The chemical evolution of gas-rich dwarf galaxies

A numerical double burst model of the chemical evolution of gas-rich dwarf galaxies has been developed. The model is fitted to a sample of N/O, O/H, Y and gas fraction observations, where N/O and O/H are the relative abundances by number of nitrogen to oxygen and oxygen to hydrogen, respectively. Y is the abundance by mass of helium. Closed models as well as models including enriched outflow, ordinary outflow and ordinary outflow combined with inflow are considered.The bursts are assumed to be instantaneous but ordered in pairs to explain the scatter in N/O-O/H. The method of gas fraction fitting is revised, and it is found that it is very important to specify whether dwarf irregulars (dIrrs) or blue compact galaxies (BCGs) are considered. Effective enriched winds fail when fitting N/O, whereas closed models, models with ordinary winds or a combination of ordinary winds and inflow are all viable.Comment: 22 pages, 25 figures, MNRAS LaTeX forma

Organization of Physical Interactomes as Uncovered by Network Schemas

Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks

The global gas and dust budget of the Large Magellanic Cloud: AGB stars and supernovae and the impact on the ISM evolution

‘The definitive version is available at: www3.interscience.wiley.com '. Copyright Blackwell / Royal Astronomical Society. DOI: 10.1111/j.1365-2966.2009.14743.xWe report on an analysis of the gas and dust budget in the interstellar medium (ISM) of the Large Magellanic Cloud (LMC). Recent observations from the Spitzer Space Telescope enable us to study the mid-infrared dust excess of asymptotic giant branch (AGB) stars in the LMC. This is the first time we can quantitatively assess the gas and dust input from AGB stars over a complete galaxy, fully based on observations. The integrated mass-loss rate over all intermediate and high mass-loss rate carbon-rich AGB candidates in the LMC is 8.5 × 10−3 M⊙ yr−1 , up to 2.1 × 10−2 M⊙ yr−1 . This number could be increased up to 2.7 × 10−2 M⊙ yr−1 if oxygen-rich stars are included. This is overall consistent with theoretical expectations, considering the star formation rate (SFR) when these low- and intermediate-mass stars where formed, and the initial mass functions. AGB stars are one of the most important gas sources in the LMC, with supernovae (SNe), which produces about 2–4 × 10−2 M⊙ yr−1 . At the moment, the SFR exceeds the gas feedback from AGB stars and SNe in the LMC, and the current star formation depends on gas already present in the ISM. This suggests that as the gas in the ISM is exhausted, the SFR will eventually decline in the LMC, unless gas is supplied externally. Our estimates suggest 'a missing dust-mass problem' in the LMC, which is similarly found in high-z galaxies: the accumulated dust mass from AGB stars and possibly SNe over the dust lifetime (400–800 Myr) is significant less than the dust mass in the ISM. Another dust source is required, possibly related to star-forming regions.Peer reviewe

Phylogenetic Approach Reveals That Virus Genotype Largely Determines HIV Set-Point Viral Load

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases