4,752 research outputs found
Non-Resonant Picosecond Three-Wave Mixing in the Gas Phase
We report on the experimental observation of non-resonant, second-order
optical Sum-Frequency Generation (SFG) in five different atomic and molecular
gases. The measured signal is attributed to a SFG process by characterizing its
intensity scaling and its polarization behavior. We show that the electric
quadrupole mechanism cannot explain the observed trends. Our results
demonstrate that SFG in the gas phase is about four orders of magnitude
stronger than Third Harmonic Generation (THG) and independent from any
externally-applied electric fields. These features make this method suitable
for gas number density measurements at the picosecond timescale in reactive
flows and plasmas
Predicting sequence and structural specificities of RNA binding regions recognized by splicing factor SRSF1
Abstract- RNA-binding proteins (RBPs) play diverse roles in eukaryotic RNA processing. Despite their pervasive functions in coding and non-coding RNA biogenesis and regulation, elucidating the specificities that define protein-RNA interactions remains a major challenge. Here, we describe a novel model-based approach — RNAMotifModeler to identify binding consensus of RBPs by integrating sequence features and RNA secondary structures. Using RNA sequences derived from Cross-linking immunoprecipitation (CLIP) followed by high-throughput sequencing for SRSF1 proteins, we identified a purine-rich octamer ‘AGAAGAAG ’ in a highly singlestranded RNA context, which is consistent with previous knowledge. The successful implementation on SRSF1 CLIPseq data demonstrates great potential to improve our understanding on the binding specificity of RNA binding proteins
Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets
The scale of functional magnetic resonance image data is rapidly increasing
as large multi-subject datasets are becoming widely available and
high-resolution scanners are adopted. The inherent low-dimensionality of the
information in this data has led neuroscientists to consider factor analysis
methods to extract and analyze the underlying brain activity. In this work, we
consider two recent multi-subject factor analysis methods: the Shared Response
Model and Hierarchical Topographic Factor Analysis. We perform analytical,
algorithmic, and code optimization to enable multi-node parallel
implementations to scale. Single-node improvements result in 99x and 1812x
speedups on these two methods, and enables the processing of larger datasets.
Our distributed implementations show strong scaling of 3.3x and 5.5x
respectively with 20 nodes on real datasets. We also demonstrate weak scaling
on a synthetic dataset with 1024 subjects, on up to 1024 nodes and 32,768
cores
Using RNase sequence specificity to refine the identification of RNA-protein binding regions
Massively parallel pyrosequencing is a high-throughput technology that can sequence hundreds of thousands of DNA/RNA fragments in a single experiment. Combining it with immunoprecipitation-based biochemical assays, such as cross-linking immunoprecipitation (CLIP), provides a genome-wide method to detect the sites at which proteins bind DNA or RNA. In a CLIP-pyrosequencing experiment, the resolutions of the detected protein binding regions are partially determined by the length of the detected RNA fragments (CLIP amplicons) after trimming by RNase digestion. The lengths of these fragments usually range from 50-70 nucleotides. Many genomic regions are marked by multiple RNA fragments. In this paper, we report an empirical approach to refine the localization of protein binding regions by using the distribution pattern of the detected RNA fragments and the sequence specificity of RNase digestion. We present two regions to which multiple amplicons map as examples to demonstrate this approach
Identification of Nuclear and Cytoplasmic mRNA Targets for the Shuttling Protein SF2/ASF
The serine and arginine-rich protein family (SR proteins) are highly conserved regulators of pre-mRNA splicing. SF2/ASF, a prototype member of the SR protein family, is a multifunctional RNA binding protein with roles in pre-mRNA splicing, mRNA export and mRNA translation. These observations suggest the intriguing hypothesis that SF2/ASF may couple splicing and translation of specific mRNA targets in vivo. Unfortunately the paucity of endogenous mRNA targets for SF2/ASF has hindered testing of this hypothesis. Here, we identify endogenous mRNAs directly cross-linked to SF2/ASF in different subcellular compartments. Cross-Linking Immunoprecipitation (CLIP) captures the in situ specificity of protein-RNA interaction and allows for the simultaneous identification of endogenous RNA targets as well as