Detection and differentiation of Plasmodium species by polymerase chain reaction and colorimetric detection in blood samples of patients with suspected malaria

Polymerase chain reaction (PCR) is now recognized as a sensitive and specific method for detecting Plasmodium species in blood. In this Study. we tested 279 blood samples, from patients with Suspected malaria, by a PCR assay utilizing species-specific colorimetric detection. and compared the results to light microscopy. Overall, both assays were in agreement for 270 of the 279 specimens. P. vivax was detected in 131 (47.0%) specimens. P. falciparum in 64 (22.9%) specimens, P. ovale in 6 (2.1%) specimens, and P. malariae in 5 (1.8%) specimens. Both P. falciparum and P. vivax were detected in a further 10 (3.6%) specimens, and 54 (19.3%) specimens were negative by both assays. In the remaining nine specimens, microscopy either failed to detect the parasite or incorrectly identified the species present. In summary, the sensitivity, specificity and simplicity of the PCR assay makes it particularly suitable for use in a diagnostic laboratory. (C) 2004 Elsevier Inc. All rights reserved.

Method for detection of respiratory viruses in the sputa of patients with cystic fibrosis

Since the role of respiratory viruses in lung exacerbations of patients with cystic fibrosis has been hampered by the difficulty of detecting viruses in viscous sputum specimens, a multiplex reverse transcriptase PCR (RT-PCR) assay combined with colorimetric amplicon detection was tested for the identification of seven common respiratory viruses in the sputa of cystic fibrosis patients. Of 52 sputa from 38 patients, 12 (23%) samples from 12 patients were positive for a respiratory virus (4 for influenza B, 3 for parainfluenza 1, 3 for influenza A and 2 for respiratory syncytial virus). These results suggest that the RT-PCR method carried out on sputum may provide a convenient means of investigating the role of virus infection in lung exacerbations of cystic fibrosis patients.

Conditional production of superpositions of coherent states with inefficient photon detection

It is shown that a linear superposition of two macroscopically distinguishable optical coherent states can be generated using a single photon source and simple all-optical operations. Weak squeezing on a single photon, beam mixing with an auxiliary coherent state, and photon detecting with imperfect threshold detectors are enough to generate a coherent state superposition in a free propagating optical field with a large coherent amplitude (alpha>2) and high fidelity (F>0.99). In contrast to all previous schemes to generate such a state, our scheme does not need photon number resolving measurements nor Kerr-type nonlinear interactions. Furthermore, it is robust to detection inefficiency and exhibits some resilience to photon production inefficiency.

Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.