Program on Earth Observation Data Management Systems (EODMS)

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products

A review of imaging techniques for systems biology

This paper presents a review of imaging techniques and of their utility in system biology. During the last decade systems biology has matured into a distinct field and imaging has been increasingly used to enable the interplay of experimental and theoretical biology. In this review, we describe and compare the roles of microscopy, ultrasound, CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), and molecular probes such as quantum dots and nanoshells in systems biology. As a unified application area among these different imaging techniques, examples in cancer targeting are highlighted

Short-term health-related quality of life consequences in a lung cancer CT screening trial (NELSON)

Item does not contain fulltextBACKGROUND: In lung cancer CT screening, participants often have an indeterminate screening result at baseline requiring a follow-up CT. In subjects with either an indeterminate or a negative result after screening, we investigated whether health-related quality of life (HRQoL) changed over time and differed between groups in the short term. METHODS: A total of 733 participants in the NELSON trial received four questionnaires: T0, before randomisation; T1, 1 week before the baseline screening; T2, 1 day after the screening; and T3, 2 months after the screening results but before the 3-month follow-up CT. HRQoL was measured as generic HRQoL (the 12-item Short Form, SF-12; the EuroQol questionnaire, EQ-5D), anxiety (the Spielberger State-Trait Anxiety Inventory, STAI-6), and lung-cancer-specific distress (the Impact of Event Scale, IES). For analyses, repeated-measures analysis of variance was used, adjusted for covariates. RESULTS: Response to each questionnaire was 88% or higher. Scores on SF-12, EQ-5D, and STAI-6 showed no clinically relevant changes over time. At T3, IES scores that were clinically relevant increased after an indeterminate result, whereas these scores showed a significant decrease after a negative result. At T3, differences in IES scores between the two baseline result groups were both significant and clinically relevant (P<0.01). CONCLUSION: This longitudinal study among participants of a lung cancer screening programme showed that in the short term recipients of an indeterminate result experienced increased lung-cancer-specific distress, whereas the HRQoL changes after a negative baseline screening result may be interpreted as a relief

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-β (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025–51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB

Genome-Wide Association Study of Relative Telomere Length

Telomere function is essential to maintaining the physical integrity of linear chromosomes and healthy human aging. The probability of forming proper telomere structures depends on the length of the telomeric DNA tract. We attempted to identify common genetic variants associated with log relative telomere length using genome-wide genotyping data on 3,554 individuals from the Nurses' Health Study and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that took part in the National Cancer Institute Cancer Genetic Markers of Susceptibility initiative for breast and prostate cancer. After genotyping 64 independent SNPs selected for replication in additional Nurses' Health Study and Women's Genome Health Study participants, we did not identify genome-wide significant loci; however, we replicated the inverse association of log relative telomere length with the minor allele variant [C] of rs16847897 at the TERC locus (per allele β = −0.03, P = 0.003) identified by a previous genome-wide association study. We did not find evidence for an association with variants at the OBFC1 locus or other loci reported to be associated with telomere length. With this sample size we had >80% power to detect β estimates as small as ±0.10 for SNPs with minor allele frequencies of ≥0.15 at genome-wide significance. However, power is greatly reduced for β estimates smaller than ±0.10, such as those for variants at the TERC locus. In general, common genetic variants associated with telomere length homeostasis have been difficult to detect. Potential biological and technical issues are discussed

Understanding preventive behaviors among mid-Western African-American men: a pilot qualitative study of prostate screening

http://dx.doi.org/10.1016/j.jomh.2011.03.00

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer

<p>Abstract</p> <p>Background</p> <p>Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohibitive amount of data needed to account for multiple hypothesis testing.</p> <p>Methods</p> <p>To address this issue, we systematically prioritized and evaluated individual effects and complex interactions among 172 apoptotic SNPs in relation to PCA risk and aggressive disease (i.e., Gleason score ≥ 7 and tumor stages III/IV). Single and joint modifying effects on PCA outcomes among European-American men were analyzed using statistical epistasis networks coupled with multi-factor dimensionality reduction (SEN-guided MDR). The case-control study design included 1,175 incident PCA cases and 1,111 controls from the prostate, lung, colo-rectal, and ovarian (PLCO) cancer screening trial. Moreover, a subset analysis of PCA cases consisted of 688 aggressive and 488 non-aggressive PCA cases. SNP profiles were obtained using the NCI Cancer Genetic Markers of Susceptibility (CGEMS) data portal. Main effects were assessed using logistic regression (LR) models. Prior to modeling interactions, SEN was used to pre-process our genetic data. SEN used network science to reduce our analysis from > 36 million to < 13,000 SNP interactions. Interactions were visualized, evaluated, and validated using entropy-based MDR. All parametric and non-parametric models were adjusted for age, family history of PCA, and multiple hypothesis testing.</p> <p>Results</p> <p>Following LR modeling, eleven and thirteen sequence variants were associated with PCA risk and aggressive disease, respectively. However, none of these markers remained significant after we adjusted for multiple comparisons. Nevertheless, we detected a modest synergistic interaction between <it>AKT3 rs2125230-PRKCQ rs571715 </it>and disease aggressiveness using SEN-guided MDR (p = 0.011).</p> <p>Conclusions</p> <p>In summary, entropy-based SEN-guided MDR facilitated the logical prioritization and evaluation of apoptotic SNPs in relation to aggressive PCA. The suggestive interaction between <it>AKT3-PRKCQ </it>and aggressive PCA requires further validation using independent observational studies.</p

Maximum likelihood inference on a mixed conditionally and marginally specified regression model for genetic epidemiologic studies with two-phase sampling

Two-phase stratified sampling designs can reduce the cost of genetic epidemiologic studies by limiting expensive ascertainments of genetic and environmental exposure to an efficiently selected subsample (phase II) of the main study (phase I). Family history and some covariate information, which may be cheaply gathered for all subjects at phase I, can be used for sampling of informative subjects at phase II. We develop alternative maximum likelihood methods for analysis of data from such studies by using a novel regression model that permits the estimation of 'marginal' risk parameters that are associated with the genetic and environmental covariates of interest, while simultaneously characterizing the 'conditional' risk of the disease associated with family history after adjusting for the other covariates. The methods and appropriate asymptotic theories are developed with and without an assumption of gene-environment independence, allowing the distribution of the environmental factors to remain non-parametric. The performance of the alternative methods and of sampling strategies is studied by using simulated data involving rare and common genetic variants. An application of the methods proposed is illustrated by using a case-control study of colorectal adenoma embedded within the prostate, lung, colorectal and ovarian cancer screening trial. Copyright Royal Statistical Society.