Respiratory Membrane endo-Hydrogenase Activity in the Microaerophile Azorhizobium caulinodans Is Bidirectional

BACKGROUND: The microaerophilic bacterium Azorhizobium caulinodans, when fixing N(2) both in pure cultures held at 20 µM dissolved O(2) tension and as endosymbiont of Sesbania rostrata legume nodules, employs a novel, respiratory-membrane endo-hydrogenase to oxidize and recycle endogenous H(2) produced by soluble Mo-dinitrogenase activity at the expense of O(2). METHODS AND FINDINGS: From a bioinformatic analysis, this endo-hydrogenase is a core (6 subunit) version of (14 subunit) NADH:ubiquinone oxidoreductase (respiratory complex I). In pure A. caulinodans liquid cultures, when O(2) levels are lowered to <1 µM dissolved O(2) tension (true microaerobic physiology), in vivo endo-hydrogenase activity reverses and continuously evolves H(2) at high rates. In essence, H(+) ions then supplement scarce O(2) as respiratory-membrane electron acceptor. Paradoxically, from thermodynamic considerations, such hydrogenic respiratory-membrane electron transfer need largely uncouple oxidative phosphorylation, required for growth of non-phototrophic aerobic bacteria, A. caulinodans included. CONCLUSIONS: A. caulinodans in vivo endo-hydrogenase catalytic activity is bidirectional. To our knowledge, this study is the first demonstration of hydrogenic respiratory-membrane electron transfer among aerobic (non-fermentative) bacteria. When compared with O(2) tolerant hydrogenases in other organisms, A. caulinodans in vivo endo-hydrogenase mediated H(2) production rates (50,000 pmol 10(9)·cells(-1) min(-1)) are at least one-thousandfold higher. Conceivably, A. caulinodans respiratory-membrane hydrogenesis might initiate H(2) crossfeeding among spatially organized bacterial populations whose individual cells adopt distinct metabolic states in response to variant O(2) availability. Such organized, physiologically heterogeneous cell populations might benefit from augmented energy transduction and growth rates of the populations, considered as a whole

The molecular genetic analysis of the expanding pachyonychia congenita case collection

BACKGROUND: Pachyonychia congenita (PC) is a rare autosomal dominant keratinizing disorder characterized by severe, painful, palmoplantar keratoderma and nail dystrophy, often accompanied by oral leucokeratosis, cysts and follicular keratosis. It is caused by mutations in one of five keratin genes: KRT6A, KRT6B, KRT6C, KRT16 or KRT17. OBJECTIVES: To identify mutations in 84 new families with a clinical diagnosis of PC, recruited by the International Pachyonychia Congenita Research Registry during the last few years. METHODS: Genomic DNA isolated from saliva or peripheral blood leucocytes was amplified using primers specific for the PC-associated keratin genes and polymerase chain reaction products were directly sequenced. RESULTS: Mutations were identified in 84 families in the PC-associated keratin genes, comprising 46 distinct keratin mutations. Fourteen were previously unreported mutations, bringing the total number of different keratin mutations associated with PC to 105. CONCLUSIONS: By identifying mutations in KRT6A, KRT6B, KRT6C, KRT16 or KRT17, this study has confirmed, at the molecular level, the clinical diagnosis of PC in these families

Pachyonychia congenita cornered: report on the 11th A nnual I nternational P achyonychia C ongenita C onsortium Meeting

