Design and development of an enzyme-linked biosensor for detection and quantification of phosphate species

The objective of this study is to design and development of an enzyme-linked biosensor for detection and quantification of phosphate species. Various concentrations of phosphate species were tested and completed for this study. Phosphate is one of the vital nutrients for all living organisms. Phosphate compounds can be found in nature (e.g., water sediments), and they often exist in aninorganic form. The amount of phosphates in the environment strongly influences the operations of living organisms. Excess amount of phosphate in the environment causes eutrophication which in turn causes oxygen deficit for the other living organisms. Fish die and degradation of habitat in the water occurs as a result of eutrophication. In contrast, low phosphate concentration causes death of vegetation since plants utilize the inorganic phosphate for photosynthesis, respiration, and regulation of enzymes. Therefore, the phosphate quantity in lakes and rivers must be monitored. Result demonstrated that phosphate species could be detected in various organisms via enzyme-linked biosensor in this research.

Detection and Classification of Whale Acoustic Signals

This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification.

In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information.

In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data.

Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear.

We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale vocalization data set. The word error rate of the DCTNet feature is similar to the MFSC in speech recognition tasks, suggesting that the convolutional network is able to reveal acoustic content of speech signals.

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.

Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio

Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.

Rapid detection and quantification of the marine toxic algae, Alexandrium minutum, using a super-paramagnetic immunochromatographic strip test

The dinoflagellates of Alexandrium genus are known to be producers of paralytic shellfish toxins that regularly impact the shellfish aquaculture industry and fisheries. Accurate detection of Alexandrium including A. minutum is crucial for environmental monitoring and sanitary issues. In this study, we firstly developed a quantitative lateral flow immunoassay (LFIA) using super-paramagnetic nanobeads for A. minutum whole cells. This dipstick assay relies on two distinct monoclonal antibodies used in a sandwich format and directed against surface antigens of this organism. No sample preparation is required. Either frozen or live cells can be detected and quantified. The specificity and sensitivity are assessed by using phytoplankton culture and field samples spiked with a known amount of cultured A. minutum cells. This LFIA is shown to be highly specific for A. minutum and able to detect reproducibly 105 cells/L within 30 min. The test is applied to environmental samples already characterized by light microscopy counting. No significant difference is observed between the cell densities obtained by these two methods. This handy super-paramagnetic lateral flow immnunoassay biosensor can greatly assist water quality monitoring programs as well as ecological research.

The SOPHIE search for northern extrasolar planets: X. Detection and characterization of giant planets by the dozen

We present new radial velocity measurements of eight stars that were secured with the spectrograph SOPHIE at the 193 cm telescope of the Haute-Provence Observatory. The measurements allow detecting and characterizing new giant extrasolar planets. The host stars are dwarfs of spectral types between F5 and K0 and magnitudes of between 6.7 and 9.6; the planets have minimum masses Mp sin i of between 0.4 to 3.8 MJup and orbitalperiods of several days to several months. The data allow only single planets to be discovered around the first six stars (HD 143105, HIP 109600, HD 35759, HIP 109384, HD 220842, and HD 12484), but one of them shows the signature of an additional substellar companion in the system. The seventh star, HIP 65407, allows the discovery of two giant planets that orbit just outside the 12:5 resonance in weak mutual interaction. The last star, HD 141399, was already known to host a four-planet system; our additional data and analyses allow new constraints to be set on it. We present Keplerian orbits of all systems, together with dynamical analyses of the two multi-planet systems. HD 143105 is one of the brightest stars known to host a hot Jupiter, which could allow numerous follow-up studies to be conducted even though this is not a transiting system. The giant planets HIP 109600b, HIP 109384b, and HD 141399c are located in the habitable zone of their host star.

A real-time reverse transcriptase polymerase chain reaction for detection and quantification of Vesiculovirus

Vesiculoviruses (VSV) are zoonotic viruses that cause vesicular stomatitis disease in cattle, horses and pigs, as well as sporadic human cases of acute febrile illness. Therefore, diagnosis of VSV infections by reliable laboratory techniques is important to allow a proper case management and implementation of strategies for the containment of virus spread. We show here a sensitive and reproducible real-time reverse transcriptase polymerase chain reaction (RT-PCR) for detection and quantification of VSV. The assay was evaluated with arthropods and serum samples obtained from horses, cattle and patients with acute febrile disease. The real-time RT-PCR amplified the Piry, Carajas, Alagoas and Indiana Vesiculovirus at a melting temperature 81.02 ± 0.8ºC, and the sensitivity of assay was estimated in 10 RNA copies/mL to the Piry Vesiculovirus. The viral genome has been detected in samples of horses and cattle, but not detected in human sera or arthropods. Thus, this assay allows a preliminary differential diagnosis of VSV infections.

The effect of sample and sample matrix on DNA processing: Mechanisms for the detection and management of inhibition in forensic samples

The presence of inhibitory substances in biological forensic samples has, and continues to affect the quality of the data generated following DNA typing processes. Although the chemistries used during the procedures have been enhanced to mitigate the effects of these deleterious compounds, some challenges remain. Inhibitors can be components of the samples, the substrate where samples were deposited or chemical(s) associated to the DNA purification step. Therefore, a thorough understanding of the extraction processes and their ability to handle the various types of inhibitory substances can help define the best analytical processing for any given sample. A series of experiments were conducted to establish the inhibition tolerance of quantification and amplification kits using common inhibitory substances in order to determine if current laboratory practices are optimal for identifying potential problems associated with inhibition. DART mass spectrometry was used to determine the amount of inhibitor carryover after sample purification, its correlation to the initial inhibitor input in the sample and the overall effect in the results. Finally, a novel alternative at gathering investigative leads from samples that would otherwise be ineffective for DNA typing due to the large amounts of inhibitory substances and/or environmental degradation was tested. This included generating data associated with microbial peak signatures to identify locations of clandestine human graves. Results demonstrate that the current methods for assessing inhibition are not necessarily accurate, as samples that appear inhibited in the quantification process can yield full DNA profiles, while those that do not indicate inhibition may suffer from lowered amplification efficiency or PCR artifacts. The extraction methods tested were able to remove >90% of the inhibitors from all samples with the exception of phenol, which was present in variable amounts whenever the organic extraction approach was utilized. Although the results attained suggested that most inhibitors produce minimal effect on downstream applications, analysts should practice caution when selecting the best extraction method for particular samples, as casework DNA samples are often present in small quantities and can contain an overwhelming amount of inhibitory substances.^

First molecular detection and characterization of herpesvirus and poxvirus in a Pacific walrus (Odobenus rosmarus divergens)

BACKGROUND Herpesvirus and poxvirus can infect a wide range of species: herpesvirus genetic material has been detected and amplified in five species of the superfamily Pinnipedia; poxvirus genetic material, in eight species of Pinnipedia. To date, however, genetic material of these viruses has not been detected in walrus (Odobenus rosmarus), another marine mammal of the Pinnipedia clade, even though anti-herpesvirus antibodies have been detected in these animals. CASE PRESENTATION In February 2013, a 9-year-old healthy captive female Pacific walrus died unexpectedly at L'Oceanografic (Valencia, Spain). Herpesvirus was detected in pharyngeal tonsil tissue by PCR. Phylogenetic analysis revealed that the virus belongs to the subfamily Gammaherpesvirinae. Poxvirus was also detected by PCR in skin, pre-scapular and tracheobronchial lymph nodes and tonsils. Gross lesions were not detected in any tissue, but histopathological analyses of pharyngeal tonsils and lymph nodes revealed remarkable lymphoid depletion and lymphocytolysis. Similar histopathological lesions have been previously described in bovine calves infected with an alphaherpesvirus, and in northern elephant seals infected with a gammaherpesvirus that is closely related to the herpesvirus found in this case. Intracytoplasmic eosinophilic inclusion bodies, consistent with poxviral infection, were also observed in the epithelium of the tonsilar mucosa. CONCLUSION To our knowledge, this is the first molecular identification of herpesvirus and poxvirus in a walrus. Neither virus was likely to have contributed directly to the death of our animal.

Detection and assessment of electrocution in endangered raptors by infrared thermography

BACKGROUND Most European birds of prey find themselves in a poor state of conservation, with electrocution as one of the most frequent causes of unnatural death. Since early detection of electrocution is difficult, treatment is usually implemented late, which reduces its effectiveness. By considering that electrocution reduces tissue temperature, it may be detectable by thermography, which would allow a more rapid identification. Three individuals from three endangered raptor species [Spanish imperial eagle (Aquila adalberti), Lammergeier (Gypaetus barbatus) and Osprey (Pandion haliaetus)] were studied thermographically from the time they were admitted to a rehabilitation centre to the time their clinical cases were resolved. CASES PRESENTATION The three raptors presented lesions lacking thermal bilateral symmetry and were consistent with electrocution of feet, wings and eyes, visible by thermography before than clinically; lesions were well-defined and showed a lower temperature than the surrounding tissue. Some lesions evolved thermally and clinically until the appearance of normal tissue recovered, while others evolved and became necrotic. A histopathological analysis of a damaged finger amputated off a Lammergeier, and the necropsy and histopathology examination of an osprey, confirmed the electrocution diagnosis. CONCLUSIONS These results suggest that thermography is effective and useful for the objective and early detection and monitoring of electrocuted birds, and that it may prove especially useful for examining live animals that require no amputation or cannot be subjected to invasive histopathology.

Analytic and heuristic processes in the detection and resolution of conflict

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dualprocess models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and singleprocess accounts, which are discussed.

Detection and Grading of Prostate Cancer in Temporal Enhanced Ultrasound using Convolutional Neural Networks

Prostate cancer is the most common non-dermatological cancer amongst men in the developed world. The current definitive diagnosis is core needle biopsy guided by transrectal ultrasound. However, this method suffers from low sensitivity and specificity in detecting cancer. Recently, a new ultrasound based tissue typing approach has been proposed, known as temporal enhanced ultrasound (TeUS). In this approach, a set of temporal ultrasound frames is collected from a stationary tissue location without any intentional mechanical excitation. The main aim of this thesis is to implement a deep learning-based solution for prostate cancer detection and grading using TeUS data. In the proposed solution, convolutional neural networks are trained to extract high-level features from time domain TeUS data in temporally and spatially adjacent frames in nine in vivo prostatectomy cases. This approach avoids information loss due to feature extraction and also improves cancer detection rate. The output likelihoods of two TeUS arrangements are then combined to form our novel decision support system. This deep learning-based approach results in the area under the receiver operating characteristic curve (AUC) of 0.80 and 0.73 for prostate cancer detection and grading, respectively, in leave-one-patient-out cross-validation. Recently, multi-parametric magnetic resonance imaging (mp-MRI) has been utilized to improve detection rate of aggressive prostate cancer. In this thesis, for the first time, we present the fusion of mp-MRI and TeUS for characterization of prostate cancer to compensates the deficiencies of each image modalities and improve cancer detection rate. The results obtained using TeUS are fused with those attained using consolidated mp-MRI maps from multiple MR modalities and cancer delineations on those by multiple clinicians. The proposed fusion approach yields the AUC of 0.86 in prostate cancer detection. The outcomes of this thesis emphasize the viable potential of TeUS as a tissue typing method. Employing this ultrasound-based intervention, which is non-invasive and inexpensive, can be a valuable and practical addition to enhance the current prostate cancer detection.