Spatial Periodicity of Galaxy Number Counts, CMB Anisotropy, and SNIa Hubble Diagram Based on the Universe Accompanied by a Non-Minimally Coupled Scalar Field

We have succeeded in establishing a cosmological model with a non-minimally coupled scalar field $\phi$ that can account not only for the spatial periodicity or the {\it picket-fence structure} exhibited by the galaxy $N$-$z$ relation of the 2dF survey but also for the spatial power spectrum of the cosmic microwave background radiation (CMB) temperature anisotropy observed by the WMAP satellite. The Hubble diagram of our model also compares well with the observation of Type Ia supernovae. The scalar field of our model universe starts from an extremely small value at around the nucleosynthesis epoch, remains in that state for sufficiently long periods, allowing sufficient time for the CMB temperature anisotropy to form, and then starts to grow in magnitude at the redshift $z$ of $\sim 1$, followed by a damping oscillation which is required to reproduce the observed picket-fence structure of the $N$-$z$ relation. To realize such behavior of the scalar field, we have found it necessary to introduce a new form of potential $V(\phi)\propto \phi^2\exp(-q\phi^2)$, with $q$ being a constant. Through this parameter $q$, we can control the epoch at which the scalar field starts growing.Comment: 19 pages, 18 figures, Accepted for publication in Astrophysics & Space Scienc

Open Issues on the Synthesis of Evolved Stellar Populations at Ultraviolet Wavelengths

In this paper we briefly review three topics that have motivated our (and others') investigations in recent years within the context of evolutionary population synthesis techniques. These are: The origin of the FUV up-turn in elliptical galaxies, the age-metallicity degeneracy, and the study of the mid-UV rest-frame spectra of distant red galaxies. We summarize some of our results and present a very preliminary application of a UV grid of theoretical spectra in the analysis of integrated properties of aged stellar populations. At the end, we concisely suggest how these topics can be tackled once the World Space Observatory enters into operation in the midst of this decade.Comment: 8 pages, 4 figures, accepted for publication in Astrophysics & Space Science, UV Universe special issu

Phytoplankton in a temperate-zone salt marsh: Net production and exchanges with coastal waters

Phytoplankton production and associated variables were measured in Flax Pond, a 52 ha salt marsh on the north shore of Long Island, New York, from July 1972 to October 1973. Measurements made up to five times per day, once per week, yielded a mean annual net primary production, determined by the 14 C technique, of 20.5 mg C/m 3 /h; daily means were as high as 60.0 mg C/m 3 /h. However, when productivity was calculated for the entire marsh ecosystem, the shallow water in the salt marsh produced only 11.7 g C/m 2 of marsh/year. There was a net flux of phytoplankton from the coastal waters into the marsh; during the summer up to 0.2 g chlorophy 11/m 2 of marsh was carried in with the tides daily and remained in the marsh. Analysis of the productivity data, as well as variables associated with productivity (pH, standing crop, nutrients, extinction coefficient), indicated that the aquatic portion of the marsh behaved more as a net consumer rather than a net producer of phytoplankton.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46630/1/227_2004_Article_BF00391561.pd

The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants