Evolution of Binary Stars in Multiple-Population Globular Clusters

The discovery of multiple stellar populations in globular clusters has implications for all the aspects of the study of these stellar systems. In this paper, by means of N-body simulations, we study the evolution of binary stars in multiple-population clusters and explore the implications of the initial differences in the spatial distribution of different stellar populations for the evolution and survival of their binary stars. Our simulations show that initial differences between the spatial distribution of first-generation (FG) and second-generation (SG) stars can leave a fingerprint in the current properties of the binary population. SG binaries are disrupted more efficiently than those of the FG population resulting in a global SG binary fraction smaller than that of the FG. As for surviving binaries, dynamical evolution produces a difference between the SG and the FG binary binding energy distribution with the SG population characterized by a larger fraction of high binding energy (more bound) binaries. We have also studied the dependence of the binary properties on the distance from the cluster centre. Although the global binary fraction decreases more rapidly for the SG population, the local binary fraction measured in the cluster inner regions may still be dominated by SG binaries. The extent of the differences between the surviving FG and SG binary binding energy distribution also varies radially within the cluster and is larger in the cluster inner regions.Comment: 10 pages, 12 figures. Accepted for publication in MNRA

Evolution of Binary Stars in Multiple-Population Globular Clusters - II. Compact Binaries

We present the results of a survey of N-body simulations aimed at exploring the evolution of compact binaries in multiple-population globular clusters.We show that as a consequence of the initial differences in the structural properties of the first-generation (FG) and the second-generation (SG) populations and the effects of dynamical processes on binary stars, the SG binary fraction decreases more rapidly than that of the FG population. The difference between the FG and SG binary fraction is qualitatively similar to but quantitatively smaller than that found for wider binaries in our previous investigations.The evolution of the radial variation of the binary fraction is driven by the interplay between binary segregation, ionization and ejection. Ionization and ejection counteract in part the effects of mass segregation but for compact binaries the effects of segregation dominate and the inner binary fraction increases during the cluster evolution. We explore the variation of the difference between the FG and the SG binary fraction with the distance from the cluster centre and its dependence on the binary binding energy and cluster structural parameters. The difference between the binary fraction in the FG and the SG populations found in our simulations is consistent with the results of observational studies finding a smaller binary fraction in the SG population.Comment: 9 pages, 12 figures. Accepted for publication in MNRA

The Hubble Space Telescope UV legacy survey of galactic globular clusters - X. The radial distribution of stellar populations in NGC2808

Due to their extreme helium abundance, the multiple stellar populations of the globular cluster NGC 2808 have been widely investigated from a photometric, spectroscopic, and kinematic perspective. The most striking feature of the colour–magnitude diagram of NGC 2808 is the triple main sequence (MS), with the red MS corresponding to a stellar population with primordial helium, and the middle and the blue MS being enhanced in helium up to Y ∼ 0.32 and ∼0.38, respectively. A recent study has revealed that this massive cluster hosts at least five distinct stellar populations (A, B, C, D, and E). Among them populations A, B, and C correspond to the red MS, while populations C and D are connected to the middle and the blue MS. In this paper, we exploit Hubble Space Telescope photometry to investigate the radial distribution of the red, the middle, and the blue MS from the cluster centre out to about 8.5 arcmin. Our analysis shows that the radial distribution of each of the three MSs is different. In particular, as predicted from multiple-population formation models, both the blue MS and the middle MS appears to be more concentrated than the red MS with a significance level for this result which is above 3

Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified

Transcription restores DNA repair to heterochromatin, determining regional mutation rates in cancer genomes

SummarySomatic mutations in cancer are more frequent in heterochromatic and late-replicating regions of the genome. We report that regional disparities in mutation density are virtually abolished within transcriptionally silent genomic regions of cutaneous squamous cell carcinomas (cSCCs) arising in an XPC−/− background. XPC−/− cells lack global genome nucleotide excision repair (GG-NER), thus establishing differential access of DNA repair machinery within chromatin-rich regions of the genome as the primary cause for the regional disparity. Strikingly, we find that increasing levels of transcription reduce mutation prevalence on both strands of gene bodies embedded within H3K9me3-dense regions, and only to those levels observed in H3K9me3-sparse regions, also in an XPC-dependent manner. Therefore, transcription appears to reduce mutation prevalence specifically by relieving the constraints imposed by chromatin structure on DNA repair. We model this relationship among transcription, chromatin state, and DNA repair, revealing a new, personalized determinant of cancer risk

Erratum to: Modeling precision treatment of breast cancer.

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum