Stimulated sweating as a therapy to reduce interdialytic weight gain and improve potassium balance in chronic hemodialysis patients: a pilot study.

Controlling the extracellular volume in hemodialysis patients is a difficult task. The aim of this study was to evaluate the capacity of different methods of stimulated sweating to reduce mean interdialytic weight gain (IWG), to improve blood pressure regulation, and potassium/urea balance. Two center, crossover pilot study. In Lausanne, hemodialysis patients took four hot-water baths a week, 30 minutes each, on nondialysis days during 1 month. In Sfax, patients visited the local Hammam Center four times a week. Hemodynamic parameters were recorded, and weekly laboratory analysis was performed. Results were compared with a preceding 1-month control period. In Lausanne, five patients (all men, median age 55 years) participated. Bathing temperature was (mean ± standard deviation) 41.2 ± 3°C and sweating-induced weight loss 600 ± 500 g. Mean IWG (control vs. intervention period) decreased from 2.3 ± 0.9 to 1.8 ± 1 kg (P = 0.004), Systolic blood pressure from 139 ± 21 to 136 ± 22 mmHg (P = 0.4), and diastolic blood pressure form 79 ± 12 to 75 ± 13 mmHg (P = 0.08); antihypertensive therapy could be reduced from 2.8 ± 0.4 to 1.9 ± 0.5 antihypertensive drugs per patient (P = 0.01). In Sfax (n = 9, median age 46 years), weight loss per Hammam session was 420 ± 100 g. No differences were found in IWG or BP, but predialysis serum potassium level decreased from 5.9 ± 0.8 to 5.5 ± 0.9 mmol/L (P = 0.04) and urea from 26.9 ± 6 to 23.1 ± 6 mmol/L (P = 0.02). Hot-water baths appear to be a safe way to reduce IWG in selected hemodialysis patients. Hammam visits reduce serum potassium and urea levels, but not IWG. More data in larger patient groups are necessary before definite conclusion can be drawn.

The Governor’s Task Force on African-Americans in Prison, 2001

Report produced by the Department of Corrections

Emotional attention as a modulatory system of perception

Report for the scientific sojourn carried out at the University Medical Center, Swiss, from 2010 to 2012. Abundant evidence suggests that negative emotional stimuli are prioritized in the perceptual systems, eliciting enhanced neural responses in early sensory regions as compared with neutral information. This facilitated detection is generally paralleled by larger neural responses in early sensory areas, relative to the processing of neutral information. In this sense, the amygdala and other limbic regions, such as the orbitofrontal cortex, may play a critical role by sending modulatory projections onto the sensory cortices via direct or indirect feedback.The present project aimed at investigating two important issues regarding these mechanisms of emotional attention, by means of functional magnetic resonance imaging. In Study I, we examined the modulatory effects of visual emotion signals on the processing of task-irrelevant visual, auditory, and somatosensory input, that is, the intramodal and crossmodal effects of emotional attention. We observed that brain responses to auditory and tactile stimulation were enhanced during the processing of visual emotional stimuli, as compared to neutral, in bilateral primary auditory and somatosensory cortices, respectively. However, brain responses to visual task-irrelevant stimulation were diminished in left primary and secondary visual cortices in the same conditions. The results also suggested the existence of a multimodal network associated with emotional attention, presumably involving mediofrontal, temporal and orbitofrontal regions Finally, Study II examined the different brain responses along the low-level visual pathways and limbic regions, as a function of the number of retinal spikes during visual emotional processing. The experiment used stimuli resulting from an algorithm that simulates how the visual system perceives a visual input after a given number of retinal spikes. The results validated the visual model in human subjects and suggested differential emotional responses in the amygdala and visual regions as a function of spike-levels. A list of publications resulting from work in the host laboratory is included in the report.

