Variability in the stellar initial mass function at low and high mass: 3-component IMF models

Three component models of the IMF are made to consider possible origins for the observed relative variations in the numbers of brown dwarfs, solar-to-intermediate mass stars, and high mass stars. Three distinct physical processes are noted. The characteristic mass for most star formation is identified with the thermal Jeans mass in the molecular cloud core, and this presumably leads to the middle mass range by the usual collapse and accretion processes. Pre-stellar condensations (PSCs) observed in mm-wave continuum studies presumably form at this mass. Significantly smaller self-gravitating masses require much larger pressures and may arise following dynamical processes inside these PSCs, including disk formation, tight-cluster ejection, and photoevaporation as studied elsewhere, but also gravitational collapse of shocked gas in colliding PSCs. Significantly larger stellar masses form in relatively low abundance by normal cloud processes, possibly leading to steep IMFs in low-pressure field regions, but this mass range can be significantly extended in high pressure cloud cores by gravitationally-focussed gas accretion onto PSCs and by the coalescence of PSCs. These models suggest that the observed variations in brown dwarf, solar-to-intermediate mass, and high mass populations are the result of dynamical effects that depend on environmental density and velocity dispersion. They accommodate observations ranging from shallow IMFs in cluster cores to Salpeter IMFs in average clusters and whole galaxies to steep and even steeper IMFs in field and remote field regions. They also suggest how the top-heavy IMFs in some starburst clusters may originate and they explain bottom-heavy IMFs in low surface brightness galaxies.Comment: 10 pages, 2 figures, accepted by Monthly Notices of the Royal Astronomical Societ

BriX: a database of protein building blocks for structural analysis, modeling and design

High-resolution structures of proteins remain the most valuable source for understanding their function in the cell and provide leads for drug design. Since the availability of sufficient protein structures to tackle complex problems such as modeling backbone moves or docking remains a problem, alternative approaches using small, recurrent protein fragments have been employed. Here we present two databases that provide a vast resource for implementing such fragment-based strategies. The BriX database contains fragments from over 7000 non-homologous proteins from the Astral collection, segmented in lengths from 4 to 14 residues and clustered according to structural similarity, summing up to a content of 2 million fragments per length. To overcome the lack of loops classified in BriX, we constructed the Loop BriX database of non-regular structure elements, clustered according to end-to-end distance between the regular residues flanking the loop. Both databases are available online (http://brix.crg.es) and can be accessed through a user-friendly web-interface. For high-throughput queries a web-based API is provided, as well as full database downloads. In addition, two exciting applications are provided as online services: (i) user-submitted structures can be covered on the fly with BriX classes, representing putative structural variation throughout the protein and (ii) gaps or low-confidence regions in these structures can be bridged with matching fragments

Three-Dimensional Structure of N-Terminal Domain of DnaB Helicase and Helicase-Primase Interactions in Helicobacter pylori

Replication initiation is a crucial step in genome duplication and homohexameric DnaB helicase plays a central role in the replication initiation process by unwinding the duplex DNA and interacting with several other proteins during the process of replication. N-terminal domain of DnaB is critical for helicase activity and for DnaG primase interactions. We present here the crystal structure of the N-terminal domain (NTD) of H. pylori DnaB (HpDnaB) helicase at 2.2 Å resolution and compare the structural differences among helicases and correlate with the functional differences. The structural details of NTD suggest that the linker region between NTD and C-terminal helicase domain plays a vital role in accurate assembly of NTD dimers. The sequence analysis of the linker regions from several helicases reveals that they should form four helix bundles. We also report the characterization of H. pylori DnaG primase and study the helicase-primase interactions, where HpDnaG primase stimulates DNA unwinding activity of HpDnaB suggesting presence of helicase-primase cohort at the replication fork. The protein-protein interaction study of C-terminal domain of primase and different deletion constructs of helicase suggests that linker is essential for proper conformation of NTD to interact strongly with HpDnaG. The surface charge distribution on the primase binding surface of NTDs of various helicases suggests that DnaB-DnaG interaction and stability of the complex is most probably charge dependent. Structure of the linker and helicase-primase interactions indicate that HpDnaB differs greatly from E.coli DnaB despite both belong to gram negative bacteria

The TERT rs2736100 Polymorphism and Cancer Risk: A Meta-analysis Based on 25 Case-Control Studies

