A pyrrole-imidazole polyamide is active against enzalutamide-resistant prostate cancer

The LREX' prostate cancer model is resistant to the antiandrogen enzalutamide via activation of an alternative nuclear hormone receptor (NHR), glucocorticoid receptor (GR), which has similar DNA binding specificity to the androgen receptor (AR). Small molecules that target DNA to interfere with protein-DNA interactions may retain activity against enzalutamide-resistant prostate cancers where ligand binding domain antagonists are ineffective. We reported previously that a pyrrole-imidazole (Py-Im) polyamide designed to bind the consensus androgen response element half-site has antitumor activity against hormone-sensitive prostate cancer. In enzalutamide-resistant LREX' cells, Py-Im polyamide interfered with both androgen receptor- and glucocorticoid receptor-driven gene expression, while enzalutamide interfered with only that of androgen receptor. Genomic analyses indicated immediate interference with the androgen receptor transcriptional pathway. Long-term treatment with Py-Im polyamide demonstrated a global decrease in RNA levels consistent with inhibition of transcription. The polyamide was active against two enzalutamide-resistant xenografts with minimal toxicity. Overall, our results identify Py-Im polyamide as a promising therapeutic strategy in enzalutamide-resistant prostate cancer

Association between dietary phyto-oestrogens and bone density in men and postmenopausal women

Phyto-oestrogens have been associated with a decreased risk for osteoporosis, but results from intervention and observational studies in Western countries have been inconsistent. In the present study, we investigated the association between habitual phyto-oestrogen intake and broadband ultrasound attenuation (BUA) of the calcanaeum as a marker of bone density. We collected 7 d records of diet, medical history and demographic and anthropometric data from participants (aged 45–75 years) in the European Prospective Investigation into Cancer-Norfolk study. Phyto-oestrogen (biochanin A, daidzein, formononetin; genistein, glycitein; matairesinol; secoisolariciresinol; enterolactone; equol) intake was determined using a newly developed food composition database. Bone density was assessed using BUA of the calcanaeum. Associations between bone density and phyto-oestrogen intake were investigated in 2580 postmenopausal women who were not on hormone replacement therapy and 4973 men. Median intake of total phyto-oestrogens was 876 (interquartile range 412) μg/d in postmenopausal women and 1212 (interquartile range 604) μg/d in men. The non-soya isoflavones formononetin and biochanin A were marginally significant or significantly associated with BUA in postmenopausal women (β = 1·2; P < 0·1) and men (β = 1·2; P < 0·05), respectively; enterolignans and equol were positively associated with bone density in postmenopausal women, but this association became non-significant when dietary Ca was added to the model. In the lowest quintile of Ca intake, soya isoflavones were positively associated with bone density in postmenopausal women (β = 1·4; P < 0·1). The present results therefore suggest that non-soya isoflavones are associated with bone density independent of Ca, whereas the association with soya or soya isoflavones is affected by dietary Ca

Lightcurves of Type Ia Supernovae from Near the Time of Explosion

We present a set of 11 type Ia supernova (SN Ia) lightcurves with dense, pre-maximum sampling. These supernovae (SNe), in galaxies behind the Large Magellanic Cloud (LMC), were discovered by the SuperMACHO survey. The SNe span a redshift range of z = 0.11 - 0.35. Our lightcurves contain some of the earliest pre-maximum observations of SNe Ia to date. We also give a functional model that describes the SN Ia lightcurve shape (in our VR-band). Our function uses the "expanding fireball" model of Goldhaber et al. (1998) to describe the rising lightcurve immediately after explosion but constrains it to smoothly join the remainder of the lightcurve. We fit this model to a composite observed VR-band lightcurve of three SNe between redshifts of 0.135 to 0.165. These SNe have not been K-corrected or adjusted to account for reddening. In this redshift range, the observed VR-band most closely matches the rest frame V-band. Using the best fit to our functional description of the lightcurve, we find the time between explosion and observed VR-band maximum to be 17.6+-1.3(stat)+-0.07(sys) rest-frame days for a SN Ia with a VR-band Delta m_{-10} of 0.52mag. For the redshifts sampled, the observed VR-band time-of-maximum brightness should be the same as the rest-frame V-band maximum to within 1.1 rest-frame days.Comment: 35 pages, 18 figures, 15 tables; Higher quality PDF available at http://ctiokw.ctio.noao.edu/~sm/sm/SNrise/index.html; AJ accepte

Performance Evaluation of Cetacean Species Distribution Models Developed Using Generalized Additive Models and Boosted Regression Trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest

Full Spectrum Archaeology

Full Spectrum Archaeology (FSA) is an aspiration stemming from the convergence of archaeology’s fundamental principles with international heritage policies and community preferences. FSA encompasses study and stewardship of the full range of heritage resources in accord with the full range of associated values and through the application of treatments selected from the full range of appropriate options. Late modern states, including British Columbia, Canada, nominally embrace de jure heritage policies consonant with international standards yet also resist de facto heritage management practice grounded in professional ethics and local values and preferences. In response, inheritor communities and their allies in archaeology are demonstrating the benefits of FSA and reclaiming control over cultural heritage. Archaeology and heritage management driven by altruistic articulation of communal, educational, scientific and other values further expose shortcomings and vulnerabilities of late modern states as well as public goods in and from FSA

Exome sequencing of Finnish isolates enhances rare-variant association power.

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power

The complete genome sequence and comparative genome analysis of the high pathogenicity Yersinia enterocolitica strain 8081

The human enteropathogen, Yersinia enterocolitica, is a significant link in the range of Yersinia pathologies extending from mild gastroenteritis to bubonic plague. Comparison at the genomic level is a key step in our understanding of the genetic basis for this pathogenicity spectrum. Here we report the genome of Y. enterocolitica strain 8081 (serotype 0:8; biotype 1B) and extensive microarray data relating to the genetic diversity of the Y. enterocolitica species. Our analysis reveals that the genome of Y. enterocolitica strain 8081 is a patchwork of horizontally acquired genetic loci, including a plasticity zone of 199 kb containing an extraordinarily high density of virulence genes. Microarray analysis has provided insights into species-specific Y. enterocolitica gene functions and the intraspecies differences between the high, low, and nonpathogenic Y. enterocolitica biotypes. Through comparative genome sequence analysis we provide new information on the evolution of the Yersinia. We identify numerous loci that represent ancestral clusters of genes potentially important in enteric survival and pathogenesis, which have been lost or are in the process of being lost, in the other sequenced Yersinia lineages. Our analysis also highlights large metabolic operons in Y. enterocolitica that are absent in the related enteropathogen, Yersinia pseudotuberculosis, indicating major differences in niche and nutrients used within the mammalian gut. These include clusters directing, the production of hydrogenases, tetrathionate respiration, cobalamin synthesis, and propanediol utilisation. Along with ancestral gene clusters, the genome of Y. enterocolitica has revealed species-specific and enteropathogen-specific loci. This has provided important insights into the pathology of this bacterium and, more broadly, into the evolution of the genus. Moreover, wider investigations looking at the patterns of gene loss and gain in the Yersinia have highlighted common themes in the genome evolution of other human enteropathogens

BVRI Light Curves for 29 Type Ia Supernovae

BVRI light curves are presented for 27 Type Ia supernovae discovered during the course of the Calan/Tololo Survey and for two other SNe Ia observed during the same period. Estimates of the maximum light magnitudes in the B, V, and I bands and the initial decline rate parameter m15(B) are also given.Comment: 17 pages, figures and tables are not included (contact first author if needed), to appear in the Astronomical Journa

Testing LMC Microlensing Scenarios: The Discrimination Power of the SuperMACHO Microlensing Survey

Characterizing the nature and spatial distribution of the lensing objects that produce the previously measured microlensing optical depth toward the Large Magellanic Cloud (LMC) remains an open problem. We present an appraisal of the ability of the SuperMACHO Project, a next-generation microlensing survey directed toward the LMC, to discriminate between various proposed lensing populations. We consider two scenarios: lensing by a uniform foreground screen of objects and self-lensing by LMC stars. We have carried out extensive simulations, based upon data obtained during the first year of the project, to assess the SuperMACHO survey's ability to discriminate between these two scenarios. We find that the event rate itself shows significant sensitivity to the choice of the LMC luminosity function, limiting the conclusions which can be drawn from the absolute rate. If instead we determine the differential event rate across the LMC, we will decrease the impact of these systematic biases and render our conclusions more robust. With this approach the SuperMACHO Project should be able to distinguish between the two categories of lens populations. This will provide important constraints on the nature of the lensing objects and their contributions to the Galactic dark matter halo.Comment: 40 pages, 9 figures, to appear in ApJ 634 (2005