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At least 415 records · Page 23

Acoustic and Genetic Data Can Reduce Uncertainty Regarding Populations of Migratory Tree-Roosting Bats Impacted by Wind Energy

Wind turbine-related mortality may pose a population-level threat for migratory tree-roosting bats, such as the hoary bat (Lasiurus cinereus) in North America. These species are dispersed within their range, making it impractical to estimate census populations size using traditional survey methods. Nonetheless, understanding population size and trends is essential for evaluating and mitigating risk from wind turbine mortality. Using various sampling techniques, including systematic acoustic sampling and genetic analyses, we argue that building a weight of evidence regarding bat population status and trends is possible to (1) assess the sustainability of mortality associated with wind turbines; (2) determine the level of mitigation required; and (3) evaluate the effectiveness of mitigation measures to ensure population viability for these species. Long-term, systematic data collection remains the most viable option for reducing uncertainty regarding population trends for migratory tree-roosting bats. We recommend collecting acoustic data using the statistically robust North American Bat Monitoring Program (NABat) protocols and that genetic diversity is monitored at repeated time intervals to show species trends. There are no short-term actions to resolve these population-level questions; however, we discuss opportunities for relatively short-term investments that will lead to long-term success in reducing uncertainty.

17 WIND ENERGY↗

Biomass Grinding Process Optimization Using Response Surface Methodology and a Hybrid Genetic Algorithm

Biomass could be a key source of renewable energy. Agricultural waste products, such as corn stover, provide a convenient means to replace fossil fuels, such as coal, and a large amount of feedstock is currently available for energy consumption in the U.S. This study has two main objectives: (1) to understand the impact of corn stover moisture content and grinder speed on grind physical properties; and (2) develop response surface models and optimize these models using a hybrid genetic algorithm. The response surface models developed were used to draw surface plots to understand the interaction effects of the corn stover grind moisture content and grinder speed on the grind physical properties and specific energy consumption. The surface plots indicated that a higher corn stover grind moisture content and grinder speed had a positive effect on the bulk and tapped density. The final grind moisture content was highly influenced by the initial moisture content of the corn stover grind. Optimization of the response surface models using the hybrid genetic algorithm indicated that moisture content in the range of 17 to 19% (w.b.) and a grinder speed of 47 to 49 Hz maximized the bulk and tapped density and minimized the geomantic mean particle length. The specific energy consumption was minimized when the grinder speed was about 20 Hz and the corn stover grind moisture content was about 10% (w.b.).

09 BIOMASS FUELS↗

Low-thrust orbit transfer optimization with refined Q-law and multi-objective genetic algorithm

An optimization method for low-thrust orbit transfers around a central body is developed using the Q-law and a multi-objective genetic algorithm. in the hybrid method, the Q-law generates candidate orbit transfers, and the multi-objective genetic algorithm optimizes the Q-law control parameters in order to simultaneously minimize both the consumed propellant mass and flight time of the orbit tranfer. This paper addresses the problem of finding optimal orbit transfers for low-thrust spacecraft.

low-thrust orbit transfer↗

Genetic Inventory Task Final Report

Contaminant terrestrial microbiota could profoundly impact the scientific integrity of extraterrestrial life-detection experiments. It is therefore important to know what organisms persist on spacecraft surfaces so that their presence can be eliminated or discriminated from authentic extraterrestrial biosignatures. Although there is a growing understanding of the biodiversity associated with spacecraft and cleanroom surfaces, it remains challenging to assess the risk of these microbes confounding life-detection or sample-return experiments. A key challenge is to provide a comprehensive inventory of microbes present on spacecraft surfaces. To assess the phylogenetic breadth of microorganisms on spacecraft and associated surfaces, the Genetic Inventory team used three technologies: conventional cloning techniques, PhyloChip DNA microarrays, and 454 tag-encoded pyrosequencing, together with a methodology to systematically collect, process, and archive nucleic acids. These three analysis methods yielded considerably different results: Traditional approaches provided the least comprehensive assessment of microbial diversity, while PhyloChip and pyrosequencing illuminated more diverse microbial populations. The overall results stress the importance of selecting sample collection and processing approaches based on the desired target and required level of detection. The DNA archive generated in this study can be made available to future researchers as genetic-inventory-oriented technologies further mature.

microbial diversity↗

BLOOD-BASED MULTI-SCALE MODEL FOR CANCER RISK FROM GCR IN GENETICALLY DIVERSE POPULATIONS

OBJECTIVES AND METHODS This project addresses the challenge of understanding and predicting individual radiation sensitivity by integrating genetics, demographics and biomarker characteristics across species (mice and humans). We hypothesize that ex vivo DNA repair response to GCR components is a central determinant of cancer risk from space radiation and can serve as a biomarker of radiation risk in combination with genetics. Automated image quantification of 53BP1+ radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET in non-immortalized primary skin fibroblasts derived from 76 mice across 15 strains (5 inbred reference strains and 10 collaborative-cross strains) exposed to X rays (0.1, 1 and 4 Gy), 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100μm2), as well as in peripheral blood mononuclear cells (PBMCs) from 768 healthy donors (matched ethnicity, 50/50 male/female, 18-70 years old) exposed to gamma rays (0.1 and 1 Gy), 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100μm2). QUANTIFICATION OF 53BP1+ FOCI IN VITRO AND ASSOCIATIONS TO IN VIVO RADIATION SUSCEPTIBILITY IN 15 MOUSE STRAINS We reported in vitro repair kinetic and repairable fractions of RIF for the 15 mouse strains and introduced a mathematical model for RIF as a function of time, dose and LET. We noted that the metabolic activity of cells modulates the RIF response, and we introduced the open access tool terRIFic (Tool for Enhanced Results of RIF In Cells, https://radbiolab.shinyapps.io/terrific/) to correct for such bias using confluence level. Notably, at 4h post-irradiation, RIF/Gy decreased with dose or LET: as the dose or LET increases, so does the proximity of DNA double-strand-breaks (DSB) and our data suggest that proximal DSBs are brought together inside isolated RIF for repair. The RIF/Gy trend was inverted at 24h, suggesting RIF with high DSB content are more difficult to repair. We showed that in vitro metrics correlate with in vivo measurements in the same 15 mouse strains, such as survival levels of immune cells or spontaneous cancer incidence, suggesting a relationship between the efficiency of DSB repair and cancer risk or radiation toxicity. In addition to the efficiency of repair and persistent RIF, the amount of spontaneous foci before irradiation was also found to be strain dependent. Finally, we performed genome-wide association study in the same 15 mouse strains using all RIF phenotypes measured in vitro, identifying genes of interest and validating RIF as an ideal biomarker for individual radiation sensitivity. BASELINE 53BP1+ FOCI PREDICTS INDIVIDUAL HUMAN RESPONSE TO GCR COMPONENTS Based on the analysis of radiation responses of 576 donor PBMCs (using quantification of 53BP1+ foci, oxidative stress and cell death), we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing with LET, though oxidative stress being notably reduced by high-LET irradiation, potentially due to a switch between hydrogen peroxide and oxygen radical-based mechanisms. We identified a relationship between few spontaneous DNA foci at baseline and increased DNA repair after irradiation, accompanied by an alteration in immunoregulatory cytokine secretion, which might be adapted as biomarkers to predict ionizing radiation sensitivity. Among demographic variables, only latent cytomegalovirus infection and age were predictive of high baseline foci formation. Finally, we have performed low-throughput whole genome sequencing of all samples and are currently in the process of identifying the genes and pathways associated with low and high-LET ionizing radiation sensitivity in humans.

53BP1↗

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks: Preprint

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution systems use to prepare for extreme events is to form multiple microgrids and thereby isolate themselves from the grid supply by using local generation as much as possible to supply critical loads. But partitioning an existing system into multiple feasible islands capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithmbased approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, USA.

edge elimination↗

Improving performance of two-group interfacial area transport equation models using genetic algorithms and high resolution experimental data

In the two-fluid transport model, the coupling of mass, momentum and energy transfer between phases is highly dependent on interfacial area transfer terms. Several research efforts in the past have been focused on the development of an interfacial area transport equation model (IATE), in order to eliminate the drawbacks of static flow regime maps currently used in best-estimate thermal-hydraulic system codes. The IATE attempts to model the dynamics that are involved in two phase flows by accounting for the different interaction mechanisms affecting bubble transport in the flow. In general, current IATE models perform poorly in high void fraction flow regimes. As both models depend on closure relations that require empirically determined coefficients, a genetic algorithm is implemented to study their optimization. The preliminary study indicates that improvements are achievable by application of the genetic algorithm. Optimization of coefficients for an entire set of high-resolution wire mesh sensor (WMS) data provided a single set of optimal coefficients. The application of WMS-optimized coefficients to external tests improved IATE performance for similar hydraulic diameters and provided a neutral change in performance for significantly smaller/larger hydraulic diameters. This is a crucial outcome as an optimized set of coefficients that provide significant improvement for a subset of experimental data - is shown to benefit performance in external data for which the coefficients are not specifically optimized. (authors)

42 ENGINEERING↗

Genetic Fusion of Thermoresponsive Polypeptides with UCST‐type Behavior Mediates 1D Assembly of Coiled‐Coil Bundlemers

Abstract Thermoresponsive resilin‐like polypeptides (RLPs) of various lengths were genetically fused to two different computationally designed coiled coil‐forming peptides with distinct thermal stability, to develop new strategies to assemble coiled coil peptides via temperature‐triggered phase separation of the RLP units. Their successful production in bacterial expression hosts was verified via gel electrophoresis, mass spectrometry, and amino acid analysis. Circular dichroism (CD) spectroscopy, ultraviolet‐visible (UV/Vis) turbidimetry, and dynamic light scattering (DLS) measurements confirmed the stability of the coiled coils and showed that the thermosensitive phase behavior of the RLPs was preserved in the genetically fused hybrid polypeptides. Cryogenic‐transmission electron microscopy and coarse‐grained modeling revealed that functionalizing the coiled coils with thermoresponsive RLPs leads to their thermally triggered noncovalent assembly into nanofibrillar assemblies.

Patkar, Sai S.↗

Genetic Fusion of Thermoresponsive Polypeptides with UCST–type Behavior Mediates 1D Assembly of Coiled–Coil Bundlemers

Thermoresponsive resilin-like polypeptides (RLPs) of various lengths were genetically fused to two different computationally designed coiled coil-forming peptides with distinct thermal stability, to develop new strategies to assemble coiled coil peptides via temperature-triggered phase separation of the RLP units. Furthermore, their successful production in bacterial expression hosts was verified via gel electrophoresis, mass spectrometry, and amino acid analysis. Circular dichroism (CD) spectroscopy, ultraviolet-visible (UV/Vis) turbidimetry, and dynamic light scattering (DLS) measurements confirmed the stability of the coiled coils and showed that the thermosensitive phase behavior of the RLPs was preserved in the genetically fused hybrid polypeptides. Cryogenic-transmission electron microscopy and coarse-grained modeling revealed that functionalizing the coiled coils with thermoresponsive RLPs leads to their thermally triggered noncovalent assembly into nanofibrillar assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic algorithm based task reordering to improve the performance of batch scheduled massively parallel scientific applications

The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on the performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.

97 MATHEMATICS AND COMPUTING↗

Genetic mapping of sugarcane aphid resistance in sorghum line SC112-14

Sugarcane aphid [Melanaphis sacchari (Zehntner)] is a destructive pest that has had an economic effect on sorghum in North America since 2013. The identification, development, and use of resistant sorghum germplasm is the most feasible strategy to control the pest. Nevertheless, the genetic control of sugarcane aphid (SCA) resistance is unknown for most sorghum resistant lines. To identify the genetic regions that confer SCA resistance in sorghum line SC112-14, 103 recombinant inbred lines (RILs) derived by its cross with the susceptible line PI 609251 were evaluated for their SCA resistance response in Georgia during two consecutive years. The resistance response was determined based on two ratings (2 wk apart) for aphid population size (APS) and aphid-induced plant damage (APD) each year. Segregation for SCA resistance was observed for the first APS and both APD ratings, and the broad-sense heritability estimate ranged from .71 to .76, respectively. A quantitative trait locus analysis using a high-density linkage map of 3,852 single nucleotide polymorphisms (SNPs) detected an 81-kb genomic region on chromosome 6 that explained 50–55% of the phenotypic variation. Comparative mapping analysis found that the resistance locus in SC112-14 is located 8- and 10-cM upstream of the Henong 16 (RMES1) and Tx2783 resistance loci, respectively, and encloses the SNP Sbv3.1_06_2316351 associated in Haitian resistant lines. Therefore, the line SC112-14 is an additional SCA resistance source that can be combined or strategically used with other resistance sources to assure a more robust host plant resistance to the SCA.

