A tribute to Michael R. Raupach for contributions to aeolian fluid dynamics

Since the pioneering work of Bagnold in the 1940s, aeolian research has grown to become an integral part of earth-system science. Many individuals have contributed to this development, and Dr. Michael R. Raupach (1950–2015) has played a pivotal role. Raupach worked intensively on wind erosion problems for about a decade (1985–1995), during which time he applied his deep knowledge of turbulence to aeolian research problems and made profound contributions with far-reaching impact. The beauty of Raupach’s work lies in his clear conceptual thinking and his ability to reduce complex problems to their bare essentials. The results of his work are fundamentally important and have many practical applications. In this review we reflect on Raupach’s contribution to a number of important aspects of aeolian research, summarise developments since his inspirational work and place Raupach’s efforts in the context of aeolian science. We also demonstrate how Raupach’s work provided a foundation for new developments in aeolian research. In this tribute, we concentrate on five areas of research: (1) drag partition theory; (2) saltation roughness length; (3) saltation bombardment; (4) threshold friction velocity and (5) the carbon cycl

A Mouse Model of Heritable Cerebrovascular Disease

The study of animal models of heritable cerebrovascular diseases can improve our understanding of disease mechanisms, identify candidate genes for related human disorders, and provide experimental models for preclinical trials. Here we describe a spontaneous mouse mutation that results in reproducible, adult-onset, progressive, focal ischemia in the brain. The pathology is not the result of hemorrhage, embolism, or an anatomical abnormality in the cerebral vasculature. The mutation maps as a single site recessive locus to mouse Chromosome 9 at 105 Mb, a region of shared synteny with human chromosome 3q22. The genetic interval, defined by recombination mapping, contains seven protein-coding genes and one processed transcript, none of which are changed in their expression level, splicing, or sequence in affected mice. Targeted resequencing of the entire interval did not reveal any provocative changes; thus, the causative molecular lesion has not been identified

Air pollution and mortality in the Canary Islands: a time-series analysis

<p>Abstract</p> <p>Background</p> <p>The island factor of the cities of Las Palmas de Gran Canaria and Santa Cruz de Tenerife, along with their proximity to Africa and their meteorology, create a particular setting that influences the air quality of these cities and provides researchers an opportunity to analyze the acute effects of air-pollutants on daily mortality.</p> <p>Methods</p> <p>From 2000 to 2004, the relationship between daily changes in PM₁₀, PM_2.5, SO₂, NO₂, CO, and ozone levels and daily total mortality and mortality due to respiratory and heart diseases were assessed using Generalized Additive Poisson models controlled for potential confounders. The lag effect (up to five days) as well as the concurrent and previous day averages and distributed lag models were all estimated. Single and two pollutant models were also constructed.</p> <p>Results</p> <p>Daily levels of PM₁₀, PM_2.5, NO₂, and SO₂were found to be associated with an increase in respiratory mortality in Santa Cruz de Tenerife and with increased heart disease mortality in Las Palmas de Gran Canaria, thus indicating an association between daily ozone levels and mortality from heart diseases. The effects spread over five successive days. SO₂was the only air pollutant significantly related with total mortality (lag 0).</p> <p>Conclusions</p> <p>There is a short-term association between current exposure levels to air pollution and mortality (total as well as that due specifically to heart and respiratory diseases) in both cities. Risk coefficients were higher for respiratory and cardiovascular mortality, showing a delayed effect over several days.</p

Constraining Present-Day Anthropogenic Total Iron Emissions Using Model and Observations

Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long-term, near-source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub-sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under- or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting-related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long-term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.Human activities, such as smelting and oil combustion, release smoke and particles into the atmosphere. These particles often contain iron, which not only absorbs sunlight, contributing to atmospheric warming, but also serves as a nutrient for phytoplankton in various ocean regions. However, the precise extent of human-induced iron emissions remains uncertain due to a lack of comprehensive monitoring data. In this study, we leverage a global data set of iron observations to refine our estimates of iron emissions attributed to human activities. Additionally, we examine other co-released substances, such as carbon and nickel, to identify specific emission sources of iron. We employ statistical techniques to distinguish human-caused iron emissions from those originating from natural sources like dust and wildfires. Moreover, we utilize iron oxide observations to constrain emissions originating from East Asia and Norway, which are estimated to originate largely from smelting emissions. Through the analysis of long-term data sets, we provide lower and upper bounds to human-caused iron emissions. Furthermore, we investigate the impact of reduced observation numbers and a sparse network on the range of estimated iron emissions. Our findings highlight the critical role of observation quality in accurately assessing iron emissions from human activities.Anthropogenic total iron emissions are constrained to a factor of 3 in most global regions using long-term aerosol observations The number of sites, interannual variability, and site selection filter can affect the model-observation comparison uncertainty by 15%-50% Smelting-related emissions are constrained to a factor of 1.5 using iron oxide observations from East Asi

Micro-CT imaging reveals<i> Mekk3 </i>heterozygosity prevents cerebral cavernous malformations in <i>Ccm2</i>-deficient mice

Mutations in CCM1 (aka KRIT1), CCM2, or CCM3 (aka PDCD10) gene cause cerebral cavernous malformation in humans. Mouse models of CCM disease have been established by deleting Ccm genes in postnatal animals. These mouse models provide invaluable tools to investigate molecular mechanism and therapeutic approaches for CCM disease. However, the full value of these animal models is limited by the lack of an accurate and quantitative method to assess lesion burden and progression. In the present study we have established a refined and detailed contrast enhanced X-ray micro-CT method to measure CCM lesion burden in mouse brains. As this study utilized a voxel dimension of 9.5μm (leading to a minimum feature size of approximately 25μm), it is therefore sufficient to measure CCM lesion volume and number globally and accurately, and provide high-resolution 3-D mapping of CCM lesions in mouse brains. Using this method, we found loss of Ccm1 or Ccm2 in neonatal endothelium confers CCM lesions in the mouse hindbrain with similar total volume and number. This quantitative approach also demonstrated a rescue of CCM lesions with simultaneous deletion of one allele of Mekk3. This method would enhance the value of the established mouse models to study the molecular basis and potential therapies for CCM and other cerebrovascular diseases

Defining the Functional Domain of Programmed Cell Death 10 through Its Interactions with Phosphatidylinositol-3,4,5-Trisphosphate

Cerebral cavernous malformations (CCM) are vascular abnormalities of the central nervous system predisposing blood vessels to leakage, leading to hemorrhagic stroke. Three genes, Krit1 (CCM1), OSM (CCM2), and PDCD10 (CCM3) are involved in CCM development. PDCD10 binds specifically to PtdIns(3,4,5)P3 and OSM. Using threading analysis and multi-template modeling, we constructed a three-dimensional model of PDCD10. PDCD10 appears to be a six-helical-bundle protein formed by two heptad-repeat-hairpin structures (α1–3 and α4–6) sharing the closest 3D homology with the bacterial phosphate transporter, PhoU. We identified a stretch of five lysines forming an amphipathic helix, a potential PtdIns(3,4,5)P3 binding site, in the α5 helix. We generated a recombinant wild-type (WT) and three PDCD10 mutants that have two (Δ2KA), three (Δ3KA), and five (Δ5KA) K to A mutations. Δ2KA and Δ3KA mutants hypothetically lack binding residues to PtdIns(3,4,5)P3 at the beginning and the end of predicted helix, while Δ5KA completely lacks all predicted binding residues. The WT, Δ2KA, and Δ3KA mutants maintain their binding to PtdIns(3,4,5)P3. Only the Δ5KA abolishes binding to PtdIns(3,4,5)P3. Both Δ5KA and WT show similar secondary and tertiary structures; however, Δ5KA does not bind to OSM. When WT and Δ5KA are co-expressed with membrane-bound constitutively-active PI3 kinase (p110-CAAX), the majority of the WT is co-localized with p110-CAAX at the plasma membrane where PtdIns(3,4,5)P3 is presumably abundant. In contrast, the Δ5KA remains in the cytoplasm and is not present in the plasma membrane. Combining computational modeling and biological data, we propose that the CCM protein complex functions in the PI3K signaling pathway through the interaction between PDCD10 and PtdIns(3,4,5)P3

Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (>40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r≥0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2