Reliability-based optimization design of geosynthetic reinforced embankment slopes

This study examines the optimization design of geosynthetic reinforced embankment slopes (GRES) considering both economic benefits and technical safety requirements. In engineering design, cost is always a big concern. To minimize the cost, engineers tend to seek an optimal combination of design parameters among the considered alternatives while ensuring the optimal solution is safe. Reliability-based optimization (RBO) is such a technique that provides engineers the optimal design with the minimum cost while all technical design requirements are satisfied. The research goal of this study is to implement a mathematical formulation algorithm of the RBO technique in GRES design. To achieve this goal, slope stability is studied using the limit equilibrium method (LEM). Considering geotechnical uncertainties, the first-order reliability method (FORM) is adopted to perform probabilistic slope stability analysis, address the critical slip surfaces, and assess the reliability of the slope system. The slope stability and reliability are then used as the crucial constraints in the following RBO procedure, wherein the constrained optimization problem will be solved by adopting a genetic algorithm (GA). Sensitivity analysis is carried out on the basis of the probabilistic slope stability analysis to highlight the influence of each involved random variable on the probabilistic performance of the slope system; and thereby, infer the corresponding impact on the optimization design. A framework of how to implement the RBO in GRES design is proposed. An engineering case history is accordingly studied to demonstrate the practical application of the proposed design framework. Compared to the conventional (manual) process, the proposed design framework is more systematic and effective, especially with the large number of design variables involved in geosynthetic reinforced slopes. --Abstract, page iii

Carbon in Red Giants in Globular Clusters and Dwarf Spheroidal Galaxies

We present carbon abundances of red giants in Milky Way globular clusters and dwarf spheroidal galaxies (dSphs). Our sample includes measurements of carbon abundances for 154 giants in the clusters NGC 2419, M68, and M15 and 398 giants in the dSphs Sculptor, Fornax, Ursa Minor, and Draco. This sample doubles the number of dSph stars with measurements of [C/Fe]. The [C/Fe] ratio in the clusters decreases with increasing luminosity above log(L/L_sun) ~= 1.6, which can be explained by deep mixing in evolved giants. The same decrease is observed in dSphs, but the initial [C/Fe] of the dSph giants is not uniform. Stars in dSphs at lower metallicities have larger [C/Fe] ratios. We hypothesize that [C/Fe] (corrected to the initial carbon abundance) declines with increasing [Fe/H] due to the metallicity dependence of the carbon yield of asymptotic giant branch stars and due to the increasing importance of Type Ia supernovae at higher metallicities. We also identified 11 very carbon-rich giants (8 previously known) in three dSphs. However, our selection biases preclude a detailed comparison to the carbon-enhanced fraction of the Milky Way stellar halo. Nonetheless, the stars with [C/Fe] < +1 in dSphs follow a different [C/Fe] track with [Fe/H] than the halo stars. Specifically, [C/Fe] in dSphs begins to decline at lower [Fe/H] than in the halo. The difference in the metallicity of the [C/Fe] "knee" adds to the evidence from [alpha/Fe] distributions that the progenitors of the halo had a shorter timescale for chemical enrichment than the surviving dSphs.Comment: accepted to ApJ; 20 pages, 11 figures, 2 machine-readable table

A Bayesian Translational Framework for Knowledge Propagation, Discovery, and Integration Under Specific Contexts

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts—rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well

Promoting synergistic research and education in genomics and bioinformatics

Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology

CD81 and claudin 1 coreceptor association: role in hepatitis C virus entry.

Hepatitis C virus (HCV) is an enveloped positive-stranded RNA hepatotropic virus. HCV pseudoparticles infect liver-derived cells, supporting a model in which liver-specific molecules define HCV internalization. Three host cell molecules have been reported to be important entry factors or receptors for HCV internalization: scavenger receptor BI, the tetraspanin CD81, and the tight junction protein claudin-1 (CLDN1). None of the receptors are uniquely expressed within the liver, leading us to hypothesize that their organization within hepatocytes may explain receptor activity. Since CD81 and CLDN1 act as coreceptors during late stages in the entry process, we investigated their association in a variety of cell lines and human liver tissue. Imaging techniques that take advantage of fluorescence resonance energy transfer (FRET) to study protein-protein interactions have been developed. Aequorea coerulescens green fluorescent protein- and Discosoma sp. red-monomer fluorescent protein-tagged forms of CD81 and CLDN1 colocalized, and FRET occurred between the tagged coreceptors at comparable frequencies in permissive and nonpermissive cells, consistent with the formation of coreceptor complexes. FRET occurred between antibodies specific for CD81 and CLDN1 bound to human liver tissue, suggesting the presence of coreceptor complexes in liver tissue. HCV infection and treatment of Huh-7.5 cells with recombinant HCV E1-E2 glycoproteins and anti-CD81 monoclonal antibody modulated homotypic (CD81-CD81) and heterotypic (CD81-CLDN1) coreceptor protein association(s) at specific cellular locations, suggesting distinct roles in the viral entry process

Synthesis and patterning of tunable multiscale materials with engineered cells

Many natural biological systems - such as biofilms, shells and skeletal tissues - are able to assemble multifunctional and environmentally responsive multiscale assemblies of living and non-living components. Here, by using inducible genetic circuits and cellular communication circuits to regulate Escherichia coli curli amyloid production, we show that E. coli cells can organize self-assembling amyloid fibrils across multiple length scales, producing amyloid-based materials that are either externally controllable or undergo autonomous patterning. We also interfaced curli fibrils with inorganic materials, such as gold nanoparticles (AuNPs) and quantum dots (QDs), and used these capabilities to create an environmentally responsive biofilm-based electrical switch, produce gold nanowires and nanorods, co-localize AuNPs with CdTe/CdS QDs to modulate QD fluorescence lifetimes, and nucleate the formation of fluorescent ZnS QDs. This work lays a foundation for synthesizing, patterning, and controlling functional composite materials with engineered cells

Molecular interaction and evolution of jasmonate signaling with transport and detoxification of heavy metals and metalloids in plants

An increase in environmental pollution resulting from toxic heavy metals and metalloids [e.g., cadmium (Cd), arsenic (As), and lead (Pb)] causes serious health risks to humans and animals. Mitigation strategies need to be developed to reduce the accumulation of the toxic elements in plant-derived foods. Natural and genetically-engineered plants with hyper-tolerant and hyper-accumulating capacity of toxic minerals are valuable for phytoremediation. However, the molecular mechanisms of detoxification and accumulation in plants have only been demonstrated in very few plant species such as Arabidopsis and rice. Here, we review the physiological and molecular aspects of jasmonic acid and the jasmonate derivatives (JAs) in response to toxic heavy metals and metalloids. Jasmonates have been identified in, limiting the accumulation and enhancing the tolerance to the toxic elements, by coordinating the ion transport system, the activity of antioxidant enzymes, and the chelating capacity in plants. We also propose the potential involvement of Ca2+ signaling in the stress-induced production of jasmonates. Comparative transcriptomics analyses using the public datasets reveal the key gene families involved in the JA-responsive routes. Furthermore, we show that JAs may function as a fundamental phytohormone that protects plants from heavy metals and metalloids as demonstrated by the evolutionary conservation and diversity of these gene families in a large number of species of the major green plant lineages. Using ATP-Binding Cassette G (ABCG) transporter subfamily of six representative green plant species, we propose that JA transporters in Subgroup 4 of ABCGs may also have roles in heavy metal detoxification. Our paper may provide guidance toward the selection and development of suitable plant and crop species that are tolerant to toxic heavy metals and metalloids

Frontal-Subcortical Protein Expression following Prenatal Exposure to Maternal Inflammation

BACKGROUND: Maternal immune activation (MIA) during prenatal life is a risk factor for neurodevelopmental disorders including schizophrenia and autism. Such conditions are associated with alterations in fronto-subcortical circuits, but their molecular basis is far from clear. METHODOLOGY/PRINCIPAL FINDINGS: Using two-dimensional differential in-gel electrophoresis (2D-DIGE) and mass spectrometry, with targeted western blot analyses for confirmation, we investigated the impact of MIA on the prefrontal and striatal proteome from an established MIA mouse model generated in C57B6 mice, by administering the viral analogue PolyI:C or saline vehicle (control) intravenously on gestation day (GD) 9. In striatum, 11 proteins were up-regulated and 4 proteins were down-regulated in the PolyI:C mice, while 10 proteins were up-regulated and 7 proteins down-regulated in prefrontal cortex (PFC). These were proteins involved in the mitogen-activated protein kinase (MAPK) signaling pathway, oxidation and auto-immune targets, including dual specificity mitogen-activated protein kinase kinase 1 (MEK), eukaryotic initiation factor (eIF) 4A-II, creatine kinase (CK)-B, L-lactate dehydrogenase (LDH)-B, WD repeat-containing protein and NADH dehydrogenase in the striatum; and guanine nucleotide-binding protein (G-protein), 14-3-3 protein, alpha-enolase, olfactory maker protein and heat shock proteins (HSP) 60, and 90-beta in the PFC. CONCLUSIONS/SIGNIFICANCE: This data fits with emerging evidence for disruption of critical converging intracellular pathways involving MAPK pathways in neurodevelopmental conditions and it shows considerable overlap with protein pathways identified by genetic modeling and clinical post-mortem studies. This has implications for understanding causality and may offer potential biomarkers and novel treatment targets for neurodevelopmental conditions

Generation of Human Striatal Neurons by MicroRNA-Dependent Direct Conversion of Fibroblasts

SummaryThe promise of using reprogrammed human neurons for disease modeling and regenerative medicine relies on the ability to induce patient-derived neurons with high efficiency and subtype specificity. We have previously shown that ectopic expression of brain-enriched microRNAs (miRNAs), miR-9/9∗ and miR-124 (miR-9/9∗-124), promoted direct conversion of human fibroblasts into neurons. Here we show that coexpression of miR-9/9∗-124 with transcription factors enriched in the developing striatum, BCL11B (also known as CTIP2), DLX1, DLX2, and MYT1L, can guide the conversion of human postnatal and adult fibroblasts into an enriched population of neurons analogous to striatal medium spiny neurons (MSNs). When transplanted in the mouse brain, the reprogrammed human cells persisted in situ for over 6 months, exhibited membrane properties equivalent to native MSNs, and extended projections to the anatomical targets of MSNs. These findings highlight the potential of exploiting the synergism between miR-9/9∗-124 and transcription factors to generate specific neuronal subtypes