Polyunsaturated fatty acid oxidation in Alzheimer’s disease.

Alzheimer’s disease is a neurodegenerative disorder which has been characterised with genetic (apolipoproteins), protein (ß-amyloid and tau) and lipid oxidation/metabolism alterations in its pathogenesis. In conjunction with the Dementia Research Group, Bristol University, investigation into genetic, protein and lipid oxidation in Alzheimer’s disease was conducted. A large sample cohort using the double-blind criteria, along with various clinical and chemical data sets were used to improve the statistical analysis and therefore the strength of this particular study. Bristol University completed genetic and protein analysis with lipid oxidation assays performed at Aston University. Lipid oxidation is a complex process that creates various biomarkers, from transient intermediates, to short carbon chain products and cyclic ring structures. Quantification of these products was performed on lipid extracts of donated clinical diseased and non-diseased frontal and temporal brain regions, from the Brain Bank within Frenchay Hospital. The initial unoxidised fatty acids, first transient oxidation intermediates the conjugated dienes and lipid hydroperoxides, the endpoint aldehyde biomarkers and finally the cyclic isoprostanes and neuroprostanes were determined to investigate lipid oxidation in Alzheimer’s. Antioxidant levels were also investigated to observe the effect of oxidation on the defence pathways. Assays utilised in this analysis included; fatty acid composition by GC-FID, conjugated diene levels by HPLC-UV and UV-spec, lipid hydroperoxide levels by FOX, aldehyde content by TBARs, antioxidant status by TEAC and finally isoprostane and neuroprostane quantification using a newly developed EI-MS method. This method involved the SIM of specific ions from F-ring isoprostane and neuroprostane fragmentation, which enabled EI-MS to be used for their quantification. Analyses demonstrated that there was no significant difference between control and Alzheimer samples across all the oxidation biomarkers for both brain regions. Antioxidants were the only marker that showed a clear variance; with Alzheimer samples having higher levels than the age matched controls. This unique finding is supported with the observed lower levels of lipid oxidation biomarkers in Alzheimer brain region samples. The increased antioxidant levels indicate protection against oxidation which may be a host response to counteract the oxidative pathways, but this requires further investigation. In terms of lipid oxidation, no definitive markers or target site for therapeutic intervention have been revealed. This study concludes that dietary supplementation of omega-3 fatty acids or antioxidants would most likely be ineffective against Alzheimer disease, although it may support improvement in other areas of general health.

A preliminary investigation into the impact of a pesticide combination on human neuronal and glial cell lines in vitro

Many pesticides are used increasingly in combinations during crop protection and their stability ensures the presence of such combinations in foodstuffs. The effects of three fungicides, pyrimethanil, cyprodinil and fludioxonil, were investigated together and separately on U251 and SH-SY5Y cells, which can be representative of human CNS glial and neuronal cells respectively. Over 48h, all three agents showed significant reductions in cellular ATP, at concentrations that were more than tenfold lower than those which significantly impaired cellular viability. The effects on energy metabolism were reflected in their marked toxic effects on mitochondrial membrane potential. In addition, evidence of oxidative stress was seen in terms of a fall in cellular thiols coupled with increases in the expression of enzymes associated with reactive species formation, such as GSH peroxidase and superoxide dismutase. The glial cell line showed significant responsiveness to the toxin challenge in terms of changes in antioxidant gene expression, although the neuronal SH-SY5Y line exhibited greater vulnerability to toxicity, which was reflected in significant increases in caspase-3 expression, which is indicative of the initiation of apoptosis. Cyprodinil was the most toxic agent individually, although oxidative stress-related enzyme gene expression increases appeared to demonstrate some degree of synergy in the presence of the combination of agents. This report suggests that the impact of some pesticides, both individually and in combinations, merits further study in terms of their impact on human cellular health.

Diagnosing autism spectrum disorder:who will get a DSM-5 diagnosis?

Background Introduction of proposed criteria for DSM-5 Autism Spectrum Disorder (ASD) has raised concerns that some individuals currently meeting diagnostic criteria for Pervasive Developmental Disorder (PDD; DSM-IV-TR/ICD-10) will not qualify for a diagnosis under the proposed changes. To date, reports of sensitivity and specificity of the new criteria have been inconsistent across studies. No study has yet considered how changes at the 'sub domain' level might affect overall sensitivity and specificity, and few have included individuals of different ages and ability levels. Methods A set of DSM-5 ASD algorithms were developed using items from the Diagnostic Interview for Social and Communication Disorders (DISCO). The number of items required for each DSM-5 subdomain was defined either according to criteria specified by DSM-5 (Initial Algorithm), a statistical approach (Youden J Algorithm), or to minimise the number of false positives while maximising sensitivity (Modified Algorithm). The algorithms were designed, tested and compared in two independent samples (Sample 1, N = 82; Sample 2, N = 115), while sensitivity was assessed across age and ability levels in an additional dataset of individuals with an ICD-10 PDD diagnosis (Sample 3, N = 190). Results Sensitivity was highest in the Initial Algorithm, which had the poorest specificity. Although Youden J had excellent specificity, sensitivity was significantly lower than in the Modified Algorithm, which had both good sensitivity and specificity. Relaxing the domain A rules improved sensitivity of the Youden J Algorithm, but it remained less sensitive than the Modified Algorithm. Moreover, this was the only algorithm with variable sensitivity across age. All versions of the algorithm performed well across ability level. Conclusions This study demonstrates that good levels of both sensitivity and specificity can be achieved for a diagnostic algorithm adhering to the DSM-5 criteria that is suitable across age and ability level. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Strategies to optimize the impact of nutritional surveys and epidemiological studies

The development of nutrition and health guidelines and policies requires reliable scientific information. Unfortunately, theoretical considerations and empirical evidence indicate that a large percentage of science-based claims rely on studies that fail to replicate. The session "Strategies to Optimize the Impact of Nutrition Surveys and Epidemiological Studies" focused on the elements of design, interpretation, and communication of nutritional surveys and epidemiological studies to enhance and encourage the production of reliable, objective evidence for use in developing dietary guidance for the public. The speakers called for more transparency of research, raw data, consistent data-staging techniques, and improved data analysis. New approaches to collecting data are urgently needed to increase the credibility and utility of findings from nutrition epidemiological studies. Such studies are critical for furthering our knowledge and understanding of the effects of diet on health.

Influential DMUs and outlier detection in data envelopment analysis with an application to health care

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric data envelopment analysis models as developed by Yang et al. (Annals of Operations Research 173:89-103, 2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection. © 2014 Springer Science+Business Media New York.

Productivity growth and efficiency measurements in fuzzy environments with an application to health care

Health care organizations must continuously improve their productivity to sustain long-term growth and profitability. Sustainable productivity performance is mostly assumed to be a natural outcome of successful health care management. Data envelopment analysis (DEA) is a popular mathematical programming method for comparing the inputs and outputs of a set of homogenous decision making units (DMUs) by evaluating their relative efficiency. The Malmquist productivity index (MPI) is widely used for productivity analysis by relying on constructing a best practice frontier and calculating the relative performance of a DMU for different time periods. The conventional DEA requires accurate and crisp data to calculate the MPI. However, the real-world data are often imprecise and vague. In this study, the authors propose a novel productivity measurement approach in fuzzy environments with MPI. An application of the proposed approach in health care is presented to demonstrate the simplicity and efficacy of the procedures and algorithms in a hospital efficiency study conducted for a State Office of Inspector General in the United States. © 2012, IGI Global.

Assessing the queuing process using data envelopment analysis:an application in health centres

Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.