55 research outputs found

    Skin sympathetic nerve activity in patients with obstructive sleep apnea

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    Background: Obstructive sleep apnea (OSA) is associated with increased cardiac arrhythmia and sudden cardiac death. We recently developed a new method (neuECG) to noninvasively measure electrocardiogram and skin sympathetic nerve activity (SKNA). Objective: The purpose of this study was to test the hypothesis that SKNA measured during sleep study is higher in patients with OSA than in those without OSA. Methods: We prospectively recorded neuECG and polysomnography in 26 patients undergoing a sleep study. Sleep stages were scored into rapid eye movement (REM), and non-REM sleep stages 1 (N1), 2 (N2), and 3 (N3). Average voltage of skin sympathetic nerve activity (aSKNA) and SKNA burst area were calculated for quantification. Apnea/hypopnea index (AHI) >5 per hour was used to diagnose OSA. Results: There was a positive correlation (r = 0.549; P = .018) between SKNA burst area and the arousal index in OSA but not in the control group. aSKNA during sleep was 0.61 ± 0.09 μV in OSA patients (n = 18) and 0.53 ± 0.04 μV in control patients (n = 8; P = .025). Burst area was 3.26 (1.90-4.47) μV·s/min in OSA patients and 1.31 (0.67-1.94) μV·s/min in control (P = .047). More apparent differences were found during N2, when the burst area in OSA (3.06 [1.46-5.52] μV·s/min) was much higher than that of the control (0.89 [0.79-1.65] μV·s/min; P = .03). Conclusion: OSA patients have higher SKNA activity than control patients, with the most pronounced differences observed during N2. Arousal at the end of apnea episodes is associated with large SKNA bursts. Overlaps of aSKNA and SKNA burst area between groups suggest that not all OSA patients have increased sympathetic tone

    Thermodynamics of deformed AdS5_5 model with a positive/negative quadratic correction in graviton-dilaton system

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    By solving the Einstein equations of the graviton coupling with a real scalar dilaton field, we establish a general framework to self-consistently solve the geometric background with black-hole for any given phenomenological holographic models. In this framwork, we solve the black-hole background, the corresponding dilaon field and the dilaton potential for the deformed AdS5_5 model with a positive/negative quadratic correction. We systematically investigate the thermodynamical properties of the deformed AdS5_5 model with a positive and negative quadratic correction, respectively, and compare with lattice QCD on the results of the equation of state, the heavy quark potential, the Polyakov loop and the spatial Wilson loop. We find that the bulk thermodynamical properties are not sensitive to the sign of the quadratic correction, and the results of both deformed holographic QCD models agree well with lattice QCD result for pure SU(3) gauge theory. However, the results from loop operators favor a positive quadratic correction, which agree well with lattice QCD result. Especially, the result from the Polyakov loop excludes the model with a negative quadratic correction in the warp factor of AdS5{\rm AdS}_5.Comment: 26 figures,36 pages,V.3: an appendix,more equations and references added,figures corrected,published versio

    A hQCD model and its phase diagram in Einstein-Maxwell-Dilaton system

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    By use of the potential reconstruction approach we obtain a series of asymptotically AdS (aAdS) black hole solutions in an Einstein-Maxwell-Dilaton (EMD) system. Basing on the solutions of the system, we reconstruct a semi-analytical holographic QCD (hQCD) model with a quadratic term in warped factor. We discuss some aspects of the hQCD model, in particular we calculate the free energy of two static color sources (a heavy quark-antiquark pair) which is an important order parameter to describe confinement/deconfinement phase transition. The behavior of the free energy with respect to temperature and chemical potential is studied. We find that in the hQCD model the deconfinement phase transition can be realized and a critical point occurs. The resulting phase diagram in the temperature-chemical potential TμT-\mu plane is in quite good agreement with the one from recent lattice results and effective models of QCD.Comment: 27 pages, 11 figures, regular paper, add some comments and references, accepted by JHE

    A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz

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    We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ~11,680 stars and planetary systems in the ~9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. In this work, we also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense RFI are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times smaller at ~6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023).Comment: 22 pages, 9 figures, submitted to AJ, revise

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    A saturated map of common genetic variants associated with human height.

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    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

    A saturated map of common genetic variants associated with human height

    Get PDF
    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants
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