Five different PCR methods for the detection of Helicobacter pylori were evaluated. The results of this study indicate that of the five PCR methods examined, the ureC (glmM) gene PCR is the most sensitive and specific for the detection ofH. pylori in gastric biopsy specimens.

Pneumocystis carinii f. sp. hominisisolates from 207 clinical specimens from nine countries were typed based on nucleotide sequence variations in the internal transcribed spacer regions I and II (ITS1 and ITS2, respectively) of rRNA genes. The number of ITS1 nucleotides has been revised from the previously reported 157 bp to 161 bp. Likewise, the number of ITS2 nucleotides has been changed from 177 to 192 bp. The number of ITS1 sequence types has increased from 2 to 15, and that of ITS2 has increased from 3 to 14. The 15 ITS1 sequence types are designated types A through O, and the 14 ITS2 types are named types a through n. A total of 59 types of P. carinii f. sp. hominis were found in this study.

We evaluated the disk susceptibility data of 671 nontyphoid Salmonella isolates collected from different parts of Taiwan from March 2001 to August 2001 and 1,261 nontyphoid Salmonella isolates from the National Taiwan University Hospital from 1996 to 2001. Overall, ciprofloxacn resistance was found in 2.7% (18/671) of all nontyphoid Salmonella isolates, in 1.4% (5/347) of Salmonella enterica serotype Typhimurium and in 7.5% (8/107) in S. enterica serotype Choleraesuis nationwide. MICs of six newer fluoroquinolones were determined for the following isolates: 37 isolates of ciprofloxacin-resistant (human) S. enterica Typhimurium (N = 26) and Choleraesuis (N = 11), 10 isolates of ciprofloxacin-susceptible (MIC <1 μg/mL) (human) isolates of these two serotypes, and 15 swine isolates from S. enterica Choleraesuis (N = 13) and Typhmurium (N = 2) with reduced susceptibility to ciprofloxacin (MIC >0.12 μg/mL). Sequence analysis of the gryA, gyrB, parC, parE, and acrR genes, ciprofloxacin accumulation; and genotypes generated by pulsed-field gel electrophoresis with three restriction enzymes (SpeI, XbaI, and BlnI) were performed. All 26 S. enterica Typhimurium isolates from humans and pigs belonged to genotype I. For S. enterica Choleraesuis isolates, 91% (10/11) of human isolates and 54% (7/13) of swine isolates belonged to genotype B. These two genotypes isolates from humans all exhibited a high-level of resistance to ciprofloxacin (MIC 16–64 μg/mL). They had two-base substitutions in the gyrA gene at codons 83 (Ser83Phe) and 87 (Asp87Gly or Asp87Asn) and in the parC gene at codon 80 (Ser80Arg, Ser80Ile, or Ser84Lys). Our investigation documented that not only did these two S. enterica isolates have a high prevalence of ciprofloxacin resistance nationwide but also that some closely related ciprofloxacin-resistant strains are disseminated from pigs to humans.

Methicillin-resistant Staphylococcus aureus (MRSA), one of the most important clinical pathogens, conducts an increasing number of morbidity and mortality in the world. Rapid and accurate strain typing of bacteria would facilitate epidemiological investigation and infection control in near real time. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry is a rapid and cost-effective tool for presumptive strain typing. To develop robust method for strain typing based on MALDI-TOF spectrum, machine learning (ML) is a promising algorithm for the construction of predictive model. In this study, a strategy of building templates of specific types was used to facilitate generating predictive models of methicillin-resistant Staphylococcus aureus (MRSA) strain typing through various ML methods. The strain types of the isolates were determined through multilocus sequence typing (MLST). The area under the receiver operating characteristic curve (AUC) and the predictive accuracy of the models were compared. ST5, ST59, and ST239 were the major MLST types, and ST45 was the minor type. For binary classification, the AUC values of various ML methods ranged from 0.76 to 0.99 for ST5, ST59, and ST239 types. In multiclass classification, the predictive accuracy of all generated models was more than 0.83. This study has demonstrated that ML methods can serve as a cost-effective and promising tool that provides preliminary strain typing information about major MRSA lineages on the basis of MALDI-TOF spectra.