The Turbulent Transport and Biological Structure of Eutrophication Models. Volume I: Preserving the Statistical Structure in Lake Transport Calculations

Project Completion Report, Volume I Office of Water Resources Research and Technology Matching Grant B-O36-OHIO(print) v. ; ill. ; 28 cm.Preface -- Acknowledgments -- List of Tables -- List of Figures -- List of Symbols -- Chapter I. Introduction and Objective -- Chapter II. Review of Turbulent Transport Models -- Chapter III. Turbulence -- Chapter IV. Filtration -- Chapter V. Derivation of Filtered Transport Equations -- Chapter VI. Numerical Solution -- Chapter VII. Model Implementation -- Chapter VIII. Results -- Chapter IX. Interpretation and Discussion -- Chapter X. Conclusions -- Appendix -- Reference

Inferring Allele Frequency Trajectories from Ancient DNA Indicates That Selection on a Chicken Gene Coincided with Changes in Medieval Husbandry Practices

Ancient DNA provides an opportunity to infer the drivers of natural selection by linking allele frequency changes to temporal shifts in environment or cultural practices. However, analyses have often been hampered by uneven sampling and uncertainties in sample dating, as well as being confounded by demographic processes. Here, we present a Bayesian statistical framework for quantifying the timing and strength of selection using ancient DNA that explicitly addresses these challenges. We applied this method to time series data for two loci: TSHR and BCDO2, both hypothesised to have undergone strong and recent selection in domestic chickens. The derived variant in TSHR, associated with reduced aggression to conspecifics and faster onset of egg laying, shows strong selection beginning around 1,100 years ago, coincident with archaeological evidence for intensified chicken production and documented changes in egg and chicken consumption. To our knowledge, this is the first example of preindustrial domesticate trait selection in response to a historically attested cultural shift in food preference. For BCDO2, we find support for selection, but demonstrate that the recent rise in allele frequency could also have been driven by gene flow from imported Asian chickens during more recent breed formations. Our findings highlight that traits found ubiquitously in modern domestic species may not necessarily have originated during the early stages of domestication. In addition, our results demonstrate the importance of precise estimation of allele frequency trajectories through time for understanding the drivers of selection.The authors are grateful to Brian Follett for his comments on the biological functions of the TSHR gene. L.L., R.A., K.D., and G.L. were supported by Natural Environment Research Council, UK (grant numbers NE/K005243/1, NE/K003259/1). M.G.T. was supported by Wellcome Trust Senior Investigator Award (grant number 100719/Z/12/Z) and Leverhulme Trust (grant number RP2011-R-045). A.M. and A.E. were supported by the European Research Council Consolidator grant (grant number 647787-LocalAdaptation). R.A., N.S., and G.L. were supported by Arts and Humanities Research Council (grant number AH/L006979/1). R.A. and G.L. were supported by European Research Council (grant number ERC-2013-StG 337574-UNDEAD)

Metabolomics guides rational development of a simplified cell culture medium for drug screening against <i>Trypanosoma brucei</i>

n vitro culture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream form &lt;i&gt;Trypanosoma brucei&lt;/i&gt;. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supports in vitro growth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (&#60;3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening

Learning and Expertise in Mineral Exploration Decision-Making: An Ecological Dynamics Perspective

The declining discovery rate of world-class ore deposits represents a significant obstacle to future global metal supply. To counter this trend, there is a requirement for mineral exploration to be conducted in increasingly challenging, uncertain, and remote environments. Faced with such increases in task and environmental complexity, an important concern in exploratory activities are the behavioural challenges of information perception, interpretation and decision-making by geoscientists tasked with discovering the next generation of deposits. Here, we outline the Dynamics model, as a diagnostic tool for situational analysis and a guiding framework for designing working and training environments to maximise exploration performance. The Dynamics model is based on an Ecological Dynamics framework, combining Newell’s Constraints model, Self Determination Theory, and including feedback loops to define an autopoietic system. By implication of the Dynamics model, several areas are highlighted as being important for improving the quality of exploration. These include: (a) provision of needs-supportive working environments that promote appropriate degrees of effort, autonomy, creativity and technical risk-taking; (b) an understanding of the wider motivational context, particularly the influence of tradition, culture and other ‘forms of life’ that constrain behaviour; (c) relevant goal-setting in the design of corporate strategies to direct exploration activities; and (d) development of practical, representative scenario-based training interventions, providing effective learning environments, with digital media and technologies presenting decision-outcome feedback, to assist in the development of expertise in mineral exploration targeting

Airborne S-Band SAR for forest biophysical retrieval in temperate mixed forests of the UK

