The AXAF technology program: The optical flats tests

The results of a technology program aimed at determining the limits of surface polishing for reflecting X-ray telescopes is presented. This program is part of the major task of developing the Advanced X-ray Astrophysical Facility (AXAF). By studying the optical properties of state-of-the-art polished flat surfaces, conclusions were drawn as to the potential capability of AXAF. Surface microtopography of the flats as well as their figure are studied by X-ray, visual, and mechanical techniques. These techniques and their results are described. The employed polishing techniques are more than adequate for the specifications of the AXAF mirrors

Interferon-γ-induced Regulation of Peroxisome Proliferator-activated Receptor γ and STATs in Adipocytes

Interferon-γ (IFN-γ) is known primarily for its roles in immunological responses but also has been shown to affect fat metabolism and adipocyte gene expression. To further investigate the effects of IFN-γ on fat cells, we examined the effects of this cytokine on the expression of adipocyte transcription factors in 3T3-L1 adipocytes. Although IFN-γ regulated the expression of several adipocyte transcription factors, IFN-γ treatment resulted in a rapid reduction of both peroxisome proliferator-activated receptor (PPAR) protein and mRNA. A 48-h exposure to IFN-γ also resulted in a decrease of both CCAAT/enhancer-binding α and sterol regulatory element binding protein (SREBP-1) expression. The short half-life of both the PPARγ mRNA and protein likely contributed to the rapid decline of both cytosolic and nuclear PPARγ in the presence of IFN-γ. Our studies clearly demonstrated that the IFN-γ-induced loss of PPARγ protein is partially inhibited in the presence of two distinct proteasome inhibitors. Moreover, IFN-γ also inhibited the transcription of PPARγ, which was accompanied by a decrease in PPARγ mRNA accumulation. In addition, exposure to IFN-γ resulted in a substantial increase in STAT I expression and a small increase in STAT 3 expression. IFN-γ treatment of 3T3-L1 adipocytes (48-96 h) resulted in a substantial inhibition of insulin-sensitive glucose uptake. These data clearly demonstrate that IFN-γ treatment results in the development of insulin resistance, which is accompanied by the regulation of various adipocyte transcription factors, in particular the synthesis and degradation of PPARγ

The tegula tango: A coevolutionary dance of interacting, positively selected sperm and egg proteins

Reproductive proteins commonly show signs of rapid divergence driven by positive selection. The mechanisms driving these changes have remained ambiguous in part because interacting male and female proteins have rarely been examined. We isolate an egg protein the vitelline envelope receptor for lysin (VERL) from Tegula, a genus of free-spawning marine snails. Like VERL from abalone, Tegula VERL is a major component of the VE surrounding the egg, includes a conserved zona pellucida (ZP) domain at its C-terminus, and possesses a unique, negatively charged domain of about 150 amino acids implicated in interactions with the positively charged lysin. Unlike for abalone VERL, where this unique VERL domain occurs in a tandem array of 22 repeats, Tegula VERL has just one such domain. Interspecific comparisons show that both lysin and the VERL domain diverge via positive selection, whereas the ZP domain evolves neutrally. Rates of nonsynonymous substitution are correlated between lysin and the VERL domain, consistent with sexual antagonism, although lineage-specific effects, perhaps owing to different ecologies, may alter the relative evolutionary rates of sperm- and egg-borne proteins. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution

American Society of Clinical Oncology Clinical Practice Guideline Update on Chemotherapy for Stage IV Non–Small-Cell Lung Cancer

The purpose of this article is to provide updated recommendations for the treatment of patients with stage IV non–small-cell lung cancer. A literature search identified relevant randomized trials published since 2002. The scope of the guideline was narrowed to chemotherapy and biologic therapy. An Update Committee reviewed the literature and made updated recommendations. One hundred sixty-two publications met the inclusion criteria. Recommendations were based on treatment strategies that improve overall survival. Treatments that improve only progression-free survival prompted scrutiny of toxicity and quality of life. For first-line therapy in patients with performance status of 0 or 1, a platinum-based two-drug combination of cytotoxic drugs is recommended. Nonplatinum cytotoxic doublets are acceptable for patients with contraindications to platinum therapy. For patients with performance status of 2, a single cytotoxic drug is sufficient. Stop first-line cytotoxic chemotherapy at disease progression or after four cycles in patients who are not responding to treatment. Stop two-drug cytotoxic chemotherapy at six cycles even in patients who are responding to therapy. The first-line use of gefitinib may be recommended for patients with known epidermal growth factor receptor (EGFR) mutation; for negative or unknown EGFR mutation status, cytotoxic chemotherapy is preferred. Bevacizumab is recommended with carboplatin-paclitaxel, except for patients with certain clinical characteristics. Cetuximab is recommended with cisplatin-vinorelbine for patients with EGFR-positive tumors by immunohistochemistry. Docetaxel, erlotinib, gefitinib, or pemetrexed is recommended as second-line therapy. Erlotinib is recommended as third-line therapy for patients who have not received prior erlotinib or gefitinib. Data are insufficient to recommend the routine third-line use of cytotoxic drugs. Data are insufficient to recommend routine use of molecular markers to select chemotherapy

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead