A TaqMan-based real-time PCR qualitative assay for the detection of three species of malaria parasitesPlasmodium falciparum, P. ovale, and P. vivax-was devised and evaluated using 122 whole-blood samples from patients who had traveled to areas where malaria is endemic and who presented with malaria-like symptoms and fever. The assay was compared to conventional microscopy and to an established nested-PCR assay. The specificity of the new assay was confirmed by sequencing the PCR products from all the positive samples and by the lack of cross-reactivity with Toxoplasma gondii and Leishmania infantum DNA. Real-time PCR assay showed a detection limit (analytical sensitivity) of 0.7, 4, and 1.5 parasites/l for P. falciparum, P. vivax, and P. ovale, respectively. Real-time PCR, like nested PCR, brought to light errors in the species identification by microscopic examination and revealed the presence of mixed infections (P. falciparum plus P. ovale). Real-time PCR can yield results within 2 h, does not require post-PCR processing, reduces sample handling, and minimizes the risks of contamination. The assay can therefore be easily implemented in routine diagnostic malaria tests. Future studies are warranted to investigate the clinical value of this technique.

No abstract

Virus detection and/or identification traditionally rely on methods based on cell culture, electron microscopy and antigen or nucleic acid detection. These techniques are good, but often expensive and/or time-consuming; furthermore, they not always lead to virus identification at the species and/or type level. In this study, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was tested as an innovative tool to identify human polioviruses and to identify specific viral protein biomarkers in infected cells. The results revealed MALDI-TOF MS to be an effective and inexpensive tool for the identification of the three poliovirus serotypes. The method was firstly applied to Sabin reference strains, and then to isolates from different clinical samples, highlighting its value as a time-saving, sensitive and specific technique when compared to the gold standard neutralization assay and casting new light on its possible application to virus detection and/or identification.

Graphical abstract

Variability in severity among different respiratory syncytial virus (RSV) seasons may influence hospital admission rates for RSV-induced lower respiratory tract infection (LRTI) in young children. The aim of the present study was to identify through logistic regression analysis, risk factors associated with higher likelihood to acquire RSV-induced LRTI, in children with symptoms severe enough to lead to hospital admission. Over four consecutive RSV seasons (2000)(2001)(2002)(2003)(2004), records from children <4 years of age admitted for RSV-induced LRTI ("cases") were compared with those from children with LRTI not due to RSV and not requiring hospitalization ("controls"). 145 "case-patients" and 295 "control-patients" were evaluated. Independent from the severity of the four epidemic seasons, seven predictors for hospitalization for RSV infection were found in the bivariate analysis: number of children in the family, chronological age at the onset of RSV season, birth weight and gestational age, birth order, daycare attendance, previous RSV infections. In the logistic regression analysis, only three predictors were detected: chronological age at the beginning of RSV season [aOR=8.46; 95% CI:3.09-23.18]; birth weight category [aOR=7.70; 95% CI:1.29-45.91]; birth order (aOR=1.92; 95% CI:1.21-3.06). Conclusions: Independent from the RSV seasonality, specific host/environmental factors can be used to identify children at greatest risk for hospitalization for RSV infection.