65 research outputs found

    Mind-wandering and alterations to default mode network connectivity when listening to naturalistic versus artificial sounds

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    Naturalistic environments have been demonstrated to promote relaxation and wellbeing. We assess opposing theoretical accounts for these effects through investigation of autonomic arousal and alterations of activation and functional connectivity within the default mode network (DMN) of the brain while participants listened to sounds from artificial and natural environments. We found no evidence for increased DMN activity in the naturalistic compared to artificial or control condition, however, seed based functional connectivity showed a shift from anterior to posterior midline functional coupling in the naturalistic condition. These changes were accompanied by an increase in peak high frequency heart rate variability, indicating an increase in parasympathetic activity in the naturalistic condition in line with the Stress Recovery Theory of nature exposure. Changes in heart rate and the peak high frequency were correlated with baseline functional connectivity within the DMN and baseline parasympathetic tone respectively, highlighting the importance of individual neural and autonomic differences in the response to nature exposure. Our findings may help explain reported health benefits of exposure to natural environments, through identification of alterations to autonomic activity and functional coupling within the DMN when listening to naturalistic sounds

    DAF-12 Regulates a Connected Network of Genes to Ensure Robust Developmental Decisions

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    The nuclear receptor DAF-12 has roles in normal development, the decision to pursue dauer development in unfavorable conditions, and the modulation of adult aging. Despite the biologic importance of DAF-12, target genes for this receptor are largely unknown. To identify DAF-12 targets, we performed chromatin immunoprecipitation followed by hybridization to whole-genome tiling arrays. We identified 1,175 genomic regions to be bound in vivo by DAF-12, and these regions are enriched in known DAF-12 binding motifs and act as DAF-12 response elements in transfected cells and in transgenic worms. The DAF-12 target genes near these binding sites include an extensive network of interconnected heterochronic and microRNA genes. We also identify the genes encoding components of the miRISC, which is required for the control of target genes by microRNA, as a target of DAF-12 regulation. During reproductive development, many of these target genes are misregulated in daf-12(0) mutants, but this only infrequently results in developmental phenotypes. In contrast, we and others have found that null daf-12 mutations enhance the phenotypes of many miRISC and heterochronic target genes. We also find that environmental fluctuations significantly strengthen the weak heterochronic phenotypes of null daf-12 alleles. During diapause, DAF-12 represses the expression of many heterochronic and miRISC target genes, and prior work has demonstrated that dauer formation can suppress the heterochronic phenotypes of many of these target genes in post-dauer development. Together these data are consistent with daf-12 acting to ensure developmental robustness by committing the animal to adult or dauer developmental programs despite variable internal or external conditions

    Testing the Ortholog Conjecture with Comparative Functional Genomic Data from Mammals

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    A common assumption in comparative genomics is that orthologous genes share greater functional similarity than do paralogous genes (the “ortholog conjecture”). Many methods used to computationally predict protein function are based on this assumption, even though it is largely untested. Here we present the first large-scale test of the ortholog conjecture using comparative functional genomic data from human and mouse. We use the experimentally derived functions of more than 8,900 genes, as well as an independent microarray dataset, to directly assess our ability to predict function using both orthologs and paralogs. Both datasets show that paralogs are often a much better predictor of function than are orthologs, even at lower sequence identities. Among paralogs, those found within the same species are consistently more functionally similar than those found in a different species. We also find that paralogous pairs residing on the same chromosome are more functionally similar than those on different chromosomes, perhaps due to higher levels of interlocus gene conversion between these pairs. In addition to offering implications for the computational prediction of protein function, our results shed light on the relationship between sequence divergence and functional divergence. We conclude that the most important factor in the evolution of function is not amino acid sequence, but rather the cellular context in which proteins act

    Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

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    YesHuman identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects’ DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European–American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.The Technology Commercialization Innovation Program (Contracts #121668, #132043) of the Utah Governors Office of Commercial Development, the Scholarship Activitie

    High-density mapping suggests cytoplasmic male sterility with two restorer genes in almond × peach progenies

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    Peach (Prunus persica) and almond (Prunus dulcis) are two sexually compatible species that produce fertile offspring. Almond, a highly polymorphic species, is a potential source of new genes for peach that has a strongly eroded gene pool. Here we describe the genetics of a male sterile phenotype that segregated in two almond ('Texas') × peach ('Earlygold') progenies: an F2 (T×E) and a backcross one (T1E) to the 'Earlygold' parent. High-density maps were developed using a 9k peach SNP chip and 135 simple-sequence repeats. Three highly syntenic and collinear maps were obtained: one for the F2 (T×E) and two for the backcross, T1E (for the hybrid) and E (for 'Earlygold'). A major reduction of recombination was observed in the interspecific maps (T×E and T1E) compared to the intraspecific parent (E). The E map also had extensive monomorphic genomic regions suggesting the presence of large DNA fragments identical by descent. Our data for the male sterility character were consistent with the existence of cytoplasmic male sterility, where individuals having the almond cytoplasm required the almond allele in at least one of two independent restorer genes, Rf1 and Rf2, to be fertile. The restorer genes were located in a 3.4 Mbp fragment of linkage group 2 (Rf1) and 1.4 Mbp of linkage group 6 (Rf2). Both fragments contained several genes coding for pentatricopeptide proteins, demonstrated to be responsible for restoring fertility in other species. The implications of these results for using almond as a source of novel variability in peach are discussed

    Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

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    DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

    Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

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    Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

    Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

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    Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation
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