Decomposition of the Mean Squared Error and NSE Performance Criteria: Implications for Improving Hydrological Modelling

The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. The analysis is illustrated by calibrating a simple conceptual precipitation-runoff model to daily data for a number of Austrian basins having a broad range of hydro-meteorological characteristics. Evaluation of the results clearly demonstrates the problems that can be associated with any calibration based on the NSE (or MSE) criterion. While we propose and test an alternative criterion that can help to reduce model calibration problems, the primary purpose of this study is not to present an improved measure of model performance. Instead, we seek to show that there are systematic problems inherent with any optimization based on formulations related to the MSE. The analysis and results have implications to the manner in which we calibrate and evaluate environmental models; we discuss these and suggest possible ways forward that may move us towards an improved and diagnostically meaningful approach to model performance evaluation and identification

Comparing biological markers of Alzheimer\u27s disease across blood fraction and platforms: Comparing apples to oranges

Introduction: This study investigated the comparability of potential Alzheimer\u27s disease (AD) biomarkers across blood fractions and assay platforms. Methods: Nonfasting serum and plasma samples from 300 participants (150 AD patients and 150 controls) were analyzed. Proteomic markers were obtained via electrochemiluminescence or Luminex technology. Comparisons were conducted via Pearson correlations. The relative importance of proteins within an AD diagnostic profile was examined using random forest importance plots. Results: On the Meso Scale Discovery multiplex platform, 10 of the 21 markers shared \u3e50% of the variance across blood fractions (serum amyloid A R2 = 0.99, interleukin (IL)10 R2 = 0.95, fatty acid-binding protein (FABP) R2 = 0.94, I309 R2 = 0.94, IL-5 R2 = 0.94, IL-6 R2 = 0.94, eotaxin3 R2 = 0.91, IL-18 R2 = 0.87, soluble tumor necrosis factor receptor 1 R2 = 0.85, and pancreatic polypeptide R2 = 0.81). When examining protein concentrations across platforms, only five markers shared \u3e50% of the variance (beta 2 microglobulin R2 = 0.92, IL-18 R2 = 0.80, factor VII R2 = 0.78, CRP R2 = 0.74, and FABP R2 = 0.70). Discussion: The current findings highlight the importance of considering blood fractions and assay platforms when searching for AD relevant biomarkers

Structure-based discovery of opioid analgesics with reduced side effects

Morphine is an alkaloid from the opium poppy used to treat pain. The potentially lethal side effects of morphine and related opioids—which include fatal respiratory depression—are thought to be mediated by μ-opioid-receptor (μOR) signalling through the β-arrestin pathway or by actions at other receptors. Conversely, G-protein μOR signalling is thought to confer analgesia. Here we computationally dock over 3 million molecules against the μOR structure and identify new scaffolds unrelated to known opioids. Structure-based optimization yields PZM21—a potent Gi activator with exceptional selectivity for μOR and minimal β-arrestin-2 recruitment. Unlike morphine, PZM21 is more efficacious for the affective component of analgesia versus the reflexive component and is devoid of both respiratory depression and morphine-like reinforcing activity in mice at equi-analgesic doses. PZM21 thus serves as both a probe to disentangle μOR signalling and a therapeutic lead that is devoid of many of the side effects of current opioids

Climate change impact on West African rivers under an ensemble of CORDEX climate projections

In the context of a region-wide hydropower potential study, the impact of climate change on the hydrology of West Africa was assessed. Climate data of 30 Regional Climate Model simulations of the CORDEX initiative based on two emission scenarios (Representative Concentration Pathways RCP4.5 and RCP8.5) were applied in a water balance model. Future changes in the water balance for an area of 3.7 million km2 and resulting changes in river discharge in 500,000 river reaches were investigated for two future periods, 2026–2045 and 2046–2065. This article focuses on 12 key locations in the 10 largest river basins, and all results for the entire West Africa region are publicly available via the ECOWAS Observatory for Renewable Energy and Energy Efficiency (www.ecowrex.org/smallhydro).For large parts of the region, projected changes in climate do not lead to substantial reductions in river discharge, with median results of the model ensemble in the range of ±5%. Stronger decreases in discharge are projected for regions in the north and east of West Africa, pronounced increases mainly for the southwest. The application of a large climate model ensemble exhibits the high uncertainty related with these projections, but also shows regions with high agreement between results with different models. The regional climate change impact analysis provides a baseline for climate-informed decision making for hydropower development and other fields of water management and water policy and enables regional focus for initiating further research and developing adaptation pathways. Keywords: Climate change impact, CORDEX, West Africa, Water balance model, River discharge, Hydropowe

Impact modelling of water resources development and climate scenarios on Zambezi River discharge

Study region: The Zambezi River basin (1.4 × 106 km2) in southern Africa, which is shared by eight countries and includes two of the World's largest reservoirs. Study focus: Impacts on future water resources in the Zambezi basin are studied, based on World Bank projections that include large scale irrigation and new hydropower plants. Also the impacts of climate change scenarios are analysed. Modelling challenges are the large basin area, data scarcity and complex hydrology. We use recent GPCC rainfall data to force a rainfall-runoff model linked to a reservoir model for the Zambezi basin. The simulations are evaluated with 60 years of observed discharge and reservoir water level data and applied to assess the impacts on historical and future discharges. New hydrological insights for the region: Comparisons between historical and future scenarios show that the biggest changes have already occurred. Construction of Kariba and CahoraBassa dams in the mid 1900s altered the seasonality and flow duration curves. Future irrigation development will cause decreases of a similar magnitude to those caused by current reservoir evaporation losses. The discharge is highly sensitive to small precipitation changes and the two climate models used give different signs for future precipitation change, suggestive of large uncertainty. The river basin model and database are available as anopen-online Decision Support System to facilitate impact assessments of additional climate or development scenarios

Active-State Models of Ternary GPCR Complexes: Determinants of Selective Receptor-G-Protein Coupling

Based on the recently described crystal structure of the β2 adrenergic receptor - Gs-protein complex, we report the first molecular-dynamics simulations of ternary GPCR complexes designed to identify the selectivity determinants for receptor-G-protein binding. Long-term molecular dynamics simulations of agonist-bound β2AR-Gαs and D2R-Gαi complexes embedded in a hydrated bilayer environment and computational alanine-scanning mutagenesis identified distinct residues of the N-terminal region of intracellular loop 3 to be crucial for coupling selectivity. Within the G-protein, specific amino acids of the α5-helix, the C-terminus of the Gα-subunit and the regions around αN-β1 and α4-β6 were found to determine receptor recognition. Knowledge of these determinants of receptor-G-protein binding selectivity is essential for designing drugs that target specific receptor/G-protein combinations