Detection sensitivity and quantitation of Plasmodium falciparum var gene transcripts by real-time RT-PCR in comparison with conventional RT-PCR

Antigenic variation in Plasmodium falciparum erythrocyte membrane protein 1, caused by a switch in transcription of the encoding var gene, is an important feature of malaria. In this study, we quantified the relative abundance of var gene transcripts present in P. falciparum parasite clones using real-time reverse transcription-polymerase chain reaction (RT-PCR) and conventional RT-PCR combined with cloning and sequencing, with the aim of directly comparing the results obtained. When there was sufficient abundance of RNA for the real-time RT-PCR assay to be operating within the region of good reproducibility, RT-PCR and real-time RT-PCR tended to identify the same dominant transcript, although some transcript-specific issues were identified. When there were differences in the estimated relative amounts of minor transcripts, the RT-PCR assay tended to produce higher estimates than real-time RT-PCR. These results provide valuable information comparing RT-PCR and real-time RT-PCR analysis of samples with small quantities of RNA as might be expected in the analysis of field or clinical samples.

Sensitive detection of nitric oxide using seeded parametric four-wave mixing

A sensitive near-resonant four-wave mixing technique based on two-photon parametric four-wave mixing has been developed. Seeded parametric four-wave mixing requires only a single laser as an additional phase matched seeder field is generated via parametric four-wave mixing of the pump beam in a high gain cell. The seeder field travels collinearly with the pump beam providing efficient nondegenerate four-wave mixing in a second medium. This simple arrangement facilitates the detection of complex molecular spectra by simply scanning the pump laser. Seeded parametric four-wave mixing is demonstrated in both a low pressure cell and an air/acetylene flame with detection of the two-photon C (2) Pi(upsilon'=0)<--X (2) Pi(upsilon =0) spectrum of nitric oxide. From the cell data a detection limit of 10(12) molecules/cm(3) is established. A theoretical model of seeded parametric four-wave mixing is developed from existing parametric four-wave mixing theory. The addition of the seeder field significantly modifies the parametric four-wave mixing behaviour such that in the small signal regime, the signal intensity can readily be made to scale as the cube of the laser pump power while the density dependence follows a more familiar square law dependence, In general, we find excellent agreement between theory and experiment. Limitations to the process result from an ac Stark shift of the two-photon resonance in the high pressure seeder cell caused by the generation of a strong seeder field, as well as a reduction in phase matching efficiency due to the presence of certain buffer species. Various optimizations are suggested which should overcome these limitations, providing even greater detection sensitivity. (C) 1998 American Institute of Physics, [S0021-9606(98)01014-9].

Sensitive detection of sodium in a flame using parametric four-wave mixing and seeded parametric four-wave mixing

Two-photon resonant parametric four-wave mixing and a newly developed variant called seeded parametric four-wave mixing are used to detect trace quantities of sodium in a flame. Both techniques are simple, requiring only a single laser to generate a signal beam at a different wavelength which propagates collinearly with the pump beam, allowing efficient signal recovery. A comparison of the two techniques reveals that seeded parametric four-wave mixing is more than two orders of magnitude more sensitive than parametric four-wave mixing, with an estimated detection sensitivity of 5 x 10(9) atoms/cm(3). Seeded parametric four-wave mixing is achieved by cascading two parametric four-wave mixing media such that one of the parametric fields generated in the first high-density medium is then used to seed the same four-wave mixing process in a second medium in order to increase the four-wave mixing gain. The behavior of this seeded parametric four-wave mixing is described using semiclassical perturbation theory. A simplified small-signal theory is found to model most of the data satisfactorily. However, an anomalous saturationlike behavior is observed in the large signal regime. The full perturbation treatment, which includes the competition between two different four-wave mixing processes coupled via the signal field, accounts for this apparently anomalous behavior.

DNA nanoprobes for molecular detection

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Biológica – especialidade Engenharia Genética, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Two sequential PCR amplifications for detection of Schistosoma mansoni in stool samples with low parasite load

Schistosomiasis constitutes a major public health problem, with an estimated 200 million individuals infected worldwide and 700 million people living in risk areas. In Brazil there are areas of high, medium and low endemicity. Studies have shown that in endemic areas with a low prevalence of Schistosoma infection the sensitivity of parasitological methods is clearly reduced. Consequently diagnosis is often impeded due to the presence of false-negative results. The aim of this study is to present the PCR reamplification (Re-PCR) protocol for the detection of Schistosoma mansoni in samples with low parasite load (with less than 100 eggs per gram (epg) of feces). Three methods were used for the lysis of the envelopes of the S. mansoni eggs and two techniques of DNA extraction were carried out. Extracted DNA was quantified, and the results suggested that the extraction technique, which mixed glass beads with a guanidine isothiocyanate/phenol/chloroform (GT) solution, produced good results. PCR reamplification was conducted and detection sensitivity was found to be five eggs per 500 mg of artificially marked feces. The results achieved using these methods suggest that they are potentially viable for the detection of Schistosoma infection with low parasite load.

