257 research outputs found
Can interventions that aim to decrease Lyme disease hazard at non-domestic sites be effective without negatively affecting ecosystem health? A systematic review protocol
Background
Lyme disease (LD) is the most commonly reported, broadly distributed vector-borne disease of the northern temperate zone. It is transmitted by ticks and, if untreated, can cause skin, cardiac, nervous system and musculoskeletal disease. The distribution and incidence of LD is increasing across much of North America and Western Europe. Interventions to decrease exposure to LD hazard by encouraging behavioural change have low acceptance in high risk groups, and a safe, effective human LD vaccine is not presently available. As a result, habitat level interventions to decrease LD hazard itself (i.e. levels of infected ticks) have been proposed. However, some interventions may potentially negatively affect ecosystem health, and consequentially be neither desirable, nor politically feasible. This systematic review will catalogue interventions that aim to reduce LD hazard at non-domestic sites, and examine the evidence supporting those which are unlikely to negatively affect ecosystem health.
Methods
The review will be carried out in two steps. First, a screening and cataloguing stage will be conducted to identify and characterise interventions to decrease LD hazard at non-domestic sites. Secondly, the subset of interventions identified during cataloguing as unlikely to negatively affect ecosystem health will be investigated. In the screening and cataloguing step literature will be collected through database searching using pre-chosen search strings, hand-searching key journals and reviewing the websites of public health bodies. Further references will be identified by contacting stakeholders and researchers. Article screening and assessment of the likely effects of interventions on ecosystem health will be carried out independently by two reviewers. A third reviewer will be consulted if disagreements arise. The cataloguing step results will be presented in tables. Study quality will then be assessed independently by two reviewers, using adapted versions of established tools developed in healthcare research. These results will be presented in a narrative synthesis alongside tables. Though a full meta-analysis is not expected to be possible, if sub-groups of studies are sufficiently similar to compare, a partial meta-analysis will be carried out
The generation of phase differences and frequency changes in a network model of inferior olive subthreshold oscillations
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedicationIt is commonly accepted that the Inferior Olive (IO) provides a timing signal to the cerebellum. Stable subthreshold oscillations in the IO can facilitate accurate timing by phase-locking spikes to the peaks of the oscillation. Several theoretical models accounting for the synchronized subthreshold oscillations have been proposed, however, two experimental observations remain an enigma. The first is the observation of frequent alterations in the frequency of the oscillations. The second is the observation of constant phase differences between simultaneously recorded neurons. In order to account for these two observations we constructed a canonical network model based on anatomical and physiological data from the IO. The constructed network is characterized by clustering of neurons with similar conductance densities, and by electrical coupling between neurons. Neurons inside a cluster are densely connected with weak strengths, while neurons belonging to different clusters are sparsely connected with stronger connections. We found that this type of network can robustly display stable subthreshold oscillations. The overall frequency of the network changes with the strength of the inter-cluster connections, and phase differences occur between neurons of different clusters. Moreover, the phase differences provide a mechanistic explanation for the experimentally observed propagating waves of activity in the IO. We conclude that the architecture of the network of electrically coupled neurons in combination with modulation of the inter-cluster coupling strengths can account for the experimentally observed frequency changes and the phase differences.Peer reviewedFinal Published versio
Body size estimation in women with anorexia nervosa and healthy controls using 3D avatars
A core feature of anorexia nervosa is an over-estimation of body size. However, quantifying this over-estimation has been problematic as existing methodologies introduce a series of artefacts and inaccuracies in the stimuli used for judgements of body size. To overcome these problems, we have: (i) taken 3D scans of 15 women who have symptoms of anorexia (referred to henceforth as anorexia spectrum disorders, ANSD) and 15 healthy control women, (ii) used a 3D modelling package to build avatars from the scans, (iii) manipulated the body shapes of these avatars to reflect biometrically accurate, continuous changes in body mass index (BMI), (iv) used these personalized avatars as stimuli to allow the women to estimate their body size. The results show that women who are currently receiving treatment for ANSD show an over-estimation of body size which rapidly increases as their own BMI increases. By contrast, the women acting as healthy controls can accurately estimate their body size irrespective of their own BMI. This study demonstrates the viability of combining 3D scanning and CGI techniques to create personalised realistic avatars of individual patients to directly assess their body image perception
Conserved properties of dendritic trees in four cortical interneuron subtypes
Dendritic trees influence synaptic integration and neuronal excitability, yet appear to develop in rather arbitrary patterns. Using electron microscopy and serial reconstructions, we analyzed the dendritic trees of four morphologically distinct neocortical interneuron subtypes to reveal two underlying organizational principles common to all. First, cross-sectional areas at any given point within a dendrite were proportional to the summed length of all dendritic segments distal to that point. Consistent with this observation, total cross-sectional area was almost perfectly conserved at bifurcation points. Second, dendritic cross-sections became progressively more elliptical at more proximal, larger diameter, dendritic locations. Finally, computer simulations revealed that these conserved morphological features limit distance dependent filtering of somatic EPSPs and facilitate distribution of somatic depolarization into all dendritic compartments. Because these features were shared by all interneurons studied, they may represent common organizational principles underlying the otherwise diverse morphology of dendritic trees
NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail
Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven neuronal models, the specialized languages they employ are generally not interoperable, limiting model accessibility and preventing reuse of model components and cross-simulator validation. To overcome these problems we have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience
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Population based models of cortical drug response: insights from anaesthesia
A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia
Taurolidine-citrate lock solution (TauroLock) significantly reduces CVAD-associated grampositive infections in pediatric cancer patients
<p>Abstract</p> <p>Background</p> <p>Taurolidin/Citrate (TauroLock™), a lock solution with broad spectrum antimicrobial activity, may prevent bloodstream infection (BSI) due to coagulase-negative staphylococci (CoNS or 'MRSE' in case of methicillin-resistant isolates) in pediatric cancer patients with a long term central venous access device (CVAD, Port- or/Broviac-/Hickman-catheter type).</p> <p>Methods</p> <p>In a single center prospective 48-months cohort study we compared all patients receiving anticancer chemotherapy from April 2003 to March 2005 (group 1, heparin lock with 200 IU/ml sterile normal saline 0.9%; Canusal<sup>® </sup>Wockhardt UK Ltd, Wrexham, Wales) and all patients from April 2005 to March 2007 (group 2; taurolidine 1.35%/Sodium Citrate 4%; TauroLock™, Tauropharm, Waldbüttelbrunn, Germany).</p> <p>Results</p> <p>In group 1 (heparin), 90 patients had 98 CVAD in use during the surveillance period. 14 of 30 (47%) BSI were 'primary Gram positive BSI due to CoNS (n = 4) or MRSE (n = 10)' [incidence density (ID); 2.30 per 1000 inpatient CVAD-utilization days].</p> <p>In group 2 (TauroLock™), 89 patients had 95 CVAD in use during the surveillance period. 3 of 25 (12%) BSI were caused by CoNS. (ID, 0.45). The difference in the ID between the two groups was statistically significant (P = 0.004).</p> <p>Conclusion</p> <p>The use of Taurolidin/Citrate (TauroLock™) significantly reduced the number and incidence density of primary catheter-associated BSI due to CoNS and MRSE in pediatric cancer patients.</p
Characterizing Deep Brain Stimulation effects in computationally efficient neural network models
A novel role of dendritic gap junction and mechanisms underlying its interaction with thalamocortical conductance in fast spiking inhibitory neurons
<p>Abstract</p> <p>Background</p> <p>Little is known about the roles of dendritic gap junctions (GJs) of inhibitory interneurons in modulating temporal properties of sensory induced responses in sensory cortices. Electrophysiological dual patch-clamp recording and computational simulation methods were used in combination to examine a novel role of GJs in sensory mediated feed-forward inhibitory responses in barrel cortex layer IV and its underlying mechanisms.</p> <p>Results</p> <p>Under physiological conditions, excitatory post-junctional potentials (EPJPs) interact with thalamocortical (TC) inputs within an unprecedented few milliseconds (i.e. over 200 Hz) to enhance the firing probability and synchrony of coupled fast-spiking (FS) cells. Dendritic GJ coupling allows fourfold increase in synchrony and a significant enhancement in spike transmission efficacy in excitatory spiny stellate cells. The model revealed the following novel mechanisms: <b><it>1) </it></b>rapid capacitive current (I<sub>cap</sub>) underlies the activation of voltage-gated sodium channels; <b><it>2) </it></b>there was less than 2 milliseconds in which the I<sub>cap </sub>underlying TC input and EPJP was coupled effectively; <b><it>3) </it></b>cells with dendritic GJs had larger input conductance and smaller membrane response to weaker inputs; <b><it>4) </it></b>synchrony in inhibitory networks by GJ coupling leads to reduced sporadic lateral inhibition and increased TC transmission efficacy.</p> <p>Conclusion</p> <p>Dendritic GJs of neocortical inhibitory networks can have very powerful effects in modulating the strength and the temporal properties of sensory induced feed-forward inhibitory and excitatory responses at a very high frequency band (>200 Hz). Rapid capacitive currents are identified as main mechanisms underlying interaction between two transient synaptic conductances.</p
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