704 research outputs found
Which lipid measurement should we monitor? An analysis of the LIPID study
OBJECTIVES: To evaluate the optimal lipid to measure in monitoring patients, we assessed three factors that influence the choice of monitoring tests: (1) clinical validity; (2) responsiveness to therapy changes and (3) the size of the long-term âsignal-to-noiseâ ratio. DESIGN: Longitudinal analyses of repeated lipid measurement over 5â
years. SETTING: Subsidiary analysis of a Long-Term Intervention with Pravastatin in Ischaemic Disease (LIPID) studyâa clinical trial in Australia, New Zealand and Finland. PARTICIPANTS: 9014 patients aged 31â75â
years with previous acute coronary syndromes. INTERVENTIONS: Patients were randomly assigned to 40â
mg daily pravastatin or placebo. PRIMARY AND SECONDARY OUTCOME MEASURES: We used data on serial lipid measurementsâat randomisation, 6â
months and 12â
months, and then annually to 5â
yearsâof total cholesterol; low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and their ratios; triglycerides; and apolipoproteins A and B and their ratio and their ability to predict coronary events. RESULTS: All the lipid measures were statistically significantly associated with future coronary events, but the associations between each of the three ratio measures (total or LDL cholesterol to HDL cholesterol, and apolipoprotein B to apolipoprotein A1) and the time to a coronary event were better than those for any of the single lipid measures. The two cholesterol ratios also ranked highly for the long-term signal-to-noise ratios. However, LDL cholesterol and non-HDL cholesterol showed the most responsiveness to treatment change. CONCLUSIONS: Lipid monitoring is increasingly common, but current guidelines vary. No single measure was best on all three criteria. Total cholesterol did not rank highly on any single criterion. However, measurements based on cholesterol subfractionsânon-HDL cholesterol (total cholesterol minus HDL cholesterol) and the two ratiosâappeared superior to total cholesterol or any of the apolipoprotein options. Guidelines should consider using non-HDL cholesterol or a ratio measure for initial treatment decisions and subsequent monitoring
Shale Investment Dashboard in Ohio Q1 and Q2 2018
This report presents findings from an investigation into shale-related investment in Ohio. The investment estimates are cumulative from January through June of 2018. Prior investments have previously been reported and are available from Cleveland State University. Subsequent reports will estimate additional investment since the date of this report
Shale Investment Dashboard in Ohio Q3 and Q4 2017
This report presents findings from an investigation into shale-related investment in Ohio. The investment estimates are cumulative from July through December of 2017. Prior investments have previously been reported and are available from Cleveland State University. Subsequent reports will estimate additional investment since the date of this report
The Economic and Fiscal Impact of a Microgrid in Downtown Cleveland, Ohio
This report relates the results of an investigation into market conditions for a proposed microgrid in downtown Cleveland, Ohio, as well the potential for additional jobs, income, and tax revenues that might accompany such an enterprise. Power interruptions have been estimated to cost commercial and industrial customers more than $100 billion each year in the United States.1 Because microgrids can reduce or eliminate power disruptions, the proposed microgrid could position Cleveland to capture growth among those industries that experience relatively greater losses when power outages occur. This includes momentary interruptions, which account for a âsubstantial portionâ2 of such costs. The improved quality, reliability, resiliency, and security associated with a Cleveland microgrid could offer a locational advantage in attracting companies for which a power interruption is particularly costly. Access to clean, distributed generation is also an attribute that is of significant interest to commercial end users
The Economic and Fiscal Impact of a Microgrid in Downtown Cleveland, Ohio
This report relates the results of an investigation into market conditions for a proposed microgrid in downtown Cleveland, Ohio, as well the potential for additional jobs, income, and tax revenues that might accompany such an enterprise. Power interruptions have been estimated to cost commercial and industrial customers more than $100 billion each year in the United States.1 Because microgrids can reduce or eliminate power disruptions, the proposed microgrid could position Cleveland to capture growth among those industries that experience relatively greater losses when power outages occur. This includes momentary interruptions, which account for a âsubstantial portionâ2 of such costs. The improved quality, reliability, resiliency, and security associated with a Cleveland microgrid could offer a locational advantage in attracting companies for which a power interruption is particularly costly. Access to clean, distributed generation is also an attribute that is of significant interest to commercial end users
Estimating HIV Medication Adherence and Persistence: Two Instruments for Clinical and Research Use
Antiretroviral therapy (ART) requires lifelong daily oral therapy. While patient characteristics associated with suboptimal ART adherence and persistence have been described in cohorts of HIV-infected persons, these factors are poor predictors of individual medication taking behaviors. We aimed to create and test instruments for the estimation of future ART adherence and persistence for clinical and research applications. Following formative work, a battery of 148 items broadly related to HIV infection and treatment was developed and administered to 181 HIV-infected patients. ART adherence and persistence were assessed using electronic monitoring for 3 months. Perceived confidence in medication taking and self-reported barriers to adherence were strongest in predicting non-adherence over time. Barriers to adherence (e.g., affordability, scheduling) were the strongest predictors of non-adherence, as well as 3- and 7-day non-persistence. A ten-item battery for prediction of these outcomes (www.med.unc.edu/ncaidstraining/adherence/for-providers) and a 30-item battery reflective of underlying psychological constructs can help identify and study individuals at risk for suboptimal ART adherence and persistence
Multiple Chemodynamic Stellar Populations of the Ursa Minor Dwarf Spheroidal Galaxy
We present a Bayesian method to identify multiple (chemodynamic) stellar
populations in dwarf spheroidal galaxies (dSphs) using velocity, metallicity,
and positional stellar data without the assumption of spherical symmetry. We
apply this method to a new Keck/DEIMOS spectroscopic survey of the Ursa Minor
(UMi) dSph. We identify 892 likely members, making this the largest UMi sample
with line-of-sight velocity and metallicity measurements. Our Bayesian method
detects two distinct chemodynamic populations with high significance
(). The metal-rich () population is
kinematically colder (radial velocity dispersion of ) and more centrally concentrated than the metal-poor () and kinematically hotter population (). Furthermore, we apply the same analysis to
an independent MMT/Hectochelle data set and confirm the existence of two
chemodynamic populations in UMi. In both data sets, the metal-rich population
is significantly flattened () and the metal-poor
population is closer to spherical (). Despite
the presence of two populations, we are unable to robustly estimate the slope
of the dynamical mass profile. We found hints for prolate rotation of order
in the MMT data set, but further observations
are required to verify this. The flattened metal-rich population invalidates
assumptions built into simple dynamical mass estimators, so we computed new
astrophysical dark matter annihilation (J) and decay profiles based on the
rounder, hotter metal-poor population and inferred
for the Keck
data set. Our results paint a more complex picture of the evolution of Ursa
Minor than previously discussed.Comment: 20 pages, 11 figures, data included. Comments welcome. Accepted to
MNRA
Nanostructural changes in cell wall pectins during strawberry fruit ripening assessed by atomic force microscopy
Rapid loss of firmness occurs during strawberry (Fragaria Ă ananassa Duch) ripening, resulting in a short shelf life and high economic losses. The disassembly of cell walls is considered the main responsible for fruit softening, being pectins extensively modified during strawberry ripening (Paniagua et al. 2014). Atomic force microscopy allows the analysis of individual polymer chains at nanostructural level with a minimal sample preparation (Morris et al., 2001). The main objective of this research was to compare pectins of green and red ripe strawberry fruits at the nanostructural level to shed light on structural changes that could be related to softening.
Cell walls from strawberry fruits were extracted and fractionated with different solvents to obtain fractions enriched in a specific component. The yield of cell wall material, as well as the amount of the different fractions, decreased in ripe fruits. CDTA and Na2CO3 fractions underwent the largest decrements, being these fractions enriched in pectins supposedly located in the middle lamella and primary cell wall, respectively. Uronic acid content also decreased significantly during ripening in both pectin fractions, but the amount of soluble pectins, those extracted with phenol:acetic acid:water (PAW) and water increased in ripe fruits. Monosaccharide composition in CDTA and Na2CO3 fractions was determined by gas chromatography. In both pectin fractions, the amount of Ara and Gal, the two most abundant carbohydrates, decreased in ripe fruits. The nanostructural characteristics of CDTA and Na2CO3 pectins were analyzed by AFM. Isolated pectic chains present in the CDTA fraction were significantly longer and more branched in samples from green fruits than those present in samples obtained from red fruit. In spite of slight differences in length distributions, Na2CO3 samples from unripe fruits displayed some longer chains at low frequency that were not detected in ripe fruits. Pectin aggregates were more frequently observed in green fruit samples from both fractions. These results support that pectic chain length and the nanostructural complexity of the pectins present in CDTA and Na2CO3 fractions diminish during strawberry fruit development, and these changes, jointly with the loss of neutral sugars, could contribute to the solubilization of pectins and fruit softening.
