The structure of gravel-bed flow with intermediate submergence: a laboratory study

The paper reports an experimental study of the flow structure over an immobile gravel bed in open channel at intermediate submergence, with particular focus on the near-bed region. The experiments consisted of velocity measurements using three-component (stereoscopic) Particle Image Velocimetry (PIV) in near-bed horizontal plane and two-component PIV in three vertical planes that covered three distinctly different hydraulic scenarios where the ratio of flow depth to roughness height (i.e., relative submergence) changes from 7.5 to 10.8. Detailed velocity measurements were supplemented with fine-scale bed elevation data obtained with a laser scanner. The data revealed longitudinal low-momentum and high-momentum "strips'' in the time-averaged velocity field, likely induced by secondary currents. This depth-scale pattern was superimposed with particle-scale patches of flow heterogeneity induced by gravel particle protrusions. A similar picture emerged when considering second-order velocity moments. The interaction between the flow field and gravel-bed protrusions is assessed using cross correlations of velocity components and bed elevations in a horizontal plane just above gravel particle crests. The cross correlations suggest that upward and downward fluid motions are mainly associated with upstream-facing and lee sides of particles, respectively. Results also show that the relative submergence affects the turbulence intensity profiles for vertical velocity over the whole flow depth, while only a weak effect, limited to the near-bed region, is noticed for streamwise velocity component. The approximation of mean velocity profiles with a logarithmic formula reveals that log-profile parameters depend on relative submergence, highlighting inapplicability of a conventional "universal'' logarithmic law for gravel-bed flows with intermediate submergence

Residential density classification for sustainable housing development using a machine learning approach

Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here we develop a methodology using a Random Forests algorithm (in combination with GIS spatial data processing) to detect and classify the residential neighbourhoods and their spatial characteristics within the region between Oxford and Cambridge, that is, the 'Oxford-Cambridge Arc'. The classification model is based on four pre-defined urban classes, that is, Centre, Urban, Suburban, and Rural for the entire region. The resolution is a grid of 500 m × 500 m. The features for classification include (1) dwelling geometric attributes (e.g. garden size, building footprint area, building perimeter), (2) street networks (e.g. street length, street density, street connectivity), (3) dwelling density (number of housing units per hectare), (4) building residential types (detached, semi-detached, terraced, and flats), and (5) characteristics of the surrounding neighbourhoods. The classification results, with overall average accuracy of 80% (accuracy per class: Centre: 38%, Urban 91%, Suburban 83%, and Rural 77%), for the Arc region show that the most important variables were three characteristics of the surrounding area: residential footprint area, dwelling density, and number of private gardens. The results of the classification are used to establish a baseline for the current status of the residential neighbourhoods in the Arc region. The results bring data-driven decision-making processes to the level of local authority and policy makers in order to support sustainable housing development at the regional scale

Forecasting magma-chamber rupture at Santorini volcano, Greece

How much magma needs to be added to a shallow magma chamber to cause rupture, dyke injection, and a potential eruption? Models that yield reliable answers to this question are needed in order to facilitate eruption forecasting. Development of a long-lived shallow magma chamber requires periodic influx of magmas from a parental body at depth. This redistribution process does not necessarily cause an eruption but produces a net volume change that can be measured geodetically by inversion techniques. Using continuum-mechanics and fracture-mechanics principles, we calculate the amount of magma contained at shallow depth beneath Santorini volcano, Greece. We demonstrate through structural analysis of dykes exposed within the Santorini caldera, previously published data on the volume of recent eruptions, and geodetic measurements of the 2011–2012 unrest period, that the measured 0.02% increase in volume of Santorini’s shallow magma chamber was associated with magmatic excess pressure increase of around 1.1 MPa. This excess pressure was high enough to bring the chamber roof close to rupture and dyke injection. For volcanoes with known typical extrusion and intrusion (dyke) volumes, the new methodology presented here makes it possible to forecast the conditions for magma-chamber failure and dyke injection at any geodetically well-monitored volcano

The CUSSH programme: supporting cities’ transformational change towards health and sustainability [version 2; peer review: 2 approved]

This paper describes a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods the Complex Urban Systems for Sustainability and Health (CUSSH) project will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st Century. CUSSH’s core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities’ energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing

A family presenting with multiple endocrine neoplasia type 2B: A case report

<p>Abstract</p> <p>Introduction</p> <p>Multiple endocrine neoplasia 2B, a rare autosomal dominant syndrome, is characterized by early onset of medullary thyroid carcinoma, pheochromocytoma, marfanoid habitus and mucosal neuromas of the tongue, lips, inner cheeks and inner eyelids. Gangliomatosis of the gastrointestinal tract and its complications may also occur in patients with this disease.</p> <p>Case presentation</p> <p>We present the case of a 16-year-old Persian man diagnosed as having a non-invasive form of multiple endocrine neoplasia 2B (medullary thyroid cancer, mucosal neuroma of the tongue, lips and inner eyelids). Our patient, who had a positive family history of medullary thyroid cancer, was of normal height with no signs of marfanoid habitus.</p> <p>Conclusions</p> <p>Ophthalmological and oral manifestations of multiple endocrine neoplasia 2B, as in the case of our patient, are rare presentations of the disease; unfortunately in the case of our patient his condition had not been noted and acted upon until he presented to our department. The diagnosis in our patient's case was made only after his mother presented with the same condition. As a result, we emphasize that physicians should pay more attention to the oral and ocular signs of multiple endocrine neoplasia 2B in order to diagnose this fatal syndrome at an earlier phase.</p

Whole-Genome Sequencing of Individuals from a Founder Population Identifies Candidate Genes for Asthma

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS

Chronic Intranasal Treatment with an Anti-Aβ30-42 scFv Antibody Ameliorates Amyloid Pathology in a Transgenic Mouse Model of Alzheimer's Disease

Amyloid-beta peptide (Aβ)-directed active and passive immunization therapeutic strategies reduce brain levels of Aβ, decrease the severity of beta-amyloid plaque pathology and reverse cognitive deficits in mouse models of Alzheimer's disease (AD). As an alternative approach to passive immunization with full IgG molecules, single-chain variable fragment (scFv) antibodies can modulate or neutralize Aβ-related neurotoxicity and inhibit its aggregation in vitro. In this study, we characterized a scFv derived from a full IgG antibody raised against the C-terminus of Aβ, and studied its passage into the brains of APP transgenic mice, as well as its potential to reduce Aβ-related pathology. We found that the scFv entered the brain after intranasal application, and that it bound to beta-amyloid plaques in the cortex and hippocampus of APP transgenic mice. Moreover, the scFv inhibited Aβ fibril formation and Aβ-mediated neurotoxicity in vitro. In a preventative therapeutic approach chronic intranasal treatment with scFv reduced congophilic amyloid angiopathy (CAA) and beta-amyloid plaque numbers in the cortex of APPswe/PS1dE9 mice. This reduction of CAA and plaque pathology was associated with a redistribution of brain Aβ from the insoluble fraction to the soluble peptide pool. Due to their lack of the effector domain of full IgG, scFv may represent an alternative tool for the treatment of Aβ-related pathology without triggering Fc-mediated effector functions. Additionally, our observations support the possibility that Aβ-directed immunotherapy can reduce Aβ deposition in brain vessels in transgenic mice

Metabolism of multiple glycosaminoglycans by <i>Bacteroides thetaiotaomicron</i> is orchestrated by a versatile core genetic locus

The human gut microbiota (HGM), which is critical to human health, utilises complex glycans as its major carbon source. Glycosaminoglycans represent an important, high priority, nutrient source for the HGM. Pathways for the metabolism of various glycosaminoglycan substrates remain ill-defined. Here we perform a biochemical, genetic and structural dissection of the genetic loci that orchestrates glycosaminoglycan metabolism in the organism Bacteroides thetaiotaomicron. Here, we report: the discovery of two previously unknown surface glycan binding proteins which facilitate glycosaminoglycan import into the periplasm; distinct kinetic and genetic specificities of various periplasmic lyases which dictate glycosaminoglycan metabolic pathways; understanding of endo sulfatase activity questioning the paradigm of how the ‘sulfation problem’ is handled by the HGM; and 3D crystal structures of the polysaccharide utilisation loci encoded sulfatases. Together with comparative genomic studies, our study fills major gaps in our knowledge of glycosaminoglycan metabolism by the HGM