estimate lead fractions from high-resolution divergence obtained from satellite synthetic-aperture radar (SAR) data and to evaluate it against existing lead products. We derived two new leadfraction products from divergence with a spatial resolution of 700m calculated from daily Sentinel-1 images. For the first lead product, we advected and accumulated the lead fractions of individual time steps. With those accumulated divergence-derived lead fractions, we described comprehensively the presence of up to 10-day-old leads and analyzed their deformation history. For the second lead product, we used only divergence pixels that were identified as part of linear kinematic features (LKFs). Both new lead products accurately captured the formation of new leads with widths of a few hundred meters. We presented a Lagrangian time series of the divergence-based lead fractions along the drift of the MOSAiC expedition in the central Arctic Ocean during winter 2019/2020. Lead activity was high in fall and spring, consistent with wind forcing and ice pack consolidation. At larger scales of 50-150 km around the MOSAiC expedition, lead activity on all scales was similar, but differences emerged at smaller scales (10 km). We compared our lead products with 6 others from satellite and airborne sources, including classified SAR, thermal infrared, microwave radiometer, and altimeter data. We found that the mean lead fractions varied by 1 magnitude across different lead products due to different physical lead and sea ice properties observed by the sensors and methodological factors such as spatial resolution. Thus, the choice of lead product should align with the specific application. [ABSTRACT FROM AUTHOR]

Automated sea ice charting from Synthetic Aperture Radar (SAR) has been researched for more than a decade and still, we are not close to unlocking the full potential of automated solutions in terms of resolution and accuracy. The central complications arise from ground truth data not being readily available in the polar regions. In this paper, we build a dataset from 20 near coincident X-Band SAR acquisitions and as many Airborne Laser Scanner (ALS) measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), between October and May. This dataset is then used to assess the accuracy and robustness of five machine learning based approaches, by deriving classes from the freeboard, surface roughness (standard deviation at 0.5 m correlation length) and reflectance. It is shown that there is only a weak correllation of the radar backscatter and the sea ice topography. Accuracies between 40 % and 69 % percent and robustnesses between 68 % and 85 % give a realistic insight into modern classifiers' performance across a range of ice conditions over 8 months. It also marks the first time algorithms are trained entirely with labels from coincident measurements, allowing for a probabilistic class retrieval. The results show that segmentation models able to learn from the class distribution significantly perform pixel-wise classification approaches. [ABSTRACT FROM AUTHOR]

Copyright of Die Pathologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Die Pathologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)