Formulations for Stronger Solid Oxide Fuel-Cell Electrolytes

Tests have shown that modification of chemical compositions can increase the strengths and fracture toughnesses of solid oxide fuel-cell (SOFC) electrolytes. Heretofore, these solid electrolytes have been made of yttria-stabilized zirconia, which is highly conductive for oxygen ions at high temperatures, as needed for operation of fuel cells. Unfortunately yttria-stabilized zirconia has a high coefficient of thermal expansion, low resistance to thermal shock, low fracture toughness, and low mechanical strength. The lack of strength and toughness are especially problematic for fabrication of thin SOFC electrolyte membranes needed for contemplated aeronautical, automotive, and stationary power-generation applications. The modifications of chemical composition that lead to increased strength and fracture toughness consist in addition of alumina to the basic yttria-stabilized zirconia formulations. Techniques for processing of yttria-stabilized zirconia/alumina composites containing as much as 30 mole percent of alumina have been developed. The composite panels fabricated by these techniques have been found to be dense and free of cracks. The only material phases detected in these composites has been cubic zirconia and a alumina: this finding signifies that no undesired chemical reactions between the constituents occurred during processing at elevated temperatures. The flexural strengths and fracture toughnesses of the various zirconia-alumina composites were measured in air at room temperature as well as at a temperature of 1,000 C (a typical SOFC operating temperature). The measurements showed that both flexural strength and fracture toughness increased with increasing alumina content at both temperatures. In addition, the modulus of elasticity and the thermal conductivity were found to increase and the density to decrease with increasing alumina content. The oxygen-ion conductivity at 1,000 C was found to be unchanged by the addition of alumina

Non-invasive analysis of intestinal development in preterm and term infants using RNA-Sequencing

The state and development of the intestinal epithelium is vital for infant health, and increased understanding in this area has been limited by an inability to directly assess epithelial cell biology in the healthy newborn intestine. To that end, we have developed a novel, noninvasive, molecular approach that utilizes next generation RNA sequencing on stool samples containing intact epithelial cells for the purpose of quantifying intestinal gene expression. We then applied this technique to compare host gene expression in healthy term and extremely preterm infants. Bioinformatic analyses demonstrate repeatable detection of human mRNA expression, and network analysis shows immune cell function and inflammation pathways to be up-regulated in preterm infants. This study provides incontrovertible evidence that whole-genome sequencing of stool-derived RNA can be used to examine the neonatal host epithelial transcriptome in infants, which opens up opportunities for sequential monitoring of gut gene expression in response to dietary or therapeutic interventions

Analysis for Science Librarians of the 2018 Nobel Prize in Physiology or Medicine: The Life and Work of James P. Allison and Tasuku Honjo

On October 1, 2018, James P. Allison and Tasuku Honjo were awarded the 2018 Physiology or Medicine Nobel for their work leading to Immune Checkpoint Inhibition (ICI). ICI is the fourth pillar of cancer treatment and has been used to treat previously un-treatable cancers. Allison discovered that the protein CTLA-4 acts as a T cell brake while Honjo discovered another T cell brake, PD-1. Releasing these brakes allows the immune system to attack tumors, sometimes leading to complete elimination. While there is still more research to be done, Allison’s and Honjo’s work is a breakthrough in cancer immunotherapy

Relationship Between Non-Hodgkin's Lymphoma and Blood Levels of Epstein-Barr Virus in Children in North-Western Tanzania: A Case Control Study.

Non-Hodgkin's Lymphomas (NHL) are common in African children, with endemic Burkitt's lymphoma (BL) being the most common subtype. While the role of Epstein-Barr Virus (EBV) in endemic BL is known, no data are available about clinical presentations of NHL subtypes and their relationship to Human Immunodeficiency Virus (HIV) infection and Epstein Barr Virus (EBV) load in peripheral blood of children in north-western, Tanzania. A matched case control study of NHL subtypes was performed in children under 15 years of age and their respective controls admitted to Bugando Medical Centre, Sengerema and Shirati district designated hospitals in north-western, Tanzania, between September 2010 and April 2011. Peripheral blood samples were collected on Whatman 903 filter papers and EBV DNA levels were estimated by multiplex real-time PCR. Clinical and laboratory data were collected using a structured data collection tool and analysed using chi-square, Fisher and Wilcoxon rank sum tests where appropriate. The association between NHL and detection of EBV in peripheral blood was assessed using conditional logistic regression model and presented as odds ratios (OR) and 95% confidence intervals (CI). A total of 35 NHL cases and 70 controls matched for age and sex were enrolled. Of NHLs, 32 had BL with equal distribution between jaw and abdominal tumour, 2 had large B cell lymphoma (DLBCL) and 1 had NHL-not otherwise specified (NHL-NOS). Central nervous system (CNS) presentation occurred only in 1 BL patient; 19 NHLs had stage I and II of disease. Only 1 NHL was found to be HIV-seropositive. Twenty-one of 35 (60%) NHL and 21 of 70 (30%) controls had detectable EBV in peripheral blood (OR = 4.77, 95% CI 1.71 - 13.33, p = 0.003). In addition, levels of EBV in blood were significantly higher in NHL cases than in controls (p = 0.024). BL is the most common childhood NHL subtype in north-western Tanzania. NHLs are not associated with HIV infection, but are strongly associated with EBV load in peripheral blood. The findings suggest that high levels of EBV in blood might have diagnostic and prognostic relevance in African children

Drug treatment of malaria infections can reduce levels of protection transferred to offspring via maternal immunity

Maternally transferred immunity can have a fundamental effect on the ability of offspring to deal with infection. However, levels of antibodies in adults can vary both quantitatively and qualitatively between individuals and during the course of infection. How infection dynamics and their modification by drug treatment might affect the protection transferred to offspring remains poorly understood. Using the rodent malaria parasite Plasmodium chabaudi, we demonstrate that curing dams part way through infection prior to pregnancy can alter their immune response, with major consequences for offspring health and survival. In untreated maternal infections, maternally transferred protection suppressed parasitaemia and reduced pup mortality by 75 per cent compared with pups from naïve dams. However, when dams were treated with anti-malarial drugs, pups received fewer maternal antibodies, parasitaemia was only marginally suppressed, and mortality risk was 25 per cent higher than for pups from dams with full infections. We observed the same qualitative patterns across three different host strains and two parasite genotypes. This study reveals the role that within-host infection dynamics play in the fitness consequences of maternally transferred immunity. Furthermore, it highlights a potential trade-off between the health of mothers and offspring suggesting that anti-parasite treatment may significantly affect the outcome of infection in newborns

Hydrogen Macro System Model User Guide, Version 1.2.1

The Hydrogen Macro System Model (MSM) is a simulation tool that links existing and emerging hydrogen-related models to perform rapid, cross-cutting analysis. It allows analysis of the economics, primary energy-source requirements, and emissions of hydrogen production and delivery pathways

Mathematical approaches for complexity/predictivity trade-offs in complex system models : LDRD final report.

The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity

RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data

Artificial immune systems

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self or nonself substances. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years