Rapid and sensitive detection of Bordetella bronchiseptica by loop-mediated isothermal amplification (LAMP)

Bordetella bronchiseptica causes acute and chronic respiratory infections in diverse animal species and occasionally in humans. In this study, we described the establishment of a simple, sensitive and cost-efficient loop-mediated isothermal amplification (LAMP) assay for the detection of B. bronchiseptica. A set of primers towards a 235 bp region within the flagellum gene of B. bronchiseptica was designed with online software.. The specificity of the LAMP assay was examined by using 6 porcine pathogens and 100 nasal swabs collected from healthy pigs and suspect infected pigs. The results indicated that positive reactions were confirmed for all B. bronchiseptica and no cross-reactivity was observed from other non-B. bronchiseptica. In sensitivity evaluations, the technique successfully detected a serial dilutions of extracted B. bronchiseptica DNA with a detection limit of 9 copies, which was 10 times more sensitive than that of PCR. Compared with conventional PCR, the higher sensitivity of LAMP method and no need for the complex instrumentation make this LAMP assay a promising alternative for the diagnosis of B. bronchiseptica in rural areas and developing countries where there lacks of complex laboratory services.

Two sequential PCR amplifications for detection of Schistosoma mansoni in stool samples with low parasite load

Schistosomiasis constitutes a major public health problem, with an estimated 200 million individuals infected worldwide and 700 million people living in risk areas. In Brazil there are areas of high, medium and low endemicity. Studies have shown that in endemic areas with a low prevalence of Schistosoma infection the sensitivity of parasitological methods is clearly reduced. Consequently diagnosis is often impeded due to the presence of false-negative results. The aim of this study is to present the PCR reamplification (Re-PCR) protocol for the detection of Schistosoma mansoni in samples with low parasite load (with less than 100 eggs per gram (epg) of feces). Three methods were used for the lysis of the envelopes of the S. mansoni eggs and two techniques of DNA extraction were carried out. Extracted DNA was quantified, and the results suggested that the extraction technique, which mixed glass beads with a guanidine isothiocyanate/phenol/chloroform (GT) solution, produced good results. PCR reamplification was conducted and detection sensitivity was found to be five eggs per 500 mg of artificially marked feces. The results achieved using these methods suggest that they are potentially viable for the detection of Schistosoma infection with low parasite load.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.

A Loop-mediated Isothermal Amplification Method for Rapid Direct Detection and Differentiation of Non-pathogenic and Verocytotoxigenic Escherichia coli in Beef and Bovine Faeces

The aim of this study was to develop a multiplex loop-mediated isothermal amplification (LAMP) method capable of detecting Escherichia coli generally and verocytotoxigenic E. coli (VTEC) specifically in beef and bovine faeces. The LAMP assay developed was highly specific (100%) and able to distinguish between E. coli and VTEC based on the amplification of the phoA, and stx1 and/or stx2 genes, respectively. In the absence of an enrichment step, the limit of detection 50% (LOD50) of the LAMP assay was determined to be 2.83, 3.17 and 2.83-3.17 log CFU/g for E. coli with phoA, stx1 and stx2 genes, respectively, when artificially inoculated minced beef and bovine faeces were tested. The LAMP calibration curves generated with pure cultures, and spiked beef and faeces, suggested that the assay had good quantification capability. Validation of the assay, performed using retail beef and bovine faeces samples, demonstrated good correlation between counts obtained by the LAMP assay and by a conventional culture method, but suggested the possibility of false negative LAMP results for 12.5-14.7% of samples tested. The multiplex LAMP assay developed potentially represents a rapid alternative to culture for monitoring E.coli levels in beef or faeces and it would provide additional information on the presence of VTEC. However, some further optimisation is needed to improve detection sensitivity.

Sensitive and specific detection of viable Mycobacterium avium subsp. paratuberculosis in raw milk by the Peptide-mediated magnetic separation (PMS)-phage assay

This study describes further validation of a previously described Peptide-mediated magnetic separation (PMS)-Phage assay, and its application to test raw cows’ milk for presence of viable Mycobacterium avium subsp. paratuberculosis (MAP). The inclusivity and exclusivity of the PMS-phage assay were initially assessed, before the 50% limit of detection (LOD50) was determined and compared with those of PMS-qPCR (targeting both IS900 and f57) and PMS-culture. These methods were then applied in parallel to test 146 individual milk samples and 22 bulk tank milk samples from Johne’s affected herds. Viable MAP were detected by the PMS-phage assay in 31 (21.2%) of 146 individual milk samples (mean plaque count of 228.1 PFU/50 ml, range 6-948 PFU/50 ml), and 13 (59.1%) of 22 bulk tank milks (mean plaque count of 136.83 PFU/50 ml, range 18-695 PFU/50 ml). In contrast, only 7 (9.1%) of 77 individual milks and 10 (45.4%) of 22 bulk tank milks tested PMS-qPCR positive, and 17 (11.6%) of 146 individual milks and 11 (50%) of 22 bulk tank milks tested PMS-culture positive. The mean 50% limits of detection (LOD50) of the PMS-phage, PMS-IS900 qPCR and PMS-f57 qPCR assays, determined by testing MAP-spiked milk, were 0.93, 135.63 and 297.35 MAP CFU/50 ml milk, respectively. Collectively, these results demonstrate that, in our laboratory, the PMS-phage assay is a sensitive and specific method to quickly detect the presence of viable MAP cells in milk. However, due to its complicated, multi-step nature, the method would not be a suitable MAP screening method for the dairy industry.

MICROFLUIDIC ASSAY PERFORMANCE ENHANCEMENT USING POROUS VOLUMETRIC DETECTION ELEMENTS FOR IMPEDEMETRIC AND OPTICAL SENSING

Microfluidic technologies have great potential to help create automated, cost-effective, portable devices for rapid point of care (POC) diagnostics in diverse patient settings. Unfortunately commercialization is currently constrained by the materials, reagents, and instrumentation required and detection element performance. While most microfluidic studies utilize planar detection elements, this dissertation demonstrates the utility of porous volumetric detection elements to improve detection sensitivity and reduce assay times. Impedemetric immunoassays were performed utilizing silver enhanced gold nanoparticle immunoconjugates (AuIgGs) and porous polymer monolith or silica bead bed detection elements within a thermoplastic microchannel. For a direct assay with 10 µm spaced electrodes the detection limit was 0.13 fM AuIgG with a 3 log dynamic range. The same assay was performed with electrode spacing of 15, 40, and 100 µm with no significant difference between configurations. For a sandwich assay the detection limit was10 ng/mL with a 4 log dynamic range. While most impedemetric assays rely on expensive high resolution electrodes to enhance planar senor performance, this study demonstrates the employment of porous volumetric detection elements to achieve similar performance using lower resolution electrodes and shorter incubation times. Optical immunoassays were performed using porous volumetric capture elements perfused with refractive index matching solutions to limit light scattering and enhance signal. First, fluorescence signal enhancement was demonstrated with a porous polymer monolith within a silica capillary. Next, transmission enhancement of a direct assay was demonstrated by infusing aqueous sucrose solutions through silica bead beds with captured silver enhanced AuIgGs yielding a detection limit of 0.1 ng/mL and a 5 log dynamic range. Finally, ex situ functionalized porous silica monolith segments were integrated into thermoplastic channels for a reflectance based sandwich assay yielding a detection limit of 1 ng/mL and a 5 log dynamic range. The simple techniques for optical signal enhancement and ex situ element integration enable development of sensitive, multiplexed microfluidic sensors. Collectively the demonstrated experiments validate the use of porous volumetric detection elements to enhance impedemetric and optical microfluidic assays. The techniques rely on commercial reagents, materials compatible with manufacturing, and measurement instrumentation adaptable to POC diagnostics.

“Green Electrodes” Modified with Au Nanoparticles Synthesized in Glycerol, as Electrochemical Nitrite Sensor

A new environmentally friendly Au nanoparticles (Au NPs) synthesis in glycerol by using ultraviolet irradiation and without extra-added stabilizers is described. The synthesis proposed in this work may impact on the non-polluting production of noble nanoparticles with simple chemicals normally found in standard laboratories. These Au NPs were used to modify a carbon paste electrode (CPE) without having to separate them from the reaction medium. This green electrode was used as an electrochemical sensor for the nitrite detection in water. At the optimum conditions the green sensor presented a linear response in the 2.0×10−7–1.5×10−5 M concentration range, a good detection sensitivity (0.268 A L mol−1), and a low detection limit of 2.0×10−7 M of nitrite. The proposed modified green CPE was used to determine nitrite in tap water samples.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment