BACKGROUND Two staging systems for oral leukoplakias have been proposed to better predict prognosis. Although one system includes site as an independent determinant, its use is controversial. METHODS Recent studies have shown that loss of heterozygosity (LOH) in oral premalignancies is associated with risk of progression. The authors analyzed 127 oral dysplasias for LOH on 3 chromosome arms (3p, 9p, and 17p). The lesions included 71 from the floor of mouth, ventrolateral tongue, and soft palate complex (designated high risk [HR] sites) and 56 from the rest of the oral cavity (low risk [LR] sites). RESULTS Dysplasias from HR sites contained significantly higher LOH frequencies than LR sites (percentage with any loss, P = 0.0004; percentage with multiple losses, P = 0.0001; percentage loss on each of the arms, P < 0.05). Loss on 3p and/or 9p, a pattern associated with a 24‐fold increased risk of progression (Rosin MP, Cheng X, Poh C, Lam WL, Huang Y, Lovas J, et al. Use of allelic loss to predict malignant risk for low‐grade oral epithelial dysplasia. Clin Cancer Res 2000;6:357–62) was more frequent among HR lesions (P = 0.0005). Loss of heterozygosity frequencies were elevated at HR sites among both genders and among smokers and nonsmokers. For different histologic groups, LOH frequencies were elevated for HR sites in mild dysplasias (P < 0.05) and moderate dysplasias (marginal significance, P = 0.06), but not in severe dysplasias/carcinoma in situ. CONCLUSIONS Anatomic location of mild and moderate oral dysplasias in Western populations may be an important diagnostic indicator because lesions at HR sites have a greater tendency to include genetic alterations associated with elevated risk of progression. Cancer 2001;91:2148–55. © 2001 American Cancer Society.
Due to the complexity and continuing evolution of such systems, it is desirable to maintain as much software controllability in the field as possible. Time to market can also be improved by reducing the amount of hardware design. This paper describes an architecture based on clusters of embedded "workhorse" processors which can be dynamically harnessed in real time to support a wide range of computational tasks. Low-power processors and memory are important ingredients in such a highly parallel environment.
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