Multiple mycotoxin exposure determined by urinary biomarkers in rural subsistence farmers in the former Transkei, South Africa

Subsistence farmers are exposed to a range of mycotoxins. This study applied novel urinary multi-mycotoxin LC-MS/MS methods to determine multiple exposure biomarkers in the high oesophageal cancer region, Transkei, South Africa. Fifty-three female participants donated part of their maize-based evening meal and first void morning urine, which was analysed both with sample clean-up (single and multi-biomarker) and by a 'dilute-and-shoot' multi-biomarker method. Results were corrected for recovery with LOD for not detected. A single biomarker method detected fumonisin B1 (FB1) (87% incidence; mean±standard deviation 0.342±0.466 ng/mg creatinine) and deoxynivalenol (100%; mean 20.4±49.4 ng/mg creatinine) after hydrolysis with β-glucuronidase. The multi-biomarker 'dilute-and-shoot' method indicated deoxynivalenol-15-glucuronide was predominantly present. A multi-biomarker method with β-glucuronidase and immunoaffinity clean-up determined zearalenone (100%; 0.529±1.60 ng/mg creatinine), FB1 (96%; 1.52±2.17 ng/mg creatinine), α-zearalenol (92%; 0.614±1.91 ng/mg creatinine), deoxynivalenol (87%; 11.3±27.1 ng/mg creatinine), β-zearalenol (75%; 0.702±2.95 ng/mg creatinine) and ochratoxin A (98%; 0.041±0.086 ng/mg creatinine). These demonstrate the value of multi-biomarker methods in measuring exposures in populations exposed to multiple mycotoxins. This is the first finding of urinary deoxynivalenol, zearalenone, their conjugates, ochratoxin A and zearalenols in Transkei.

A markerless deletion method for genetic manipulation of Burkholderia cenocepacia and other multidrug-resistant gram-negative bacteria

Genetic manipulation of multidrug-resistant bacteria is often difficult and hinders progress in understanding their physiology and pathogenesis. This book chapter highlights advances in genetic manipulation of Burkholderia cenocepacia, which are also applicable to other members of the Burkholderia cepacia complex and multidrug-resistant gram-negative bacteria of other genera. The method detailed here is based on the I-SceI homing endonuclease system, which can be efficiently used for chromosomal integration, deletion, and genetic replacement. This system creates markerless mutations and insertions without leaving a genetic scar and thus can be reused successively to generate multiple modifications in the same strain.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

CLUSTER LEED - A VERY FAST METHOD FOR SURFACE-STRUCTURE DETERMINATION

A very fast method, cluster low-energy electron diffraction (LEED) is proposed for LEED I-V spectral analysis, in which three appproximations are introduced: the small-atom approximation, omission of the structure factors, and truncation of higher order ( > 2) scattering events. The method has been tested using a total of four sets of I-V spectra calculated by fully dynamic LEED for (i) the simple overlayer system, O on Ni{100}, and (ii) the reconstructed system, Cu on W{100}, and also one set of experimental data from W{100}-c(2 X 2)-Cu. In each case the correct structural parameters are recovered. It is suggested that for complex systems cluster LEED provides an efficient fast route to trial structures, which could be refined by automated tenser LEED.

A DIRECT INVERSION METHOD FOR SURFACE-STRUCTURE DETERMINATION FROM LEED INTENSITIES

LOW-ENERGY electron diffraction (LEED) has become the most successful technique in surface crystallography1, but because of the complexity of the surface-electron scattering interactions, analyses of LEED data are still conducted on a trial-and-error basis: a direct-inversion method for treating LEED intensity data remains an attractive goal2. Building on recent theoretical and experimental developments in electron holography from surface structures3-16, we show here that three-dimensional images with atomic resolution can be obtained by a direct transform of conventional LEED intensity spectra.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

Low complexity greedy detection method with generalized multicarrier index keying OFDM

Multicarrier Index Keying (MCIK) is a recently developed technique that modulates subcarriers but also indices of the subcarriers. In this paper a novel low-complexity detection scheme of subcarrier indices is proposed for an MCIK system and addresses a substantial reduction in complexity over the optimalmaximum likelihood (ML) detection. For the performance evaluation, a closed-form expression for the pairwise error probability (PEP) of an active subcarrier index, and a tight approximation of the average PEP of multiple subcarrier indices are derived in closed-form. The theoretical outcomes are validated usingsimulations, at a difference of less than 0.1dB. Compared to the optimal ML, the proposed detection achieves a substantial reduction in complexity with small loss in error performance (<= 0.6dB).

Closed circuit rebreathing to achieve inert gas wash-in for multiple breath wash-out

Multiple breath wash-out (MBW) testing requires prior wash-in of inert tracer gas. Wash-in efficiency can be enhanced by a rebreathing tracer in a closed circuit. Previous attempts to deploy this did not account for the impact of CO2 accumulation on patients and were unsuccessful. We hypothesised that an effective rebreathe wash-in could be delivered and it would not alter wash-out parameters. Computer modelling was used to assess the impact of the rebreathe method on wash-in efficiency. Clinical testing of open and closed circuit wash-in–wash-out was performed in healthy controls and adult patients with cystic fibrosis (CF) using a circuit with an effective CO2 scrubber and a refined wash-in protocol. Wash-in efficiency was enhanced by rebreathing. There was no difference in mean lung clearance index between the two wash-in methods for controls (6.5 versus 6.4; p=0.2, n=12) or patients with CF (10.9 versus 10.8; p=0.2, n=19). Test time was reduced by rebreathe wash-in (156 versus 230 s for CF patients, p<0.001) and both methods were well tolerated. End wash-in CO2 was maintained below 2% in most cases. Rebreathe–wash-in is a promising development that, when correctly deployed, reduces wash-in time and facilitates portable MBW testing. For mild CF, wash-out outcomes are equivalent to an open circuit.

A validated UPLC–MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/ swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9 min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6 ng/L of original sample. Intra- and inter-day precision analysis showed relative
standard deviations (RSD) of 1.2–9.6% and 1.3–12.0% respectively. The method was applied to the analysis of aquatic samples (n = 206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n = 22), cylindrospermopsin (n = 25), microcystin-RR (n = 17), microcystin-LR (n = 12), microcystin-LY (n = 1), microcystin-LF (n = 1) and nodularin (n = 5). For microcystins, the levels detected ranged from 0.001 to 1.51 mg/L, with two samples showing combined levels above the guideline set by the WHO of 1 mg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

Application of DPSIR framework integrated with multiple regression model to simulate Guadiana catchment - estuary continuum, south eastern Iberia

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

New method for the simultaneous identification of pathogenic human viruses using multiplex PCR

Tese de mestrado. Biologia (Biologia Molecular e Genética). Universidade de Lisboa, Faculdade de Ciências, 2014

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

How reliable is the monitoring of permanent vegetation plots? A test with multiple observers

Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.