A 72-year-old Caucasian man incurring a prostate hypertrophy presented with a right forearm nodule, the growth of which appeared to parallel the rise in his blood prostate-specific antigen (PSA) level. Echographic examination was consistent with a median-nerve schwannoma, and was confirmed upon magnetic resonance imaging (MRI). Excision of the nodule was readily performed without significant neural damage, and its schwannoma nature was confirmed upon immunohistochemistry analysis. Importantly, blood PSA dropped abruptly from ≈13 to ≈5 ng/ml within 2 months postschwannoma resection, a swift drastic reduction unachievable with oral dutasteride alone. However, 6 weeks later, a new nodule became apparent on the back of the left knee and was identified as a second schwannoma, thereby suggesting that its growth could have been stimulated by the resection of the first schwannoma, as previously described for vestibular schwannomas. The second schwannoma was in fact two: the bigger one was in the common fibular nerve and the smaller one in the tibial nerve. Both echography and MRI results were confirmed upon surgical resection of the bigger knee schwannoma. Although the third schwannoma has not yet been resected and formally characterized, we face a schwannomatosis case with an unexpected potential exosome-mediated stimulating effect on PSA secretion (PSA immunohistochemistry was negative on both schwannomas). On the other hand, preliminary genomic analysis showed a deficient balance for chromosome 22, the very chromosome carrying the three main genes involved in schwannomatosis. This age-related schwannomatosis case is thus discussed in light of the following: age-related DNA repair deficiency culminating in loss of chromosome/heterozygosity; CpG methylation/demethylation-based epigenetic aging; age-related functional decline of the immune system responsible for inefficient elimination of abnormal cells and subsequent tumorigenic cell turn-over; exosome-mediated pathologic intercellular communications; and prostate-invading brain neural progenitors as pathologic peripheral nervous system (PNS) cells.
Classification technique in data mining focuses on prediction which is done by classical C4.5 decision tree algorithm, but limited by its computation complexities due to large datasets. However, this results to inefficient implementation of the algorithm with reference to computing time, memory utilization and data complexity. Meanwhile, several researches have been done to curb these limitations. One of such improvements is the parallelizing of the algorithm using the MapReduce model. This involves splitting the large dataset into smaller units and distributing them on multiple computers for parallel processing, but the recursive nature of the algorithm makes the computational cost high due to large number of calculations that are repeated. This research is aimed at further reducing computation time, using memoized MapReduce model that involves storing the result of previous calculations in a cache. Thus, when same calculations re-occur, the cached result is returned, thereby eliminating re-computation.
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