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Bare soil evaporation is controlled by a combination of capillary flow, vapour diffusion and film flow. Relevant analytical solutions mostly assume horizontal flow conditions and ignore gravitational effects. Salvucci ( 1997 ) provided a rare example of a semi-analytical solution for vertical bare soil evaporation. However, they did not explicitly represent vapour diffusion and film flow, which are likely to account for a significant proportion of total flow during vertical evaporation from soils. Vapour diffusion and film flow can be incorporated via Salvucci’s desorptivity parameter, which represents the proportionality constant relating Stage 2 cumulative evaporation to the square root of time under horizontal flow conditions. The objective of this article is to implement vapour diffusion and film flow within Salvucci’s semi-analytical solution and test its performance by comparison with isothermal numerical simulation and relevant experimental data. The following important conclusions are drawn. Analytical solutions that assume horizontal flow conditions are inadequate for understanding vertical evaporation problems because they overestimate evaporation rates and mostly predict vapour diffusion and film flow to be of negligible influence. Salvucci’s semi-analytical solution is effective at predicting the order-of-magnitude reduction in evaporation caused by gravitational effects. However, it is unable to identify the correct importance of vapour diffusion and film flow because these processes can only be represented through its desorptivity parameter.

This paper considers the two-dimensional saturated and unsaturated flow of water through inclined porous media, namely a waste dump or hill slope. Since the partial differential equation governing this water flow transforms from being parabolic to elliptic as the water flow varies from unsaturated to saturated, an iterative, finite differencing scheme is used to develop a numerical solution. The model can be used to investigate the effects that hill slope angle, depth of soil cover and hilltop width have on water accumulation in the dump and the time required for saturation to occur at different areas in the dump domain. The accuracy and reliability of the computer based solution is tested for two different boundary conditions - (1) no flow on all boundaries (i.e., the internal redistribution of soil moisture to steady state) and (2) a constant rainfall flux on the dump surface. Numerical studies then show the effects of changing the hill slope angle, depth of layer, and dump geometry on the flow characteristics in the dump. [PUBLICATION ASBTRACT]

Central to tumor evolution is the generation of genetic diversity. However, the extent and patterns by which de novo karyotype alterations emerge and propagate within human tumors are not well understood, especially at single-cell resolution. Here, we present 3D Live-Seq—a protocol that integrates live-cell imaging of tumor organoid outgrowth and whole-genome sequencing of each imaged cell to reconstruct evolving tumor cell karyotypes across consecutive cell generations. Using patient-derived colorectal cancer organoids and fresh tumor biopsies, we demonstrate that karyotype alterations of varying complexity are prevalent and can arise within a few cell generations. Sub-chromosomal acentric fragments were prone to replication and collective missegregation across consecutive cell divisions. In contrast, gross genome-wide karyotype alterations were generated in a single erroneous cell division, providing support that aneuploid tumor genomes can evolve via punctuated evolution. Mapping the temporal dynamics and patterns of karyotype diversification in cancer enables reconstructions of evolutionary paths to malignant fitness. Analysis of live-cell imaging and single-cell genome sequencing data of colorectal cancer organoids identifies temporal dynamics of sub-chromosomal copy-number amplifications.

Differentiated vulvar intraepithelial neoplasia (dVIN) is a premalignant lesion that is known to progress rapidly to invasive carcinoma. Accurate histological diagnosis is therefore crucial to allow appropriate treatment. To identify reliable diagnostic features, we evaluated the inter-observer agreement in the histological assessment of dVIN, among a bi-national, multi-institutional group of pathologists. Two investigators from Erasmus MC selected 36 hematoxylin-eosin-stained glass slides of dVIN and no-dysplasia, and prepared a list of 15 histological features of dVIN. Nine participating pathologists (i) diagnosed each slide as dVIN or no-dysplasia, (ii) indicated which features they used for the diagnosis, and (iii) rated these features in terms of their diagnostic usefulness. Diagnoses rendered by > 50% participants were taken as the consensus (gold standard). p53-immunohistochemistry (IHC) was performed for all cases, and the expression patterns were correlated with the consensus diagnoses. Kappa (ĸ)-statistics were computed to measure inter-observer agreements, and concordance of the p53-IHC patterns with the consensus diagnoses. For the diagnosis of dVIN, overall agreement was moderate (ĸ = 0.42), and pair-wise agreements ranged from slight (ĸ = 0.10) to substantial (ĸ = 0.73). Based on the levels of agreement and ratings of usefulness, the most helpful diagnostic features were parakeratosis, cobblestone appearance, chromatin abnormality, angulated nuclei, atypia discernable under × 100, and altered cellular alignment. p53-IHC patterns showed substantial concordance (ĸ = 0.67) with the consensus diagnoses. Histological interpretation of dVIN remains challenging with suboptimal inter-observer agreement. We identified the histological features that may facilitate the diagnosis of dVIN. For cases with a histological suspicion of dVIN, consensus-based pathological evaluation may improve the reliability of the diagnosis.

Abdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in AAA pathogenesis. These genes also indicate overlap between the development of AAA and other monogenic aortopathies, particularly via transforming growth factor β signaling. Motivated by the strong evidence for the role of lipid metabolism in AAA, we used Mendelian randomization to establish the central role of nonhigh-density lipoprotein cholesterol in AAA and identified the opportunity for repurposing of proprotein convertase, subtilisin/kexin-type 9 (PCSK9) inhibitors. This was supported by a study demonstrating that PCSK9 loss of function prevented the development of AAA in a preclinical mouse model. Genome-wide association meta-analysis of AAA identifies 121 independent risk loci and highlights potential therapeutic targets such as proprotein convertase, subtilisin/kexin-type 9 (PCSK9).

International Cancer Genome Consortium members review and recommend computational approaches for identifying mutations that drive cancer progression from among the many sequence variants present in tumor genomes. The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.

We develop a network-based model of a catchment basin that incorporates the possibility of small-scale, in-channel, leaky barriers as flood attenuation features, on each of the edges of the network. The model can be used to understand effective risk reduction strategies considering the whole-system performance; here we focus on identifying network dam placements promoting effective dynamic utilisation of storage and placements that also reduce risk of breach or cascade failure of dams during high flows. We first demonstrate the model using idealised networks and explore risk of cascade failure using probabilistic barrier-fragility assumptions. The investigation highlights the need for robust design of nature-based measures, to avoid inadvertent exposure of communities to a flood risk, and we conclude that the principle of building the leaky barriers on the upstream tributaries is generally less risky than building on the main trunk, although this may depend on the network structure specific to the catchment under study. The efficient scheme permits rapid assessment of the whole-system performance of dams placed in different locations in real networks, demonstrated in application to a real system of leaky barriers built in Penny Gill, a stream in the West Cumbria region of Britain.

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis. In breast cancer the contribution of different genetic variants to disease heritability is complex and not fully understood. Here, the authors present a network-based analysis in 84,567 patients studying ~7.3 million variants, identifying gene modules associated with breast cancer survival.

Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union (EGU) in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals.