40 research outputs found

    Myocardial extravascular extracellular volume fraction measurement by gadolinium cardiovascular magnetic resonance in humans: slow infusion versus bolus

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    <p>Abstract</p> <p>Background</p> <p>Myocardial extravascular extracellular volume fraction (Ve) measures quantify diffuse fibrosis not readily detectable by conventional late gadolinium (Gd) enhancement (LGE). Ve measurement requires steady state equilibrium between plasma and interstitial Gd contrast. While a constant infusion produces steady state, it is unclear whether a simple bolus can do the same. Given the relatively slow clearance of Gd, we hypothesized that a bolus technique accurately measures Ve, thus facilitating integration of myocardial fibrosis quantification into cardiovascular magnetic resonance (CMR) workflow routines. Assuming equivalence between techniques, we further hypothesized that Ve measures would be reproducible across scans.</p> <p>Methods</p> <p>In 10 volunteers (ages 20-81, median 33 yr, 3 females), we compared serial Ve measures from a single short axis slice from two scans: first, during a constant infusion, and second, 12-50 min after a bolus (0.2 mmol/kg gadoteridol) on another day. Steady state during infusion was defined when serial blood and myocardial T1 data varied <5%. We measured T1 on a 1.5 T Siemens scanner using a single-shot modified Look Locker inversion recovery sequence (MOLLI) with balanced SSFP. To shorten breath hold times, T1 values were measured with a shorter sampling scheme that was validated with spin echo relaxometry (TR = 15 sec) in CuSO4-Agar phantoms. Serial infusion vs. bolus Ve measures (n = 205) from the 10 subjects were compared with generalized estimating equations (GEE) with exchangeable correlation matrices. LGE images were also acquired 12-30 minutes after the bolus.</p> <p>Results</p> <p>No subject exhibited LGE near the short axis slices where Ve was measured. The Ve range was 19.3-29.2% and 18.4-29.1% by constant infusion and bolus, respectively. In GEE models, serial Ve measures by constant infusion and bolus did not differ significantly (difference = 0.1%, p = 0.38). For both techniques, Ve was strongly related to age (p < 0.01 for both) in GEE models, even after adjusting for heart rate. Both techniques identically sorted older individuals with higher mean Ve values.</p> <p>Conclusion</p> <p>Myocardial Ve can be measured reliably and accurately 12-50 minutes after a simple bolus. Ve measures are also reproducible across CMR scans. Ve estimation can be integrated into CMR workflow easily, which may simplify research applications involving the quantification of myocardial fibrosis.</p

    Meta-analysis of pharmacogenetic interactions in amyotrophic lateral sclerosis clinical trials

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    OBJECTIVE: To assess whether genetic subgroups in recent amyotrophic lateral sclerosis (ALS) trials responded to treatment with lithium carbonate, but that the treatment effect was lost in a large cohort of nonresponders. METHODS: Individual participant data were obtained from 3 randomized trials investigating the efficacy of lithium carbonate. We matched clinical data with data regarding the UNC13A and C9orf72 genotype. Our primary outcome was survival at 12 months. On an exploratory basis, we assessed whether the effect of lithium depended on the genotype. RESULTS: Clinical data were available for 518 of the 606 participants. Overall, treatment with lithium carbonate did not improve 12-month survival (hazard ratio [HR] 1.0, 95% confidence interval [CI] 0.7-1.4; p = 0.96). Both the UNC13A and C9orf72 genotype were independent predictors of survival (HR 2.4, 95% CI 1.3-4.3; p = 0.006 and HR 2.5, 95% CI 1.1-5.2; p = 0.032, respectively). The effect of lithium was different for UNC13A carriers (p = 0.027), but not for C9orf72 carriers (p = 0.22). The 12-month survival probability for UNC13A carriers treated with lithium carbonate improved from 40.1% (95% CI 23.2-69.1) to 69.7% (95% CI 50.4-96.3). CONCLUSIONS: This study incorporated genetic data into past ALS trials to determine treatment effects in a genetic post hoc analysis. Our results suggest that we should reorient our strategies toward finding treatments for ALS, start focusing on genotype-targeted treatments, and standardize genotyping in order to optimize randomization and analysis for future clinical trials

    Spatially-coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: The NASA ACTIVATE dataset

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    The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol-cloud-meteorology interactions. An HU-25 Falcon and King Air conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes

    Social Bonding and Nurture Kinship: Compatibility between Cultural and Biological Approaches

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    Trafficking of Kv1.4 potassium channels: interdependence of a pore region determinant and a cytoplasmic C-terminal VXXSL determinant in regulating cell-surface trafficking.

