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Dataset results
12 results for “PACo”
The PACO RCT Study
ClinicalTrials.gov study NCT03937336. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
The PACO Study ("Personnalité Alzheimer COmportement")
ClinicalTrials.gov study NCT01297140. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Personalized Activity Intervention in Rehabilitation After Cardiac Operations (the PACO Trial)
ClinicalTrials.gov study NCT03470246. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: The genetic inheritance of the blue-eyed white phenotype in alpacas (Vicugna pacos)
White spotting patterns in mammals can be caused by mutations in the gene KIT, whose protein is necessary for the normal migration and survival of melanocytes from the neural crest. The alpaca (Vicugna pacos) blue-eyed white phenotype (BEW) is characterized by two blue eyes and a solid white coat over the whole body. Breeders hypothesize that the BEW phenotype in alpacas is caused by the combination of the gene causing grey fleece and a white-spotting gene. We performed an association study using KIT flanking and intragenic markers with 40 unrelated alpacas, of which 17 were BEW. Two microsatellite alleles at KIT-related markers were significantly associated (P < 0.0001) with the BEW phenotype (bew1 and bew2). In a larger cohort of 171 related individuals we identify an abundance of an allele (bew1) in grey animals and the occurrence of bew2 homozygotes that are solid white with pigmented eyes. Association tests accounting for population structure and familial relatedness are consistent with a proposed model where these alleles are in linkage disequilibrium with a mutation or mutations that contribute to the BEW phenotype and to individual differences in fleece color.
Data from: paco: implementing Procrustean Approach to Cophylogeny in R
1. The concordance of evolutionary histories and extant species interactions provides a useful metric for addressing questions of how the structure of ecological communities is influenced by macro-evolutionary processes. 2. We introduce paco (v.0.3.1), an R package to perform Procrustean Approach to Cophylogeny. This method assesses the phylogenetic congruence, or evolutionary dependence, of two groups of interacting species using both ecological interaction networks and their phylogenetic history. 3. We demonstrate the functionality of paco through its application to empirical host-parasite and plant-pollinator communities 4. Although the package is intended to assess phylogenetic congruence between groups of interacting species, the method is also directly applicable to other scenarios that may show phylogenetic congruence including historical biogeography, molecular systematics, and cultural evolution.
Data from: The genetic inheritance of the blue-eyed white phenotype in alpacas (Vicugna pacos)
Open the record for dataset details and reuse information.
Data from: paco: implementing Procrustean Approach to Cophylogeny in R
Open the record for dataset details and reuse information.
The PACO Project: A Clinical Study of a PAtient COach Program in Vulnerable Lung Cancer Patients
ClinicalTrials.gov study NCT02686775. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Investigation of the EtCO₂- PaCO₂ Relation During Laparoscopic Colon Surgery
ClinicalTrials.gov study NCT01707511. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Planck-ATCA Co-eval Observations (PACO) Project Bright Sample Catalog
The Planck Australia Telescope Compact Array (Planck-ATCA) Co-eval Observations (PACO) have provided flux density measurements of well-defined samples of Australia Telescope 20-GHz (AT20G) radio sources at frequencies below and overlapping with Planck frequency bands, almost simultaneously with Planck observations. The authors have observed with the ATCA a total of 482 sources in the frequency range between 4.5 and 40 GHz in the period between 2009 July and 2010 August. Several sources were observed more than once. In their paper, the authors present the aims of the project, the selection criteria, and the observation and data reduction procedures. They also discuss the data in total intensity for a complete sample of 189 sources with 20-GHz flux densities > 500 mJy, Galactic latitude |b| > 5 degrees and Declination < -30 degrees, and some statistical analysis of the spectral behavior and variability of this sample, referred to as the 'bright PACO sample'. Finally, the authors discuss how these data could be used to transfer absolute calibrations to ground-based telescopes using the cosmic microwave background dipole calibrated flux densities measured by the Planck satellite, and they provide some test fluxes on bright calibrators. This table contains the catalog of 1004 observations of 180 of the 189 sources that comprise the 'bright PACO sample'. Thus, each row in this table corresponds to a specific observation of a source, and there can be several rows for any source, corresponding to different observations. The ATCA observations were made in 6 2-GHz wide observing bands: 4732 - 6780 MHz, 8232 - 10280 MHz, 17232 - 19280 MHz, 23232 - 25280 MHz, 32232 - 34280 MHz and 38232 - 40280 MHz. In order to properly define the detailed source spectral behavior, the authors have split each 2-GHz band into 4 x 512 MHz sub-bands, and calibrated each sub-band independently. Thus, for each observation, the flux density at 24 frequencies is given. The frequency identifier in the flux density appears (at least to this HEASARC scientist) to be the lower frequency of the sub-band rather than its central frequency. In order to provide the easiest way to extrapolate the observed counts or model predictions from one frequency to another, the authors have modeled the observed source spectra. As their observations covered a wide frequency range from 4.5 to 40 GHz over which a single power law is not enough to describe the spectral behavior of the sources, they studied the spectra of the 174 point-like sources in this sample by fitting the observed data with a double power law of the form S<sub>nu</sub> = S<sub>0</sub>/[(nu/nu<sub>0</sub>)<sup>-a</sup> + (nu/nu<sub>0</sub>)<sup>-b</sup>], where nu is the frequency, S<sub>nu</sub> is the flux density in Jy, and S<sub>0</sub>, nu<sub>0</sub>, a and b are free parameters. The authors considered only those sources for which they had at least four data points for each of the 2 x 2 GHz bands considered. Full details of the fitting procedure are given in Section 3.1 of the reference paper. This table was created by the HEASARC in January 2014 based on the machine-readable version of Table S1 from the reference paper which was obtained from the CDS (their catalog J/MNRAS/415/1597 file table1.dat). This is a service provided by NASA HEASARC .
Planck-ATCA Co-eval Observations (PACO) Project Faint Sample Catalog
The Planck-ATCA Co-eval Observations (PACO) project collected data between 4.5 and 40 GHz for 482 sources selected within the Australia Telescope 20-GHz (AT20G) catalog and observed with the Australia Telescope Compact Array (ATCA). Observations were done almost simultaneously with the Planck satellite, in the period between 2009 July and 2010 August. In this paper, the authors present and discuss the data for the complete sample of 159 sources with AT20G flux densities > 200 mJy in the South Ecliptic Pole (SEP) region. The Planck Early Release Compact Source Catalogue (ERCSC) contains 57 of their sources. A comparison between the PACO catalog and the ERCSC confirms that the reliability of the latter is better than 95%. The missing ERCSC sources are typically associated with the Large Magellanic Cloud, the Milky Way or are otherwise extended. The spectral analysis of the PACO faint catalog shows a spectral steepening of the sources at high frequencies, confirming the results obtained from the PACO bright sample (the HEASARC PACOBSCAT table). A comparison with AT20G measurements, carried out, on average, a few years earlier, has demonstrated that, on these time-scales, these sources show a rather high variability with an rms amplitude of approximately 40% at 20 GHz. The source spectral properties are found not to vary substantially with flux density, except for an increase in the fraction of steep spectrum sources at fainter flux densities. These data also allow the authors to extend by a factor of ~ 5 downwards in flux density the source counts at ~ 33 and ~ 40 GHz obtained from the ERCSC. This allows the authors to substantially improve their control on the contribution of unresolved extragalactic sources to the power spectrum of small-scale fluctuations in cosmic microwave background (CMB) maps. The PACO faint sample, presented in this paper, is made up of 159 sources with 20-GHz flux densities >= 200 mJy in the SEP region (ecliptic latitude < -75 degrees) and with 3h < RA < 9h, Dec. < -30 degrees. Near the Ecliptic Poles, Planck's scan circles intersect. Therefore, the area is covered many times, and Planck's sensitivity is maximal in these regions. A full description of the PACO project and of its main goals is given in Massardi et al. (2011, MNRAS, 415, 1597). The aims specific to the PACO faint sample are as follows: (i) Extend to fainter flux densities the characterization of radio source spectra from 4.5 GHz to the Planck frequency range; (ii) Extend the determination of source counts at ~ 33 and ~ 40 GHz obtained