Electrochemical processes in a wire-in-a-capillary bulk-loaded, nano-electrospray emitter

AbstractExperiments are described that illustrate solvent oxidation, emitter electrode corrosion, and analyte oxidation in positive ion mode nano-electrospray mass spectrometry using a wire-in-a-capillary, bulk-loaded nano-electrospray emitter geometry. Time-lapsed color photography of pH and metal specific indicator solutions within operating nano-electrospray emitters, as well as temporal changes in the ions observed in the nano-electrospray mass spectra, are used to probe these reactions, judge their magnitude, and study the time dependent changes in solution composition and gas-phase ion signal brought about as a result of these electrochemical reactions. The significance of these observations for analytical applications of nano-electrospray mass spectrometry are discussed. (J Am Soc Spectrom 2001, 853–862) Published by Elsevier Science Inc

Relevanz suszeptibilitätsinduzierter geometrischer Fehlkodierungen für die Validität MR-basierter Knorpelvolumen- und -dickenmessungen im Kniegelenk - Relevance of susceptibility-induced geometrical distortion for the accuracy of MR-based cartilage volume and thickness measurement

The aim of the present study was to analyze the relevance of susceptibility-induced geometrical distortion to the accuracy of MR-based cartilage volume and thickness measurement in the human knee joint. Nine cadaveric knee joints were imaged in the sagittal plane with MRI at a resolution of a x 0.31 x 0.81 mm³, using a fat-suppressed gradient echo sequence, with a normal gradient orientation and also with the frequency- and phase-encoding directions changed. CT arthrographic data sets were then obtained. On the basis of 3-D constructions, we determined the cartilage volume and, with a 3-D minimal distance algorithm, the thickness distribution, of the patella, femur and tibia. Irrespective of the gradient orientation, good agreement was observed between MRI and CT arthrography in terms of cartilage volumes and maximum cartilage thickness. With a normal gradient orientation the volume was overestimated by 2.5 % in MRI, and 2.3 % when the gradients were changed. The maximum cartilage thickness was underestimated by 0.24 intervals (interval = 0.5 mm) with a normal gradient orientation, and by 0.22 intervals when the gradient orientation was changed. In none of the joint surfaces was a relevant difference between the two methods observed. It can be shown that, using high-resolution, fat-suppressed gradient-echo sequences - suseeptibility-induced geometrical distortion has no significant effect on the accuracy of KR-based cartilage volume and thickness measurements. MRI would therefore appear suitable for the design of patient-specific finite element models with the aim of analysing load transmission in diarthrodial joints and planning surgical interventions

The Secure Anonymised Information Linkage databank Dementia e-cohort (SAIL-DeC)

Introduction: The rising burden of dementia is a global concern, and there is a need to study its causes, natural history and outcomes. The Secure Anonymised Information Linkage (SAIL) Databank contains anonymised, routinely-collected healthcare data for the population of Wales, UK. It has potential to be a valuable resource for dementia research owing to its size, long follow-up time and prospective collection of data during clinical care. Objectives:We aimed to apply reproducible methods to create the SAIL dementia e-cohort (SAIL-DeC). We created SAIL-DeC with a view to maximising its utility for a broad range of research questions whilst minimising duplication of effort for researchers. Methods:SAIL contains individual-level, linked primary care, hospital admission, mortality and demographic data. Data are currently available until 2018 and future updates will extend participant follow-up time. We included participants who were born between 1st January 1900 and 1st January 1958 and for whom primary care data were available. We applied algorithms consisting of International Classification of Diseases (versions 9 and 10) and Read (version 2) codes to identify participants with and without all-cause dementia and dementia subtypes. We also created derived variables for comorbidities and risk factors. Results:From 4.4 million unique participants in SAIL, 1.2 million met the cohort inclusion criteria, resulting in 18.8 million person-years of follow-up. Of these, 129,650 (10%) developed all-cause dementia, with 77,978 (60%) having dementia subtype codes. Alzheimer's disease was the most common subtype diagnosis (62%). Among the dementia cases, the median duration of observation time was 14 years. Conclusion:We have created a generalisable, national dementia e-cohort, aimed at facilitating epidemiological dementia research

Patterns of mortality in domesticated ruminants in Ethiopia

BACKGROUND: Premature death of livestock is a problem in all ruminant production systems. While the number of premature ruminant deaths in a country is a reasonable indicator for the nation's health, few data sources exist in a country like Ethiopia that can be used to generate valid estimates. The present study aimed to establish if three different data sets, each with imperfect information on ruminant mortality, including abortions, could be combined into improved estimates of nationwide mortality in Ethiopia. METHODS: We combined information from a recent survey of ruminant mortality with information from the Living Standards Measurement Study and the Disease Outbreak and Vaccination Reporting dataset. Generalized linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes. RESULTS: Analyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope. CONCLUSIONS: The models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as number of offspring raised to 1 year old per dam, would be more stable over time and likely more indicative

Identifying dementia cases with routinely collected health data: A systematic review.

INTRODUCTION: Prospective, population-based studies can be rich resources for dementia research. Follow-up in many such studies is through linkage to routinely collected, coded health-care data sets. We evaluated the accuracy of these data sets for dementia case identification. METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely collected data sets to any expert-led reference standard. We recorded study characteristics and two accuracy measures-positive predictive value (PPV) and sensitivity. RESULTS: We identified 27 eligible studies with 25 estimating PPV and eight estimating sensitivity. Study settings and methods varied widely. For all-cause dementia, PPVs ranged from 33%-100%, but 16/27 were >75%. Sensitivities ranged from 21% to 86%. PPVs for Alzheimer's disease (range 57%-100%) were generally higher than those for vascular dementia (range 19%-91%). DISCUSSION: Linkage to routine health-care data can achieve a high PPV and reasonable sensitivity in certain settings. Given the heterogeneity in accuracy estimates, cohorts should ideally conduct their own setting-specific validation

Optimizing the scale of markets for water quality trading

Applying market approaches to environmental regulations requires establishing a spatial scale for trading. Spatially large markets usually increase opportunities for abatement cost savings but increase the potential for pollution damages (hot spots), vice versa for spatially small markets. We develop a coupled hydrologic-economic modeling approach for application to point source emissions trading by a large number of sources and apply this approach to the wastewater treatment plants (WWTPs) within the watershed of the second largest estuary in the U.S. We consider two different administrative structures that govern the trade of emission permits: one-for-one trading (the number of permits required for each unit of emission is the same for every WWTP) and trading ratios (the number of permits required for each unit of emissions varies across WWTP). Results show that water quality regulators should allow trading to occur at the river basin scale as an appropriate first-step policy, as is being done in a limited number of cases via compliance associations. Larger spatial scales may be needed under conditions of increased abatement costs. The optimal scale of the market is generally the same regardless of whether one-for-one trading or trading ratios are employed

Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: a systematic review

Background: Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate. Follow-up in many such studies relies on linkage to routinely-collected health datasets. We systematically evaluated the accuracy of such datasets in identifying MND cases. Methods: We performed an electronic search of MEDLINE, EMBASE, Cochrane Library and Web of Science for studies published between 01/01/1990-16/11/2015 that compared MND cases identified in routinely-collected, coded datasets to a reference standard. We recorded study characteristics and two key measures of diagnostic accuracy—positive predictive value (PPV) and sensitivity. We conducted descriptive analyses and quality assessments of included studies. Results: Thirteen eligible studies provided 13 estimates of PPV and five estimates of sensitivity. Twelve studies assessed hospital and/or death certificate-derived datasets; one evaluated a primary care dataset. All studies were from high income countries (UK, Europe, USA, Hong Kong). Study methods varied widely, but quality was generally good. PPV estimates ranged from 55–92% and sensitivities from 75–93%. The single (UK-based) study of primary care data reported a PPV of 85%. Conclusions: Diagnostic accuracy of routinely-collected health datasets is likely to be sufficient for identifying cases of MND in large-scale prospective epidemiological studies in high income country settings. Primary care datasets, particularly from countries with a widely-accessible national healthcare system, are potentially valuable data sources warranting further investigation