Revising the Cannabis Use Disorders Identification Test (CUDIT) by means of Item Response Theory.

Cannabis use among adolescents and young adults has become a major public health challenge. Several European countries are currently developing short screening instruments to identify 'problematic' forms of cannabis use in general population surveys. One such instrument is the Cannabis Use Disorders Identification Test (CUDIT), a 10-item questionnaire based on the Alcohol Use Disorders Identification Test. Previous research found that some CUDIT items did not perform well psychometrically. In the interests of improving the psychometric properties of the CUDIT, this study replaces the poorly performing items with new items that specifically address cannabis use. Analyses are based on a sub-sample of 558 recent cannabis users from a representative population sample of 5722 individuals (aged 13-32) who were surveyed in the 2007 Swiss Cannabis Monitoring Study. Four new items were added to the original CUDIT. Psychometric properties of all 14 items, as well as the dimensionality of the supplemented CUDIT were then examined using Item Response Theory. Results indicate the unidimensionality of CUDIT and an improvement in its psychometric performance when three original items (usual hours being stoned; injuries; guilt) are replaced by new ones (motives for using cannabis; missing out leisure time activities; difficulties at work/school). However, improvements were limited to cannabis users with a high problem score. For epidemiological purposes, any further revision of CUDIT should therefore include a greater number of 'easier' items.

Micro-patterning of biomolecules on polymer substrates.

UV−excimer laser photoablation was used, in combination with surface blocking techniques, to pattern proteins on the surfaces of polyimide and poly(ethylene terephthalate). This technique involves physical adsorption of avidin through laser-defined openings in low-temperature laminates or adsorbed protein blocking layers. Visualization of biomolecular patterns were monitored using avidin and fluorescein-labeled biotin as a model receptor−ligand couple. Adsorbed proteins could be shown to bind to UV-laser-treated polymer surfaces up to three times higher than on commercially available polymers. UV-laser photoablation was also used for the generation of three-dimensional structure, which leads to the possibility of biomolecule patterning within polymer-based microanalytical systems. The simplicity and easy handling of the described technique facilitate its application in microdiagnostic devices.

Continuous arterial spin labeling of mouse cerebral blood flow using an actively-detuned two-coil system at 9.4T.

Among numerous magnetic resonance imaging (MRI) techniques, perfusion MRI provides insight into the passage of blood through the brain's vascular network non-invasively. Studying disease models and transgenic mice would intrinsically help understanding the underlying brain functions, cerebrovascular disease and brain disorders. This study evaluates the feasibility of performing continuous arterial spin labeling (CASL) on all cranial arteries for mapping murine cerebral blood flow at 9.4 T. We showed that with an active-detuned two-coil system, a labeling efficiency of 0.82 ± 0.03 was achieved with minimal magnetization transfer residuals in brain. The resulting cerebral blood flow of healthy mouse was 99 ± 26 mL/100g/min, in excellent agreement with other techniques. In conclusion, high magnetic fields deliver high sensitivity and allowing not only CASL but also other MR techniques, i.e. (1)H MRS and diffusion MRI etc, in studying murine brains.

Taking "Galton's problem" Seriously : Towards a Theory of Policy Diffusion

This article builds on the recent policy diffusion literature and attempts to overcome one of its major problems, namely the lack of a coherent theoretical framework. The literature defines policy diffusion as a process where policy choices are interdependent, and identifies several diffusion mechanisms that specify the link between the policy choices of the various actors. As these mechanisms are grounded in different theories, theoretical accounts of diffusion currently have little internal coherence. In this article we put forward an expected-utility model of policy change that is able to subsume all the diffusion mechanisms. We argue that the expected utility of a policy depends on both its effectiveness and the payoffs it yields, and we show that the various diffusion mechanisms operate by altering these two parameters. Each mechanism affects one of the two parameters, and does so in distinct ways. To account for aggregate patterns of diffusion, we embed our model in a simple threshold model of diffusion. Given the high complexity of the process that results, strong analytical conclusions on aggregate patterns cannot be drawn without more extensive analysis which is beyond the scope of this article. However, preliminary considerations indicate that a wide range of diffusion processes may exist and that convergence is only one possible outcome.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

A double-quadrature radiofrequency coil design for proton-decoupled carbon-13 magnetic resonance spectroscopy in humans at 7T

Purpose Carbon-13 magnetic resonance spectroscopy (13C-MRS) is challenging because of the inherent low sensitivity of 13C detection and the need for radiofrequency transmission at the 1H frequency while receiving the 13C signal, the latter requiring electrical decoupling of the 13C and 1H radiofrequency channels. In this study, we added traps to the 13C coil to construct a quadrature-13C/quadrature-1H surface coil, with sufficient isolation between channels to allow simultaneous operation at both frequencies without compromise in coil performance. Methods Isolation between channels was evaluated on the bench by measuring all coupling parameters. The quadrature mode of the quadrature-13C coil was assessed using in vitro 23Na gradient echo images. The signal-to-noise ratio (SNR) was measured on the glycogen and glucose resonances by 13C-MRS in vitro, compared with that obtained with a linear-13C/quadrature-1H coil, and validated by 13C-MRS in vivo in the human calf at 7T. Results Isolation between channels was better than â^'30 dB. The 23Na gradient echo images indicate a region where the field is strongly circularly polarized. The quadrature coil provided an SNR enhancement over a linear coil of 1.4, in vitro and in vivo. Conclusion It is feasible to construct a double-quadrature 13C-1H surface coil for proton decoupled sensitivity enhanced 13C-NMR spectroscopy in humans at 7T. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Inclusive fitness theory and eusociality.

Arising from M. A. Nowak, C. E. Tarnita & E. O. Wilson 466, 1057-1062 (2010); Nowak et al. reply. Nowak et al. argue that inclusive fitness theory has been of little value in explaining the natural world, and that it has led to negligible progress in explaining the evolution of eusociality. However, we believe that their arguments are based upon a misunderstanding of evolutionary theory and a misrepresentation of the empirical literature. We will focus our comments on three general issues.

Social Cognition is not Reducible to Theory of Mind. When Children use Deontic Rules to Predict Others' Behaviors

The objective of this paper is to discuss whether children have a capacity for deonticreasoning that is irreducible to mentalizing. The results of two experiments point tothe existence of such non-mentalistic understanding and prediction of the behaviourof others. In Study 1, young children (3- and 4-year-olds) were told different versionsof classic false-belief tasks, some of which were modified by the introduction of a ruleor a regularity. When the task (a standard change of location task) included a rule, theperformance of 3-year-olds, who fail traditional false-belief tasks, significantly improved.In Study 2, 3-year-olds proved to be able to infer a rule from a social situation and touse it in order to predict the behaviour of a character involved in a modified versionof the false-belief task. These studies suggest that rules play a central role in the socialcognition of young children and that deontic reasoning might not necessarily involvemind reading.

Rapid identification of malaria vaccine candidates based on alpha-helical coiled coil protein motif.

To identify malaria antigens for vaccine development, we selected alpha-helical coiled coil domains of proteins predicted to be present in the parasite erythrocytic stage. The corresponding synthetic peptides are expected to mimic structurally "native" epitopes. Indeed the 95 chemically synthesized peptides were all specifically recognized by human immune sera, though at various prevalence. Peptide specific antibodies were obtained both by affinity-purification from malaria immune sera and by immunization of mice. These antibodies did not show significant cross reactions, i.e., they were specific for the original peptide, reacted with native parasite proteins in infected erythrocytes and several were active in inhibiting in vitro parasite growth. Circular dichroism studies indicated that the selected peptides assumed partial or high alpha-helical content. Thus, we demonstrate that the bioinformatics/chemical synthesis approach described here can lead to the rapid identification of molecules which target biologically active antibodies, thus identifying suitable vaccine candidates. This strategy can be, in principle, extended to vaccine discovery in a wide range of other pathogens.

Combined Electrostatic and Covalent Polymer Networks for Cell Microencapsulation

Two types of hydrogel microspheres have been developed. Fast ionotropic gelation of sodium alginate (Na-alg) in the presence of calcium ions was combined with slow covalent cross-linking of poly(ethylene glycol) (PEG) derivatives. For the first type, the fast obtainable Ca-alg hydrogel served as spherical matrix for the simultaneously occurring covalent cross-linking of multi-arm PEG derivative. A two-component interpenetrating network was formed in one step upon extruding the mixture of the two polymers into the gelation bath. For the second type, heterobifunctional PEG was grafted onto Na-alg prior to gelation. Upon extrusion of the polymer solution into the gelation bath, fast Ca-alg formation ensured the spherical shape and was accompanied by cross-linker-free covalent cross-linking of the PEG side chains. Thus, one-component hydrogel microspheres resulted. We present the physical properties of the hydrogel microspheres and demonstrate the feasibility of cell microencapsulation for both types of polymer networks.