the locations of binding sites within the RNA transcript. Using the CLIP method we identified 326 binding sites for SF2/ASF in RNA transcripts from 180 protein coding genes. A purine-rich consensus motif was identified in binding sites located within exon sequences but not introns. Furthermore, 72 binding sites were occupied by SF2/ASF in different sub-cellular fractions suggesting that these binding sites may influence the splicing or translational control of endogenous mRNA targets. We demonstrate that ectopic expression of SF2/ASF regulates the splicing and polysome association of transcripts derived from the SFRS1, PABC1, NETO2 and ENSA genes. Taken together the data presented here indicate that SF2/ASF has the capacity to co-regulate the nuclear and cytoplasmic processing of specific mRNAs and provide further evidence that the nuclear history of an mRNA ma
Entanglement Evolution in the Presence of Decoherence
The entanglement of two qubits, each defined as an effective two-level, spin
1/2 system, is investigated for the case that the qubits interact via a
Heisenberg XY interaction and are subject to decoherence due to population
relaxation and thermal effects. For zero temperature, the time dependent
concurrence is studied analytically and numerically for some typical initial
states, including a separable (unentangled) initial state. An analytical
formula for non-zero steady state concurrence is found for any initial state,
and optimal parameter values for maximizing steady state concurrence are given.
The steady state concurrence is found analytically to remain non-zero for low,
finite temperatures. We also identify the contributions of global and local
coherence to the steady state entanglement.Comment: 12 pages, 4 figures. The second version of this paper has been
significantly expanded in response to referee comments. The revised
manuscript has been accepted for publication in Journal of Physics
Mifepristone increases mRNA translation rate, triggers the unfolded protein response, increases autophagic flux, and kills ovarian cancer cells in combination with proteasome or lysosome inhibitors
The synthetic steroid mifepristone blocks the growth of ovarian cancer cells, yet the mechanism driving such effect is not entirely understood. Unbiased genomic and proteomic screenings using ovarian cancer cell lines of different genetic backgrounds and sensitivities to platinum led to the identification of two key genes upregulated by mifepristone and involved in the unfolded protein response (UPR): the master chaperone of the endoplasmic reticulum (ER), glucose regulated protein (GRP) of 78 kDa, and the CCAAT/enhancer binding protein homologous transcription factor (CHOP). GRP78 and CHOP were upregulated by mifepristone in ovarian cancer cells regardless of p53 status and platinum sensitivity. Further studies revealed that the three UPR-associated pathways, PERK, IRE1α, and ATF6, were activated by mifepristone. Also, the synthetic steroid acutely increased mRNA translation rate, which, if prevented, abrogated the splicing of XBP1 mRNA, a non-translatable readout of IRE1α activation. Moreover, mifepristone increased LC3-II levels due to increased autophagic flux. When the autophagic–lysosomal pathway was inhibited with chloroquine, mifepristone was lethal to the cells. Lastly, doses of proteasome inhibitors that are inadequate to block the activity of the proteasomes, caused cell death when combined with mifepristone; this phenotype was accompanied by accumulation of poly-ubiquitinated proteins denoting proteasome inhibition. The stimulation by mifepristone of ER stress and autophagic flux offers a therapeutic opportunity for utilizing this compound to sensitize ovarian cancer cells to proteasome or lysosome inhibitors.Fil: Zhang, Lei. University Of South Dakota; Estados UnidosFil: Hapon, María Belén. University Of South Dakota; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Goyeneche, Alicia A.. University Of South Dakota; Estados Unidos. McGill University; CanadáFil: Srinivasan, Rekha. University Of South Dakota; Estados UnidosFil: Gamarra Luques, Carlos Diego. University Of South Dakota; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Callegari, Eduardo A.. University Of South Dakota; Estados UnidosFil: Drappeau, Donis D.. University Of South Dakota; Estados UnidosFil: Terpstra, Erin J.. University Of South Dakota; Estados UnidosFil: Pan, Bo. University Of South Dakota; Estados UnidosFil: Knapp, Jennifer R.. University of Kansas; Estados UnidosFil: Chien, Jeremy. University of Kansas; Estados UnidosFil: Wang, Xuejun. University Of South Dakota; Estados UnidosFil: Eyster, Kathleen M.. University Of South Dakota; Estados UnidosFil: Telleria, Carlos Marcelo. University Of South Dakota; Estados Unidos. McGill University; Canadá. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
