Accounting for black carbon lowers estimates of blue carbon storage services

The canopies and roots of seagrass, mangrove, and saltmarsh protect a legacy of buried sedimentary organic carbon from resuspension and remineralisation. This legacy’s value, in terms of mitigating anthropogenic emissions of CO2, is based on total organic carbon (TOC) inventories to a depth likely to be disturbed. However, failure to subtract allochthonous recalcitrant carbon overvalues the storage service. Simply put, burial of oxidation-resistant organics formed outside of the ecosystem provides no additional protection from remineralisation. Here, we assess whether black carbon (BC), an allochthonous and recalcitrant form of organic carbon, is contributing to a significant overestimation of blue carbon stocks. To test this supposition, BC and TOC contents were measured in different types of seagrass and mangrove sediment cores across tropical and temperate regimes, with different histories of air pollution and fire together with a reanalysis of published data from a subtropical system. The results suggest current carbon stock estimates are positively biased, particularly for low-organic-content sandy seagrass environs, by 18 ± 3% (±95% confidence interval) and 43 ± 21% (±95% CI) for the temperate and tropical regions respectively. The higher BC fractions appear to originate from atmospheric deposition and substantially enrich the relatively low TOC fraction within these environs

Jean-Baptiste Bélanger, hydraulic engineer, researcher and academic

Jean-Baptiste BÉLANGER (1790-1874) worked as a hydraulic engineer at the beginning of his career. He developed the backwater equation to calculate gradually-varied open channel flow properties for steady flow conditions. Later, as an academic at the leading French engineering schools (Ecole Centrale des Arts et Manufactures, Ecole des Ponts et Chaussées, and Ecole Polytechnique), he developed a new university curriculum in mechanics and several textbooks including a seminal text in hydraulic engineering. His influence on his contemporaries was considerable, and his name is written on the border of one of the four facades of the Eiffel Tower. BÉLANGER's leading role demonstrated the dynamism of practicing engineers at the time, and his contributions paved the way to many significant works in hydraulics

Specific isoforms of the ubiquitin ligase gene <em>WWP2 </em>are targets of osteoarthritis genetic risk via a differentially methylated DNA sequence

Background Transitioning from a genetic association signal to an effector gene and a targetable molecular mechanism requires the application of functional fine-mapping tools such as reporter assays and genome editing. In this report, we undertook such studies on the osteoarthritis (OA) risk that is marked by single nucleotide polymorphism (SNP) rs34195470 (A &gt; G). The OA risk-conferring G allele of this SNP associates with increased DNA methylation (DNAm) at two CpG dinucleotides within WWP2. This gene encodes a ubiquitin ligase and is the host gene of microRNA-140 (miR-140). WWP2 and miR-140 are both regulators of TGFβ signaling. Methods Nucleic acids were extracted from adult OA (arthroplasty) and foetal cartilage. Samples were genotyped and DNAm quantified by pyrosequencing at the two CpGs plus 14 flanking CpGs. CpGs were tested for transcriptional regulatory effects using a chondrocyte cell line and reporter gene assay. DNAm was altered using epigenetic editing, with the impact on gene expression determined using RT-qPCR. In silico analysis complemented laboratory experiments. Results rs34195470 genotype associates with differential methylation at 14 of the 16 CpGs in OA cartilage, forming a methylation quantitative trait locus (mQTL). The mQTL is less pronounced in foetal cartilage (5/16 CpGs). The reporter assay revealed that the CpGs reside within a transcriptional regulator. Epigenetic editing to increase their DNAm resulted in altered expression of the full-length and N-terminal transcript isoforms of WWP2. No changes in expression were observed for the C-terminal isoform of WWP2 or for miR-140. Conclusions As far as we are aware, this is the first experimental demonstration of an OA association signal targeting specific transcript isoforms of a gene. The WWP2 isoforms encode proteins with varying substrate specificities for the components of the TGFβ signaling pathway. Future analysis should focus on the substrates regulated by the two WWP2 isoforms that are the targets of this genetic risk

Stereotactic cyst aspiration directly followed by Gamma Knife radiosurgery for large cystic brain metastases

Background: Gamma Knife radiosurgery (GKRS) has been proven to be a successful primary treatment for metastatic brain tumors (BM). BM can come in cystic lesions and are often too large for GKRS. An alternative approach to treat cystic BM is stereotactic cyst aspiration (SCA) for volume reduction, making it suitable for GKRS afterwards. Objective: Our objective is evaluation of volumetric reduction after SCA, tumor control, and complications after SCA directly followed by GKRS. Methods: We performed a retrospective analysis of all patients who underwent SCA directly followed by GKRS at the Gamma Knife Center of the Elisabeth-Tweesteden Hospital in Tilburg between 2002 and 2015. In total, 54 patients had undergone this combined approach. Two patients were excluded because of prior intracranial treatment. The other 52 patients were included for analysis. Results: SCA resulted in a mean volumetric reduction of 56.5% (range 5.50–87.00%). In 83.6% of the tumors (46 tumors), SCA led to sufficient volumetric reduction making GKRS possible. The overall local tumor control (OLTC) of the aspirated lesions post-GKRS was 60.9% (28 out of 46 tumors). Median progression-free survival (PFS) and overall survival (OS) for all patients were 3 (range 5 days–14 months) and 12 months (range 5 days–58 months), respectively. Leptomeningeal disease was reported in 5 (9.6%) cases. Conclusion: SCA directly followed by GKRS is an effective and time-efficient treatment for large cystic BM in selected patients in which surgery is contraindicated and those with deeply located lesions.</p

