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Glioblastomas (GBMs) are malignant brain tumors that can be divided into different molecular subtypes based on genetics, global gene expression, and methylation patterns. Among these subgroups, "IDH" GBMs carry mutations within IDH1 or IDH2 The "K27" and "G34" subgroups are characterized by distinct mutations within Histone 3 (H3). These subtypes can be identified by sequencing methods and are particularly found in younger patients. To determine whether the molecular subtypes correlate with distinct histological features among the diverse histologic patterns of GBM, we performed a blinded assessment of the histology of GBMs of 77 patients ≤30 years old at the time of biopsy. The tumors were of the following molecular subtypes: IDH (n = 12), H3 K27M (n = 25), H3 G34R (n = 12), or no IDH/H3 mutations (n = 28). Of IDH-mutated cases, 75% had microcystic features or gemistocytic tumor cells. K27 GBMs had higher cell densities and pronounced nuclear pleomorphism, with 28% harboring tumor giant cells. All G34 GBMs had variable extents of a poorly differentiated/primitive neuroectodermal tumor-like morphology. GBMs without IDH/H3 mutations had foci of epitheliod-appearing cells. Thus, molecular GBM subgroups are associated with distinct histological patterns, suggesting that morphological features reflect the specific underlying molecular genetic abnormalities., (© 2016 American Association of Neuropathologists, Inc. All rights reserved.)

Universally conserved positions in ribosomal proteins have significant biases in amino acid usage, likely indicating the expansion of the genetic code at the time leading up to the most recent common ancestor(s) (MRCA). Here, we apply this principle to the evolutionary history of the ribosome before the MRCA. It has been proposed that the experimentally determined order of assembly for ribosomal subunits recapitulates their evolutionary chronology. Given this model, we produce a probabilistic evolutionary ordering of the universally conserved small subunit (SSU) and large subunit (LSU) ribosomal proteins. Optimizing the relative ordering of SSU and LSU evolutionary chronologies with respect to minimizing differences in amino acid usage bias, we find strong compositional evidence for a more ancient origin for early LSU proteins. Furthermore, we find that this ordering produces several trends in specific amino acid usages compatible with models of genetic code evolution.

Promoting cessation is a cornerstone of tobacco control efforts by public-health agencies. Economic information to support cessation programs has generally emphasized cost-effectiveness or the impact of cigarette pricing and smoking restrictions on quit rates. In contrast, this study provides empirical estimates of smoker preferences for increased efficacy and other attributes of smoking cessation therapies (SCTs). Choice data were collected through a national survey of Canadian smokers. We find systematic preference heterogeneity for therapy types and SCT attributes between light and heavy smokers, as well as random heterogeneity using random parameters logit models. Preference heterogeneity is greatest between length of use and types of SCTs. We estimate that light smokers would be willing to pay nearly $500 ($CAN) to increase success rates to 40% with the comparable figure for heavy smokers being near $300 ($CAN). Results from this study can be used to inform research and development for smoking cessation products and programs and suggest important areas of future inquiry regarding heterogeneity of smoker preferences and preferences for other health programs.

Section 812 of the Clean Air Act Amendments (CAAA) of 1990 requires the U.S. Environmental Protection Agency (EPA) to perform periodic, comprehensive analyses of the total costs and total benefits of programs implemented pursuant to the CAAA. The first prospective analysis was completed in 1999. The second prospective analysis was initiated during 2005. The first step in the second prospective analysis was the development of base and projection year emission estimates that will be used to generate benefit estimates of CAAA programs. This paper describes the analysis, methods, and results of the recently completed emission projections. There are several unique features of this analysis. One is the use of consistent economic assumptions from the Department of Energy's Annual Energy Outlook 2005 (AEO 2005) projections as the basis for estimating 2010 and 2020 emissions for all sectors. Another is the analysis of the different emissions paths for both with and without CAAA scenarios. Other features of this analysis include being the first EPA analysis that uses the 2002 National Emission Inventory files as the basis for making 48-state emission projections, incorporating control factor files from the Regional Planning Organizations (RPOs) that had completed emission projections at the time the analysis was performed, and modeling the emission benefits of the expected adoption of measures to meet the 8-hr ozone National Ambient Air Quality Standards (NAAQS), the Clean Air Visibility Rule, and the PM2.5 NAAQS. This analysis shows that the 1990 CAAA have produced significant reductions in criteria pollutant emissions since 1990 and that these emission reductions are expected to continue through 2020. CAAA provisions have reduced volatile organic compound (VOC) emissions by approximately 7 million t/yr by 2000, and are estimated to produce associated VOC emission reductions of 16.7 million t by 2020. Total oxides of nitrogen (NO(x)) emission reductions attributable to the CAAA are 5, 12, and 17 million t in 2000, 2010, and 2020, respectively. Sulfur dioxide (SO2) emission benefits during the study period are dominated by electricity-generating unit (EGU) SO2 emission reductions. These EGU emission benefits go from 7.5 million t reduced in 2000 to 15 million t reduced in 2020.