Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network

<p>Abstract</p> <p>Background</p> <p>How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron.</p> <p>Results</p> <p>The probabilities of synapses between 7 types of identified spinal neuron were measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models that were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity.</p> <p>Conclusion</p> <p>Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that detailed cellular recognition between spinal neuron types may not be necessary for the reliable formation of functional networks to generate early behaviour like swimming.</p

The Course and Impact of Post-Stroke Insomnia in Stroke Survivors aged 18 to 65 years: results from the Psychosocial Outcomes in StrokE (POISE) study

BACKGROUND: Insomnia symptoms are common in the population and have negative psychosocial and functional sequelae. There are no prospective studies of the course of such symptoms and their impact, if any, in stroke survivors. This prospective cohort study investigated insomnia after stroke in working-age adults, and evaluated its impact on psychological and functional outcomes over the subsequent year. METHODS: We prospectively recruited 441 young (<65 years) consecutive stroke survivors from 20 public hospitals in the New South Wales Stroke Service network. Participants were assessed by self-report and interview at 28 days, six months and 12 months after stroke. Insomnia was defined using a common epidemiological measure of sleep disturbance and daytime consequences. Depression, anxiety, disability and return to work were assessed through standardized measures. RESULTS The point prevalence of insomnia at each time point in the year after stroke was stable at 30-37% and more common in females. 58 (16%) of all participants reported 'chronic' insomnia, with symptoms at both baseline and six months later. At 12 months this group was more likely to be depressed (OR 6.75, 95% CI 2.78-16.4), anxious (OR 3.31, 95% CI 1.54- 7.09), disabled (OR 3.60, 95% CI 2.07-6.25) and not have returned to work, compared to those without insomnia over the same period. CONCLUSIONS Chronic insomnia has a negative effect on disability and return to work one year after stroke even after adjusting for demographic, psychiatric and disability factors. Identifying and appropriately targeting insomnia through known effective treatments may improve functional outcomes after stroke

Attributing variations of temporal and spatial groundwater recharge: a statistical analysis of climatic and non-climatic factors

This paper demonstrated the benefits of statistical methods when investigating the climatic and non-climatic drivers responsible for variations in groundwater recharge with a series of up to 43 years of annual recharge for 426 bores in South-East South Australia. We identified the factors influencing groundwater recharge based on 71 climatic metrics and 13 non-climatic metrics (including groundwater abstraction). The results showed: 1) Rainfall during April to October was the most important variable influencing recharge temporal variation, with its decline identified as the most significant factor related to recharge reduction; 2) In contrast, a negative correlation between rainfall during December to February (DJF) and annual groundwater recharge was found. This suggests that a seasonal shift in rainfall (such as decreasing rainfall during April to October and an increase during DJF) can result in a decline in recharge even when the annual rainfall remains unchanged; 3) The length of wet spells (consecutive rain days) and increasing PET were additional significant predictors for recharge temporal variation. It demonstrated that a simple empirical relationship (such as recharge as a fixed percentage of rainfall) is not a reliable estimation of renewable groundwater resources under changing climatic conditions; 4) There is a statistically significant spatial correlation between mean groundwater depth and recharge, and this implies that a reduction in rainfall can lead to a positive feedback loop of declining recharge and water level; 5) Spatially the most statistically significant factors influencing groundwater recharge were soil types and land attributes. The findings of this study can identify which stressors should be included when investigating the impact of climate change on groundwater recharge

Probing the magnetic polaron state in the ferromagnetic semiconductor HgCr2Se4 with muon-spin spectroscopy and resistance-fluctuation measurements

Combined resistance noise and muon-spin relaxation (μSR) measurements of the ferromagnetic semiconductor HgCr2Se4 suggest a degree of magnetoelectric coupling and provide evidence for the existence of isolated magnetic polarons. These form at elevated temperatures and undergo a percolation transition with a drastic enhancement of the low-frequency 1/ f -type charge fluctuations at the insulator-to-metal transition at ∼95–98 K in the vicinity of the magnetic ordering temperature TC ∼ 105–107 K. Upon approaching the percolation threshold from above, the strikingly unusual dynamics of a distinct two-level fluctuator superimposed on the 1/ f noise can be described by a slowing down of the dynamics of a nanoscale magnetic cluster, a magnetic polaron, when taking into account an effective radius of the polaron depending on the spin correlation length. Coinciding temperature scales found in μSR and noise measurements suggest changes in the magnetic dynamics over a wide range of frequencies and are consistent with the existence of large polarized and domain-wall-like regions at low temperatures, that result from the freezing of spin dynamics at the magnetic polaron percolation transition

Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially-expressed genes from microarray data.

BACKGROUND: There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. RESULTS: Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. CONCLUSION: Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Transport of Streptococcus pneumoniae Capsular Polysaccharide in MHC Class II Tubules

Bacterial capsular polysaccharides are virulence factors and are considered T cell–independent antigens. However, the capsular polysaccharide Sp1 from Streptococcus pneumoniae serotype 1 has been shown to activate CD4(+) T cells in a major histocompatibility complex (MHC) class II–dependent manner. The mechanism of carbohydrate presentation to CD4(+) T cells is unknown. We show in live murine dendritic cells (DCs) that Sp1 translocates from lysosomal compartments to the plasma membrane in MHCII-positive tubules. Sp1 cell surface presentation results in reduction of self-peptide presentation without alteration of the MHCII self peptide repertoire. In DM-deficient mice, retrograde transport of Sp1/MHCII complexes resulting in T cell–dependent immune responses to the polysaccharide in vitro and in vivo is significantly reduced. The results demonstrate the capacity of a bacterial capsular polysaccharide antigen to use DC tubules as a vehicle for its transport as an MHCII/saccharide complex to the cell surface for the induction of T cell activation. Furthermore, retrograde transport requires the functional role of DM in self peptide–carbohydrate exchange. These observations open new opportunities for the design of vaccines against microbial encapsulated pathogens

YbV3_3Sb4_4 and EuV3_3Sb4_4, vanadium-based kagome metals with Yb2+^{2+} and Eu2+^{2+} zig-zag chains

Here we present YbV$_3$Sb$_4$ and EuV$_3$Sb$_4$, two new compounds exhibiting slightly distorted vanadium-based kagome nets interleaved with zig-zag chains of divalent Yb$^{2+}$ and Eu$^{2+}$ ions. Single crystal growth methods are reported alongside magnetic, electronic, and thermodynamic measurements. YbV$_3$Sb$_4$ is a nonmagnetic metal with no collective phase transitions observed between 60mK and 300K. Conversely, EuV$_3$Sb$_4$ is a magnetic kagome metal exhibiting easy-plane ferromagnetic-like order below $T_\text{C}$=32K with signatures of noncollinearity under low field. Our discovery of YbV$_3$Sb$_4$ and EuV$_3$Sb$_4$ demonstrate another direction for the discovery and development of vanadium-based kagome metals while incorporating the chemical and magnetic degrees of freedom offered by a rare-earth sublattice