354 research outputs found

    Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice

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    Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation) and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup) gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP) scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones

    The inflammatory and normal transcriptome of mouse bladder detrusor and mucosa

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    BACKGROUND: An organ such as the bladder consists of complex, interacting set of tissues and cells. Inflammation has been implicated in every major disease of the bladder, including cancer, interstitial cystitis, and infection. However, scanty is the information about individual detrusor and urothelium transcriptomes in response to inflammation. Here, we used suppression subtractive hybridizations (SSH) to determine bladder tissue- and disease-specific genes and transcriptional regulatory elements (TRE)s. Unique TREs and genes were assembled into putative networks. RESULTS: It was found that the control bladder mucosa presented regulatory elements driving genes such as myosin light chain phosphatase and calponin 1 that influence the smooth muscle phenotype. In the control detrusor network the Pax-3 TRE was significantly over-represented. During development, the Pax-3 transcription factor (TF) maintains progenitor cells in an undifferentiated state whereas, during inflammation, Pax-3 was suppressed and genes involved in neuronal development (synapsin I) were up-regulated. Therefore, during inflammation, an increased maturation of neural progenitor cells in the muscle may underlie detrusor instability. NF-κB was specifically over-represented in the inflamed mucosa regulatory network. When the inflamed detrusor was compared to control, two major pathways were found, one encoding synapsin I, a neuron-specific phosphoprotein, and the other an important apoptotic protein, siva. In response to LPS-induced inflammation, the liver X receptor was over-represented in both mucosa and detrusor regulatory networks confirming a role for this nuclear receptor in LPS-induced gene expression. CONCLUSION: A new approach for understanding bladder muscle-urothelium interaction was developed by assembling SSH, real time PCR, and TRE analysis results into regulatory networks. Interestingly, some of the TREs and their downstream transcripts originally involved in organogenesis and oncogenesis were also activated during inflammation. The latter represents an additional link between inflammation and cancer. The regulatory networks represent key targets for development of novel drugs targeting bladder diseases

    Intracranial Vertebrobasilar Artery Dissection Associated with Postpartum Angiopathy

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    Background. Cervicocephalic arterial dissection (CCAD) is rare in the postpartum period. To our knowledge this is the first reported case of postpartum angiopathy (PPA) presenting with ischemic stroke due to intracranial arterial dissection. Case. A 41-year-old woman presented with blurred vision, headache, and generalized seizures 5 days after delivering twins. She was treated with magnesium for eclampsia. MRI identified multiple posterior circulation infarcts. Angiography identified a complex dissection extending from both intradural vertebral arteries, through the basilar artery, and into both posterior cerebral arteries. Multiple segments of arterial dilatation and narrowing consistent with PPA were present. Xenon enhanced CT (Xe-CT) showed reduced regional cerebral blood flow that is improved with elevation in blood pressure. Conclusion. Intracranial vertebrobasilar dissection causing stroke is a rare complication of pregnancy. Eclampsia and PPA may play a role in its pathogenesis. Blood pressure management may be tailored using quantitative blood flow studies, such as Xe-CT

    Systematic inference of the long-range dependence and heavy-tail distribution parameters of ARFIMA models

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    Long-Range Dependence (LRD) and heavy-tailed distributions are ubiquitous in natural and socio-economic data. Such data can be self-similar whereby both LRD and heavy-tailed distributions contribute to the self-similarity as measured by the Hurst exponent. Some methods widely used in the physical sciences separately estimate these two parameters, which can lead to estimation bias. Those which do simultaneous estimation are based on frequentist methods such as Whittle’s approximate maximum likelihood estimator. Here we present a new and systematic Bayesian framework for the simultaneous inference of the LRD and heavy-tailed distribution parameters of a parametric ARFIMA model with non-Gaussian innovations. As innovations we use the α-stable and t-distributions which have power law tails. Our algorithm also provides parameter uncertainty estimates. We test our algorithm using synthetic data, and also data from the Geostationary Operational Environmental Satellite system (GOES) solar X-ray time series. These tests show that our algorithm is able to accurately and robustly estimate the LRD and heavy-tailed distribution parameters

    Thermal Conductivity across the Phase Diagram of Cuprates: Low-Energy Quasiparticles and Doping Dependence of the Superconducting Gap

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    Heat transport in the cuprate superconductors YBa2_2Cu3_3Oy_{y} and La2x_{2-x}Srx_xCuO4_4 was measured at low temperatures as a function of doping. A residual linear term kappa_{0}/T is observed throughout the superconducting region and it decreases steadily as the Mott insulator is approached from the overdoped regime. The low-energy quasiparticle gap extracted from kappa_{0}/T is seen to scale closely with the pseudogap. The ubiquitous presence of nodes and the tracking of the pseudogap shows that the overall gap remains of the pure d-wave form throughout the phase diagram, which excludes the possibility of a complex component (ix) appearing at a putative quantum phase transition and argues against a non-superconducting origin to the pseudogap. A comparison with superfluid density measurements reveals that the quasiparticle effective charge is weakly dependent on doping and close to unity.Comment: 12 pages, 9 figure

    The Polarization of Ambient Noise on Mars

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    Seismic noise recorded at the surface of Mars has been monitored since February 2019, using the InSight seismometers. This noise can reach −200 dB. It is 500 times lower than on Earth at night and it increases of 30 dB during the day. We analyze its polarization as a function of time and frequency in the band 0.03–1 Hz. We use the degree of polarization to extract signals with stable polarization independent of their amplitude and type of polarization. We detect polarized signals at all frequencies and all times. Glitches correspond to linear polarized signals which are more abundant during the night. For signals with elliptical polarization, the ellipse is in the horizontal plane below 0.3 Hz. In the 0.3-1Hz high frequency band (HF) and except in the evening, the ellipse is in the vertical plane and the major axis is tilted. While polarization azimuths are different in the two frequency bands, they both vary as a function of local hour and season. They are also correlated with wind direction, particularly during the daytime. We investigate possible aseismic and seismic origins of the polarized signals. Lander or tether noise can be discarded. Pressure fluctuations transported by wind may explain part of the HF polarization but not the tilt of the ellipse. This tilt can be obtained if the source is an acoustic emission coming from high altitude at critical angle. Finally, in the evening when the wind is low, the measured polarized signals may correspond to the seismic wavefield of the Mars background noise

    A Comprehensive and Universal Method for Assessing the Performance of Differential Gene Expression Analyses

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    The number of methods for pre-processing and analysis of gene expression data continues to increase, often making it difficult to select the most appropriate approach. We present a simple procedure for comparative estimation of a variety of methods for microarray data pre-processing and analysis. Our approach is based on the use of real microarray data in which controlled fold changes are introduced into 20% of the data to provide a metric for comparison with the unmodified data. The data modifications can be easily applied to raw data measured with any technological platform and retains all the complex structures and statistical characteristics of the real-world data. The power of the method is illustrated by its application to the quantitative comparison of different methods of normalization and analysis of microarray data. Our results demonstrate that the method of controlled modifications of real experimental data provides a simple tool for assessing the performance of data preprocessing and analysis methods
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