Establishing Frameworks of Contentment: Income Satisfaction in Germany

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A Chromosome-Scale Assembly of the Axolotl Genome

The axolotl (Ambystoma mexicanum) provides critical models for studying regeneration, evolution, and development. However, its large genome (∼32 Gb) presents a formidable barrier to genetic analyses. Recent efforts have yielded genome assemblies consisting of thousands of unordered scaffolds that resolve gene structures, but do not yet permit large-scale analyses of genome structure and function. We adapted an established mapping approach to leverage dense SNP typing information and for the first time assemble the axolotl genome into 14 chromosomes. Moreover, we used fluorescence in situ hybridization to verify the structure of these 14 scaffolds and assign each to its corresponding physical chromosome. This new assembly covers 27.3 Gb and encompasses 94% of annotated gene models on chromosomal scaffolds. We show the assembly\u27s utility by resolving genome-wide orthologies between the axolotl and other vertebrates, identifying the footprints of historical introgression events that occurred during the development of axolotl genetic stocks, and precisely mapping several phenotypes including a large deletion underlying the cardiac mutant. This chromosome-scale assembly will greatly facilitate studies of the axolotl in biological research

Distribution of cardiovascular health by individual- and neighborhood-level socioeconomic status: Findings from the Jackson Heart Study

BACKGROUND: Data demonstrate a positive relationship between socioeconomic status (SES) and cardiovascular health (CVH). OBJECTIVE: To assess the association between individual- and neighborhood-level SES and CVH among participants of the JHS (Jackson Heart Study), a community-based cohort of African Americans in Jackson, Mississippi. METHODS: We included all JHS participants with complete SES and CVH information at the baseline study visit (n = 3,667). We characterized individual- and neighborhood-level SES according to income (primary analysis) and education (secondary analysis), respectively. The outcome of interest for these analyses was a CVH score, based on 7 modifiable behaviors and factors, summed to a total of 0 (worst) to 14 (best) points. We utilized generalized estimating equations to account for the clustering of participants within the same residential areas to estimate the linear association between SES and CVH. RESULTS: The median age of the participants was 55 years, and 64% were women. Nearly one-third of eligible participants had individual incomes \u3c$20,000 and close to 40$25,480). Adjusted for age, sex, and neighborhood SES, there was an average increase in CVH score of 0.31 points associated with each 1-category increase in individual income. Similarly, each 1-category increase in neighborhood SES was associated with a 0.19-point increase in CVH score. These patterns held for our secondary analyses, which used educational attainment in place of income. These data did not suggest a synergistic effect of individual- and neighborhood-level SES on CVH. CONCLUSIONS: Our findings suggest a potential causal pathway for disparities in CVH among vulnerable populations. These data can be useful to the JHS community to empower public health and clinical interventions and policies for the improvement of CVH

Initial Thoracic Endovascular Aortic Repair vs Medical Therapy for Acute Uncomplicated Type B Aortic Dissection

IMPORTANCE: Thoracic endovascular aortic repair (TEVAR) has increasingly been used for uncomplicated type B aortic dissection (uTBAD) despite limited supporting data. OBJECTIVE: To assess whether initial TEVAR following uTBAD is associated with reduced mortality or morbidity compared with medical therapy alone. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included Centers for Medicare & Medicaid Services inpatient claims data for adults aged 65 years or older with index admissions for acute uTBAD from January 1, 2011, to December 31, 2018, with follow-up available through December 31, 2019. EXPOSURES: Initial TEVAR was defined as TEVAR within 30 days of admission for acute uTBAD. MAIN OUTCOMES AND MEASURES: Outcomes included all-cause mortality, cardiovascular hospitalizations, aorta-related and repeated aorta-related hospitalizations, and aortic interventions associated with initial TEVAR vs medical therapy. Propensity score inverse probability weighting was used. RESULTS: Of 7105 patients with eligible index admissions for acute uTBAD, 1140 (16.0%) underwent initial TEVAR (623 [54.6%] female; median age, 74 years [IQR, 68-80 years]) and 5965 (84.0%) did not undergo TEVAR (3344 [56.1%] female; median age, 76 years [IQR, 69-83 years]). Receipt of TEVAR was associated with region (vs South; Midwest: adjusted odds ratio [aOR], 0.66 [95% CI, 0.53-0.81]; P \u3c .001; Northeast: aOR, 0.63 [95% CI, 0.50-0.79]; P \u3c .001), Medicaid dual eligibility (aOR, 0.76; 95% CI, 0.63-0.91; P = .003), hypertension (aOR, 1.26; 95% CI, 1.03-1.54; P = .03), peripheral vascular disease (aOR, 1.24; 95% CI, 1.02-1.49; P = .03), and year of admission (2012, 2013, 2014, and 2015 were associated with greater odds of TEVAR compared with 2011). After inverse probability weighting, mortality was similar for the 2 strategies up to 5 years (hazard ratio [HR], 0.95; 95% CI, 0.85-1.06), as were aorta-related hospitalizations (HR, 1.12; 95% CI, 0.99-1.27), aortic interventions (HR, 1.01; 95% CI, 0.84-1.20), and cardiovascular hospitalizations (HR, 1.05; 95% CI, 0.93-1.20). In a sensitivity analysis that included deaths within the first 30 days, initial TEVAR was associated with lower mortality over a period of 1 year (adjusted HR [aHR], 0.86; 95% CI, 0.75-0.99; P = .03), 2 years (aHR, 0.85; 95% CI, 0.75-0.96; P = .008), and 5 years (aHR, 0.87; 95% CI, 0.80-0.96; P = .004). CONCLUSIONS AND RELEVANCE: In this study, 16.0% of patients underwent initial TEVAR within 30 days of uTBAD, and receipt of initial TEVAR was associated with hypertension, peripheral vascular disease, region, Medicaid dual eligibility, and year of admission. Initial TEVAR was not associated with improved mortality or reduced hospitalizations or aortic interventions over a period of 5 years, but in a sensitivity analysis that included deaths within the first 30 days, initial TEVAR was associated with lower mortality. These findings, along with cost-effectiveness and quality of life, should be assessed in a prospective trial in the US population

Clarifying hierarchical age–period–cohort models: A rejoinder to Bell and Jones

Previously, Reither et al. (2015) demonstrated that hierarchical age–period–cohort (HAPC) models perform well when basic assumptions are satisfied. To contest this finding, Bell and Jones (2015) invent a data generating process (DGP) that borrows age, period and cohort effects from different equations in Reither et al. (2015). When HAPC models applied to data simulated from this DGP fail to recover the patterning of APC effects, B&J reiterate their view that these models provide “misleading evidence dressed up as science.” Despite such strong words, B&J show no curiosity about their own simulated data—and therefore once again misapply HAPC models to data that violate important assumptions. In this response, we illustrate how a careful analyst could have used simple descriptive plots and model selection statistics to verify that (a) period effects are not present in these data, and (b) age and cohort effects are conflated. By accounting for the characteristics of B&J's artificial data structure, we successfully recover the “true” DGP through an appropriately specified model. We conclude that B&Js main contribution to science is to remind analysts that APC models will fail in the presence of exact algebraic effects (i.e., effects with no random/stochastic components), and when collinear temporal dimensions are included without taking special care in the modeling process. The expanded list of coauthors on this commentary represents an emerging consensus among APC scholars that B&J's essential strategy—testing HAPC models with data simulated from contrived DGPs that violate important assumptions—is not a productive way to advance the discussion about innovative APC methods in epidemiology and the social sciences

Ensemble Modeling of the Likely Public Health Impact of a Pre-Erythrocytic Malaria Vaccine

Using an ensemble modeling approach, Thomas Smith and colleagues find that targeted mass vaccination with a pre-erythrocytic malaria vaccine RTS,S in low-transmission settings might have better health effects than vaccination through national EPI programs

RNA Oxidation Adducts 8-OHG and 8-OHA Change with Aβ42 Levels in Late-Stage Alzheimer's Disease

While research supports amyloid-β (Aβ) as the etiologic agent of Alzheimer's disease (AD), the mechanism of action remains unclear. Evidence indicates that adducts of RNA caused by oxidation also represent an early phenomenon in AD. It is currently unknown what type of influence these two observations have on each other, if any. We quantified five RNA adducts by gas chromatography/mass spectroscopy across five brain regions from AD cases and age-matched controls. We then used a reductive directed analysis to compare the RNA adducts to common indices of AD neuropathology and various pools of Aβ. Using data from four disease-affected brain regions (Brodmann's Area 9, hippocampus, inferior parietal lobule, and the superior and middle temporal gyri), we found that the RNA adduct 8-hydroxyguanine (8-OHG) decreased, while 8-hydroxyadenine (8-OHA) increased in AD. The cerebellum, which is generally spared in AD, did not show disease related changes, and no RNA adducts correlated with the number of plaques or tangles. Multiple regression analysis revealed that SDS-soluble Aβ42 was the best predictor of changes in 8-OHG, while formic acid-soluble Aβ42 was the best predictor of changes in 8-OHA. This study indicates that although there is a connection between AD related neuropathology and RNA oxidation, this relationship is not straightforward

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods