Establishing uncertainty ranges of hydrologic indices across climate and physiographic regions of the Congo River Basin

Study region The five drainage systems of the Congo River Basin in central Africa. Study focus This study aims to establish uncertainty ranges of hydrologic indices and to provide a basis for transferring hydrologic indices from gauged to ungauged sub-basins by identifying the most influential climate and physiographic attributes. New insights for this region Only limited information on individual sub-basins natural hydrology exists across the Congo River Basin, limiting the application of commonly used regionalization approaches for prediction in ungauged sub-basins. This study uses predictive equations for the hydrologic indices across all climate and physiographic regions based only on the aridity index. The degree of uncertainty in the derived uncertainty bounds is less than 41% for both Q10/MMQ and Q50/MMQ indices across the basin. A greater degree of uncertainty is associated with the runoff ratio and the Q90/MMQ indices. The uncertainty is assumed to be due to uncertainty in rainfall and evapotranspiration estimates, a lack of spatial representativeness of the available observed streamflow data and other factors (e.g., geology) that might control the hydrologic indices rather than the aridity index alone. The uncertainty ranges provide the first estimates of hydrologic indices that are intended to constrain the outputs from hydrologic models and appropriately quantify prediction uncertainty and risks associated with water resources decision making

Groundwater fluxes in a shallow seasonal wetland pond: The effect of bathymetric uncertainty on predicted water and solute balances

The successful management of groundwater dependent shallow seasonal wetlands requires a sound understanding of groundwater fluxes. However, such fluxes are hard to quantify. Water volume and solute mass balance models can be used in order to derive an estimate of groundwater fluxes within such systems. This approach is particularly attractive, as it can be undertaken using measurable environmental variables, such as; rainfall, evaporation, pond level and salinity. Groundwater fluxes estimated from such an approach are subject to uncertainty in the measured variables as well as in the process representation and in parameters within the model. However, the shallow nature of seasonal wetland ponds means water volume and surface area can change rapidly and non-linearly with depth, requiring an accurate representation of the wetland pond bathymetry. Unfortunately, detailed bathymetry is rarely available and simplifying assumptions regarding the bathymetry have to be made. However, the implications of these assumptions are typically not quantified. We systematically quantify the uncertainty implications for eight different representations of wetland bathymetry for a shallow seasonal wetland pond in South Australia. The predictive uncertainty estimation methods provided in the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST) are used to quantify the effect of bathymetric uncertainty on the modelled fluxes. We demonstrate that bathymetry can be successfully represented within the model in a simple parametric form using a cubic Bézier curve, allowing an assessment of bathymetric uncertainty due to measurement error and survey detail on the derived groundwater fluxes compared with the fixed bathymetry models. Findings show that different bathymetry conceptualisations can result in very different mass balance components and hence process conceptualisations, despite equally good fits to observed data, potentially leading to poor management decisions for the wetlands. Model predictive uncertainty increases with the crudity of the bathymetry representation, however, approximations that capture the general shape of the wetland pond such as a power law or Bézier curve show only a small increase in prediction uncertainty compared to the full dGPS surveyed bathymetry, implying these may be sufficient for most modelling purposes

The Drosophila basic helix-loop-helix protein DIMMED directly activates PHM, a gene encoding a neuropeptide-amidating enzyme

The basic helix-loop-helix (bHLH) protein DIMMED (DIMM) supports the differentiation of secretory properties in numerous peptidergic cells of Drosophila melanogaster. DIMM is coexpressed with diverse amidated neuropeptides and with the amidating enzyme peptidylglycine α-hydroxylating monooxygenase (PHM) in approximately 300 cells of the late embryo. Here we confirm that DIMM has transcription factor activity in transfected HEK 293 cells and that the PHM gene is a direct target. The mammalian DIMM orthologue MIST1 also transactivated the PHM gene. DIMM activity was dependent on the basic region of the protein and on the sequences of three E-box sites within PHM's first intron; the sites make different contributions to the total activity. These data suggest a model whereby the three E boxes interact cooperatively and independently to produce high PHM transcriptional activation. This DIMM-controlled PHM regulatory region displayed similar properties in vivo. Spatially, its expression mirrored that of the DIMM protein, and its activity was largely dependent on dimm. Further, in vivo expression was highly dependent on the sequences of the same three E boxes. This study supports the hypothesis that DIMM is a master regulator of a peptidergic cell fate in Drosophila and provides a detailed transcriptional mechanism of DIMM action on a defined target gene

The influence of Au substitution and hydrostatic pressure on the phase transitions and magnetocaloric properties of MnCoGe alloys

In this work, the phase transitions and magnetocaloric properties of Mn 1-xAu xCoGe (0 ≤ x ≤ 0.025) alloys were studied as a function of concentration x and applied hydrostatic pressure. The increasing substitution of Au for Mn results in the decrease of the first-order martensitic transition temperature, and this first-order martensitic transition was ultimately converted to a second-order magnetic transition when the Au substitution (x) reached 0.025. The magnitudes of the maximum magnetic entropy changes increased when the magnetic and structural transitions were coupled, which occurred for 0.005 ≤ x ≤ 0.020. The largest maximum magnetic entropy change for a field change of μ 0 Δ H = 7 T was 33.1 J/kg K for the sample with x = 0.020. Similar to the effect of Au substitution, the first-order martensitic transition temperature initially decreased, and then converted to second order, when the applied hydrostatic pressure reached a large enough value. Interestingly, both Au substitution and pressure application cause a volume reduction and, in both cases, the first-order martensitic transition temperature initially reduced and then converted to second-order. These results suggest two different methods of tuning the transition temperatures in these magnetocaloric materials. One can either apply hydrostatic pressure and temporarily adjust the transition temperatures or modify the composition chemically and permanently change the transition temperatures

Early detection of pre-malignant lesions in a KRASG12D-driven mouse lung cancer model by monitoring circulating free DNA.

Lung cancer is the leading cause of cancer-related death. Two-thirds of cases are diagnosed at an advanced stage that is refractory to curative treatment. Therefore, strategies for the early detection of lung cancer are urgently sought. Total circulating free DNA (cfDNA) and tumour-derived circulating tumour DNA (ctDNA) are emerging as important biomarkers within a 'liquid biopsy' for monitoring human disease progression and response to therapy. Owing to the late clinical diagnosis of lung adenocarcinoma, the potential for cfDNA and ctDNA as early detection biomarkers remains unexplored. Here, using a Cre-regulated genetically engineered mouse model of lung adenocarcinoma development, driven by KrasG12D (the KrasLSL-G12D mouse), we serially tracked the release of cfDNA/ctDNA and compared this with tumour burden as determined by micro-computed tomography (CT). To monitor ctDNA, a droplet digital PCR assay was developed to permit discrimination of the KrasLox-G12D allele from the KrasLSL-G12D and KrasWT alleles. We show that micro-CT correlates with endpoint histology and is able to detect pre-malignant tumours with a combined volume larger than 7 mm3 Changes in cfDNA/ctDNA levels correlate with micro-CT measurements in longitudinal sampling and are able to monitor the emergence of lesions before the adenoma-adenocarcinoma transition. Potentially, this work has implications for the early detection of human lung adenocarcinoma using ctDNA/cfDNA profiling.A video abstract for this article is available at https://youtu.be/Ku8xJJyGs3UThis article has an associated First Person interview with the joint first authors of the paper.Medical Research Counci

Assessing the potential value of the regionalised input constraint indices for constraining hydrological model simulations in the Congo River Basin

The regionalised characteristics of a sub-basin's long-term hydrological behaviour are used as multiple constraint filters for constraining hydrological model simulations in the Congo Basin using the monthly time step Pitman model. The results suggest that the constraints are appropriate in many sub-basins (≥ 20 gauging stations), but not all. Detailed examination of these results suggested that the effects of high slopes (> 7%) could increase the runoff ratio and Q90/MMQ (low flow index) constraint values and that implementing an adjustment factor based on slope did improve some of the very poor results. The percentage points on the FDC falling within the simulated uncertainty band has increased from 0% to 59.6% and 2.4% to 39.9% for the Rift valley and Batéké plateaux regions, respectively. Future studies ideally need a range of different rainfall products to quantify the uncertainties related to the inappropriateness of the CRU rainfall data in some parts of the Congo Basin

Health-related quality of life in Huntington’s Disease patients: a comparison of proxy assessment and patient self-rating using the disease-specific Huntington’s Disease health-related quality of life questionnaire (HDQoL)

Huntington’s disease (HD) is a fatal, neurodegenerative disease for which there is no known cure. Proxy evaluation is relevant for HD as its manifestation might limit the ability of persons to report their health-related quality of life (HrQoL). This study explored patient–proxy ratings of HrQoL of persons at different stages of HD, and examined factors that may affect proxy ratings. A total of 105 patient–proxy pairs completed the Huntington’s disease health-related quality of life questionnaire (HDQoL) and other established HrQoL measures (EQ-5D and SF-12v2). Proxy–patient agreement was assessed in terms of absolute level (mean ratings) and intraclass correlation. Proxies’ ratings were at a similar level to patients’ self-ratings on an overall Summary Score and on most of the six Specific Scales of the HDQoL. On the Specific Hopes and Worries Scale, proxies on average rated HrQoL as better than patients’ self-ratings, while on both the Specific Cognitive Scale and Specific Physical and Functional Scale proxies tended to rate HrQoL more poorly than patients themselves. The patient’s disease stage and mental wellbeing (SF-12 Mental Component scale) were the two factors that primarily affected proxy assessment. Proxy scores were strongly correlated with patients’ self-ratings of HrQoL, on the Summary Scale and all Specific Scales. The patient–proxy correlation was lower for patients at moderate stages of HD compared to patients at early and advanced stages. The proxy report version of the HDQoL is a useful complementary tool to self-assessment, and a promising alternative when individual patients with advanced HD are unable to self-report

Remote sensing of vegetation fires and its contribution to a fire management information system

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the type of information remote sensing can provide to the fire community. It considers first fire management information needs in the context of fire management information system. An introduction to remote sensing then precedes the description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate how the information can be used in practice