The emergence of the cortisol circadian rhythm in monozygotic and dizygotic twin infants: the twin-pair synchrony

OBJECTIVE: Studies on the influence of genetic factors on the ontogeny of cortisol circadian rhythm in infants are lacking. This study evaluated the influence of twinning and the heritability on the age of emergence of salivary cortisol rhythm. DESIGN AND SUBJECTS: A longitudinal study was performed using salivary samples obtained during morning and night, at 2, 4, 8, 12, 16, 20 and 24 weeks of postnatal life in 34 infants, 10 monozygotic (MZ) and 7 dizygotic (DZ) twin pairs. Salivary cortisol was determined by radioimmunoassay (RIA). Zigosity was verified by DNA analysis of at least 13 short tandem repeat polymorphisms. Difference of the emergence of cortisol circadian rhythm, within each twin pair, the intraclass correlation coefficient and the heritability index (h(2)) were calculated. RESULTS: The mean (± SEM) age of emergence of salivary cortisol circadian rhythm was similar in MZ and DZ (7·8 ± 1·0 vs 7·4 ± 1·3 weeks). Seven pairs showed coincidence of the emergence of cortisol rhythm. Ten pairs were not coincident; among them the within-pair difference of emergence of salivary circadian rhythm was similar in both MZ and DZ groups. The intraclass correlation coefficients were rMZ = 0·60, P = 0·02; and rDZ = 0·65, P = 0·03, respectively. The heritability index (h(2)) was 0·21 (ns). CONCLUSIONS: Salivary circadian rhythm appeared at the same postnatal age in MZ and DZ twin infants. Although several physiological aspects might be involved, the heritability index, obtained in the present study, suggests less genetic than environmental impact on the age of the onset of the cortisol circadian rhythm. Our data also indicated that each twin-pair show synchrony because they probably shared prenatal and postnatal environmental synchronizers

Discovery and Observations of ASASSN-13db, an EX Lupi-Type Accretion Event on a Low-Mass T Tauri Star

We discuss ASASSN-13db, an EX Lupi-type ("EXor") accretion event on the young stellar object (YSO) SDSS J051011.01$-$032826.2 (hereafter SDSSJ0510) discovered by the All-Sky Automated Survey for SuperNovae (ASAS-SN). Using archival photometric data of SDSSJ0510 we construct a pre-outburst spectral energy distribution (SED) and find that it is consistent with a low-mass class II YSO near the Orion star forming region ($d \sim 420$ pc). We present follow-up photometric and spectroscopic observations of the source after the $\Delta V \sim-$5.4 magnitude outburst that began in September 2013 and ended in early 2014. These data indicate an increase in temperature and luminosity consistent with an accretion rate of $\sim10^{-7}$ $\rm{M}_\odot$ yr$^{-1}$, three or more orders of magnitude greater than in quiescence. Spectroscopic observations show a forest of narrow emission lines dominated by neutral metallic lines from Fe I and some low-ionization lines. The properties of ASASSN-13db are similar to those of the EXor prototype EX Lupi during its strongest observed outburst in late 2008.Comment: 14 pages, 4 figures, 1 table. Updated May 2014 to reflect changes in the final version published in ApJL. Photometric data presented in this submission are included as ancillary files. For a brief video explaining this paper, see http://youtu.be/yRCCrNJnvt

Intra-sexual competition alters the relationship between testosterone and ornament expression in a wild territorial bird

Open Access funded by Natural Environment Research Council Under a Creative Commons licensePeer reviewedPublisher PD

Spreading Dynamics of Polymer Nanodroplets

The spreading of polymer droplets is studied using molecular dynamics simulations. To study the dynamics of both the precursor foot and the bulk droplet, large drops of ~200,000 monomers are simulated using a bead-spring model for polymers of chain length 10, 20, and 40 monomers per chain. We compare spreading on flat and atomistic surfaces, chain length effects, and different applications of the Langevin and dissipative particle dynamics thermostats. We find diffusive behavior for the precursor foot and good agreement with the molecular kinetic model of droplet spreading using both flat and atomistic surfaces. Despite the large system size and long simulation time relative to previous simulations, we find no evidence of hydrodynamic behavior in the spreading droplet.Comment: Physical Review E 11 pages 10 figure

Deviation From \Lambda CDM With Cosmic Strings Networks

In this work, we consider a network of cosmic strings to explain possible deviation from \Lambda CDM behaviour. We use different observational data to constrain the model and show that a small but non zero contribution from the string network is allowed by the observational data which can result in a reasonable departure from \Lambda CDM evolution. But by calculating the Bayesian Evidence, we show that the present data still strongly favour the concordance \Lambda CDM model irrespective of the choice of the prior.Comment: 15 Pages, Latex Style, 4 eps figures, Revised Version, Accepted for publication in European Physical Journal

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field

Oncogenic Signaling Pathways in The Cancer Genome Atlas

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFb signaling, p53 and beta-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis