Case report: optic atrophy and nephropathy with m.13513G>A/MT-ND5 mtDNA pathogenic variant

Isolated complex I deficiency represents the most common mitochondrial respiratory chain defect involved in mitochondrial disorders. Among these, the mitochondrial DNA (mtDNA) m.13513G>A pathogenic variant in the NADH dehydrogenase 5 subunit gene (MT-ND5) has been associated with heterogenous manifestations, including phenotypic overlaps of mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes, Leigh syndrome, and Leber’s hereditary optic neuropathy (LHON). Interestingly, this specific mutation has been recently described in patients with adult-onset nephropathy. We, here, report the unique combination of LHON, nephropathy, sensorineural deafness, and subcortical and cerebellar atrophy in association with the m.13513G>A variant

An upgraded CFA - FLC - MS/MS system for the semi-continuous detection of levoglucosan in ice cores

A new Continuous Flow Analysis (CFA) system coupled with Fast Liquid Chromatography – tandem Mass Spectrometry (FLC-MS/MS) has been recently developed for determining organic markers in ice cores. In this work we present an upgrade of this innovative technique, optimized for the detection of levoglucosan in ice cores, a crucial tracer for reconstructing past fires. The upgrade involved a specific optimization of the chromatographic and mass spectrometric parameters, allowing for a higher sampling resolution (down to 1 cm) and the simultaneous collection of discrete samples, for off-line analysis of water stable isotopes and additional chemical markers. The robustness and repeatability of the method has been tested by the analysis of multiple sticks of ice cut from the same shallow alpine ice core, and running the system for several hours on different days. The results show similar and comparable trends between the ice sticks. With this upgraded system, a higher sensitivity and a lower limit of detection (LOD) was achieved compared to discrete analysis of alpine samples for levoglucosan measurements. The new LOD was as low as 66 ng L−1, a net improvement over the previous LOD of 600 ng L−1

Calibration and assessment of electrochemical low-cost sensors in remote alpine harsh environments

This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) 0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.publishedVersio

Spatial variability shapes microbial communities of permafrost soils and their reaction to warming

Climate change threatens the Earth’s biggest terrestrial organic carbon reservoir: permafrost soils. With climate warming, frozen soil organic matter may thaw and become available for microbial decomposition and subsequent greenhouse gas emissions. Permafrost soils are extremely heterogenous within the soil profile and between landforms. This heterogeneity in environmental conditions, carbon content and soil organic matter composition, potentially leads to different microbial communities with different responses to warming. The aim of the present study is to (1) elucidate these differences in microbial community compositions and (2) investigate how these communities react to warming. We performed short-term warming experiments with permafrost soil organic matter from northwestern Canada. We compared two sites characterized by different glacial histories (Laurentide Ice Sheet cover during LGM and without glaciation), three landscape types (low-center, flat-center, high-center polygons) and four different soil horizons (organic topsoil layer, mineral topsoil layer, cryoturbated soil layer, and the upper permanently frozen soil layer). We incubated aliquots of all soil samples at 4 °C and at 14 °C for 8 weeks and analyzed microbial community compositions (amplicon sequencing of 16S rRNA gene and ITS1 region) before and after the incubation, comparing them to microbial growth, microbial respiration, microbial biomass and soil organic matter composition. We found distinct bacterial, archaeal and fungal communities for soils of different glaciation history, polygon types and for different soil layers. Communities of low-center polygons differ from high-center and flat-center polygons in bacterial, archaeal and fungal community compositions, while communities of organic soil layers are significantly different from all other horizons. Interestingly, permanently frozen soil layers differ from all other horizons in bacterial and archaeal, but not fungal community composition. The 8-week incubations led to minor shifts in bacterial and archaeal community composition between initial soils and those subjected to 14 °C warming. We also found a strong warming effect on the community compositions in some of the extreme habitats: microbial community compositions of (i) the upper permanently frozen layer and of (ii) low-center polygons differ significantly for incubations at 4 °C and 14 °C. Yet, the lack of a community change in horizons of the active layer suggests that microbes are adapted to fluctuating temperatures due to seasonal thaw events. Our results suggest that warming responses of permafrost soil organic matter, if not frozen or water-saturated, may be predictable by current models. Process changes induced by short-term warming can be rather attributed to changes in microbial physiology than community composition. This work is part of the EU H2020 project “Nunataryuk”

