Detection of the protein dimers, multiple monomeric states and hydrated forms of Plasmodium falciparum triosephosphate isomerase in the gas phase

Dimeric and monomeric forms of the enzyme triosephosphate isomerase (TIM) from Plasmodium falciparum (Pf) have been detected under conditions of nanoflow by electrospray mass spectrometry. The dimer (M = 55 663 Da) exhibits a narrow charge state distribution with intense peaks limited to values of 18(+) to 21(+), maximal intensity being observed for charge states 19(+) and 20(+). A monomeric species with a charge state distribution ranging from 11(+) to 16(+) is also observed, which may be assigned to folded dissociated subunits. Complete dimer dissociation results under normal electrospray condition. The effects of solution pH and source temperature have been investigated. The observation of four distinct charge state distributions which may be assigned to a dimer, folded monomer, partially folded monomer and unfolded monomer is reported. Circular dichromism and fluorescence studies of Pf TIM at low pH support the retention of substantial secondary and tertiary structures. Satellite peaks in mass spectra corresponding to hydrated species are also observed and isotope shift upon deuteration is demonstrated. The analysis of all available independent crystal structures of Pf TIM and TIMs from other organisms permits identification of structurally conserved water molecules. Hydration observed in the dimer and folded monomeric forms in the gas phase may correspond to these conserved sites.

Efficient Hg and Ag ion detection with luminescent PbS quantum dots grown in poly vinyl alcohol and capped with mercaptoethanol

PbS quantum dots capped with mercaptoethanol (C2H5OSH) have been synthesized in poly vinyl alcohol and used to investigate their photoluminescence (PL) response to various ions such as zinc (Zn), cadmium (Cd), mercury (Hg), silver (Ag), copper (Cu), iron (Fe), manganese (Mn), cobalt (Co), chromium (Cr) and nickel (Ni). The enhancement in the PL intensity was observed with specific ions namely Zn, Cd, Hg and Ag. Among these four ions, the PL response to Hg and Ag even at sub-micro-molar concentrations was quite high, compared to that of Zn and Cd. It was observed that the change in Pb and S molar ratio has profound effect on the sensitivity of these ions. These results indicate that the sensitivity of these QDs could be fine-tuned by controlling the S concentration at the surface. Contrary to the above, Cu quenched the photoluminescence. In Cd based QDs related ion probing, Hg and Cu was found to have quenching properties, however, our PbS QDs have quenching property only for Cu ions. This was attributed to the formation HgS at the surface that has bandgap higher than PbS. Another interesting property of PbS in PVA observed is photo-brightening mechanism due to the curing of the polymer with laser. However, the presence of excess ions at the surface changes its property to photo-darkening/brightening that depends on the direction of carrier transfer mechanism (from QDs to the surface adsorbed metal ions or vice-versa). which is an interesting feature for metal ion detectivity.

A Bayesian Framework for the Assessment of Vision-based Weed and Fruit Detection and Classification Algorithms

This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Thin-Layer Chromatography with Ultraviolet and Mass Spectrometric Detection: From Preparative-Layer to Miniaturized Ultra-Thin-Layer Technique

The present challenge in drug discovery is to synthesize new compounds efficiently in minimal time. The trend is towards carefully designed and well-characterized compound libraries because fast and effective synthesis methods easily produce thousands of new compounds. The need for rapid and reliable analysis methods is increased at the same time. Quality assessment, including the identification and purity tests, is highly important since false (negative or positive) results, for instance in tests of biological activity or determination of early-ADME parameters in vitro (the pharmacokinetic study of drug absorption, distribution, metabolism, and excretion), must be avoided. This thesis summarizes the principles of classical planar chromatographic separation combined with ultraviolet (UV) and mass spectrometric (MS) detection, and introduces powerful, rapid, easy, low-cost, and alternative tools and techniques for qualitative and quantitative analysis of small drug or drug-like molecules. High performance thin-layer chromatography (HPTLC) was introduced and evaluated for fast semi-quantitative assessment of the purity of synthesis target compounds. HPTLC methods were compared with the liquid chromatography (LC) methods. Electrospray ionization mass spectrometry (ESI MS) and atmospheric pressure matrix-assisted laser desorption/ionization MS (AP MALDI MS) were used to identify and confirm the product zones on the plate. AP MALDI MS was rapid, and easy to carry out directly on the plate without scraping. The PLC method was used to isolate target compounds from crude synthesized products and purify them for bioactivity and preliminary ADME tests. Ultra-thin-layer chromatography (UTLC) with AP MALDI MS and desorption electrospray ionization mass spectrometry (DESI MS) was introduced and studied for the first time. Because of the thinner adsorbent layer, the monolithic UTLC plate provided 10 100 times better sensitivity in MALDI analysis than did HPTLC plates. The limits of detection (LODs) down to low picomole range were demonstrated for UTLC AP MALDI and UTLC DESI MS. In a comparison of AP and vacuum MALDI MS detection for UTLC plates, desorption from the irregular surface of the plates with the combination of an external AP MALDI ion source and an ion trap instrument provided clearly less variation in mass accuracy than the vacuum MALDI time-of-flight (TOF) instrument. The performance of the two-dimensional (2D) UTLC separation with AP MALDI MS method was studied for the first time. The influence of the urine matrix on the separation and the repeatability was evaluated with benzodiazepines as model substances in human urine. The applicability of 2D UTLC AP MALDI MS was demonstrated in the detection of metabolites in an authentic urine sample.

Learning Temporal Alignment Uncertainty for Efficient Event Detection

In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

A simplified PCR test for early detection of dwarf off-types in micropropagated Cavendish bananas (Musa spp. AAA)

The dwarf somaclonal variant is a major problem affecting micropropagation of the banana cultivar Williams (Musa spp. AAA; subgroup Cavendish). This problem arises from genetic changes that occur during the tissue culture process. Early identification of this problem is difficult and propagators must wait until plants are ex vitro in order to visualise the dwarfism phenotype. In this study, we have improved a SCAR-based molecular diagnostic technique, developed by Damasco et al. [Acta Hortic. 461 (1997) 157], for the early identification of dwarf off-types. We have included a positive internal control in a multiplex PCR and adapted the technique for use with small amounts of fresh in vitro leaf material as PCR template. The control product is a 500 bp fragment from 18S rRNA and is amplified in all tissues irrespective of phenotype. The use of small in vitro leaf material removing the need for genomic DNA extraction.

Characterisation and early detection of an offtype from micropropagated Lady Finger bananas

An offtype has been identified from micropropagated Lady Finger bananas (Musa spp., AAB group, Pome subgroup) that is characterised by its slow growth and poor bunch size. Bunch weights were approximately 25% those of normal Lady Finger plants and all of the fruit produced was unmarketable. This particular offtype is the most commonly encountered from micropropagated Lady Finger plants and, in 2 instances, blocks of 3000 and 1500 plants were entirely comprised of this single offtype. Detection of offtype plants was possible during establishment and growth of plants in the glasshouse by the presence of chlorotic streaks in the leaves. In more severe cases the streaks coalesced into chlorotic patches that developed thin, necrotic areas that eventually produced holes or splits in the leaves. Symptom expression was not ameliorated by the addition of fertiliser and even though symptoms were similar to severe Ca and B deficiency, both normal and offtype plants had similar levels of these elements in the leaves. The offtype plants were also slow growing in the glasshouse and produced significantly (P<0.05) smaller pseudostems and leaves than normal plants. Offtype plants could be readily detected after 4 weeks deflasking using the presence of chlorotic streaks in the leaves as the main selection criterion. Maximum discrimination was possible between weeks 5–7 and at the 6-leaf stage when all of the offtypes could be detected.

Pasteurella multocida detection by 5' Taq nuclease assay: a new tool for use in diagnosing fowl cholera

A 5′ Taq nuclease assay utilising minor groove binder technology and targeting the 16S rRNA gene was designed to detect Pasteurella multocida (the causative agent of fowl cholera) in swabs collected from poultry. The assay was first evaluated using pure cultures. The assay correctly identified four P. multocida taxonomic type strains, 18 P. multocida serovar reference strains and 40 Australian field isolates (17 from poultry, 11 from pigs and 12 from cattle). Representatives of nine other Pasteurella species, 26 other bacterial species (18 being members of the family Pasteurellaceae) and four poultry virus isolates did not react in the assay. The assay detected a minimum of approximately 10 cfu of P. multocida per reaction. Of 79 poultry swabs submitted to the laboratory for routine bacteriological culture, 17 were positive in the 5′ Taq nuclease assay, but only 10 were positive by culture. The other 62 swabs were negative for P. multocida by both 5′ Taq nuclease assay and culture. The assay is suitable for use in diagnosing fowl cholera, is more rapid than bacteriological culture, and may also have application in diagnosing P. multocida infections in cattle and pigs.

