Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging

Many analyses of neuroimaging data involve studying one or more regions of interest (ROIs) in a brain image. In order to do so, each ROI must first be identified. Since every brain is unique, the location, size, and shape of each ROI varies across subjects. Thus, each ROI in a brain image must either be manually identified or (semi-) automatically delineated, a task referred to as segmentation. Automatic segmentation often involves mapping a previously manually segmented image to a new brain image and propagating the labels to obtain an estimate of where each ROI is located in the new image. A more recent approach to this problem is to propagate labels from multiple manually segmented atlases and combine the results using a process known as label fusion. To date, most label fusion algorithms either employ voting procedures or impose prior structure and subsequently find the maximum a posteriori estimator (i.e., the posterior mode) through optimization. We propose using a fully Bayesian spatial regression model for label fusion that facilitates direct incorporation of covariate information while making accessible the entire posterior distribution. We discuss the implementation of our model via Markov chain Monte Carlo and illustrate the procedure through both simulation and application to segmentation of the hippocampus, an anatomical structure known to be associated with Alzheimer's disease.Comment: 24 pages, 10 figure

Self-immolative linkers in polymeric delivery systems

There has been significant interest in the methodologies of controlled release for a diverse range of applications spanning drug delivery, biological and chemical sensors, and diagnostics. The advancement in novel substrate-polymer coupling moieties has led to the discovery of self-immolative linkers. This new class of linker has gained popularity in recent years in polymeric release technology as a result of stable bond formation between protecting and leaving groups, which becomes labile upon activation, leading to the rapid disassembly of the parent polymer. This ability has prompted numerous studies into the design and development of self-immolative linkers and the kinetics surrounding their disassembly. This review details the main concepts that underpin self-immolative linker technologies that feature in polymeric or dendritic conjugate systems and outlines the chemistries of amplified self-immolative elimination

"The pass-along effect: investigating word-of-mouth effects on online survey procedures"

Andrew T. Norman is a professor of marketing in the College of Business and Public Administration at Drake University. He can be contacted at [email protected] petitions to complete online surveys may be forwarded beyond the intended sample. We term this phenomenon the pass-along effect and investigate it as a factor that can influence the nature and size of survey samples in an online context. We establish the pass-along effect as a form of word-of-mouth communication and draw from the literature in this area to present and test a model of factors that influence the occurrence of this effect. The results of two studies provide empirical support for the existence and impact of the pass-along effect. Among the factors that lead to this effect are involvement and relationship with the survey topic, size of a participant’s social network, and tie strength. The appropriateness of employing pass-along respondents as well as other implications for online sampling and survey research are discussed

A hydrazine-free Wolff–Kishner reaction suitable for an undergraduate laboratory

A Wolff–Kishner reaction that does not require hydrazine has been developed. The reaction sequence has two steps; formation of a carbomethoxyhydrazone from methyl hydrazinocarboxylate and acetophenone, then decomposition of this intermediate by treatment with potassium hydroxide in triethylene glycol. Purification is by filtration through a plug of silica encased in the barrel of a plastic syringe. The reaction sequence can be completed within a day-long laboratory class (8 hours)

Methyl hydrazinocarboxylate as a practical alternative to hydrazine in the Wolff–Kishner reaction

Herein we describe a facile protocol for the reduction of aromatic ketones and aldehydes to the corresponding methylene unit. The procedure involves isolation of a carbomethoxyhydrazone intermediate that is easily decomposed to the reduced product without the requirement for large quantities of pernicious hydrazine

Spatial variations in economic attitudes and voting behaviour in Britain, 1983-92.

The objective of this thesis is to assess the role of geography in the construction of economic attitudes and electoral behaviour in Britain during the 1980s and the early 1990s. Aggregate and individual level data are used to separate two specific time periods - the economic recovery of the 1980s and the 'new' recession of the early 1990s. The new recession also coincided with the long campaign leading to the 1992 General Election, when the Conservatives were returned for a fourth successive term. A two stage model of the relationship between social class, geography, economic attitudes and party support is constructed. Initially the link between geography and economic attitudes appears enigmatic. However, as the analysis progresses a clearer picture emerges of the geographic basis of prospective and retrospective, egocentric and sociotropic economic evaluations. Analysis of Variance and Multiple Classification Analysis techniques reveal the extent of the growing geographic divide in party support and certain economic attitudes during the 1980s. A particularly crucial theme emerges with the investigation of partisanship during inter-election periods. Groups that tend to form the core of the Conservative vote in Election years, are identified as reluctant Conservatives in non-election years. Important contextual effects are perceived in the analysis of reported vote intention, geography and economic attitudes in the run-up to the 1992 General Election. As well as the orthodox personal economic expectations variable, ascription of economic responsibility and economic approval for the Government's programme are shown to be critical to levels of Government support - and are spatially variable. Ordinary Least Squares and Logistic regression analysis reveal the precise role of geography in economic attitudes and party support. Here the 'devil is in the detail' as the interactions effects of the dependent variables reveal that when an individual's economic evaluations clashes with their geographic context, the contextual effect either dilutes - or overcomes completely - the economic effect. The analysis of individual level data represents an advance for electoral geography and for the study of geographic milieux and local socialisation effects