Radar backscatter from forest canopies is related to forest cover, canopy structure and aboveground biomass (AGB). The S-band frequency (3.1–3.3 GHz) lies between the longer L-band (1–2 GHz) and the shorter C-band (5–6 GHz) and has been insufficiently studied for forest applications due to limited data availability. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest biophysical properties. To understand the scattering mechanisms in forest canopies at S-band the Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model was used. S-band backscatter was found to have high sensitivity to the forest canopy characteristics across all polarisations and incidence angles. This sensitivity originates from ground/trunk interaction as the dominant scattering mechanism related to broadleaved species for co-polarised mode and specific incidence angles. The study was carried out in the temperate mixed forest at Savernake Forest and Wytham Woods in southern England, where airborne S-band SAR imagery and field data are available from the recent AirSAR campaign. Field data from the test sites revealed wide ranges of forest parameters, including average canopy height (6–23 m), diameter at breast-height (7–42 cm), basal area (0.2–56 m2/ha), stem density (20–350 trees/ha) and woody biomass density (31–520 t/ha). S-band backscatter-biomass relationships suggest increasing backscatter sensitivity to forest AGB with least error between 90.63 and 99.39 t/ha and coefficient of determination (r2) between 0.42 and 0.47 for the co-polarised channel at 0.25 ha resolution. The conclusion is that S-band SAR data such as from NovaSAR-S is suitable for monitoring forest aboveground biomass less than 100 t/ha at 25 m resolution in low to medium incidence angle rang

Classification of Foetal Distress and Hypoxia Using Machine Learning Approaches

© 2018, Springer International Publishing AG, part of Springer Nature. Foetal distress and hypoxia (oxygen deprivation) is considered as a serious condition and one of the main factors for caesarean section in the obstetrics and Gynecology department. It is the third most common cause of death in new-born babies. Many foetuses that experienced some sort of hypoxic effects can develop series risks including damage to the cells of the central nervous system that may lead to life-long disability (cerebral palsy) or even death. Continuous labour monitoring is essential to observe the foetal well being. Foetal surveillance by monitoring the foetal heart rate with a cardiotocography is widely used. Despite the indication of normal results, these results are not reassuring, and a small proportion of these foetuses are actually hypoxic. In this paper, machine-learning algorithms are utilized to classify foetuses which are experiencing oxygen deprivation using PH value (a measure of hydrogen ion concentration of blood used to specify the acidity or alkalinity) and Base Deficit of extra cellular fluid level (a measure of the total concentration of blood buffer base that indicates the metabolic acidosis or compensated respiratory alkalosis) as indicators of respiratory and metabolic acidosis, respectively, using open source partum clinical data obtained from Physionet. Six well know machine learning classifier models are utilised in our experiments for the evaluation; each model was presented with a set of selected features derived from the clinical data. Classifier’s evaluation is performed using the receiver operating characteristic curve analysis, area under the curve plots, as well as the confusion matrix. Our simulation results indicate that machine-learning algorithms provide viable methods that could delivery improvements over conventional analysis

Red noise increases extinction risk during rapid climate change

Aim: As the global climate is changing rapidly, there is a need to make conservation decisions to facilitate species' persistence under climate change. Models employed to make predictions regarding the impacts of climate change on species' distributions, and ultimately persistence, typically assume that interannual variability in environmental conditions is independent between years. However, the colour of environmental noise has been shown to affect extinction risk in populations occupying spatially static environments, and should therefore affect persistence during climate change. This study aims to investigate the importance of noise colour for extinction risk during climate-induced range shifts. Methods: We use a spatially explicit coupled map lattice with a latitudinal gradient in climatic suitability, together with time series of environmental noise, to simulate periods of directional climate change and investigate the effects of noise colour on extinction risk and range size. Results: Extinction risk increases with reddening of the environmental noise, and this effect is particularly pronounced over short time frames when climate change is rapid. Main conclusions: Given that management decisions are typically made over such short time frames, and the rapid rates of climate change currently being experienced, we highlight the importance of incorporating realistic time series of environmental noise into models used for conservation planning under climate change

High throughput chemical screening for anti-virulence developmental phenotypes in Trypanosoma brucei

In the bloodstream of mammalian hosts, the sleeping sickness parasite, Trypanosoma brucei, exists as a proliferative slender form or a nonproliferative, transmissible, stumpy form. The transition between these developmental forms is controlled by a density-dependent mechanism that is important for the parasite's infection dynamics, immune evasion via ordered antigenic variation, and disease transmissibility. However, stumpy formation has been lost in most laboratory-adapted trypanosome lines, generating monomorphic parasites that proliferate uncontrolled as slender forms in vitro and in vivo. Nonetheless, these forms are readily amenable to cell culture and high-throughput screening for trypanocidal lead compounds. Here, we have developed and exploited a high-throughput screen for developmental phenotypes using a transgenic monomorphic cell line expressing a reporter under the regulation of gene control signals from the stumpy-specific molecule PAD1. Using a whole-cell fluorescence-based assay to screen over 6,000 small molecules from a kinase-focused compound library, small molecules able to activate stumpy-specific gene expression and proliferation arrest were assayed in a rapid assay format. Independent follow-up validation identified one hit able to induce modest, yet specific, changes in mRNA expression indicative of a partial differentiation to stumpy forms in monomorphs. Further, in pleomorphs this compound induced a stumpy-like phenotype, entailing growth arrest, morphological changes, PAD1 expression, and enhanced differentiation to procyclic forms. This not only provides a potential tool compound for the further understanding of stumpy formation but also demonstrates the use of high-throughput screening in the identification of compounds able to induce specific phenotypes, such as differentiation, in African trypanosomes