Submillimeter Array CO(2-1) Imaging of the NGC 6946 Giant Molecular Clouds

We present a CO(2-1) mosaic map of the spiral galaxy NGC 6946 by combining data from the Submillimeter Array and the IRAM 30 m telescope. We identify 390 giant molecular clouds (GMCs) from the nucleus to 4.5 kpc in the disk. GMCs in the inner 1 kpc are generally more luminous and turbulent, some of which have luminosities >10^6 K km/s pc^2 and velocity dispersions >10 km/s. Large-scale bar-driven dynamics likely regulate GMC properties in the nuclear region. Similar to the Milky Way and other disk galaxies, GMC mass function of NGC 6946 has a shallower slope (index>-2) in the inner region, and a steeper slope (index<-2) in the outer region. This difference in mass spectra may be indicative of different cloud formation pathways: gravitational instabilities might play a major role in the nuclear region, while cloud coalescence might be dominant in the outer disk. Finally, the NGC 6946 clouds are similar to those in M33 in terms of statistical properties, but they are generally less luminous and turbulent than the M51 clouds.Comment: Published in Ap

Theory of the "honeycomb chain-channel" reconstruction of Si(111)3x1

First-principles electronic-structure methods are used to study a structural model for Ag/Si(111)3x1 recently proposed on the basis of transmission electron diffraction data. The fully relaxed geometry for this model is far more energetically favorable than any previously proposed, partly due to the unusual formation of a Si double bond in the surface layer. The calculated electronic properties of this model are in complete agreement with data from angle-resolved photoemission and scanning tunneling microscopy.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Lett (the ugly postscript error on page 4 has now been repaired

Willman 1 - a probable dwarf galaxy with an irregular kinematic distribution

We investigate the kinematic properties and stellar population of the Galactic satellite Willman 1 (Wil 1) by combining Keck/DEIMOS spectroscopy with KPNO mosaic camera imaging. Wil 1 is an ultra-low luminosity Milky Way companion. This object lies in a region of size-luminosity space (M_V ~ -2 mag, d ~ 38 kpc, r_half ~ 20 pc) also occupied by the Galactic satellites Bo\"otes II and Segue 1 and 2, but no other known old stellar system. We use kinematic and color-magnitude criteria to identify 45 stars as possible members of Wil 1. With a systemic velocity of v_helio = -12.8 +/- 1.0 km/s, Wil 1 stars have velocities similar to those of foreground Milky Way stars. Informed by Monte-Carlo simulations, we identify 5 of the 45 candidate member stars as likely foreground contaminants. We confirm a significant spread in the abundances of the likely Wil 1 red giant branch members ([Fe/H] = -1.73 +/- 0.12 and -2.65 +/- 0.12, [Ca/Fe] = -0.4 +/- 0.18 and +0.13 +/- 0.28). This spread supports the scenario that Wil 1 is an ultra-low luminosity dwarf galaxy rather than a star cluster. Wil 1's innermost stars move with radial velocities offset by 8 km/s from its outer stars and have a velocity dispersion consistent with 0 km/s, suggesting that Wil 1 may not be in dynamical equilibrium. The combination of the foreground contamination and unusual kinematic distribution make it difficult to robustly determine the dark matter mass of Wil 1. As a result, X-ray or gamma-ray observations of Wil 1 that attempt to constrain models of particle dark matter using an equilibrium mass model are strongly affected by the systematics in the observations presented here. We conclude that, despite the unusual features in the Wil 1 kinematic distribution, evidence indicates that this object is, or at least once was, a dwarf galaxy.Comment: AJ accepted version. The primary improvements are a detailed investigation of the membership probability (Section 3.4 and new Figures 6, 7 and 8) and the revised spectroscopic [Fe/H] and [Ca/Fe] measurements of the two brightest member stars. Conclusions are unchanged from the submitted versio

Theory of Star Formation

We review current understanding of star formation, outlining an overall theoretical framework and the observations that motivate it. A conception of star formation has emerged in which turbulence plays a dual role, both creating overdensities to initiate gravitational contraction or collapse, and countering the effects of gravity in these overdense regions. The key dynamical processes involved in star formation -- turbulence, magnetic fields, and self-gravity -- are highly nonlinear and multidimensional. Physical arguments are used to identify and explain the features and scalings involved in star formation, and results from numerical simulations are used to quantify these effects. We divide star formation into large-scale and small-scale regimes and review each in turn. Large scales range from galaxies to giant molecular clouds (GMCs) and their substructures. Important problems include how GMCs form and evolve, what determines the star formation rate (SFR), and what determines the initial mass function (IMF). Small scales range from dense cores to the protostellar systems they beget. We discuss formation of both low- and high-mass stars, including ongoing accretion. The development of winds and outflows is increasingly well understood, as are the mechanisms governing angular momentum transport in disks. Although outstanding questions remain, the framework is now in place to build a comprehensive theory of star formation that will be tested by the next generation of telescopes.Comment: 120 pages, to appear in ARAA. No changes from v1 text; permission statement adde

Role of AMP-activated protein kinase in adipose tissue metabolism and inflammation

AMPK (AMP-activated protein kinase) is a key regulator of cellular and whole-body energy balance. AMPK phosphorylates and regulates many proteins concerned with nutrient metabolism, largely acting to suppress anabolic ATP-consuming pathways while stimulating catabolic ATP-generating pathways. This has led to considerable interest in AMPK as a therapeutic target for the metabolic dysfunction observed in obesity and insulin resistance. The role of AMPK in skeletal muscle and the liver has been extensively studied, such that AMPK has been demonstrated to inhibit synthesis of fatty acids, cholesterol and isoprenoids, hepatic gluconeogenesis and translation while increasing fatty acid oxidation, muscle glucose transport, mitochondrial biogenesis and caloric intake. The role of AMPK in the other principal metabolic and insulin-sensitive tissue, adipose, remains poorly characterized in comparison, yet increasing evidence supports an important role for AMPK in adipose tissue function. Obesity is characterized by hypertrophy of adipocytes and the development of a chronic sub-clinical pro-inflammatory environment in adipose tissue, leading to increased infiltration of immune cells. This combination of dysfunctional hypertrophic adipocytes and a pro-inflammatory environment contributes to insulin resistance and the development of Type 2 diabetes. Exciting recent studies indicate that AMPK may not only influence metabolism in adipocytes, but also act to suppress this pro-inflammatory environment, such that targeting AMPK in adipose tissue may be desirable to normalize adipose dysfunction and inflammation. In the present review, we discuss the role of AMPK in adipose tissue, focussing on the regulation of carbohydrate and lipid metabolism, adipogenesis and pro-inflammatory pathways in physiological and pathophysiological conditions

Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions

Logic integration of mRNA signals by an RNAi-based molecular computer

Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting