Collective intelligence for promoting changes in behaviour: a case study on energy conservation

Climate change is one of the biggest challenges humanity faces today. Despite of high investments in technology, battling climate change is futile without the participation of the public, and changing their perception and habits. Collective intelligence tools can play an important role in translating this “distant” concept that is climate change into practical hints for everyday life. In this paper, we report a case study grounded on collective intelligence tools to collaboratively build knowledge around energy conservation. A preliminary study to raise energy awareness in an academic environment is summarised, setting the scene to a more ambitious initiative based on personal stories to transform energy awareness into behaviour change. The role of the collective intelligence tools and other technical artefacts involved are discussed, suggesting strategies and features that contributed (or not) to users’ engagement and collective awareness. Lessons learned from both studies are reported with a sociotechnical approach as implications for design pursuing behaviour change

Beetroot supplementation in women enjoying exercise together (BEE SWEET): Rationale, design and methods

Background: Postmenopausal women exhibit higher rates of disability and cardiovascular disease (CVD) with aging compared to men. Whereas habitual exercise training is a known strategy to enhance physiologic function in men and premenopausal women, exercise-related adaptations are often modest in postmenopausal women. We propose dietary nitrate (beetroot juice) administered prior to exercise training may be a feasible approach to improve mobility and cardio-metabolic health outcomes in postmenopausal women. Methods: Our randomized, placebo-controlled study aims to determine preliminary effects sizes for changes in functional mobility and endothelium-dependent vasodilation across three study arms: exercise only (EX), exercise + placebo (EX + PL), and exercise + beetroot (EX + BR). Thirty-six postmenopausal women are recruited in small cohorts wherein group exercise is implemented to facilitate social support and adherence to an 8-week training progression. Participants are randomized to one of three study arms (n = 12 per group) following baseline assessments. Post-intervention assessments are used to determine pre-post changes in outcome measures including distance covered during a 6 min walk test, walking economy, muscle speed and power, and endothelial-dependent vasodilation as determined by flow-mediated dilation. Measures of feasibility include recruitment, retention, adherence to exercise prescription, perceived exercise session difficulty, and adverse event rates. Discussion: Evidence-based, translational strategies are needed to optimize exercise training-related adaptations in postmenopausal women. Findings will inform larger randomized clinical trials to determine if pre-exercise consumption of beetroot juice is an efficacious strategy to promote mobility and attenuate CVD disease risk

Monitoramento de safras via Web: um caso de sucesso em pesquisa multidisciplinar.

Este trabalho descreve o projeto WebMaps em desenvolvimento na UNICAMP, um esforço multidisciplinar envolvendo ciências agrárias e de computação , cujo objetivo é desenvolver uma plataforma baseada em serviços Web para o planejamento agro-ambiental.SBIAgro 2007

Scanning tunneling microscopy of the electronic structure of chemical vapor deposited diamond films

This article discusses scanning tunneling microscopy of the electronic structure of chemical vapor deposited diamond films

Membranes with the Same Ion Channel Populations but Different Excitabilities

Electrical signaling allows communication within and between different tissues and is necessary for the survival of multicellular organisms. The ionic transport that underlies transmembrane currents in cells is mediated by transporters and channels. Fast ionic transport through channels is typically modeled with a conductance-based formulation that describes current in terms of electrical drift without diffusion. In contrast, currents written in terms of drift and diffusion are not as widely used in the literature in spite of being more realistic and capable of displaying experimentally observable phenomena that conductance-based models cannot reproduce (e.g. rectification). The two formulations are mathematically related: conductance-based currents are linear approximations of drift-diffusion currents. However, conductance-based models of membrane potential are not first-order approximations of drift-diffusion models. Bifurcation analysis and numerical simulations show that the two approaches predict qualitatively and quantitatively different behaviors in the dynamics of membrane potential. For instance, two neuronal membrane models with identical populations of ion channels, one written with conductance-based currents, the other with drift-diffusion currents, undergo transitions into and out of repetitive oscillations through different mechanisms and for different levels of stimulation. These differences in excitability are observed in response to excitatory synaptic input, and across different levels of ion channel expression. In general, the electrophysiological profiles of membranes modeled with drift-diffusion and conductance-based models having identical ion channel populations are different, potentially causing the input-output and computational properties of networks constructed with these models to be different as well. The drift-diffusion formulation is thus proposed as a theoretical improvement over conductance-based models that may lead to more accurate predictions and interpretations of experimental data at the single cell and network levels

Central sensitization: a biopsychosocial explanation for chronic widespread pain in patients with fibromyalgia and chronic fatigue syndrome

In addition to the debilitating fatigue, the majority of patients with chronic fatigue syndrome (CFS) experience chronic widespread pain. These pain complaints show the greatest overlap between CFS and fibromyalgia (FM). Although the literature provides evidence for central sensitization as cause for the musculoskeletal pain in FM, in CFS this evidence is currently lacking, despite the observed similarities in both diseases. The knowledge concerning the physiological mechanism of central sensitization, the pathophysiology and the pain processing in FM, and the knowledge on the pathophysiology of CFS lead to the hypothesis that central sensitization is also responsible for the sustaining pain complaints in CFS. This hypothesis is based on the hyperalgesia and allodynia reported in CFS, on the elevated concentrations of nitric oxide presented in the blood of CFS patients, on the typical personality styles seen in CFS and on the brain abnormalities shown on brain images. To examine the present hypothesis more research is required. Further investigations could use similar protocols to those already used in studies on pain in FM like, for example, studies on temporal summation, spatial summation, the role of psychosocial aspects in chronic pain, etc

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum

Intermolecular channels direct crystal orientation in mineralized collagen

The mineralized collagen fibril is the basic building block of bone, and is commonly pictured as a parallel array of ultrathin carbonated hydroxyapatite (HAp) platelets distributed throughout the collagen. This orientation is often attributed to an epitaxial relationship between the HAp and collagen molecules inside 2D voids within the fibril. Although recent studies have questioned this model, the structural relationship between the collagen matrix and HAp, and the mechanisms by which collagen directs mineralization remain unclear. Here, we use XRD to reveal that the voids in the collagen are in fact cylindrical pores with diameters of ~2 nm, while electron microscopy shows that the HAp crystals in bone are only uniaxially oriented with respect to the collagen. From in vitro mineralization studies with HAp, CaCO3 and γ-FeOOH we conclude that confinement within these pores, together with the anisotropic growth of HAp, dictates the orientation of HAp crystals within the collagen fibril

Dynamics of Action Potential Initiation in the GABAergic Thalamic Reticular Nucleus In Vivo

Understanding the neural mechanisms of action potential generation is critical to establish the way neural circuits generate and coordinate activity. Accordingly, we investigated the dynamics of action potential initiation in the GABAergic thalamic reticular nucleus (TRN) using in vivo intracellular recordings in cats in order to preserve anatomically-intact axo-dendritic distributions and naturally-occurring spatiotemporal patterns of synaptic activity in this structure that regulates the thalamic relay to neocortex. We found a wide operational range of voltage thresholds for action potentials, mostly due to intrinsic voltage-gated conductances and not synaptic activity driven by network oscillations. Varying levels of synchronous synaptic inputs produced fast rates of membrane potential depolarization preceding the action potential onset that were associated with lower thresholds and increased excitability, consistent with TRN neurons performing as coincidence detectors. On the other hand the presence of action potentials preceding any given spike was associated with more depolarized thresholds. The phase-plane trajectory of the action potential showed somato-dendritic propagation, but no obvious axon initial segment component, prominent in other neuronal classes and allegedly responsible for the high onset speed. Overall, our results suggest that TRN neurons could flexibly integrate synaptic inputs to discharge action potentials over wide voltage ranges, and perform as coincidence detectors and temporal integrators, supported by a dynamic action potential threshold

A Threshold Equation for Action Potential Initiation

In central neurons, the threshold for spike initiation can depend on the stimulus and varies between cells and between recording sites in a given cell, but it is unclear what mechanisms underlie this variability. Properties of ionic channels are likely to play a role in threshold modulation. We examined in models the influence of Na channel activation, inactivation, slow voltage-gated channels and synaptic conductances on spike threshold. We propose a threshold equation which quantifies the contribution of all these mechanisms. It provides an instantaneous time-varying value of the threshold, which applies to neurons with fluctuating inputs. We deduce a differential equation for the threshold, similar to the equations of gating variables in the Hodgkin-Huxley formalism, which describes how the spike threshold varies with the membrane potential, depending on channel properties. We find that spike threshold depends logarithmically on Na channel density, and that Na channel inactivation and K channels can dynamically modulate it in an adaptive way: the threshold increases with membrane potential and after every action potential. Our equation was validated with simulations of a previously published multicompartemental model of spike initiation. Finally, we observed that threshold variability in models depends crucially on the shape of the Na activation function near spike initiation (about −55 mV), while its parameters are adjusted near half-activation voltage (about −30 mV), which might explain why many models exhibit little threshold variability, contrary to experimental observations. We conclude that ionic channels can account for large variations in spike threshold