Magnetar-like X-ray Bursts from an Anomalous X-ray Pulsar

Anomalous X-ray Pulsars (AXPs) are a class of rare X-ray pulsars whose energy source has been perplexing for some 20 years. Unlike other, better understood X-ray pulsars, AXPs cannot be powered by rotation or by accretion from a binary companion, hence the designation ``anomalous.'' AXP rotational and radiative properties are strikingly similar to those of another class of exotic objects, the Soft Gamma Repeaters (SGRs). However, the defining property of SGRs, namely their low-energy gamma-ray and X-ray bursts, have heretofore not been seen in AXPs. SGRs are thought to be ``magnetars,'' young neutron stars powered by the decay of an ultra-high magnetic field. The suggestion that AXPs are magnetars has been controversial. Here we report the discovery, from the direction of AXP 1E 1048-5937, of two X-ray bursts that have many properties similar to those of SGR bursts. These events imply a close relationship between AXPs and SGRs, with both being magnetars.Comment: 14 pages, 2 figures, accepted for publication in Nature. Note: The content of this paper is embargoed until 1900 hrs London time / 1400 US Eastern Time on Sept 1

Methods for attributing land-use emissions to products

Roughly one-third of anthropogenic GHG emissions are caused by agricultural and forestry activities and land-use change (collectively, land-use emissions'). Understanding the ultimate drivers of these emissions requires attributing emissions to specific land-use activities and products. Although quantities of land-use emissions are matters of fact, the methodological choices and assumptions required to attribute those emissions to activities and products depend on research goals and data availability. In this review, we explore several possible accounting methods. Our results highlight the sensitivity of accounting to temporal distributions of emissions and the consequences of replacing spatially-explicit data with aggregate proxies such as production or harvested area data. Different accounting options emphasize different causes of land-use emissions (e.g., proximate or indirect drivers of deforestation). To support public policies that effectively balance competing objectives, analysts should carefully consider and communicate implications of accounting choices

Evolution of protein-coupled RNA dynamics during hierarchical assembly of ribosomal complexes

Assembly of 30S ribosomes involves the hierarchical addition of ribosomal proteins that progressively stabilize the folded 16S rRNA. Here, we use three-color single molecule FRET to show how combinations of ribosomal proteins uS4, uS17 and bS20 in the 16S 5' domain enable the recruitment of protein bS16, the next protein to join the complex. Analysis of real-time bS16 binding events shows that bS16 binds both native and non-native forms of the rRNA. The native rRNA conformation is increasingly favored after bS16 binds, explaining how bS16 drives later steps of 30S assembly. Chemical footprinting and molecular dynamics simulations show that each ribosomal protein switches the 16S conformation and dampens fluctuations at the interface between rRNA subdomains where bS16 binds. The results suggest that specific protein-induced changes in the rRNA dynamics underlie the hierarchy of 30S assembly and simplify the search for the native ribosome structure

Will systems biology offer new holistic paradigms to life sciences?

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms

Male breast cancer

Male breast cancer (MBC) is a rare disease representing less than 1% of all breast cancers (BC) and less than 1% of cancers in men. Age at presentation is mostly in the late 60s. MBC is recognized as an estrogen-driven disease, specifically related to hyperestrogenism. About 20% of MBC patients have family history for BC. Mutations in BRCA1 and, predominantly, BRCA2, account for approximately 10% of MBC cases. Because of its rarity, MBC is often compared with female BC (FBC). Based on age-frequency distribution, age-specific incidence rate patterns and prognostic factors profiles, MBC is considered similar to late-onset, postmenopausal estrogen/progesterone receptor positive (ER+/PR+) FBC. However, clinical and pathological characteristics of MBC do not exactly overlap FBC. Compared with FBC, MBC has been reported to occur later in life, present at a higher stage, and display lower histologic grade, with a higher proportion of ER+ and PR+ tumors. Although rare, MBC remains a substantial cause for morbidity and mortality in men, probably because of its occurrence in advanced age and delayed diagnosis. Diagnosis and treatment of MBC generally is similar to that of FBC. Men tend to be treated with mastectomy rather than breast-conserving surgery. The backbone of adjuvant therapy or palliative treatment for advanced disease is endocrine, mostly tamoxifen. Use of FBC-based therapy led to the observation that treatment outcomes for MBC are worse and that survival rates for MBC do not improve like FBC. These different outcomes may suggest a non-appropriate utilization of treatments and that different underlying pathogenetic mechanisms may exist between male and female BC

