Such protocol can be recommended for decontaminating PCR reagents for routine use. Using our procedure, we detected specific microbial DNA sequences in 14/144 tested teeth. With the exception of P. stutzeri that may result from contamination of water, we think that these sequences were authentic, that is they were present in the respective dental pulp before laboratory processing. In all instances, negative controls remained negative and the 16S rDNA based detection was Betamipron confirmed by a second rpoB gene-based amplification and sequencing of specific sequence. Also, each individual yielded unique 16S rDNA and rpoB gene sequences that were not found in other individuals. At last, the fact that we recovered identical identifying sequences in several teeth from the same individual reinforced the results. Because of differences in DNA extraction yield between different bacterial species, our protocol may have miss some organisms it the dental pulp, and the bacterial species we identified, mainly gram-negative species, may not be representative of the overall dental pulp flora. We identified mainly two groups of bacteria, aerobic gramnegative Penfluridol bacteria presumably responsible for blood-borne in fection and oral flora species associated with periodontopathyborne infection. Most of the detected gram-negative bacteria are known to cause bacteremia in humans and are not found in the safe or diseased periodontal tissue. These include Enterobacter cloacae, Enterobacter dissolvens, an emerging species closely related to Enterobacter cloacae, Acinetobacter johnsonii and Klebsiella oxytoca and Klebsiella variicola, a genotype of Klebsiella pneumoniae. In fact, a close examination of their sequencing data suggests that there could be a quantitative difference in allelic expression in fetal and placental tissues. We used several different measures of classifier performance. On the RB198 dataset, performance measures were obtained by carrying out sequence-based 5-fold cross-validation. Sequencebased 5-fold cross-validation randomly divides protein chains in RB198 into 5 sets and alternatively uses 4 sets as the training set and 1 set as the test set. The average performance on the 5 test sets is used as the final evaluation of the classifier.