Assessment of the learning curve in health technologies: a systematic review

Objective: We reviewed and appraised the methods by which the issue of the learning curve has been addressed during health technology assessment in the past. Method: We performed a systematic review of papers in clinical databases (BIOSIS, CINAHL, Cochrane Library, EMBASE, HealthSTAR, MEDLINE, Science Citation Index, and Social Science Citation Index) using the search term "learning curve:" Results: The clinical search retrieved 4,571 abstracts for assessment, of which 559 (12%) published articles were eligible for review. Of these, 272 were judged to have formally assessed a learning curve. The procedures assessed were minimal access (51%), other surgical (41%), and diagnostic (8%). The majority of the studies were case series (95%). Some 47% of studies addressed only individual operator performance and 52% addressed institutional performance. The data were collected prospectively in 40%, retrospectively in 26%, and the method was unclear for 31%. The statistical methods used were simple graphs (44%), splitting the data chronologically and performing a t test or chi-squared test (60%), curve fitting (12%), and other model fitting (5%). Conclusions: Learning curves are rarely considered formally in health technology assessment. Where they are, the reporting of the studies and the statistical methods used are weak. As a minimum, reporting of learning should include the number and experience of the operators and a detailed description of data collection. Improved statistical methods would enhance the assessment of health technologies that require learning

Assessing the learning curve effect in health technologies: Lessons from the non-clinical literature

Introduction: Many health technologies exhibit some form of learning effect, and this represents a barrier to rigorous assessment. It has been shown that the statistical methods used are relatively crude. Methods to describe learning curves in fields outside medicine, for example, psychology and engineering, may be better. Methods: To systematically search non–health technology assessment literature (for example, PsycLit and Econlit databases) to identify novel statistical techniques applied to learning curves. Results: The search retrieved 9,431 abstracts for assessment, of which 18 used a statistical technique for analyzing learning effects that had not previously been identified in the clinical literature. The newly identified methods were combined with those previously used in health technology assessment, and categorized into four groups of increasing complexity: a) exploratory data analysis; b) simple data analysis; c) complex data analysis; and d) generic methods. All the complex structured data techniques for analyzing learning effects were identified in the nonclinical literature, and these emphasized the importance of estimating intra- and interindividual learning effects. Conclusion: A good dividend of more sophisticated methods was obtained by searching in nonclinical fields. These methods now require formal testing on health technology data sets

Structural variability of 4f and 5f thiocyanate complexes and dissociation of uranium(III)–thiocyanate bonds with increased ionicity

A series of complexes [Et4N][Ln(NCS)4(H2O)4] (Ln = Pr, Tb, Dy, Ho, Yb) have been structurally characterized, all showing the same structure, namely a distorted square antiprismatic coordination geometry, and the Ln–O and Ln–N bond lengths following the expected lanthanide contraction. When the counterion is Cs+, a different structural motif is observed and the eight-coordinate complex Cs5[Nd(NCS)8] isolated. The thorium compounds [Me4N]4[Th(NCS)7(NO3)] and [Me4N]4[Th(NCS)6(NO3)2] have been characterized, and high coordination numbers are also observed. Finally, attempts to synthesize a U(III) thiocyanate compound has been unsuccessful; from the reaction mixture, a heterocycle formed by condensation of five MeCN solvent molecules, possibly promoted by U(III), was isolated and structurally characterized. To rationalize the inability to isolate U(III) thiocyanate compounds, thin-layer cyclic voltammetry and IR spectroelectrochemistry have been utilized to explore the cathodic behavior of [Et4N]4[U(NCS)8] and [Et4N][U(NCS)5(bipy)2] along with a related uranyl compound [Et4N]3[UO2(NCS)5]. In all examples, the reduction triggers a rapid dissociation of [NCS]− ions and decomposition. Interestingly, the oxidation chemistry of [Et4N]3[UO2(NCS)5] in the presence of bipy gives the U(IV) compound [Et4N]4[U(NCS)8], an unusual example of a ligand-based oxidation triggering a metal-based reduction. The experimental results have been augmented by a computational investigation, concluding that the U(III)–NCS bond is more ionic than the U(IV)–NCS bond