Raster land cover product derived from TerraSAR-X imagery for the Komakuk Beach study site on the Beaufort Coast, Canada

The dataset contains a high-resolution (5m) land cover classification product for the Komakuk Beach study site located on the Beaufort Coast, Canada. Land cover types were classified using a Random Forest classifier with predictors derived from the Kennaugh elements K0 and K1 of seven dual-polarimetric HH/HV TerraSAR-X images acquired between July and December 2019. Land cover in-situ data were collected in August 2019 and upscaled to image objects (314 to 4766 m2) using segmentation of a WorldView-3 image and ArcticDEM elevation data. The SAR pixel values within these objects were used as reference data for the land cover classification. This dataset was produced to examine the potential of the Kennaugh Element Framework applied on dual-pol SAR data for Arctic tundra land cover classification

Arctic Tundra Land Cover Classification on the Beaufort Coast using the Kennaugh Element Framework on Dual-Polarimetric TerraSAR-X Imagery

Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets which document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the seasonal backscatter mechanisms in Arctic tundra environments and their potential for land cover classification purposes using a time series of HH/HV TerraSAR-X imagery. A Random Forest classification was applied on multi-temporal backscatter intensity and Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models show that the land cover classes can be distinguished with 92.4% accuracy using the Kennaugh element data, compared to 57.7% accuracy for backscatter intensity data. The accuracy was improved by adding texture measures to the predictor datasets, but the spatial resolution was reduced. TerraSAR-X acquisitions from the summer as well as from the autumn and winter seasons were important for the classification. The results of this study demonstrate that the Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping

Does the etiology of cardiac amyloidosis determine the myocardial uptake of [18F]-NaF PET/CT?

Cardiac amyloidosis (CA) leads to variable degrees of myocardial infiltration with a final echocardiographic phenotype of \u201chypertrophy.\u201d Although many non-invasive imaging techniques (MRI, CT, scintigraphy, PET) are useful, the definitive diagnosis is still based on myocardial histology. We explored the possible role of [18F]-NaF PET/CT in the diagnosis of this disease in two cases with wild-type (ATTRwt) or mutant (ATTRm) Ile68Leu transthyretin (TTR)-related CA

High resolution mapping shows differences in soil carbon and nitrogen stocks in areas of varying landscape history in Canadian lowland tundra

Soil organic carbon (SOC) in Arctic coastal polygonal tundra is vulnerable to climate change, especially in soils with occurrence of large amounts of ground ice. Pan-arctic studies of mapping SOC exist, yet they fail to describe the high spatial variability of SOC storage in permafrost landscapes. An important factor is the landscape history which determines landform development and consequently the spatial variability of SOC. Our aim was to map SOC stocks, and which environmental variables that determine SOC, in two adjacent coastal areas along Canadian Beaufort Sea coast with different glacial history. We used the machine learning technique random forest and environmental variables to map the spatial distribution of SOC stocks down to 1 m depth at a spatial resolution of 2 m for depth increments of 0–5, 5–15, 15–30, 30–60 and 60–100 cm.The results show that the two study areas had large differences in SOC stocks in the depth 60–100 cm due to high amounts of ground ice in one of the study areas. There are also differences in variable importance of the explanatory variables between the two areas. The area low in ground ice content had with 66.6 kg C/m−2 more stored SOC than the area rich in ground ice content with 40.0 kg C/m−2. However, this SOC stock could be potentially more vulnerable to climate change if ground ice melts and the ground subsides. The average N stock of the area low in ground ice is 3.77 kg m−2 and of the area rich in ground ice is 3.83 kg m−2.These findings support that there is a strong correlation between ground ice and SOC, with less SOC in ice-rich layers on a small scale. In addition to small scale studies of SOC mapping, detailed maps of ground ice content and distribution are needed for a validation of large-scale quantifications of SOC stocks and transferability of models