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109650/1/bjd13341.pd

Probabilistic Robot Localization using Visual Landmarks

Effective robot navigation and route planning is impossible unless the position of the robot within its environment is known. Motion sensors that track the relative movement of a robot are inherently unreliable, so it is necessary to use cues from the external environment to periodically localize the robot. There are many methods for accomplishing this, most of which either probabilistically estimate the robot\u27s movement based on range sensors, or require having enough unique visual landmarks present to geometrically calculate the robot\u27s position at any time. In this project I examined the feasibility of using the probabilistic Monte Carlo localization algorithm to estimate a robot\u27s location based off of occasional visual landmark cues. Using visual landmarks has several advantages over using range sensor data in that landmark readings are less affected by unexpected objects and can be used for fast global localization. To test this system I designed a robot capable of navigating Olin-Rice by observing pieces of colored paper placed at regular intervals along the halls as an extension of my summer 2005 research on RUPART. The localization system could not localize the robot in many situations due to the sparse nature of the landmarks, but results suggest that with minor modifications the system could become a reliable localization scheme

Scarcity-weighted global land and metal footprints

Resource scarcity poses an increasing threat to the supply security of modern economies. Some grand challenges ahead are the limits to agricultural expansion and the geologic scarcity of metals. To better understand the drivers behind land and metal depletion, footprint-type indicators are gaining importance. Such indicators, however, fail to differentiate between vastly different degrees of resource availability across regions. Using crop suitability areas and metal reserve base data, we calculate scarcity-weighted land and metal footprints for the major economies with the EXIOBASE global multi-regional input-output model. Scarcity-weighting causes a significant reordering of the global rankings of countries for both land and metal footprints. Land scarcity focuses mostly on cereals (∼54% from the total agricultural land used) and oil crops (∼15%), the former being notably affected by water scarcity issues in Asia and the Middle East. Metal scarcity focuses on copper ores (∼69%) and iron (∼11%), the former being a globally scarce metal impacting multiple economies. The large impact of scarcity-weighting suggests that, while non-weighted resource footprints are a valid proxy of resource use, these are not always aligned with further implications of resource depletion and supply security. In this sense, scarcity-weighting can offer an initial overview of those countries where analyses at finer scales may be more valuable. Our results also show that international trade is a major driver of land and metal depletion in some developing regions. This highlights the intersection of environmental justice and globalization, as the burden of resource depletion often falls into poorer regions which critically rely on exports

Compassion motivations: Distinguishing submissive compassion from genuine compassion and its association with shame, submissive behavior, depression, anxiety and stress

Abstract Recent research has suggested that being compassionate and helpful to others is linked to well-being. However, people can pursue compassionate motives for different reasons, one of which may be to be liked or valued. Evolutionary theory suggests this form of helping may be related to submissive appeasing behavior and therefore could be negatively associated with well-being. To explore this possibility we developed a new scale called the submissive compassion scale and compared it to other established submissive and shame-based scales, along with measures of depression, anxiety and stress in a group of 192 students. As predicted, a submissive form of compassion (being caring in order to be liked) was associated with submissive behavior, shame-based caring, ego-goals and depression, anxiety, and stress. In contrast, compassionate goals and compassion for others were not. As research on compassion develops, new ways of understanding the complex and mixed motivations that can lie behind compassion are required. The desire to be helpful, kind, and compassionate, when it arises from fears of rejection and desires for acceptance, needs to be explored.N/

Transitioning to low-carbon residential heating: the impacts of material-related emissions

To achieve climate neutrality, future urban heating systems will need to use a variety of low-carbon heating technologies. The transition toward low-carbon heating technologies necessitates a complete restructuring of the heating system, with significant associated material requirements. However, little research has been done into the quantity and environmental impact of the required materials for this system change. We analyzed the material demand and the environmental impact of the transition toward low-carbon heating in the Netherlands across three scenarios based on the local availability and capacity for sources of low-carbon heat. A wide range of materials are included, covering aggregates, construction materials, metals, plastics, and critical materials. We find that while the Dutch policy goal of reducing GHG emissions by 90% before 2050 can be achieved if only direct emissions from the heating system are considered, this is no longer the case when the cradle-to-gate emissions from the additional materials, especially insulation materials, are taken into account. The implementation of these technologies will require 59–63 megatons of materials in the period of 2021–2050, leading to a maximum reduction of 62%.Industrial Ecolog