Emotional attention as a modulatory system of perception

Report for the scientific sojourn carried out at the University Medical Center, Swiss, from 2010 to 2012. Abundant evidence suggests that negative emotional stimuli are prioritized in the perceptual systems, eliciting enhanced neural responses in early sensory regions as compared with neutral information. This facilitated detection is generally paralleled by larger neural responses in early sensory areas, relative to the processing of neutral information. In this sense, the amygdala and other limbic regions, such as the orbitofrontal cortex, may play a critical role by sending modulatory projections onto the sensory cortices via direct or indirect feedback.The present project aimed at investigating two important issues regarding these mechanisms of emotional attention, by means of functional magnetic resonance imaging. In Study I, we examined the modulatory effects of visual emotion signals on the processing of task-irrelevant visual, auditory, and somatosensory input, that is, the intramodal and crossmodal effects of emotional attention. We observed that brain responses to auditory and tactile stimulation were enhanced during the processing of visual emotional stimuli, as compared to neutral, in bilateral primary auditory and somatosensory cortices, respectively. However, brain responses to visual task-irrelevant stimulation were diminished in left primary and secondary visual cortices in the same conditions. The results also suggested the existence of a multimodal network associated with emotional attention, presumably involving mediofrontal, temporal and orbitofrontal regions Finally, Study II examined the different brain responses along the low-level visual pathways and limbic regions, as a function of the number of retinal spikes during visual emotional processing. The experiment used stimuli resulting from an algorithm that simulates how the visual system perceives a visual input after a given number of retinal spikes. The results validated the visual model in human subjects and suggested differential emotional responses in the amygdala and visual regions as a function of spike-levels. A list of publications resulting from work in the host laboratory is included in the report.

Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms.

BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Temporo-Parietal Junction encodes the Embodied Self: Neuro-Robotics, fMRI, and Lesion mapping.

Introduction: Neuroimaging of the self focused on high-level mechanisms such as language, memory or imagery of the self. Recent evidence suggests that low-level mechanisms of multisensory and sensorimotor integration may play a fundamental role in encoding self-location and the first-person perspective (Blanke and Metzinger, 2009). Neurological patients with out-of body experiences (OBE) suffer from abnormal self-location and the first-person perspective due to a damage in the temporo-parietal junction (Blanke et al., 2004). Although self-location and the first-person perspective can be studied experimentally (Lenggenhager et al., 2009), the neural underpinnings of self-location have yet to be investigated. To investigate the brain network involved in self-location and first-person perspective we used visuo-tactile multisensory conflict, magnetic resonance (MR)-compatible robotics, and fMRI in study 1, and lesion analysis in a sample of 9 patients with OBE due to focal brain damage in study 2. Methods: Twenty-two participants saw a video showing either a person's back or an empty room being stroked (visual stimuli) while the MR-compatible robotic device stroked their back (tactile stimulation). Direction and speed of the seen stroking could either correspond (synchronous) or not (asynchronous) to those of the seen stroking. Each run comprised the four conditions according to a 2x2 factorial design with Object (Body, No-Body) and Synchrony (Synchronous, Asynchronous) as main factors. Self-location was estimated using the mental ball dropping (MBD; Lenggenhager et al., 2009). After the fMRI session participants completed a 6-item adapted from the original questionnaire created by Botvinick and Cohen (1998) and based on questions and data obtained by Lenggenhager et al. (2007, 2009). They were also asked to complete a questionnaire to disclose the perspective they adopted during the illusion. Response times (RTs) for the MBD and fMRI data were analyzed with a 3-way mixed model ANOVA with the in-between factor Perspective (up, down) and the two with-in factors Object (body, no-body) and Stroking (synchronous, asynchronous). Quantitative lesion analysis was performed using MRIcron (Rorden et al., 2007). We compared the distributions of brain lesions confirmed by multimodality imaging (Knowlton, 2004) in patients with OBE with those showing complex visual hallucinations involving people or faces, but without any disturbance of self-location and first person perspective. Nine patients with OBE were investigated. The control group comprised 8 patients. Structural imaging data were available for normalization and co-registration in all the patients. Normalization of each patient's lesion into the common MNI (Montreal Neurological Institute) reference space permitted simple, voxel-wise, algebraic comparisons to be made. Results: Even if in the scanner all participants were lying on their back and were facing upwards, analysis of perspective showed that half of the participants had the impression to be looking down at the virtual human body below them, despite any cues about their body position (Down-group). The other participants had the impression to be looking up at the virtual body above them (Up-group). Analysis of Q3 ("How strong was the feeling that the body you saw was you?") indicated stronger self-identification with the virtual body during the synchronous stroking. RTs in the MBD task confirmed these subjective data (significant 3-way interaction between perspective, object and stroking). fMRI results showed eight cortical regions where the BOLD signal was significantly different during at least one of the conditions resulting from the combination of Object and Stroking, relative to baseline: right and left temporo-parietal junction, right EBA, left middle occipito-temporal gyrus, left postcentral gyrus, right medial parietal lobe, bilateral medial occipital lobe (Fig 1). The activation patterns in right and left temporo-parietal junction and right EBA reflected changes in self-location and perspective as revealed by statistical analysis that was performed on the percentage of BOLD change with respect to the baseline. Statistical lesion overlap comparison (using nonparametric voxel based lesion symptom mapping) with respect to the control group revealed the right temporo-parietal junction, centered at the angular gyrus (Talairach coordinates x = 54, y =-52, z = 26; p>0.05, FDR corrected). Conclusions: The present questionnaire and behavioural results show that - despite the noisy and constraining MR environment) our participants had predictable changes in self-location, self-identification, and first-person perspective when robotic tactile stroking was applied synchronously with the robotic visual stroking. fMRI data in healthy participants and lesion data in patients with abnormal self-location and first-person perspective jointly revealed that the temporo-parietal cortex especially in the right hemisphere encodes these conscious experiences. We argue that temporo-parietal activity reflects the experience of the conscious "I" as embodied and localized within bodily space.

Bristle pattern formation in the thorax formation of Drosophila: a systems level approach

A fundamental question in developmental biology is how tissues are patterned to give rise to differentiated body structures with distinct morphologies. The Drosophila wing disc offers an accessible model to understand epithelial spatial patterning. It has been studied extensively using genetic and molecular approaches. Bristle patterns on the thorax, which arise from the medial part of the wing disc, are a classical model of pattern formation, dependent on a pre-pattern of trans-activators and –repressors. Despite of decades of molecular studies, we still only know a subset of the factors that determine the pre-pattern. We are applying a novel and interdisciplinary approach to predict regulatory interactions in this system. It is based on the description of expression patterns by simple logical relations (addition, subtraction, intersection and union) between simple shapes (graphical primitives). Similarities and relations between primitives have been shown to be predictive of regulatory relationships between the corresponding regulatory factors in other Systems, such as the Drosophila egg. Furthermore, they provide the basis for dynamical models of the bristle-patterning network, which enable us to make even more detailed predictions on gene regulation and expression dynamics. We have obtained a data-set of wing disc expression patterns which we are now processing to obtain average expression patterns for each gene. Through triangulation of the images we can transform the expression patterns into vectors which can easily be analysed by Standard clustering methods. These analyses will allow us to identify primitives and regulatory interactions. We expect to identify new regulatory interactions and to understand the basic Dynamics of the regulatory network responsible for thorax patterning. These results will provide us with a better understanding of the rules governing gene regulatory networks in general, and provide the basis for future studies of the evolution of the thorax-patterning network in particular.

Biodiversity and global change in Mediterranean benthic communities: perspectives over large spatial and long temporal scales

Many terrestrial and marine systems are experiencing accelerating decline due to the effects of global change. This situation has raised concern about the consequences of biodiversity losses for ecosystem function, ecosystem service provision, and human well-being. Coastal marine habitats are a main focus of attention because they harbour a high biological diversity, are among the most productive systems of the world and present high anthropogenic interaction levels. The accelerating degradation of many terrestrial and marine systems highlights the urgent need to evaluate the consequence of biodiversity loss. Because marine biodiversity is a dynamic entity and this study was interested global change impacts, this study focused on benthic biodiversity trends over large spatial and long temporal scales. The main aim of this project was to investigate the current extent of biodiversity of the high diverse benthic coralligenous community in the Mediterranean Sea, detect its changes, and predict its future changes over broad spatial and long temporal scales. These marine communities are characterized by structural species with low growth rates and long life spans; therefore they are considered particularly sensitive to disturbances. For this purpose, this project analyzed permanent photographic plots over time at four locations in the NW Mediterranean Sea. The spatial scale of this study provided information on the level of species similarity between these locations, thus offering a solid background on the amount of large scale variability in coralligenous communities; whereas the temporal scale was fundamental to determine the natural variability in order to discriminate between changes observed due to natural factors and those related to the impact of disturbances (e.g. mass mortality events related to positive thermal temperatures, extreme catastrophic events). This study directly addressed the challenging task of analyzing quantitative biodiversity data of these high diverse marine benthic communities. Overall, the scientific knowledge gained with this research project will improve our understanding in the function of marine ecosystems and their trajectories related to global change.

Auditory-visual multisensory interactions in humans: timing, topography, directionality, and sources.

Current models of brain organization include multisensory interactions at early processing stages and within low-level, including primary, cortices. Embracing this model with regard to auditory-visual (AV) interactions in humans remains problematic. Controversy surrounds the application of an additive model to the analysis of event-related potentials (ERPs), and conventional ERP analysis methods have yielded discordant latencies of effects and permitted limited neurophysiologic interpretability. While hemodynamic imaging and transcranial magnetic stimulation studies provide general support for the above model, the precise timing, superadditive/subadditive directionality, topographic stability, and sources remain unresolved. We recorded ERPs in humans to attended, but task-irrelevant stimuli that did not require an overt motor response, thereby circumventing paradigmatic caveats. We applied novel ERP signal analysis methods to provide details concerning the likely bases of AV interactions. First, nonlinear interactions occur at 60-95 ms after stimulus and are the consequence of topographic, rather than pure strength, modulations in the ERP. AV stimuli engage distinct configurations of intracranial generators, rather than simply modulating the amplitude of unisensory responses. Second, source estimations (and statistical analyses thereof) identified primary visual, primary auditory, and posterior superior temporal regions as mediating these effects. Finally, scalar values of current densities in all of these regions exhibited functionally coupled, subadditive nonlinear effects, a pattern increasingly consistent with the mounting evidence in nonhuman primates. In these ways, we demonstrate how neurophysiologic bases of multisensory interactions can be noninvasively identified in humans, allowing for a synthesis across imaging methods on the one hand and species on the other.

Do antibody responses to malaria vaccine candidates influenced by the level of malaria transmission protect from malaria?

OBJECTIVES: To examine whether the humoural response to malaria vaccine candidate antigens, Plasmodium falciparum [circumsporozoite repetitive sequence (NANP)(5) GLURP fragments (R0 and R2) and MSP3] varies with the level of malaria transmission and to determine whether the antibodies (IgG) present at the beginning of the malaria transmission season protect against clinical malaria. METHODS: Cross-sectional surveys were conducted to measure antibody response before, at the peak and at the end of the transmission season in children aged 6 months to 10 years in two villages with different levels of malaria transmission. A cohort study was performed to estimate the incidence of clinical malaria. RESULTS: Antibodies to these antigens showed different seasonal patterns. IgG concentrations to any of the four antigens were higher in the village with high entomological inoculation rate. Multivariate analysis of combined data from the two villages indicated that children who were classified as responders to the selected antigens were at lower risk of clinical malaria than children classified as non-responders [(NANP)(5) (incidence rate ratio (IRR) = 0.65, 95% CI: 0.46-0.92; P = 0.016), R0 (IRR = 0.69, 95% CI: 0.48-0.97; P = 0.032), R2 (IRR = 0.73, 95% CI: 0.50-1.06; P = 0.09), MSP3 (IRR = 0.52, 95% CI: 0.32-0.85; P = 0.009)]. Fitting a model with all four antibody responses showed that MSP3 looked the best malaria vaccine candidate (IRR = 0.63; 95% CI: 0.38-1.05; P = 0.08). CONCLUSION: Antibody levels to the four antigens are affected by the intensity of malaria transmission and associated with protection against clinical malaria. It is worthwhile investing in the development of these antigens as potential malaria vaccine candidates.

Collage, a Collaborative Learning Design Editor Based on Patterns

This paper introduces Collage, a high-level IMS-LD compliant authoring tool that is specialized for CSCL (Computer-Supported Collaborative Learning). Nowadays CSCL is a key trend in elearning since it highlights the importance of social interactions as an essential element of learning. CSCL is an interdisciplinary domain, which demands participatory design techniques that allow teachers to get directly involved in design activities. Developing CSCL designs using LD is a difficult task for teachers since LD is a complex technical specification and modelling collaborative characteristics can be tricky. Collage helps teachers in the process of creating their own potentially effective collaborative Learning Designs by reusing and customizing patterns, according to the requirements of a particular learning situation. These patterns, called Collaborative Learning Flow Patterns (CLFPs), represent best practices that are repetitively used by practitioners when structuring the flow of (collaborative) learning activities. An example of an LD that can be created using Collage is illustrated in the paper. Preliminary evaluation results show that teachers, with experience in CL but without LD knowledge, can successfully design real collaborative learning experiences using Collage.

Neuronal adaptation effects in decision making

Recently, there has been an increased interest on the neural mechanisms underlying perceptual decision making. However, the effect of neuronal adaptation in this context has not yet been studied. We begin our study by investigating how adaptation can bias perceptual decisions. We considered behavioral data from an experiment on high-level adaptation-related aftereffects in a perceptual decision task with ambiguous stimuli on humans. To understand the driving force behind the perceptual decision process, a biologically inspired cortical network model was used. Two theoretical scenarios arose for explaining the perceptual switch from the category of the adaptor stimulus to the opposite, nonadapted one. One is noise-driven transition due to the probabilistic spike times of neurons and the other is adaptation-driven transition due to afterhyperpolarization currents. With increasing levels of neural adaptation, the system shifts from a noise-driven to an adaptation-driven modus. The behavioral results show that the underlying model is not just a bistable model, as usual in the decision-making modeling literature, but that neuronal adaptation is high and therefore the working point of the model is in the oscillatory regime. Using the same model parameters, we studied the effect of neural adaptation in a perceptual decision-making task where the same ambiguous stimulus was presented with and without a preceding adaptor stimulus. We find that for different levels of sensory evidence favoring one of the two interpretations of the ambiguous stimulus, higher levels of neural adaptation lead to quicker decisions contributing to a speed–accuracy trade off.

Edge detection by selection of pieces of level lines

We propose an edge detector based on the selection of wellcontrasted pieces of level lines, following the proposal ofDesolneux-Moisan-Morel (DMM) [1]. The DMM edge detectorhas the problem of over-representation, that is, everyedge is detected several times in slightly different positions.In this paper we propose two modifications of the originalDMM edge detector in order to solve this problem. The firstmodification is a post-processing of the output using a generalmethod to select the best representative of a bundle of curves.The second modification is the use of Canny’s edge detectorinstead of the norm of the gradient to build the statistics. Thetwo modifications are independent and can be applied separately.Elementary reasoning and some experiments showthat the best results are obtained when both modifications areapplied together.

Farm-Level Analysis of Risk Management Proposals, March 2000

This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.