Digital Processing of Remotely Sensed Imagery

Digital images can be acquired from various devices. Image scanners on personal computers can generate digital images of hard copy material. New digital cameras operate without film, recording a digital image of the scene in local solid state memory. Remote sensing instruments routinely return digital imagery to receiving stations for processing and display. Digital processing of remotely sensed imagery is a technology that is now over thirty years old. Earth orbitting and deep space exploration spacecraft have been returning digital imagery for many years. Earth-based systems, including biomedical imaging devices and other commercially available types of equipment, have also been producing digital imagery for many years. Each of these devices produce a digital version of an image as a two dimensional array of numbers. The values in the matrix represent the brightness of the scene at each individual sampled position in the image

Southeastern Colorado survey of critical biological resources, 2007

Prepared for: Colorado Cattleman's Agricultural Land Trust, Great Outdoors Colorado, Colorado Dept. of Natural Resources.May 2008.Includes bibliographical references

Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality: A Pooled Analysis of 20 Prospective Studies

Background: The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity. Methods and Findings: In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19–83 y at baseline, classified as obese class III (BMI 40.0–59.9 kg/m2) compared with those classified as normal weight (BMI 18.5–24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976–2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40–44.9, 45–49.9, 50–54.9, and 55–59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7–7.3), 8.9 (95% CI: 7.4–10.4), 9.8 (95% CI: 7.4–12.2), and 13.7 (95% CI: 10.5–16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report. Conclusions: Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight. Please see later in the article for the Editors' Summar

Variants in autophagy-related genes and clinical characteristics in melanoma: a population-based study

Autophagy has been linked with melanoma risk and survival, but no polymorphisms in autophagy-related (ATG) genes have been investigated in relation to melanoma progression. We examined five single-nucleotide polymorphisms (SNPs) in three ATG genes (ATG5; ATG10; and ATG16L) with known or suspected impact on autophagic flux in an international population-based case-control study of melanoma. DNA from 911 melanoma patients was genotyped. An association was identified between (GG) (rs2241880) and earlier stage at diagnosis (OR 0.47; 95% Confidence Intervals (CI) = 0.27-0.81, P = 0.02) and a decrease in Breslow thickness (P = 0.03). The ATG16L heterozygous genotype (AG) (rs2241880) was associated with younger age at diagnosis (P = 0.02). Two SNPs in ATG5 were found to be associated with increased stage (rs2245214 CG, OR 1.47; 95% CI = 1.11-1.94, P = 0.03; rs510432 CC, OR 1.84; 95% CI = 1.12-3.02, P = 0.05). Finally, we identified inverse associations between ATG5 (GG rs2245214) and melanomas on the scalp or neck (OR 0.20, 95% CI = 0.05-0.86, P = 0.03); ATG10 (CC) (rs1864182) and brisk tumor infiltrating lymphocytes (TILs) (OR 0.42; 95% CI = 0.21-0.88, P = 0.02), and ATG5 (CC) (rs510432) with nonbrisk TILs (OR 0.55; 95% CI = 0.34-0.87, P = 0.01). Our data suggest that ATG SNPs might be differentially associated with specific host and tumor characteristics including age at diagnosis, TILs, and stage. These associations may be critical to understanding the role of autophagy in cancer, and further investigation will help characterize the contribution of these variants to melanoma progression

Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers.

PURPOSE: CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS: CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS: Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION: These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.NIH

Associations of Cumulative Sun Exposure and Phenotypic Characteristics with Histologic Solar Elastosis

Solar elastosis adjacent to melanomas in histologic sections is regarded as an indicator of sun exposure although the associations of ultraviolet (UV) exposure and phenotype with solar elastosis are yet to be fully explored

Comparison of 6q25 Breast Cancer Hits from Asian and European Genome Wide Association Studies in the Breast Cancer Association Consortium (BCAC)

Peer reviewe

CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Funder: Breast Cancer Now (BCN); doi: https://doi.org/10.13039/100009794Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Funder: RCUK | Medical Research Council (MRC); doi: https://doi.org/10.13039/501100000265Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH)Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440Funder: EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013)); doi: https://doi.org/10.13039/100011199; Grant(s): HEALTH-F2-2009-223175, HEALTH-F2-2009-223175Funder: Genome Canada (Génome Canada); doi: https://doi.org/10.13039/100008762Funder: Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada); doi: https://doi.org/10.13039/501100000024Funder: Quebec Breast cancer Foundation Genome QuebecFunder: U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (NLM); doi: https://doi.org/10.13039/100000092Funder: EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))Funder: European Union’s Horizon 2020Funder: Deutsche Krebshilfe (German Cancer Aid); doi: https://doi.org/10.13039/501100005972Funder: BCAST - European Union’s Horizon 2020Funder: Breast Cancer Now; doi: https://doi.org/10.13039/501100007913Abstract: Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (−49.2%, 95% CI −56.1% to −41.1%, P = 3.1 × 10–18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (−26.7%, 95% CI −39.4% to −11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82–0.91, P = 6.9 × 10–8). Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women

Digital Processing of Remotely Sensed Imagery

Digital images can be acquired from various devices. Image scanners on personal computers can generate digital images of hard copy material. New digital cameras operate without film, recording a digital image of the scene in local solid state memory. Remote sensing instruments routinely return digital imagery to receiving stations for processing and display. Digital processing of remotely sensed imagery is a technology that is now over thirty years old. Earth orbitting and deep space exploration spacecraft have been returning digital imagery for many years. Earth-based systems, including biomedical imaging devices and other commercially available types of equipment, have also been producing digital imagery for many years. Each of these devices produce a digital version of an image as a two dimensional array of numbers. The values in the matrix represent the brightness of the scene at each individual sampled position in the image.</p