<p>Abstract</p> <p>Background</p> <p>The association between the <it>TERT rs2736100 </it>single nucleotide polymorphism (SNP) and cancer risk has been studied by many researchers, but the results remain inconclusive. To further explore this association, we performed a meta-analysis.</p> <p>Methods</p> <p>A computerized search of PubMed and Embase database for publications on the <it>TERT rs2736100 </it>polymorphism and cancer risk was performed and the genotype data were analyzed in a meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis and assessment of bias were performed in our meta-analysis.</p> <p>Results</p> <p>A significant association between the <it>TERT rs2736100 </it>polymorphism and cancer susceptibility was revealed by the results of the meta-analysis of the 25 case-control studies (GG versus TT: OR = 1.72, 95% CI: 1.58, 1.88; GT versus TT: OR = 1.38, 95% CI: 1.29, 1.47; dominant model-TG + GG versus TT: OR = 1.47, 95% CI: 1.37, 1.58; recessive model-GG versus TT + TG: OR = 1.37, 95% CI 1.31, 1.43; additive model-2GG + TG versus 2TT + TG: OR = 1.30, 95% CI: 1.25, 1.36). Moreover, increased cancer risk in all genetic models was found after stratification of the SNP data by cancer type, ethnicity and source of controls.</p> <p>Conclusions</p> <p>In all genetic models, the association between the <it>TERT rs2736100 </it>polymorphism and cancer risk was significant. This meta-analysis suggests that the <it>TERT rs2736100 </it>polymorphism may be a risk factor for cancer. Further functional studies between this polymorphism and cancer risk are warranted.</p

Mining protein loops using a structural alphabet and statistical exceptionality

<p>Abstract</p> <p>Background</p> <p>Protein loops encompass 50% of protein residues in available three-dimensional structures. These regions are often involved in protein functions, e.g. binding site, catalytic pocket... However, the description of protein loops with conventional tools is an uneasy task. Regular secondary structures, helices and strands, have been widely studied whereas loops, because they are highly variable in terms of sequence and structure, are difficult to analyze. Due to data sparsity, long loops have rarely been systematically studied.</p> <p>Results</p> <p>We developed a simple and accurate method that allows the description and analysis of the structures of short and long loops using structural motifs without restriction on loop length. This method is based on the structural alphabet HMM-SA. HMM-SA allows the simplification of a three-dimensional protein structure into a one-dimensional string of states, where each state is a four-residue prototype fragment, called structural letter. The difficult task of the structural grouping of huge data sets is thus easily accomplished by handling structural letter strings as in conventional protein sequence analysis. We systematically extracted all seven-residue fragments in a bank of 93000 protein loops and grouped them according to the structural-letter sequence, named structural word. This approach permits a systematic analysis of loops of all sizes since we consider the structural motifs of seven residues rather than complete loops. We focused the analysis on highly recurrent words of loops (observed more than 30 times). Our study reveals that 73% of loop-lengths are covered by only 3310 highly recurrent structural words out of 28274 observed words). These structural words have low structural variability (mean RMSd of 0.85 Å). As expected, half of these motifs display a flanking-region preference but interestingly, two thirds are shared by short (less than 12 residues) and long loops. Moreover, half of recurrent motifs exhibit a significant level of amino-acid conservation with at least four significant positions and 87% of long loops contain at least one such word. We complement our analysis with the detection of statistically over-represented patterns of structural letters as in conventional DNA sequence analysis. About 30% (930) of structural words are over-represented, and cover about 40% of loop lengths. Interestingly, these words exhibit lower structural variability and higher sequential specificity, suggesting structural or functional constraints.</p> <p>Conclusions</p> <p>We developed a method to systematically decompose and study protein loops using recurrent structural motifs. This method is based on the structural alphabet HMM-SA and not on structural alignment and geometrical parameters. We extracted meaningful structural motifs that are found in both short and long loops. To our knowledge, it is the first time that pattern mining helps to increase the signal-to-noise ratio in protein loops. This finding helps to better describe protein loops and might permit to decrease the complexity of long-loop analysis. Detailed results are available at <url>http://www.mti.univ-paris-diderot.fr/publication/supplementary/2009/ACCLoop/</url>.</p

β1-integrins signaling and mammary tumor progression in transgenic mouse models: implications for human breast cancer

Consistent with their essential role in cell adhesion to the extracellular matrix, integrins and their associated signaling pathways have been shown to be involved in cell proliferation, migration, invasion and survival, processes required in both tumorigenesis and metastasis. β1-integrins represent the predominantly expressed integrins in mammary epithelial cells and have been proven crucial for mammary gland development and differentiation. Here we provide an overview of the studies that have used transgenic mouse models of mammary tumorigenesis to establish β1-integrin as a critical mediator of breast cancer progression and thereby as a potential therapeutic target for the development of new anticancer strategies

Measurement of the WZ production cross section in pp collisions at root s=7 and 8 TeV and search for anomalous triple gauge couplings at root s=8 TeV

Peer reviewe