Studies in Human Inheritance XXXIV. Further Data on the Linkage of the Genes for Sickle Cells and the M-N Blood Types

Author Institution: The University of Oklahoma, Norman, Oklahoma; Department of Medicine, Washington University, and Barnes Hospital, St. Loui

Emerging approaches to measure photosynthesis from the leaf to the ecosystem

Measuring photosynthesis is critical for quantifying and modeling leaf to regional scale productivity of managed and natural ecosystems. This review explores existing and novel advances in photosynthesis measurements that are certain to provide innovative directions in plant science research. First, we address gas exchange approaches from leaf to ecosystem scales. Leaf level gas exchange is a mature method but recent improvements to the user interface and environmental controls of commercial systems have resulted in faster and higher quality data collection. Canopy chamber and micrometeorological methods have also become more standardized tools and have an advanced understanding of ecosystem functioning under a changing environment and through long time series data coupled with community data sharing. Second, we review proximal and remote sensing approaches to measure photosynthesis, including hyperspectral reflectance- A nd fluorescence-based techniques. These techniques have long been used with aircraft and orbiting satellites, but lower-cost sensors and improved statistical analyses are allowing these techniques to become applicable at smaller scales to quantify changes in the underlying biochemistry of photosynthesis. Within the past decade measurements of chlorophyll fluorescence from earth-orbiting satellites have measured Solar Induced Fluorescence (SIF) enabling estimates of global ecosystem productivity. Finally, we highlight that stronger interactions of scientists across disciplines will benefit our capacity to accurately estimate productivity at regional and global scales. Applying the multiple techniques outlined in this review at scales from the leaf to the globe are likely to advance understanding of plant functioning from the organelle to the ecosystem

A review of transformative strategies for climate mitigation by grasslands

Grasslands can significantly contribute to climate mitigation. However, recent trends indicate that human activities have switched their net cooling effect to a warming effect due to management intensification and land conversion. This indicates an urgent need for strategies directed to mitigate climate warming while enhancing productivity and efficiency in the use of land and natural (nutrients, water) resources. Here, we examine the potential of four innovative strategies to slow climate change including: 1) Adaptive multi-paddock grazing that consists of mimicking how ancestral herds roamed the Earth; 2) Agrivoltaics that consists of simultaneously producing food and energy from solar panels on the same land area; 3) Agroforestry with a reverse phenology tree species, Faidherbia (Acacia) albida, that has the unique trait of being photosynthetically active when intercropped herbaceous plants are dormant; and, 4) Enhanced Weathering, a negative emission technology that removes atmospheric CO2 from the atmosphere. Further, we speculate about potential unknown consequences of these different management strategies and identify gaps in knowledge. We find that all these strategies could promote at least some of the following benefits of grasslands: CO2 sequestration, non-CO2 GHG mitigation, productivity, resilience to climate change, and an efficient use of natural resources. However, there are obstacles to be overcome. Mechanistic assessment of the ecological, environmental, and socio-economic consequences of adopting these strategies at large scale are urgently needed to fully assess the potential of grasslands to provide food, energy and environmental security

A Clinical Trial to Validate Event-Related Potential Markers of Alzheimer\u27s Disease in Outpatient Settings

INTRODUCTION: We investigated whether event-related potentials (ERP) collected in outpatient settings and analyzed with standardized methods can provide a sensitive and reliable measure of the cognitive deficits associated with early Alzheimer\u27s disease (AD). METHODS: A total of 103 subjects with probable mild AD and 101 healthy controls were recruited at seven clinical study sites. Subjects were tested using an auditory oddball ERP paradigm. RESULTS: Subjects with mild AD showed lower amplitude and increased latency for ERP features associated with attention, working memory, and executive function. These subjects also had decreased accuracy and longer reaction time in the target detection task associated with the ERP test. DISCUSSION: Analysis of ERP data showed significant changes in subjects with mild AD that are consistent with the cognitive deficits found in this population. The use of an integrated hardware/software system for data acquisition and automated data analysis methods make administration of ERP tests practical in outpatient settings

Substantial carbon loss respired from a corn-soybean agroecosystem highlights the importance of careful management as we adapt to changing climate

Understanding agroecosystem carbon (C) cycle response to climate change and management is vital for maintaining their long-term C storage. We demonstrate this importance through an in-depth examination of a ten-year eddy covariance dataset from a corn-corn-soybean crop rotation grown in the Midwest United States. Ten-year average annual net ecosystem exchange (NEE) showed a net C sink of -0.39 Mg C ha-1 yr-1. However, NEE in 2014 and 2015 from the corn ecosystem was 3.58 and 2.56 Mg C ha-1 yr-1, respectively. Most C loss occurred during the growing season, when photosynthesis should dominate and C fluxes should reflect a net ecosystem gain. Partitioning NEE into gross primary productivity (GPP) and ecosystem respiration (ER) showed this C \u27burp\u27 was driven by higher ER, with a 51% (2014) and 57% (2015) increase from the ten-year average (15.84 Mg C ha-1 yr-1). GPP was also higher than average (16.24 Mg C ha-1 yr-1) by 25% (2014) and 37% (2015), but this was not enough to offset the C emitted from ER. This increased ER was likely driven by enhanced soil microbial respiration associated with ideal growing season climate, substrate availability, nutrient additions, and a potential legacy effect from drought

Full Connectivity: Corners, edges and faces

We develop a cluster expansion for the probability of full connectivity of high density random networks in confined geometries. In contrast to percolation phenomena at lower densities, boundary effects, which have previously been largely neglected, are not only relevant but dominant. We derive general analytical formulas that show a persistence of universality in a different form to percolation theory, and provide numerical confirmation. We also demonstrate the simplicity of our approach in three simple but instructive examples and discuss the practical benefits of its application to different models.Comment: 28 pages, 8 figure

On the strength of the finite intersection principle

We study the logical content of several maximality principles related to the finite intersection principle (F\IP) in set theory. Classically, these are all equivalent to the axiom of choice, but in the context of reverse mathematics their strengths vary: some are equivalent to \ACA over \RCA, while others are strictly weaker, and incomparable with \WKL. We show that there is a computable instance of F\IP all of whose solutions have hyperimmune degree, and that every computable instance has a solution in every nonzero c.e.\ degree. In terms of other weak principles previously studied in the literature, the former result translates to F\IP implying the omitting partial types principle ($\mathsf{OPT}$). We also show that, modulo $\Sigma^0_2$ induction, F\IP lies strictly below the atomic model theorem ($\mathsf{AMT}$).Comment: This paper corresponds to section 3 of arXiv:1009.3242, "Reverse mathematics and equivalents of the axiom of choice", which has been abbreviated and divided into two pieces for publicatio

Nodal dynamics, not degree distributions, determine the structural controllability of complex networks

Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set (PDS), is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.Comment: 1 Figures, 6 page

Drug capture materials based on genomic DNA-functionalized magnetic nanoparticles

Chemotherapy agents are notorious for producing severe side-effects. One approach to mitigating this off-target damage is to deliver the chemotherapy directly to a tumor via transarterial infusion, or similar procedures, and then sequestering any chemotherapeutic in the veins draining the target organ before it enters the systemic circulation. Materials capable of such drug capture are yet to be fully realized. Here, we report the covalent attachment of genomic DNA to iron-oxide nanoparticles. With these magnetic materials, we captured three common chemotherapy agents—doxorubicin, cisplatin, and epirubicin—from biological solutions. We achieved 98% capture of doxorubicin from human serum in 10 min. We further demonstrate that DNA-coated particles can rescue cultured cardiac myoblasts from lethal levels of doxorubicin. Finally, the in vivo efficacy of these materials was demonstrated in a porcine model. The efficacy of these materials demonstrates the viability of genomic DNA-coated materials as substrates for drug capture applications

Inversão sísmica bayesiana com modelagem a priori integrada com física de rocha

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas, Programa de Pós-Graduação em Física, Florianópolis, 2017.A inversão sísmica conjunta para as propriedades elásticas e petrofísicas é um problema inverso com solução não única. Existem vários fatores que afetam a precisão dos resultados como a relação estatística de física de rocha, os erros dos dados experimentais e de modelagem. Apresentamos uma metodologia para incorporar um modelo linearizado de física de rocha em uma distribuição Gaussiana multivariada. A proposta é usada para definir um modelo de mistura Gaussiana para a distribuiçãoconjunta a priori das propriedades elásticas e petrofísicas, no qual cada componente é interpretada como uma litofácies. Este processo permite introduzir uma correlação teórica entre as propriedades, com interpretação geológica específica dos parâmetros da física de rocha para cada fácies. Com base nesta modelagem a priori e no modelo convolucional, obtemos analiticamente as distribuições condicionais da amostragem de Gibbs. Em seguida, combinamos o algoritmo de amostragem com métodos de simulação geoestatística para obter a distribuição a posteriori de Bayes. Aplicamos a proposta em um conjunto de dados sísmicos reais, com três poços, para obter múltiplas realizações geoestatísticas tridimensionais das propriedades e das litofácies. A proposta é validada através de testes de poço cego e comparações com a inversão Bayesiana tradicional. Usando a probabilidade das litofácies, também calculamos a isosuperfície de probabilidade do reservatório de óleo principal do campo estudado. Além da proposta de inversão sísmica conjunta, apresentamos também uma formulação revisitada para o método de simulação geoestatística FFT-Moving Average. Nessa formulação, o filtro de correlação é derivado através de apenas um único ruído aleatório, o que permite a aplicação do método sem qualquer suposição sobre as características do ruído.Abstract : Joint seismic inversion for elastic and petrophysical properties is an inverse problem with a nonunique solution. There are several factors that affect the accuracy of the results such as the statistical rock-physics relation and observation errors. We present a general methodology to incorporate a linearized rock-physics model into a multivariate Gaussian distribution. The proposal is used to define a Gaussian mixture model for the joint prior distribution of the elastic and petrophysical properties, in which each component is interpreted as a lithofacies. This process allows to introduce a theoretical correlation between the properties with specific geological interpretation for the rock physicsparameters of each facies. Based on the prior model and on the convolutional model, we analytically obtain the conditional distributions of the Gibbs sampling. Then, we combine the sampling algorithm with geostatistical simulation methods to calculate the Bayesian posterior distribution. We applied the proposal to a real seismic data set with three wells to obtain multiple three-dimensional geostatistical simulations of the properties and the lithofacies. The proposal is validated through a blind well test and a comparison with the traditional Bayesian inversion. Using the probability of the reservoir lithofacies, we also calculated a 3D isosurface probability model of the main oil reservoir in the studied field