The epidemiology of prostate cancer - with a focus on nonsteroidal anti-inflammatory drugs
ABSTRACT Aspirin and other NSAIDs have a potential role in the primary and secondary prevention of many common diseases associated with aging, including the top two causes of mortality in the United States-cardiovascular disease and cancer. These agents may be beneficial in the management of Alzheimer's disease,other forms of dementia, and Parkinson's. disease. Because men with prostate cancer or precancer are likely to present with coexisting conditions that would be affected by systemic aspirin, NSAID, or other COX-2 inhibitor therapies, it is important to consider any possible preventive studies or future clinical recommendations of aspirin or NSAIDs for prostate cancer within the context of these comorbid conditions. Aspirin or nonaspirin NSAIDs may be appropriate prevention therapy for patients at high risk of prostate cancer, myocardial infarction, Parkinson's disease, Alzheimer's disease, lung cancer, or colorectal cancer, but low risk for gastrointestinal complications or stroke. Further quantitative comparative studies of the risks and benefits of these common comorbidities in older Americans, with special attention to dose and duration parameters, are warranted.
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Conference Paper: Neural network for LIDAR detection of fish[Show abstract] [Hide abstract]
ABSTRACT: In this paper we present a neural network for detection of fish, from light detection and ranging (LIDAR) data and have described a classification method for distinguishing between water-layer, bottom and fish. Four multi-layer perceptrons (MLP) were developed for the classification purpose, where classes include fish, bottom and water-layer. The LIDAR data gives a sequence of intensity of laser backscatters obtained from laser shots at various heights above the Earth surface. The data is preprocessed to remove the high frequency noise and then a window of the sample is selected for further processing to extract features for classification purposes. We have used linear predictive coding (LPC) analysis for the feature detection purpose. The results show that the detection technique is effective and can do the required classification with a high degree of accuracy. We have tried our approach with four different MLPs and are presenting the data obtained from each of them.Neural Networks, 2003. Proceedings of the International Joint Conference on; 08/2003
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ABSTRACT: About 20% of all human cancers are caused by chronic infection or chronic inflammatory states. Recently, a new hypothesis has been proposed for prostate carcinogenesis. It proposes that exposure to environmental factors such as infectious agents and dietary carcinogens, and hormonal imbalances lead to injury of the prostate and to the development of chronic inflammation and regenerative 'risk factor' lesions, referred to as proliferative inflammatory atrophy (PIA). By developing new experimental animal models coupled with classical epidemiological studies, genetic epidemiological studies and molecular pathological approaches, we should be able to determine whether prostate cancer is driven by inflammation, and if so, to develop new strategies to prevent the disease.Nature reviews. Cancer 05/2007; 7(4):256-69. DOI:10.1038/nrc2090 · 37.91 Impact Factor