Actinobaculum suis Detection Using Polymerase Chain Reaction

Actinobaculum suis is an important agent related to urinary infection in swine females. Due to its fastidious growth characteristics, the isolation of this anaerobic bacterium is difficult, thus impairing the estimation of its prevalence. The purpose of this study was to develop and test a polymerase chain reaction (PCR) for the detection and identification of A. suis and then compare these results with traditional isolation methods. Bacterial isolation and PCR were performed on one hundred and ninety-two urine samples from sows and forty-five preputial swabs from boars. The results indicate that this PCR was specific for A. suis, presenting a detection limit between 1.0 x 10(1) CFU/mL and 1.0 x 10(2) CFU/mL. A. suis frequencies, as measured by PCR, were 8.9% (17/192) in sow urine samples and 82.2% (37/45) in preputial swabs. Assessed using conventional culturing techniques, none of the urine samples were positive for A. suis; however, A. suis was detected in 31.1% (14/45) of the swabs. This PCR technique was shown to be an efficient method for the detection of A. suis in urine and preputial swabs.

Real-time PCR assay targeting the actin gene for the detection of Cryptosporidium parvum in calf fecal samples

Cryptosporidium parvum infection is very important with respect to public health, owing to foodborne and waterborne outbreaks and gastrointestinal illness in immunocompetent and immunocompromised persons. In cattle, infection with this species manifests either as a subclinical disease or with diarrheal illness, which occurs more often in the presence of other infectious agents than when alone. The aim of this study was to develop a real-time polymerase chain reaction (PCR) assay for the detection of C. parvum in calf fecal samples and to compare the results of this assay with those of the method routinely used for the diagnosis of Cryptosporidium spp., nested PCR targeting the 18S rRNA gene. Two hundred and nine fecal samples from calves ranging in age from 1 day to 6 months were examined using real-time PCR specific for the actin gene of C. parvum and by a nested PCR targeting the 18S rRNA gene of Cryptosporidium spp. Using real-time PCR detection, 73.2% (153 out of 209) of the samples were positive for C. parvum, while 56.5% (118 out of 209) of the samples were positive for Cryptosporidium spp. when the nested PCR amplification method was used for the detection. The analytical sensitivity of the real-time PCR was approximately one C. parvum oocyst. There was no significant nonspecific DNA amplification of any of the following species and genotype: Cryptosporidium andersoni, Cryptosporidium baileyi, Cryptosporidium bovis, Cryptosporidium canis, Cryptosporidium galli, Cryptosporidium ryanae, Cryptosporidium serpentis, or avian genotype II. Thus, we conclude that real-time PCR targeting the actin gene is a sensitive and specific method for the detection of C. parvum in calf fecal samples.

Serological detection of Plasmodium vivax malaria using recombinant proteins corresponding to the 19-kDa C-terminal region of the merozoite surface protein-1

Abstract Background Serological tests to detect antibodies specific to Plasmodium vivax could be a valuable tool for epidemiological studies, for screening blood donors in areas where the malaria is not endemic and for diagnosis of infected individuals. Because P. vivax cannot be easily obtained in vitro, ELISA assays using total or semi-purified antigens are rarely used. Based on this limitation, we tested whether recombinant proteins representing the 19 kDa C-terminal region of the merozoite surface protein-1 of P. vivax (MSP119) could be useful for serological detection of malaria infection. Methods Three purified recombinant proteins produced in Escherichia coli (GST-MSP119, His6-MSP119 and His6-MSP119-PADRE) and one in Pichia pastoris (yMSP119-PADRE) were compared for their ability to bind to IgG antibodies of individuals with patent P. vivax infection. The method was tested with 200 serum samples collected from individuals living in the north of Brazil in areas endemic for malaria, 53 serum samples from individuals exposed to Plasmodium falciparum infection and 177 serum samples from individuals never exposed to malaria. Results Overall, the sensitivity of the ELISA assessed with sera from naturally infected individuals was 95%. The proportion of serum samples that reacted with recombinant proteins GST-MSP119, His6-MSP119, His6-MSP119-PADRE and yMSP119-PADRE was 90%, 93.5%, 93.5% and 93.5%, respectively. The specificity values of the ELISA determined with sera from healthy individuals and from individuals with other infectious diseases were 98.3% (GST-MSP119), 97.7% (His6-MSP119 and His6-MSP119-PADRE) or 100% (yMSP119-PADRE). Conclusions Our study demonstrated that for the Brazilian population, an ELISA using a recombinant protein of the MSP119 can be used as the basis for the development of a valuable serological assay for the detection of P. vivax malaria.

Severe lower respiratory tract infection in infants and toddlers from a non-affluent population: viral etiology and co-detection as risk factors

Abstract Background Lower respiratory tract infection (LRTI) is a major cause of pediatric morbidity and mortality, especially among non-affluent communities. In this study we determine the impact of respiratory viruses and how viral co-detections/infections can affect clinical LRTI severity in children in a hospital setting. Methods Patients younger than 3 years of age admitted to a tertiary hospital in Brazil during the months of high prevalence of respiratory viruses had samples collected from nasopharyngeal aspiration. These samples were tested for 13 different respiratory viruses through real-time PCR (rt-PCR). Patients were followed during hospitalization, and clinical data and population characteristics were collected during that period and at discharge to evaluate severity markers, especially length of hospital stay and oxygen use. Univariate regression analyses identified potential risk factors and multivariate logistic regressions were used to determine the impact of specific viral detections as well as viral co-detections in relation to clinical outcomes. Results We analyzed 260 episodes of LRTI with a viral detection rate of 85% (n = 222). Co-detection was observed in 65% of all virus-positive episodes. The most prevalent virus was Respiratory Syncytial Virus (RSV) (54%), followed by Human Metapneumovirus (hMPV) (32%) and Human Rhinovirus (HRV) (21%). In the multivariate models, infants with co-detection of HRV + RSV stayed 4.5 extra days (p = 0.004), when compared to infants without the co-detection. The same trends were observed for the outcome of days of supplemental oxygen use. Conclusions Although RSV remains as the main cause of LRTI in infants our study indicates an increase in the length of hospital stay and oxygen use in infants with HRV detected by RT-PCR compared to those without HRV. Moreover, one can speculate that when HRV is detected simultaneously with RSV there is an additive effect that may be reflected in more severe clinical outcome. Also, our study identified a significant number of children infected by recently identified viruses, such as hMPV and Human Bocavirus (HBov), and this is a novel finding for poor communities from developing countries.

A serological follow-up of toxocariasis patients after chemotherapy based on the detection of IgG, IgA, and IgE antibodies by enzyme-linked immunosorbent assay.

A serological follow-up study was carried out on 27 children (1–12 years old) with visceral and/or ocular toxocariasis, after treatment with thiabendazole. A total of 159 serum samples were collected in a period ranging from 22–116 months. Enzyme-linked immunosorbent assays (IgG, IgA, and IgE ELISA) were standardized, using excretory–secretory antigens obtained from the second-stage larvae of a Toxocara canis culture. The sensitivity found for the IgG, IgA, and IgE ELISA, as determined in visceral toxocariasis patients, was 100%, 47.8%, and 78.3%, respectively. Approximately 84% of the patients presented single or multiple parasitosis, as diagnosed by stool examination, yet such variables did not appear to affect the anti-Toxocara immune response. Titers of specific IgE antibody showed a significant decrease during the first year after treatment, followed by a decrease in the IgA titers in the second year, and in the IgG titers from the fourth year onwards. Sera from all patients presented high avidity IgG antibodies, indicating that they were in the chronic phase of the disease. Moreover, 1 year after treatment, the level of leukocytes, eosinophils, and anti-A isohemagglutinin in patients decreased significantly. The present data suggest that IgE antibodies plus eosinophil counts are helpful parameters for patient followup after chemotherapy.

A quantitative TaqMan PCR assay for the detection of Ureaplasma diversum

Ureaplasma diversum in veterinary studies is an undesirable microbe, which may cause infection in bulls and may result in seminal vesiculitis, balanopostitis, and alterations in spermatozoids, whereas in cows, it may cause placentitis, fetal alveolitis, abortion, and birth of weak calves. U. diversum is released through organic secretions, especially semen, preputial and vaginal mucus, conjunctival secretion, and milk. The aim of the present study was to develop a TaqMan probe, highly sensitive and specific quantitative PCR (qPCR) assay for the detection and quantification of U. diversum from genital swabs of bovines. Primers and probes specific to U. diversum 16S rRNA gene were designed. The specificity, detection limit, intra- and inter-assay variability of qPCR to detect this ureaplasma was compared with the results of the conventional PCR assay (cPCR). Swabs of vaginal mucus from 169 cows were tested. The qPCR assay detected as few as 10 copies of U. diversum and was 100-fold more sensitive than the cPCR. No cross-reactivity with other Mollicutes or eubacteria was observed. U. diversum was detected in 79 swabs (46.42%) by qPCR, while using cPCR it was detected in 42 (25%) samples. The difference in cPCR and qPCR ureaplasma detection between healthy and sick animals was not statistically significant. But the U. diversum load in samples from animals with genital disorders was higher than in healthy animals. The qPCR assay developed herein is highly sensitive and specific for the detection and quantification of U. diversum in vaginal bovine samples.

Quantitative detection of Staphylococcus aureus, Enterococcus faecalis and Pseudomonas aeruginosa in human oral epithelial cells from subjects with periodontitis and periodontal health

Epithelial cells in oral cavities can be considered reservoirs for a variety of bacterial species. A polymicrobial intracellular flora associated with periodontal disease has been demonstrated in buccal cells. Important aetiological agents of systemic and nosocomial infections have been detected in the microbiota of subgingival biofilm, especially in individuals with periodontal disease. However, non-oral pathogens internalized in oral epithelial cells and their relationship with periodontal status are poorly understood. The purpose of this study was to detect opportunistic species within buccal and gingival crevice epithelial cells collected from subjects with periodontitis or individuals with good periodontal health, and to associate their prevalence with periodontal clinical status. Quantitative detection of total bacteria and Staphylococcus aureus, Pseudomonas aeruginosa and Enterococcus faecalis in oral epithelial cells was determined by quantitative real-time PCR using universal and species-specific primer sets. Intracellular bacteria were visualized by confocal microscopy and fluorescence in situ hybridization. Overall, 33 % of cell samples from patients with periodontitis contained at least one opportunistic species, compared with 15 % of samples from healthy individuals. E. faecalis was the most prevalent species found in oral epithelial cells (detected in 20.6 % of patients with periodontitis, P = 0.03 versus healthy individuals) and was detected only in cells from patients with periodontitis. Quantitative real-time PCR showed that high levels of P. aeruginosa and S. aureus were present in both the periodontitis and healthy groups. However, the proportion of these species was significantly higher in epithelial cells of subjects with periodontitis compared with healthy individuals (P = 0.016 for P. aeruginosa and P = 0.047 for S. aureus). Although E. faecalis and P. aeruginosa were detected in 57 % and 50 % of patients, respectively, with probing depth and clinical attachment level ≥6 mm, no correlation was found with age, sex, bleeding on probing or the presence of supragingival biofilm. The prevalence of these pathogens in epithelial cells is correlated with the state of periodontal disease.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

From fall-risk assessment to fall detection: inertial sensors in the clinical routine and daily life

Falls are caused by complex interaction between multiple risk factors which may be modified by age, disease and environment. A variety of methods and tools for fall risk assessment have been proposed, but none of which is universally accepted. Existing tools are generally not capable of providing a quantitative predictive assessment of fall risk. The need for objective, cost-effective and clinically applicable methods would enable quantitative assessment of fall risk on a subject-specific basis. Tracking objectively falls risk could provide timely feedback about the effectiveness of administered interventions enabling intervention strategies to be modified or changed if found to be ineffective. Moreover, some of the fundamental factors leading to falls and what actually happens during a fall remain unclear. Objectively documented and measured falls are needed to improve knowledge of fall in order to develop more effective prevention strategies and prolong independent living. In the last decade, several research groups have developed sensor-based automatic or semi-automatic fall risk assessment tools using wearable inertial sensors. This approach may also serve to detect falls. At the moment, i) several fall-risk assessment studies based on inertial sensors, even if promising, lack of a biomechanical model-based approach which could provide accurate and more detailed measurements of interests (e.g., joint moments, forces) and ii) the number of published real-world fall data of older people in a real-world environment is minimal since most authors have used simulations with healthy volunteers as a surrogate for real-world falls. With these limitations in mind, this thesis aims i) to suggest a novel method for the kinematics and dynamics evaluation of functional motor tasks, often used in clinics for the fall-risk evaluation, through a body sensor network and a biomechanical approach and ii) to define the guidelines for a fall detection algorithm based on a real-world fall database availability.

Structured antibody surfaces for bio-recognition and a label-free detection of bacteria

Antibody microarrays are of great research interest because of their potential application as biosensors for high-throughput protein and pathogen screening technologies. In this active area, there is still a need for novel structures and assemblies providing insight in binding interactions such as spherical and annulus-shaped protein structures, e.g. for the utilization of curved surfaces for the enhanced protein-protein interactions and detection of antigens. Therefore, the goal of the presented work was to establish a new technique for the label-free detection of bio-molecules and bacteria on topographically structured surfaces, suitable for antibody binding.rnIn the first part of the presented thesis, the fabrication of monolayers of inverse opals with 10 μm diameter and the immobilization of antibodies on their interior surface is described. For this purpose, several established methods for the linking of antibodies to glass, including Schiff bases, EDC/S-NHS chemistry and the biotin-streptavidin affinity system, were tested. The employed methods included immunofluorescence and image analysis by phase contrast microscopy. It could be shown that these methods were not successful in terms of antibody immobilization and adjacent bacteria binding. Hence, a method based on the application of an active-ester-silane was introduced. It showed promising results but also the need for further analysis. Especially the search for alternative antibodies addressing other antigens on the exterior of bacteria will be sought-after in the future.rnAs a consequence of the ability to control antibody-functionalized surfaces, a new technique employing colloidal templating to yield large scale (~cm2) 2D arrays of antibodies against E. coli K12, eGFP and human integrin αvβ3 on a versatile useful glass surface is presented. The antibodies were swept to reside around the templating microspheres during solution drying, and physisorbed on the glass. After removing the microspheres, the formation of annuli-shaped antibody structures was observed. The preserved antibody structure and functionality is shown by binding the specific antigens and secondary antibodies. The improved detection of specific bacteria from a crude solution compared to conventional “flat” antibody surfaces and the setting up of an integrin-binding platform for targeted recognition and surface interactions of eukaryotic cells is demonstrated. The structures were investigated by atomic force, confocal and fluorescence microscopy. Operational parameters like drying time, temperature, humidity and surfactants were optimized to obtain a stable antibody structure.

Detection and molecular characterization of viruses infecting Actinidia spp.

Kiwifruit (genus Actinidia) is an important horticultural crop grown in the temperate regions. The four world’s largest producers are China, Italy, New Zealand and Chile. More than 50 species are recognized in the genus but the principal species in cultivation are A. deliciosa and A. chinensis. In Italy, as well as in many other countries, the kiwifruit crop has been considered to be relatively disease free and then no certification system for this species has been developed to regulate importation of propagation plant material in the European Union. During the last years a number of fungal and bacterial diseases have been recorded such as Botrytis cinerea and Pseudomonas syringae pv. actinidiae. Since 2003, several viruses and virus-like diseases have been identified and more recent studies demonstrated that Actinidia spp can be infected by a wide range of viral agents. In collaboration with the University of Auckland we have been detected thirteen different viral species on kiwifruit plants. During the three years of my PhD I worked on the characterization of Cucumber mosaic virus (CMV) and Pelargonium zonate spot virus (PZSV). The determination of causal agents has been based on host range, symptom expression in the test plant species and morphological properties of the virus particles using transmission electron microscopy (TEM) and using specific oligonucleotide primers in reverse transcription-polymerase chain reaction (RT-PCR). Both viruses induced several symptoms on kiwifruit plants. Moreover with new technologies such as high-throughput sequencing we detected additional viruses, a new member of the family Closteroviridae and a new member of the family Totiviridae. Taking together all results of my studies it is clear that, in order to minimize the risk of serious viral disease in kiwifruit, it is vital to use virus-free propagation material in order to prevent the spread of these viruses.

Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.

Multiple pathogen detection using nanoplasmonic sensing

Opportunistic diseases caused by Human Immunodeficiency Virus (HIV) and Hepatitis B Virus (HBV) is an omnipresent global challenge. In order to manage these epidemics, we need to have low cost and easily deployable platforms at the point-of-care in high congestions regions like airports and public transit systems. In this dissertation we present our findings in using Localized Surface Plasmon Resonance (LSPR)-based detection of pathogens and other clinically relevant applications using microfluidic platforms at the point-of-care setting in resource constrained environment. The work presented here adopts the novel technique of LSPR to multiplex a lab-on-a-chip device capable of quantitatively detecting various types of intact viruses and its various subtypes, based on the principle of a change in wavelength occurring when metal nano-particle surface is modified with a specific surface chemistry allowing the binding of a desired pathogen to a specific antibody. We demonstrate the ability to detect and quantify subtype A, B, C, D, E, G and panel HIV with a specificity of down to 100 copies/mL using both whole blood sample and HIV-patient blood sample discarded from clinics. These results were compared against the gold standard Reverse Transcriptase Polymerase Chain Reaction (RT-qPCR). This microfluidic device has a total evaluation time for the assays of about 70 minutes, where 60 minutes is needed for the capture and 10 minutes for data acquisition and processing. This LOC platform eliminates the need for any sample preparation before processing. This platform is highly multiplexable as the same surface chemistry can be adapted to capture and detect several other pathogens like dengue virus, E. coli, M. Tuberculosis, etc.

Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.