Forecasting Consumer Adoption of Technological Innovation: Choosing the Appropriate Diffusion Models for New Products and Services before Launch

There are many good articles on various forecasting models. There is consensus that no single diffusion model is best for every situation. Experts in the field have asked for studies to provide empirical-based guidelines for recommending when various models should be used. This research investigates multiple diffusion models and provides recommendations for which diffusion models are appropriate for radical and really new products and services before the launch of the innovation

An International Quiet Ocean Experiment

Author Posting. © Oceanography Society, 2011. This article is posted here by permission of Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 24, no. 2 (2011): 174–181, doi:10.5670/oceanog.2011.37.The effect of noise on marine life is one of the big unknowns of current marine science. Considerable evidence exists that the human contribution to ocean noise has increased during the past few decades: human noise has become the dominant component of marine noise in some regions, and noise is directly correlated with the increasing industrialization of the ocean. Sound is an important factor in the lives of many marine organisms, and theory and increasing observations suggest that human noise could be approaching levels at which negative effects on marine life may be occurring. Certain species already show symptoms of the effects of sound. Although some of these effects are acute and rare, chronic sublethal effects may be more prevalent, but are difficult to measure. We need to identify the thresholds of such effects for different species and be in a position to predict how increasing anthropogenic sound will add to the effects. To achieve such predictive capabilities, the Scientific Committee on Oceanic Research (SCOR) and the Partnership for Observation of the Global Oceans (POGO) are developing an International Quiet Ocean Experiment (IQOE), with the objective of coordinating the international research community to both quantify the ocean soundscape and examine the functional relationship between sound and the viability of key marine organisms. SCOR and POGO will convene an open science meeting to gather community input on the important research, observations, and modeling activities that should be included in IQOE

Identification of Amazonian Trees with DNA Barcodes

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A three-way comparative genomic analysis of Mannheimia haemolytica isolates

<p>Abstract</p> <p>Background</p> <p><it>Mannhemia haemolytica </it>is a Gram-negative bacterium and the principal etiological agent associated with bovine respiratory disease complex. They transform from a benign commensal to a deadly pathogen, during stress such as viral infection and transportation to feedlots and cause acute pleuropneumonia commonly known as shipping fever. The U.S beef industry alone loses more than one billion dollars annually due to shipping fever. Despite its enormous economic importance there are no specific and accurate genetic markers, which will aid in understanding the pathogenesis and epidemiology of <it>M. haemolytica </it>at molecular level and assist in devising an effective control strategy.</p> <p>Description</p> <p>During our comparative genomic sequence analysis of three <it>Mannheimia haemolytica </it>isolates, we identified a number of genes that are unique to each strain. These genes are "high value targets" for future studies that attempt to correlate the variable gene pool with phenotype. We also identified a number of high confidence single nucleotide polymorphisms (hcSNPs) spread throughout the genome and focused on non-synonymous SNPs in known virulence genes. These SNPs will be used to design new hcSNP arrays to study variation across strains, and will potentially aid in understanding gene regulation and the mode of action of various virulence factors.</p> <p>Conclusions</p> <p>During our analysis we identified previously unknown possible type III secretion effector proteins, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated sequences (Cas). The presence of CRISPR regions is indicative of likely co-evolution with an associated phage. If proven functional, the presence of a type III secretion system in <it>M. haemolytica </it>will help us re-evaluate our approach to study host-pathogen interactions. We also identified various adhesins containing immuno-dominant domains, which may interfere with host-innate immunity and which could potentially serve as effective vaccine candidates.</p

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Common Genetic Variation in Circadian Rhythm Genes and Risk of Epithelial Ovarian Cancer (EOC)

Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68–0.90, p = 5.59 × 10−4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways

Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk

Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.Other Research Uni

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer