Analytical investigation of correlated charge collection in CCDs

Correlated charge collection phenomena in CCD sensors are presently of interest due to their potentially major implications in space and ground based astronomy missions. These effects may manifest as a signal dependent Point Spread Function (PSF), or as a nonlinearity in the Photon Transfer Curve (PTC). We present the theoretical background to a simple analytical model based on previously published solutions of Poisson's equation which aims to aid conceptual understanding of how various device parameters relate to the magnitude of correlated charge collection. We separate correlated charge collection into two components - firstly excess diffusion caused by increasing drift time as the electric field in the device decreases, which is isotropic, and secondly anisotropic pixel boundary shifting as the fringing field in the parallel transfer direction collapses. Equations are presented which can be solved numerically to give reasonable detail, or solved analytically using simplifying approximations

Detection and diversity of a putative novel heterogeneous polymorphic proline-glycine repeat (Pgr) protein in the footrot pathogen Dichelobacter nodosus

Dichelobacter nodosus, a Gram-negative anaerobic bacterium, is the essential causative agent of footrot in sheep. Currently, depending on the clinical presentation in the field, footrot is described as benign or virulent; D. nodosus strains have also been classified as benign or virulent, but this designation is not always consistent with clinical disease. The aim of this study was to determine the diversity of the pgr gene, which encodes a putative proline-glycine repeat protein (Pgr). The pgr gene was present in all 100 isolates of D. nodosus that were examined and, based on sequence analysis had two variants, pgrA and pgrB. In pgrA, there were two coding tandem repeat regions, R1 and R2: different strains had variable numbers of repeats within these regions. The R1 and R2 were absent from pgrB. Both variants were present in strains from Australia, Sweden and the UK, however, only pgrB was detected in isolates from Western Australia. The pgrA gene was detected in D. nodosus from tissue samples from two flocks in the UK with virulent footrot and only pgrB from a flock with no virulent or benign footrot for >10 years. Bioinformatic analysis of the putative PgrA protein indicated that it contained a collagen-like cell surface anchor motif. These results suggest that the pgr gene may be a useful molecular marker for epidemiological studies

Definition of the σW regulon of Bacillus subtilis in the absence of stress

Bacteria employ extracytoplasmic function (ECF) sigma factors for their responses to environmental stresses. Despite intensive research, the molecular dissection of ECF sigma factor regulons has remained a major challenge due to overlaps in the ECF sigma factor-regulated genes and the stimuli that activate the different ECF sigma factors. Here we have employed tiling arrays to single out the ECF σW regulon of the Gram-positive bacterium Bacillus subtilis from the overlapping ECF σX, σY, and σM regulons. For this purpose, we profiled the transcriptome of a B. subtilis sigW mutant under non-stress conditions to select candidate genes that are strictly σW-regulated. Under these conditions, σW exhibits a basal level of activity. Subsequently, we verified the σW-dependency of candidate genes by comparing their transcript profiles to transcriptome data obtained with the parental B. subtilis strain 168 grown under 104 different conditions, including relevant stress conditions, such as salt shock. In addition, we investigated the transcriptomes of rasP or prsW mutant strains that lack the proteases involved in the degradation of the σW anti-sigma factor RsiW and subsequent activation of the σW-regulon. Taken together, our studies identify 89 genes as being strictly σW-regulated, including several genes for non-coding RNAs. The effects of rasP or prsW mutations on the expression of σW-dependent genes were relatively mild, which implies that σW-dependent transcription under non-stress conditions is not strictly related to RasP and PrsW. Lastly, we show that the pleiotropic phenotype of rasP mutant cells, which have defects in competence development, protein secretion and membrane protein production, is not mirrored in the transcript profile of these cells. This implies that RasP is not only important for transcriptional regulation via σW, but that this membrane protease also exerts other important post-transcriptional regulatory functions

Risk of high-grade serous ovarian cancer associated with pelvic inflammatory disease, parity and breast cancer

Background: Ovarian carcinoma is not a single disease, but rather a collection of subtypes with differing molecular properties and risk profiles. The most common of these, and the subject of this work, is high-grade serous ovarian carcinoma (HGSC). Methods: In this population-based study we identified a cohort of 441,382 women resident in Western Australia who had ever been admitted to hospital in the State. Of these, 454 were diagnosed with HGSC. We used Cox regression to derive hazard ratios (HRs) comparing the risk of disease in women who had each of a range of medical diagnoses and surgical procedures with women who did not. Results: We found an increased risk of HGSC associated with a diagnosis of pelvic inflammatory disease (PID) (HR 1.47, 95% CI 1.04–2.07) but not with a diagnosis of infertility or endometriosis with HRs of 1.12 (95% CI 0.73–1.71) and 0.82 (95% CI 0.55–1.22) respectively. A personal history of breast cancer was associated with a three-fold increase in the rate of HGSC. Increased parity was associated with a reduced risk of HGSC in women without a personal history of breast cancer (HR 0.57; 95% CI 0.44-0.73), but not in women with a personal history of breast cancer (HR 1.48; 95% CI 0.74–2.95). Conclusions: Our finding of an increased risk of HGSC associated with PID lends support to the hypothesis that inflammatory processes may be involved in the etiology of HGSC

A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships