The association of parity with osteoarthritis and knee replacement in the Multicenter Osteoarthritis Study

SummaryObjectiveWe evaluated the association of parity to both risk of knee replacement (KR) and knee osteoarthritis (OA).DesignThe NIH-funded Multicenter Osteoarthritis Study (MOST) is a longitudinal observational study of persons age 50–79 years with either symptomatic knee OA or at elevated risk of disease. Baseline and 30-month knee radiographic OA (ROA) was defined as Kellgren/Lawrence (K/L) grade ≥2 or KR. Women were grouped based by number of births: 0; 1 (reference group); 2; 3; 4; and 5 or more. We examined the relation of parity to the incidence over 30 months of ROA and KR using a Poisson regression model. Generalized estimating equations (GEE) were used to control for correlation between two knees within a subject. We adjusted for age, BMI, race, education, occupation, baseline estrogen use, clinical site, injury, and for KR analyses WOMAC pain and use of pain medication.ResultsAmong 1618 women who reported parity information, mean age was 62.6 years, mean BMI 30.7 kg/m2, mean WOMAC pain subscale score 3.7 at baseline. There were 115 KRs and 134 cases of incident knee ROA over 30 months. The relative risk of incident KR was 2.7 times as high (95% CI: 1.0, 7.3) and relative risk of incident knee ROA was 2.6 times as high (95% CI: 1.2, 5.3) among women with five to 12 children compared with those with one birth.ConclusionParity in women at risk for OA is associated with both incident ROA and KR, particularly for those with more than four children

Atenolol versus losartan in children and young adults with Marfan's syndrome

BACKGROUND : Aortic-root dissection is the leading cause of death in Marfan's syndrome. Studies suggest that with regard to slowing aortic-root enlargement, losartan may be more effective than beta-blockers, the current standard therapy in most centers. METHODS : We conducted a randomized trial comparing losartan with atenolol in children and young adults with Marfan's syndrome. The primary outcome was the rate of aortic-root enlargement, expressed as the change in the maximum aortic-root-diameter z score indexed to body-surface area (hereafter, aortic-root z score) over a 3-year period. Secondary outcomes included the rate of change in the absolute diameter of the aortic root; the rate of change in aortic regurgitation; the time to aortic dissection, aortic-root surgery, or death; somatic growth; and the incidence of adverse events. RESULTS : From January 2007 through February 2011, a total of 21 clinical centers enrolled 608 participants, 6 months to 25 years of age (mean [+/- SD] age, 11.5 +/- 6.5 years in the atenolol group and 11.0 +/- 6.2 years in the losartan group), who had an aorticroot z score greater than 3.0. The baseline-adjusted rate of change (+/- SE) in the aortic-root z score did not differ significantly between the atenolol group and the losartan group (-0.139 +/- 0.013 and -0.107 +/- 0.013 standard-deviation units per year, respectively; P = 0.08). Both slopes were significantly less than zero, indicating a decrease in the degree of aortic-root dilatation relative to body-surface area with either treatment. The 3-year rates of aortic-root surgery, aortic dissection, death, and a composite of these events did not differ significantly between the two treatment groups. CONCLUSIONS : Among children and young adults with Marfan's syndrome who were randomly assigned to losartan or atenolol, we found no significant difference in the rate of aorticroot dilatation between the two treatment groups over a 3-year period

Evaluating Quality of Service for Service Level Agreements

Quantitative analysis of quality-of-service metrics is an important tool in early evaluation of service provision. This analysis depends on being able to estimate the average duration of critical activities used by the service but at the earliest stages of service planning it may be impossible to obtain accurate estimates of the expected duration of these activities. We analyse the time-dependent behaviour of an automotive rescue service in the context of uncertainty about durations. We deploy a distributed computing platform to allow the efficient derivation of quantitative analysis results across the range of possible values for assignments of durations to the symbolic rates of our high-level formal model of the service expressed in a stochastic process algebra

Tests of sunspot number sequences: 1. Using ionosonde data

More than 70 years ago it was recognised that ionospheric F2-layer critical frequencies [foF2] had a strong relationship to sunspot number. Using historic datasets from the Slough and Washington ionosondes, we evaluate the best statistical fits of foF2 to sunspot numbers (at each Universal Time [UT] separately) in order to search for drifts and abrupt changes in the fit residuals over Solar Cycles 17-21. This test is carried out for the original composite of the Wolf/Zürich/International sunspot number [R], the new “backbone” group sunspot number [RBB] and the proposed “corrected sunspot number” [RC]. Polynomial fits are made both with and without allowance for the white-light facular area, which has been reported as being associated with cycle-to-cycle changes in the sunspot number - foF2 relationship. Over the interval studied here, R, RBB, and RC largely differ in their allowance for the “Waldmeier discontinuity” around 1945 (the correction factor for which for R, RBB and RC is, respectively, zero, effectively over 20 %, and explicitly 11.6 %). It is shown that for Solar Cycles 18-21, all three sunspot data sequences perform well, but that the fit residuals are lowest and most uniform for RBB. We here use foF2 for those UTs for which R, RBB, and RC all give correlations exceeding 0.99 for intervals both before and after the Waldmeier discontinuity. The error introduced by the Waldmeier discontinuity causes R to underestimate the fitted values based on the foF2 data for 1932-1945 but RBB overestimates them by almost the same factor, implying that the correction for the Waldmeier discontinuity inherent in RBB is too large by a factor of two. Fit residuals are smallest and most uniform for RC and the ionospheric data support the optimum discontinuity multiplicative correction factor derived from the independent Royal Greenwich Observatory (RGO) sunspot group data for the same interval

Punishing Terrorists: A Re-Examination of U.S. Federal Sentencing in the Postguidelines Era

The empirical literature on the theory and practice of sentencing politically motivated offenders such as terrorists in U.S. federal courts is limited. Thus, we know relatively little about the dealings between terrorist offenders and the criminal justice system or how these interactions may be influenced by changes in American legal or political context. This study summarizes previous findings relative to sentencing disparity among terrorists and nonterrorists in U.S. federal courts prior to the imposition of the U.S. Sentencing Guidelines. We then identify events occurring after the advent of the guidelines, including the early acts of terrorism on American soil. We evaluate the sentencing of terrorists versus nonterrorists following the confluence imposition of the guidelines and these events. We determine whether and how the sentencing disparity between terrorist and nonterrorist has changed since the implementation of the U.S. Sentencing Guidelines and the terrorist events of the early 1990s. Based on our findings, we put forth suggestions as to the possible ways these conditions may have affected sentencing outcomes.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

RELICS: Strong Lens Models for Five Galaxy Clusters from the Reionization Lensing Cluster Survey

Large scale structure and cosmolog

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio