Quantitative analysis of methyl and propyl parabens in neonatal DBS using LC–MS/MS

Aim: Excipients are used to overcome the chemical, physical and microbiological challenges posed by developing formulated medicines. Both methyl and propyl paraben are commonly used in pediatric liquid formulations. There is no data on systemic exposure to parabens in neonates. The European Study of Neonatal Exposure to Excipients project has investigated this. Results & methodology: DBS sampling was used to collect opportunistic blood samples. Parabens were extracted from the DBS and analyzed using a validated LC-MS/MS assay.

Discussion & Conclusion: The above assay was applied to analyze neonatal DBS samples. The blood concentrations of parabens in neonates confirm systemic exposure to parabens following administration of routine medicines.

Oil Market Modelling: A Comparative Analysis of Fundamental and Latent Factor Approaches

We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short- medium- and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

Evaluation of an alternative spectroscopic approach for aflatoxin analysis: Comparative analysis of food and feed samples with UPLC-MS/MS

Increasing research has highlighted the effects of changing climates on the occurrence and prevalence of toxigenic Aspergillus species producing aflatoxins. There is concern of the toxicological effects to human health and animal productivity following acute and chronic exposure that may affect the future ability to provide safe and sufficient food globally. Considerable research has focused on the detection of these toxins, based on the physicochemical and biochemical properties of the aflatoxin compounds, in agricultural products for human and animal consumption. As improvements in food security continue more regulations for acceptable levels of aflatoxins have arisen globally; the most stringent in Europe. These regulations are important for developing countries as aflatoxin occurrence is high significantly effecting international trade and the economy. In developed countries analytical approaches have become highly sophisticated, capable of attaining results with high precision and accuracy, suitable for regulatory laboratories. Regrettably, many countries that are affected by aflatoxin contamination do not have resources for high tech HPLC and MS instrumentation and require more affordable, yet robust equally accurate alternatives that may be used by producers, processors and traders in emerging economies. It is especially important that those companies wishing to exploit the opportunities offered by lucrative but highly regulated markets in the developed world, have access to analytical methods that will ensure that their exports meet their customers quality and safety requirements.

This work evaluates the ToxiMet system as an alternative approach to UPLC–MS/MS for the detection and determination of aflatoxins relative to current European regulatory standards. Four commodities: rice grain, maize cracked and flour, peanut paste and dried distillers grains were analysed for natural aflatoxin contamination. For B1 and total aflatoxins determination the qualitative correlation, above or below the regulatory limit, was good for all commodities with the exception of the dried distillers grain samples for B1 for which no calibration existed. For B1 the quantitative R² correlations were 0.92, 0.92, 0.88 (<250 μg/kg) and 0.7 for rice, maize, peanuts and dried distillers grain samples respectively whereas for total aflatoxins the quantitative correlation was 0.92, 0.94, 0.88 and 0.91. The ToxiMet system could be used as an alternative for aflatoxin analysis for current legislation but some consideration should be given to aflatoxin M1 regulatory levels for these commodities considering the high levels detected in this study especially for maize and peanuts

An analysis of wind curtailment and constraint at a nodal level

Many countries have set challenging wind power targets to achieve by 2020. This paper implements a realistic analysis of curtailment and constraint of wind energy at a nodal level using a unit commitment and economic dispatch model of the Irish Single Electricity Market in 2020. The key findings show that significant reduction in curtailment can be achieved when the system non-synchronous penetration limit increases from 65% to 75%. For the period analyzed, this results in a decreased total generation cost and a reduction in the dispatch-down of wind. However, some nodes experience significant dispatch-down of wind, which can be in the order of 40%. This work illustrates the importance of implementing analysis at a nodal level for the purpose of power system planning.

Frequency of mutations and polymorphisms in borderline ovarian tumors of known cancer genes.

Borderline ovarian tumors represent an understudied subset of ovarian tumors. Most studies investigating aberrations in borderline tumors have focused on KRAS/BRAF mutations. In this study, we conducted an extensive analysis of mutations and single-nucleotide polymorphisms (SNPs) in borderline ovarian tumors. Using the Sequenom MassArray platform, we investigated 160 mutations/polymorphisms in 33 genes involved in cell signaling, apoptosis, angiogenesis, cell cycle regulation and cellular senescence. Of 52 tumors analyzed, 33 were serous, 18 mucinous and 1 endometrioid. KRAS c.35G>A p.Gly12Asp mutations were detected in eight tumors (six serous and two mucinous), BRAF V600E mutations in two serous tumors, and PIK3CA H1047Y and PIK3CA E542K mutations in a serous and an endometrioid BOT, respectively. CTNNB1 mutation was detected in a serous tumor. Potentially functional polymorphisms were found in vascular endothelial growth factor (VEGF), ABCB1, FGFR2 and PHLPP2. VEGF polymorphisms were the most common and detected at four loci. PHLPP2 polymorphisms were more frequent in mucinous as compared with serous tumors (P=0.04), with allelic imbalance in one case. This study represents the largest and most comprehensive analysis of mutations and functional SNPs in borderline ovarian tumors to date. At least 25% of borderline ovarian tumors harbor somatic mutations associated with potential response to targeted therapeutics.

Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.