Semiconductor catalysis: simultaneous measurement of kinetics and surface electrical properties

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1964.Includes bibliographical references (leaves 144-147).by Robert P. Merrill.Sc.D

Asteroid Redirect Mission Concept: A Bold Approach for Utilizing Space Resources

The utilization of natural resources from asteroids is an idea that is older than the Space Age. The technologies are now available to transform this endeavour from an idea into reality. The Asteroid Redirect Mission (ARM) is a mission concept which includes the goal of robotically returning a small Near-Earth Asteroid (NEA) or a multi-ton boulder from a large NEA to cislunar space in the mid 2020's using an advanced Solar Electric Propulsion (SEP) vehicle and currently available technologies. The paradigm shift enabled by the ARM concept would allow in-situ resource utilization (ISRU) to be used at the human mission departure location (i.e., cislunar space) versus exclusively at the deep-space mission destination. This approach drastically reduces the barriers associated with utilizing ISRU for human deep-space missions. The successful testing of ISRU techniques and associated equipment could enable large-scale commercial ISRU operations to become a reality and enable a future space-based economy utilizing processed asteroidal materials. This paper provides an overview of the ARM concept and discusses the mission objectives, key technologies, and capabilities associated with the mission, as well as how the ARM and associated operations would benefit humanity's quest for the exploration and settlement of space

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Extraordinary Late-Time Infrared Emission of Type IIn Supernovae

Near-Infrared (NIR) observations are presented for five Type IIn supernovae (SN 1995N, SN 1997ab, SN 1998S, SN 1999Z, and SN 1999el) that exhibit strong infrared excesses at late times (t >= 100 d). H- and K-band emission from these objects is dominated by a continuum that rises toward longer wavelengths. The data are interpreted as thermal emission from dust, probably situated in a pre-existing circumstellar nebula. The IR luminosities implied by single temperature blackbody fits are quite large,> 10^(41 - 42) erg s^-1, and the emission evolves slowly, lasting for years after maximum light. For SN 1995N, the integrated energy release via IR dust emission was 0.5 -- 1 * 10^50 erg. A number of dust heating scenarios are considered, the most likely being an infrared echo poweredby X-ray and UV emissions from the shock interaction with a dense circumstellar medium.Comment: 14 Pages, 3 Figures, Accecpted for publication in The Astrophysical Journa

Inhibitory Role of Notch1 in Calcific Aortic Valve Disease

Aortic valve calcification is the most common form of valvular heart disease, but the mechanisms of calcific aortic valve disease (CAVD) are unknown. NOTCH1 mutations are associated with aortic valve malformations and adult-onset calcification in families with inherited disease. The Notch signaling pathway is critical for multiple cell differentiation processes, but its role in the development of CAVD is not well understood. The aim of this study was to investigate the molecular changes that occur with inhibition of Notch signaling in the aortic valve. Notch signaling pathway members are expressed in adult aortic valve cusps, and examination of diseased human aortic valves revealed decreased expression of NOTCH1 in areas of calcium deposition. To identify downstream mediators of Notch1, we examined gene expression changes that occur with chemical inhibition of Notch signaling in rat aortic valve interstitial cells (AVICs). We found significant downregulation of Sox9 along with several cartilage-specific genes that were direct targets of the transcription factor, Sox9. Loss of Sox9 expression has been published to be associated with aortic valve calcification. Utilizing an in vitro porcine aortic valve calcification model system, inhibition of Notch activity resulted in accelerated calcification while stimulation of Notch signaling attenuated the calcific process. Finally, the addition of Sox9 was able to prevent the calcification of porcine AVICs that occurs with Notch inhibition. In conclusion, loss of Notch signaling contributes to aortic valve calcification via a Sox9-dependent mechanism

Adding a Little Reality to Building Ontologies for Biology

BACKGROUND: Many areas of biology are open to mathematical and computational modelling. The application of discrete, logical formalisms defines the field of biomedical ontologies. Ontologies have been put to many uses in bioinformatics. The most widespread is for description of entities about which data have been collected, allowing integration and analysis across multiple resources. There are now over 60 ontologies in active use, increasingly developed as large, international collaborations. There are, however, many opinions on how ontologies should be authored; that is, what is appropriate for representation. Recently, a common opinion has been the "realist" approach that places restrictions upon the style of modelling considered to be appropriate. METHODOLOGY/PRINCIPAL FINDINGS: Here, we use a number of case studies for describing the results of biological experiments. We investigate the ways in which these could be represented using both realist and non-realist approaches; we consider the limitations and advantages of each of these models. CONCLUSIONS/SIGNIFICANCE: From our analysis, we conclude that while realist principles may enable straight-forward modelling for some topics, there are crucial aspects of science and the phenomena it studies that do not fit into this approach; realism appears to be over-simplistic which, perversely, results in overly complex ontological models. We suggest that it is impossible to avoid compromise in modelling ontology; a clearer understanding of these compromises will better enable appropriate modelling, fulfilling the many needs for discrete mathematical models within computational biology

Trans-Ancestral Studies Fine Map the SLE-Susceptibility Locus TNFSF4

We previously established an 80 kb haplotype upstream of TNFSF4 as a susceptibility locus in the autoimmune disease SLE. SLE-associated alleles at this locus are associated with inflammatory disorders, including atherosclerosis and ischaemic stroke. In Europeans, the TNFSF4 causal variants have remained elusive due to strong linkage disequilibrium exhibited by alleles spanning the region. Using a trans-ancestral approach to fine-map the locus, utilising 17,900 SLE and control subjects including Amerindian/Hispanics (1348 cases, 717 controls), African-Americans (AA) (1529, 2048) and better powered cohorts of Europeans and East Asians, we find strong association of risk alleles in all ethnicities; the AA association replicates in African-American Gullah (152,122). The best evidence of association comes from two adjacent markers: rs2205960-T (P = 1.71×10-34, OR = 1.43[1.26-1.60]) and rs1234317-T (P = 1.16×10-28, OR = 1.38[1.24-1.54]). Inference of fine-scale recombination rates for all populations tested finds the 80 kb risk and non-risk haplotypes in all except African-Americans. In this population the decay of recombination equates to an 11 kb risk haplotype, anchored in the 5′ region proximal to TNFSF4 and tagged by rs2205960-T after 1000 Genomes phase 1 (v3) imputation. Conditional regression analyses delineate the 5′ risk signal to rs2205960-T and the independent non-risk signal to rs1234314-C. Our case-only and SLE-control cohorts demonstrate robust association of rs2205960-T with autoantibody production. The rs2205960-T is predicted to form part of a decameric motif which binds NF-κBp65 with increased affinity compared to rs2205960-G. ChIP-seq data also indicate NF-κB interaction with the DNA sequence at this position in LCL cells. Our research suggests association of rs2205960-T with SLE across multiple groups and an independent non-risk signal at rs1234314-C. rs2205960-T is associated with autoantibody production and lymphopenia. Our data confirm a global signal at TNFSF4 and a role for the expressed product at multiple stages of lymphocyte dysregulation during SLE pathogenesis. We confirm the validity of trans-ancestral mapping in a complex trait. © 2013 Manku et al

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions.

BACKGROUND: The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models. FINDINGS: We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described. CONCLUSIONS: RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are