AMO EXPRESS: A Command and Control Experiment for Crew Autonomy Onboard the International Space Station
NASA is investigating a range of future human spaceflight missions, including both Mars-distance and Near Earth Object (NEO) targets. Of significant importance for these missions is the balance between crew autonomy and vehicle automation. As distance from Earth results in increasing communication delays, future crews need both the capability and authority to independently make decisions. However, small crews cannot take on all functions performed by ground today, and so vehicles must be more automated to reduce the crew workload for such missions.NASAs Advanced Exploration Systems Program funded Autonomous Mission Operations (AMO) project conducted an autonomous command and control experiment on-board the International Space Station that demonstrated single action intelligent procedures for crew command and control. The target problem was to enable crew initialization of a facility class rack with power and thermal interfaces, and involving core and payload command and telemetry processing, without support from ground controllers. This autonomous operations capability is enabling in scenarios such as initialization of a medical facility to respond to a crew medical emergency, and representative of other spacecraft autonomy challenges. The experiment was conducted using the Expedite the Processing of Experiments for Space Station (EXPRESS) rack 7, which was located in the Port 2 location within the U.S Laboratory onboard the International Space Station (ISS)
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Technoeconomic and life-cycle analysis of single-step catalytic conversion of wet ethanol into fungible fuel blendstocks
Technoeconomic and life-cycle analyses are presented for catalytic conversion of ethanol to fungible hydrocarbon fuel blendstocks, informed by advances in catalyst and process development. Whereas prior work toward this end focused on 3-step processes featuring dehydration, oligomerization, and hydrogenation, the consolidated alcohol dehydration and oligomerization (CADO) approach described here results in 1-step conversion of wet ethanol vapor (40 wt% in water) to hydrocarbons and water over a metal-modified zeolite catalyst. A development project increased liquid hydrocarbon yields from 36% of theoretical to >80%, reduced catalyst cost by an order of magnitude, scaled up the process by 300-fold, and reduced projected costs of ethanol conversion 12-fold. Current CADO products conform most closely to gasoline blendstocks, but can be blended with jet fuel at low levels today, and could potentially be blended at higher levels in the future. Operating plus annualized capital costs for conversion of wet ethanol to fungible blendstocks are estimated at 1.44/GJ in the future, similar to the unit energy cost of producing anhydrous ethanol from wet ethanol (100 per barrel but not at 60 per barrel. Life-cycle greenhouse gas emission reductions for CADO-derived hydrocarbon blendstocks closely follow those for the ethanol feedstock
FMLRC: Hybrid long read error correction using an FM-index
Abstract Background Long read sequencing is changing the landscape of genomic research, especially de novo assembly. Despite the high error rate inherent to long read technologies, increased read lengths dramatically improve the continuity and accuracy of genome assemblies. However, the cost and throughput of these technologies limits their application to complex genomes. One solution is to decrease the cost and time to assemble novel genomes by leveraging “hybrid” assemblies that use long reads for scaffolding and short reads for accuracy. Results We describe a novel method leveraging a multi-string Burrows-Wheeler Transform with auxiliary FM-index to correct errors in long read sequences using a set of complementary short reads. We demonstrate that our method efficiently produces significantly more high quality corrected sequence than existing hybrid error-correction methods. We also show that our method produces more contiguous assemblies, in many cases, than existing state-of-the-art hybrid and long-read only de novo assembly methods. Conclusion Our method accurately corrects long read sequence data using complementary short reads. We demonstrate higher total throughput of corrected long reads and a corresponding increase in contiguity of the resulting de novo assemblies. Improved throughput and computational efficiency than existing methods will help better economically utilize emerging long read sequencing technologies
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