60 APPLIED LIFE SCIENCES↗

Grandparent Inference from Genetic Data: The Potential for Parentage-Based Tagging Programs to Identify Offspring of Hatchery Strays

Abstract Fisheries managers routinely use hatcheries to increase angling opportunity. Many hatcheries operate as segregated programs where hatchery-origin fish are not intended to spawn with natural-origin conspecifics in order to prevent potential negative effects on the natural-origin population. Currently available techniques to monitor the frequency with which hatchery-origin strays successfully spawn in the wild rely on either genetic differentiation between the hatchery- and natural-origin fish or extensive sampling of fish on the spawning grounds. We present a method to infer grandparent–grandchild trios by using only genotypes from two putative grandparents and one putative grandchild. We developed estimators of false-positive and false-negative error rates and showed that genetic panels containing 500–700 single-nucleotide polymorphisms or 200–300 microhaplotypes are expected to allow application of this technique for monitoring segregated hatchery programs. We discuss the ease with which this technique can be implemented by pre-existing parentage-based tagging programs and provide an R package that applies the method.

Delomas, Thomas A. (ORCID:000000015154759X)↗

Genetic dissection of natural variation in oilseed traits of camelina by whole‐genome resequencing and QTL mapping

Abstract Camelina [ Camelina sativa (L.) Crantz] is an oilseed crop in the Brassicaceae family that is currently being developed as a source of bioenergy and healthy fatty acids. To facilitate modern breeding efforts through marker‐assisted selection and biotechnology, we evaluated genetic variation among a worldwide collection of 222 camelina accessions. We performed whole‐genome resequencing to obtain single nucleotide polymorphism (SNP) markers and to analyze genomic diversity. We also conducted phenotypic field evaluations in two consecutive seasons for variations in key agronomic traits related to oilseed production such as seed size, oil content (OC), fatty acid composition, and flowering time. We determined the population structure of the camelina accessions using 161,301 SNPs. Further, we identified quantitative trait loci (QTL) and candidate genes controlling the above field‐evaluated traits by genome‐wide association studies (GWAS) complemented with linkage mapping using a recombinant inbred line (RIL) population. Characterization of the natural variation at the genome and phenotypic levels provides valuable resources to camelina genetic studies and crop improvement. The QTL and candidate genes should assist in breeding of advanced camelina varieties that can be integrated into the cropping systems for the production of high yield of oils of desired fatty acid composition.

59 BASIC BIOLOGICAL SCIENCES↗

Using a Genetic Algorithm to Optimize Configurations in a Data-Driven Application

Users of highly-configurable software systems often want to optimize a particular objective such as improving a functional outcome or increasing system performance. One approach is to use an evolutionary algorithm. However, many applications today are data-driven, meaning they depend on inputs or data which can be complex and varied. Hence, a search needs to be run (and re-run) for all inputs, making optimization a heavy-weight and potentially impractical process. In this paper, we explore this issue on a data-driven highly-configurable scientific application. We build an exhaustive database containing 3,000 configurations and 10,000 inputs, leading to almost 100 million records as our oracle, and then run a genetic algorithm individually on each of the 10,000 inputs. We ask if (1) a genetic algorithm can find configurations to improve functional objectives; (2) whether patterns of best configurations over all input data emerge; and (3) if we can we use sampling to approximate the results. We find that the original (default) configuration is best only 34% of the time, while clear patterns emerge of other best configurations. Out of 3,000 possible configurations, only 112 distinct configurations achieve the optimal result at least once across all 10,000 inputs, suggesting the potential for lighter weight optimization approaches. We show that sampling of the input data finds similar patterns at a lower cost.

Sinha, Urjoshi↗

Genetics of rectal cancer and novel therapies: primer for radiologists

Rectal cancer accounts for one-third of newly diagnosed colorectal cancer cases. Given its anatomical location and risk for local recurrence, a multidisciplinary treatment program including surgery, radiation therapy, and chemotherapy has demonstrated improved outcomes in localized disease. Genetic analysis has become part of the standard approach for management of advanced disease and new trials are considering tailored therapies for locally advanced disease. This review describes molecular subsets of colorectal cancer; implications for clinical management, including patterns of metastatic spread and response to therapies; and emerging matched therapies. During the last decade, significant biological differences have been noted based on colorectal cancer primary location and here we focus on rectal cancers and relevant markers for this disease. As more treatment for localized rectal cancer is shifted to the neoadjuvant setting and more targeted regimens are developed for metastatic disease, radiologists will increasingly see patients defined by molecular subsets and their awareness of the genetics of rectal cancer will help further refine our understanding of this disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Identification of a genetic interaction between the tumor suppressor EAF2 and the retinoblastoma protein (Rb) signaling pathway in C. elegans and prostate cancer cells