Methods in Molecular Biology

Developmental processes are inherently dynamic and understanding them requires quantitative measurements of gene and protein expression levels in space and time. While live imaging is a powerful approach for obtaining such data, it is still a challenge to apply it over long periods of time to large tissues, such as the embryonic spinal cord in mouse and chick. Nevertheless, dynamics of gene expression and signaling activity patterns in this organ can be studied by collecting tissue sections at different developmental stages. In combination with immunohistochemistry, this allows for measuring the levels of multiple developmental regulators in a quantitative manner with high spatiotemporal resolution. The mean protein expression levels over time, as well as embryo-to-embryo variability can be analyzed. A key aspect of the approach is the ability to compare protein levels across different samples. This requires a number of considerations in sample preparation, imaging and data analysis. Here we present a protocol for obtaining time course data of dorsoventral expression patterns from mouse and chick neural tube in the first 3 days of neural tube development. The described workflow starts from embryo dissection and ends with a processed dataset. Software scripts for data analysis are included. The protocol is adaptable and instructions that allow the user to modify different steps are provided. Thus, the procedure can be altered for analysis of time-lapse images and applied to systems other than the neural tube

Dusty Planetary Systems

Extensive photometric stellar surveys show that many main sequence stars show emission at infrared and longer wavelengths that is in excess of the stellar photosphere; this emission is thought to arise from circumstellar dust. The presence of dust disks is confirmed by spatially resolved imaging at infrared to millimeter wavelengths (tracing the dust thermal emission), and at optical to near infrared wavelengths (tracing the dust scattered light). Because the expected lifetime of these dust particles is much shorter than the age of the stars (>10 Myr), it is inferred that this solid material not primordial, i.e. the remaining from the placental cloud of gas and dust where the star was born, but instead is replenished by dust-producing planetesimals. These planetesimals are analogous to the asteroids, comets and Kuiper Belt objects (KBOs) in our Solar system that produce the interplanetary dust that gives rise to the zodiacal light (tracing the inner component of the Solar system debris disk). The presence of these "debris disks" around stars with a wide range of masses, luminosities, and metallicities, with and without binary companions, is evidence that planetesimal formation is a robust process that can take place under a wide range of conditions. This chapter is divided in two parts. Part I discusses how the study of the Solar system debris disk and the study of debris disks around other stars can help us learn about the formation, evolution and diversity of planetary systems by shedding light on the frequency and timing of planetesimal formation, the location and physical properties of the planetesimals, the presence of long-period planets, and the dynamical and collisional evolution of the system. Part II reviews the physical processes that affect dust particles in the gas-free environment of a debris disk and their effect on the dust particle size and spatial distribution.Comment: 68 pages, 25 figures. To be published in "Solar and Planetary Systems" (P. Kalas and L. French, Eds.), Volume 3 of the series "Planets, Stars and Stellar Systems" (T.D. Oswalt, Editor-in-chief), Springer 201

Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework

<p>Abstract</p> <p>Background</p> <p>Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Standard analyses of SAGE data, however, ignore the fact that the probability of generating an observable tag varies across genes and between experiments. As a consequence, these analyses result in biased estimators and posterior probability intervals for gene expression levels in the transcriptome.</p> <p>Results</p> <p>Using the yeast <it>Saccharomyces cerevisiae </it>as an example, we introduce a new Bayesian method of data analysis which is based on a model of SAGE tag formation. Our approach incorporates the variation in the probability of tag formation into the interpretation of SAGE data and allows us to derive exact joint and approximate marginal posterior distributions for the mRNA frequency of genes detectable using SAGE. Our analysis of these distributions indicates that the frequency of a gene in the tag pool is influenced by its mRNA frequency, the cleavage efficiency of the anchoring enzyme (AE), and the number of informative and uninformative AE cleavage sites within its mRNA.</p> <p>Conclusion</p> <p>With a mechanistic, model based approach for SAGE data analysis, we find that inter-genic variation in SAGE tag formation is large. However, this variation can be estimated and, importantly, accounted for using the methods we develop here. As a result, SAGE based estimates of mRNA frequencies can be adjusted to remove the bias introduced by the SAGE tag formation process.</p

Towards a science of climate and energy choices

The linked problems of energy sustainability and climate change are among the most complex and daunting facing humanity at the start of the twenty-first century. This joint Nature Energy and Nature Climate Change Collection illustrates how understanding and addressing these problems will require an integrated science of coupled human and natural systems; including technological systems, but also extending well beyond the domain of engineering or even economics. It demonstrates the value of replacing the stylized assumptions about human behaviour that are common in policy analysis, with ones based on data-driven science. We draw from and engage articles in the Collection to identify key contributions to understanding non-technological factors connecting economic activity and greenhouse gas emissions, describe a multi-dimensional space of human action on climate and energy issues, and illustrate key themes, dimensions and contributions towards fundamental understanding and informed decision making