Detection of Arcobacter spp. in piggery effluent and effluent-irrigated soils in southeast Queensland

Aims: To investigate the occurrence and levels of Arcobacter spp. in pig effluent ponds and effluent-treated soil. Methods and Results: A Most Probable Number (MPN) method was developed to assess the levels of Arcobacter spp. in seven pig effluent ponds and six effluent-treated soils, immediately after effluent irrigation. Arcobacter spp. levels in the effluent ponds varied from 6.5 × 105 to 1.1 × 108 MPN 100 ml-1 and in freshly irrigated soils from 9.5 × 102 to 2.8 × 104 MPN g-1 in all piggery environments tested. Eighty-three Arcobacter isolates were subjected to an abbreviated phenotypic test scheme and examined using a multiplex polymerase chain reaction (PCR). The PCR identified 35% of these isolates as Arcobacter butzleri, 49% as Arcobacter cryaerophilus while 16% gave no band. All 13 nonreactive isolates were subjected to partial 16S rDNA sequencing and showed a high similarity (>99%) to Arcobacter cibarius. Conclusions: A. butzleri, A. cryaerophilus and A. cibarius were isolated from both piggery effluent and effluent-irrigated soil, at levels suggestive of good survival in the effluent pond. Significance and Impact of the Study: This is the first study to provide quantitative information on Arcobacter spp. levels in piggery effluent and to associate A. cibarius with pigs and piggery effluent environments.

Detection of Chlamydiaceae DNA in veterinary specimens using a family-specific PCR

Aims: The aim of this work was to develop a rapid molecular test for the detection of the Chlamydiaceae family, irrespective of the species or animal host. Methods and Results: The method described herein is a polymerase chain reaction targeting the 16S rRNA gene of the Chlamydiaceae family, and the results demonstrate that the test reacts with five reference Chlamydiaceae but none of the 19 other bacterial species or five uninfected animal tissues tested. The results also indicate the enhanced sensitivity of this test when compared with conventional culture or serology techniques. This is demonstrated through parallel testing of six real clinical veterinary cases and confirmatory DNA sequence analysis. Conclusions, Significance and Impact of the Study: This test can be used by veterinary diagnostic laboratories for rapid detection of Chlamydiaceae in veterinary specimens, with no restriction of chlamydial species or animal host. The test does not differentiate chlamydial species, and if required, speciation must be carried out retrospectively using alternate methods. However, for the purpose of prescribing therapy for chlamydiosis, this test would be an invaluable laboratory tool.

Validation of a Competitive Enzyme-Linked Immunosorbent Assay for Detection of Babesia bigemina Antibodies in Cattle

A competitive enzyme-linked immunosorbent assay (cELISA) based on a broadly conserved, species-specific, B-cell epitope within the C terminus of Babesia bigemina rhoptry-associated protein 1a was validated for international use. Receiver operating characteristic analysis revealed 16% inhibition as the threshold for a negative result, with an associated specificity of 98.3% and sensitivity of 94.7%. Increasing the threshold to 21% increased the specificity to 100% but modestly decreased the sensitivity to 87.2%. By using 21% inhibition, the positive predictive values ranged from 90.7% (10% prevalence) to 100% (95% prevalence) and the negative predictive values ranged from 97.0% (10% prevalence) to 48.2% (95% prevalence). The assay was able to detect serum antibody as early as 7 days after intravenous inoculation. The cELISA was distributed to five different laboratories along with a reference set of 100 defined bovine serum samples, including known positive, known negative, and field samples. The pairwise concordance among the five laboratories ranged from 100% to 97%, and all kappa values were above 0.8, indicating a high degree of reliability. Overall, the cELISA appears to have the attributes necessary for international application.