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    Kv1.4 and Kv1.1 potassium channel homomers have been shown to exhibit different intracellular trafficking programmes and cell-surface expression levels in cell lines: a determinant in the pore region of Kv1.4 and Kv1.1 [Zhu, Watanabe, Gomez and Thornhill (2001) J. Biol. Chem. 276, 39419-39427] and a cytoplasmic C-terminal VXXSL determinant on Kv1.4 [Li, Takimoto and Levitan (2000) J. Biol. Chem. 275, 11597-11602] have been described, which affected trafficking and cell-surface expression levels. In the present study, we examined whether trafficking pore determinants influenced any cytoplasmic C-terminal trafficking determinant. We found that removal of VXXSL from a Kv1.4 chimaera that contained the pore of Kv1.1 did not affect cell-surface trafficking. Therefore removal of the C-terminal VXXSL of Kv1.4 inhibited protein surface levels only in the presence of the Kv1.4 pore. In contrast, truncating the cytoplasmic C-terminus of Kv1.1 or truncating a Kv1.1 chimaera with the pore of Kv1.4, had little effect on surface protein levels. Furthermore, the subregion of the Kv1.4 pore trafficking determinant that was required for the inhibitory effect of VXXSL removal was mapped to a threonine residue in the deep pore region. Therefore the Kv1.4 pore determinant affected the trafficking and cell-surface levels directed by the C-terminal VXXSL determinant. Different Kv1 trafficking programmes would affect cell-surface expression levels either positively or negatively and also cell signalling. Cells may use differential trafficking programmes of membrane proteins as a post-translational mechanism to regulate surface protein levels and cell function

    Primary total hip replacement in childhood, adolescence and young patients: Quality and outcome of clinical studies

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    Objective: The present meta-analysis illustrates relevant information about hip replacement in young patients that has been published during the past 3 decades. Material and methods: Based on a MedLine literature review a total of 95 studies were evaluated. Parameters for evaluation of study quality and outcome were implant survival rates (ISR), number of patients, indications, follow-up, surgical approaches and number of surgeons. Results: Most studies consider patient numbers &lt;50. In 33 studies one implant system was applied compared to 65 studies in which more than one system was used. Most studies include different surgical approaches. 20% of all studies contained neither the number of surgeons, nor the type of surgical approach. The overall ISR could be evaluated in 67 studies. Sufficient data about the ISR of stem and/or sockets were available in 50 papers. Conclusions: Most published studies analyzed inhomogeneous study populations; study variables vary as do the implants used for treatment.M. Jager, M. J. W. Begg, J. Ready, B. Bittersbohl, M. Millis, R. Krauspe and T. S. Thornhillhttp://portal.acm.org/citation.cfm?id=140265

    CNS Voltage-Dependent Na(+) Channel Expression and Distribution in an Undifferentiated and Differentiated CNS Cell Line

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    Upon serum removal, CAD-R1 cells undergo neurite outgrowth and an increase in voltage-dependent Na(+) current (VDNaC) density without changing their activation and inactivation properties. Insulin and endothelial cell growth supplement inhibited the increase in VDNaC density but not the neurite outgrowth. RI, RII, RIII Na(+) channel proteins were expressed in CAD-R1 cells. These proteins exhibited both similar and different distribution and clustering patterns which suggested the channel\u27s structural differences play a role in channel distribution

    CNS Voltage-Dependent Na(+) Channel Expression and Distribution in an Undifferentiated and Differentiated CNS Cell Line

    No full text
    Upon serum removal, CAD-R1 cells undergo neurite outgrowth and an increase in voltage-dependent Na(+) current (VDNaC) density without changing their activation and inactivation properties. Insulin and endothelial cell growth supplement inhibited the increase in VDNaC density but not the neurite outgrowth. RI, RII, RIII Na(+) channel proteins were expressed in CAD-R1 cells. These proteins exhibited both similar and different distribution and clustering patterns which suggested the channel\u27s structural differences play a role in channel distribution

    CNS Voltage-Dependent Na(+) Channel Expression and Distribution in an Undifferentiated and Differentiated CNS Cell Line

    No full text
    Upon serum removal, CAD-R1 cells undergo neurite outgrowth and an increase in voltage-dependent Na(+) current (VDNaC) density without changing their activation and inactivation properties. Insulin and endothelial cell growth supplement inhibited the increase in VDNaC density but not the neurite outgrowth. RI, RII, RIII Na(+) channel proteins were expressed in CAD-R1 cells. These proteins exhibited both similar and different distribution and clustering patterns which suggested the channel\u27s structural differences play a role in channel distribution
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