from the analysis of the ERCSC downwards in flux density by a factor of ~ 5. Going down in flux density is important to control the contamination of CMB maps by faint radio sources. This table contains the catalog of 674 observations of 152 of the 159 sources that comprise the 'faint PACO sample'. Thus, each row in this table corresponds to a specific observation of a source, and there can be several rows for any source, corresponding to different observations. The ATCA observations were made in 6 2-GHz wide observing bands: 4732 - 6780 MHz, 8232 - 10280 MHz, 17232 - 19280 MHz, 23232 - 25280 MHz, 32232 - 34280 MHz and 38232 - 40280 MHz. In order to properly define the detailed source spectral behavior, the authors have split each 2-GHz band into 4 x 512 MHz sub-bands, and calibrated each sub-band independently. Thus, for each observation, the flux density at 24 frequencies is given. The frequency identifier in the flux density appears (at least to this HEASARC scientist) to be the lower frequency of the sub-band rather than its central frequency. In order to provide the easiest way to extrapolate the observed counts or model predictions from one frequency to another, the authors have modeled the observed source spectra. As their observations covered a wide frequency range from 4.5 to 40 GHz over which a single power law is not enough to describe the spectral behavior of the sources, they studied the spectra of the 174 point-like sources in this sample by fitting the observed data with a double power law of the form S<sub>nu</sub> = S<sub>0</sub>/[(nu/nu<sub>0</sub>)<sup>-a</sup> + (nu/nu<sub>0</sub>)<sup>-b</sup>], where nu is the frequency, S<sub>nu</sub> is the flux density in Jy, and S<sub>0</sub>, nu<sub>0</sub>, a and b are free parameters. The authors considered only those sources for which they had at least four data points for each of the 2 x 2 GHz bands considered. When observations at more than one epoch were available, the authors chose the one with the greatest number of data points. Full details of the fitting procedure are given in Section 3.1 of Massardi et al. (2011, MNRAS, 415, 1597) and Section 4 of the reference paper. This table was created by the HEASARC in January 2014 based on the machine-readable version of the Paco faint cata
Dataset related to the article "Comparison between PtCO 2 and PaCO 2 and Derived Parameters in Heart Failure Patients during Exercise: A Preliminary Study"
<p>Abstract</p> <p>Evaluation of arterial carbon dioxide pressure (PaCO<sub>2</sub>) and dead space to tidal volume ratio (V<sub>D</sub>/V<sub>T</sub>) during exercise is important for the identification of exercise limitation causes in heart failure (HF). However, repeated sampling of arterial or arterialized ear lobe capillary blood may be clumsy. The aim of our study was to estimate PaCO<sub>2</sub> by means of a non-invasive technique, transcutaneous PCO<sub>2</sub> (PtCO<sub>2</sub>), and to verify the correlation between PtCO<sub>2</sub> and PaCO<sub>2</sub> and between their derived parameters, such as V<sub>D</sub>/V<sub>T</sub>, during exercise in HF patients. 29 cardiopulmonary exercise tests (CPET) performed on a bike with a ramp protocol aimed at achieving maximal effort in ≈10 min were analyzed. PaCO<sub>2</sub> and PtCO<sub>2</sub> values were collected at rest and every 2 min during active pedaling. The uncertainty of PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> measurements were determined by analyzing the error between the two methods. The accuracy of PtCO<sub>2</sub> measurements vs. PaCO<sub>2</sub> decreases towards the end of exercise. Therefore, a correction to PtCO<sub>2</sub> that keeps into account the time of the measurement was implemented with a multiple regression model. PtCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes at 6, 8 and 10 min vs. 2 min data were evaluated before and after PtCO<sub>2</sub> correction. PtCO<sub>2</sub> overestimates PaCO<sub>2</sub> for high timestamps (median error 2.45, IQR -0.635-5.405, at 10 min vs. 2 min, <em>p</em>-value = 0.011), while the error is negligible after correction (median error 0.50, IQR = -2.21-3.19, <em>p</em>-value > 0.05). The correction allows removing differences also in PCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub> changes. In HF patients PtCO<sub>2</sub> is a reliable PaCO<sub>2</sub> estimation at rest and at low exercise intensity. At high exercise intensity the overall response appears delayed but reproducible and the error can be overcome by mathematical modeling allowing an accurate estimation by PtCO<sub>2</sub> of PaCO<sub>2</sub> and V<sub>D</sub>/V<sub>T</sub>.</p>
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