Highlights: • RNAi screen identified genetic enhancers for the C. elegans homolog of EAF2. • EAF2 and RBBP4 proteins physically bind to each other and alter transcription. • Overexpression of EAF2 and RBBP4 induces the cell death in prostate cancer cells. - Abstract: The tumor suppressor EAF2 is regulated by androgen signaling and associated with prostate cancer. While EAF2 and its partner ELL have been shown to be members of protein complexes involved in RNA polymerase II transcriptional elongation, the biologic roles for EAF2 especially with regards to the development of cancer remains poorly understood. We have previously identified the eaf-1 gene in Caenorhabditiselegans as the ortholog of EAF2, and shown that eaf-1 interacts with the ELL ortholog ell-1 to control development and fertility in worms. To identify genetic pathways that interact with eaf-1, we screened RNAi libraries consisting of transcription factors, phosphatases, and chromatin-modifying factors to identify genes which enhance the effects of eaf-1(tm3976) on fertility. From this screen, we identified lin-53, hmg-1.2, pha-4, ruvb-2 and set-6 as hits. LIN-53 is the C. elegans ortholog of human retinoblastoma binding protein 4/7 (RBBP 4/7), which binds to the retinoblastoma protein and inhibits the Ras signaling pathway. We find that lin-53 showed a synthetic interaction with eaf-1(tm3976) where knockdown of lin-53 in an eaf-1(tm3976) mutant resulted in sterile worms. This phenotype may be due to cell death as the treated worms contain degenerated embryos with increased expression of the ced-1:GFP cell death marker. Further we find that the interaction between eaf-1 and lin-53/RBBP4/7 also exists in vertebrates, which is reflected by the formation of a protein complex between EAF2 and RBBP4/7. Finally, overexpression of either human EAF2 or RBBP4 in LNCaP cells induced the cell death while knockdown of EAF2 in LNCaP enhanced cell proliferation, indicating an important role of EAF2 in controlling the growth and survival of prostate cancer cells. Together these findings identify a novel physical and functional interaction between EAF2 and the Rb pathway.

60 APPLIED LIFE SCIENCES↗

Upgrading aminoacyl-tRNA synthetases for genetic code expansion

Synthesis of proteins with non-canonical amino acids via genetic code expansion is at the forefront of synthetic biology. Progress in this field has enabled site-specific incorporation of over 200 chemically and structurally diverse amino acids into proteins in an increasing number of organisms. This has been facilitated by our ability to repurpose aminoacyl-tRNA synthetases to attach non-canonical amino acids to engineered tRNAs. Current efforts in the field focus on overcoming existing limitations to the simultaneous incorporation of multiple non-canonical amino acids or amino acids that differ from the l-α-amino acid structure (e.g. d-amino acid or β-amino acid). Here, we summarize the progress and challenges in developing more selective and efficient aminoacyl-tRNA synthetases for genetic code expansion.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic genetic adaptation of Bacteroides thetaiotaomicron during murine gut colonization

To understand how a bacterium ultimately succeeds or fails in adapting to a new host, it is essential to assess the temporal dynamics of its fitness over the course of colonization. Here, we introduce a human-derived commensal organism, Bacteroides thetaiotaomicron (Bt), into the guts of germ-free mice to determine whether and how the genetic requirements for colonization shift over time. Combining a high-throughput functional genetics assay and transcriptomics, we find that gene usage changes drastically during the first days of colonization, shifting from high expression of amino acid biosynthesis genes to broad upregulation of diverse polysaccharide utilization loci. Within the first week, metabolism becomes centered around utilization of a predominant dietary oligosaccharide, and these changes are largely sustained through 6 weeks of colonization. Spontaneous mutations in wild-type Bt also evolve around this locus. These findings highlight the importance of considering temporal colonization dynamics in developing more effective micro biome-based therapies.

59 BASIC BIOLOGICAL SCIENCES↗