Paniagua et al. (2014). Ann Bot, 114: 1375-1383
Morris et al. (2001). Food Sci Tech 34: 3-10
This research was supported by FEDER EU Funds and the Ministerio de EducaciĂłn y Ciencia of Spain (grant reference AGL2011-24814)Universidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂa Tech
Unravelling the nanostructure of strawberry fruit pectins by atomic force microscopy
Atomic force microscopy (AFM) allows the analysis of individual polymers at nanostructural level with a minimal sample preparation. This technique has been used to analyse the pectin disassembly process during the ripening and postharvest storage of several fleshy fruits. In general, pectins analysed by AFM are usually visualized as isolated chains, unbranched or with a low number of branchs and, occasionally, as large aggregates. However, the exact nature of these structures is unknown. It has been suggested that pectin aggregates represent a mixture of rhamnonogalacturonan I and homogalacturonan, while isolated chains and their branches are mainly composed by polygalacturonic acid. In order to gain insight into the nature of these structures, sodium carbonate soluble pectins from ripe strawberry (Fragaria x ananassa, Duch.) fruits were subjected to enzymatic digestion with endo-Polygalacturonase M2 from Aspergillus aculeatus, and the samples visualized by AFM at different time intervals. Pectins isolated from control, non-transformed plants, and two transgenic genotypes with low level of expression of ripening-induced pectinase genes encoding a polygalacturonase (APG) or a pectate lyase (APEL) were also included in this study. Before digestion, isolated pectin chains from control were shorter than those from transgenic fruits, showing number-average (LN) contour length values of 73.2 nm vs. 95.9 nm and 91.4 nm in APG and APEL, respectively. The percentage of branched polymers was significantly higher in APG polyuronides than in the remaining genotypes, 33% in APG vs. 6% in control and APEL. As a result of the endo-PG treatment, a gradual decrease in the main backbone length of isolated chains was observed in the three samples. The minimum LN value was reached after 8 h of digestion, being similar in the three genotypes, 22 nm. By contrast, the branches were not visible after 1.5-2 h of digestion. LN values were plotted against digestion time and the data fitted to a first-order exponential decay curve, obtaining R2 values higher than 0.9. The half digestion time calculated with these equations were similar for control and APG pectins, 1.7 h, but significantly higher in APEL, 2.5 h, indicating that these polymer chains were more resistant to endo-PG digestion. Regarding the pectin aggregates, their volumes were estimated and used to calculate LN molecular weights. Before digestion, control and APEL samples showed complexes of similar molecular weights, 1722 kDa, and slightly higher than those observed in APG samples. After endo-PG digestion, size of complexes diminished significantly, reaching similar values in the three pectin samples, around 650 kDa. These results suggest that isolated polymer chains visualized by AFM are formed by a HG domain linked to a shorter polymer resistant to endo-PG digestion, maybe xylogalacturonan or RG-I. The silencing of the pectate lyase gene slightly modified the structure and/or chemical composition of polymer chains making these polyuronides more resistant to enzymatic degradation. Similarly, polygalacturonic acid is one of the main component of the aggregates.Universidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂa Tech
Autosomal Monoallelic Expression in the Mouse
Background: Random monoallelic expression defines an unusual class of genes displaying random choice for expression between the maternal and paternal alleles. Once established, the allele-specific expression pattern is stably maintained and mitotically inherited. Examples of random monoallelic genes include those found on the X-chromosome and a subset of autosomal genes, which have been most extensively studied in humans. Here, we report a genome-wide analysis of random monoallelic expression in the mouse. We used high density mouse genome polymorphism mapping arrays to assess allele-specific expression in clonal cell lines derived from heterozygous mouse strains. Results: Over 1,300 autosomal genes were assessed for allele-specific expression, and greater than 10% of them showed random monoallelic expression. When comparing mouse and human, the number of autosomal orthologs demonstrating random monoallelic expression in both organisms was greater than would be expected by chance. Random monoallelic expression on the mouse autosomes is broadly similar to that in human cells: it is widespread throughout the genome, lacks chromosome-wide coordination, and varies between cell types. However, for some mouse genes, there appears to be skewing, in some ways resembling skewed X-inactivation, wherein one allele is more frequently active. Conclusions: These data suggest that autosomal random monoallelic expression was present at least as far back as the last common ancestor of rodents and primates. Random monoallelic expression can lead to phenotypic variation beyond the phenotypic variation dictated by genotypic variation. Thus, it is important to take into account random monoallelic expression when examining genotype-phenotype correlation
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