Fitness benefits of prolonged post-reproductive lifespan in women

Most animals reproduce until they die, but in humans, females can survive long after ceasing reproduction. In theory, a prolonged post-reproductive lifespan will evolve when females can gain greater fitness by increasing the success of their offspring than by continuing to breed themselves. Although reproductive success is known to decline in old age, it is unknown whether women gain fitness by prolonging lifespan post-reproduction. Using complete multi-generational demographic records, we show that women with a prolonged post-reproductive lifespan have more grandchildren, and hence greater fitness, in pre-modern populations of both Finns and Canadians. This fitness benefit arises because post-reproductive mothers enhance the lifetime reproductive success of their offspring by allowing them to breed earlier, more frequently and more successfully. Finally, the fitness benefits of prolonged lifespan diminish as the reproductive output of offspring declines. This suggests that in female humans, selection for deferred ageing should wane when one's own offspring become post-reproductive and, correspondingly, we show that rates of female mortality accelerate as their offspring terminate reproduction

Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering

In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering. In a cold-start setting, on three publicly available datasets, we evaluate approaches from four method families: (i) factorization-based, (ii) random walk-based, (iii) deep learning-based, and (iv) the Large-scale Information Network Embedding (LINE) approach. We find that across the four families, random-walk-based approaches consistently achieve the best accuracy. Besides, they result in highly novel and diverse recommendations. Furthermore, our results show that the use of graph embeddings in trust-based collaborative filtering significantly improves user coverage.Comment: 10 pages, Accepted as a full paper on the 25th International Symposium on Methodologies for Intelligent Systems (ISMIS'20

Estimating the intrinsic dimension of datasets by a minimal neighborhood information

Analyzing large volumes of high-dimensional data is an issue of fundamental importance in data science, molecular simulations and beyond. Several approaches work on the assumption that the important content of a dataset belongs to a manifold whose Intrinsic Dimension (ID) is much lower than the crude large number of coordinates. Such manifold is generally twisted and curved; in addition points on it will be non-uniformly distributed: two factors that make the identification of the ID and its exploitation really hard. Here we propose a new ID estimator using only the distance of the first and the second nearest neighbor of each point in the sample. This extreme minimality enables us to reduce the effects of curvature, of density variation, and the resulting computational cost. The ID estimator is theoretically exact in uniformly distributed datasets, and provides consistent measures in general. When used in combination with block analysis, it allows discriminating the relevant dimensions as a function of the block size. This allows estimating the ID even when the data lie on a manifold perturbed by a high-dimensional noise, a situation often encountered in real world data sets. We demonstrate the usefulness of the approach on molecular simulations and image analysis

Emissions of organic carbon and methane from petroleum and dairy operations in California's San Joaquin Valley

Petroleum and dairy operations are prominent sources of gas-phase organic compounds in California's San Joaquin Valley. It is essential to understand the emissions and air quality impacts of these relatively understudied sources, especially for oil/gas operations in light of increasing US production. Ground site measurements in Bakersfield and regional aircraft measurements of reactive gas-phase organic compounds and methane were part of the CalNex (California Research at the Nexus of Air Quality and Climate Change) project to determine the sources contributing to regional gas-phase organic carbon emissions. Using a combination of near-source and downwind data, we assess the composition and magnitude of emissions, and provide average source profiles. To examine the spatial distribution of emissions in the San Joaquin Valley, we developed a statistical modeling method using ground-based data and the FLEXPART-WRF transport and meteorological model. We present evidence for large sources of paraffinic hydrocarbons from petroleum operations and oxygenated compounds from dairy (and other cattle) operations. In addition to the small straight-chain alkanes typically associated with petroleum operations, we observed a wide range of branched and cyclic alkanes, most of which have limited previous in situ measurements or characterization in petroleum operation emissions. Observed dairy emissions were dominated by ethanol, methanol, acetic acid, and methane. Dairy operations were responsible for the vast majority of methane emissions in the San Joaquin Valley; observations of methane were well correlated with non-vehicular ethanol, and multiple assessments of the spatial distribution of emissions in the San Joaquin Valley highlight the dominance of dairy operations for methane emissions. The petroleum operations source profile was developed using the composition of non-methane hydrocarbons in unrefined natural gas associated with crude oil. The observed source profile is consistent with fugitive emissions of condensate during storage or processing of associated gas following extraction and methane separation. Aircraft observations of concentration hotspots near oil wells and dairies are consistent with the statistical source footprint determined via our FLEXPART-WRF-based modeling method and ground-based data. We quantitatively compared our observations at Bakersfield to the California Air Resources Board emission inventory and find consistency for relative emission rates of reactive organic gases between the aforementioned sources and motor vehicles in the region. We estimate that petroleum and dairy operations each comprised 22% of anthropogenic non-methane organic carbon at Bakersfield and were each responsible for 8-13% of potential precursors to ozone. Yet, their direct impacts as potential secondary organic aerosol (SOA) precursors were estimated to be minor for the source profiles observed in the San Joaquin Valley