Topology recapitulates morphogenesis of neuronal dendrites.

Branching allows neurons to make synaptic contacts with large numbers of other neurons, facilitating the high connectivity of nervous systems. Neuronal arbors have geometric properties such as branch lengths and diameters that are optimal in that they maximize signaling speeds while minimizing construction costs. In this work, we asked whether neuronal arbors have topological properties that may also optimize their growth or function. We discovered that for a wide range of invertebrate and vertebrate neurons the distributions of their subtree sizes follow power laws, implying that they are scale invariant. The power-law exponent distinguishes different neuronal cell types. Postsynaptic spines and branchlets perturb scale invariance. Through simulations, we show that the subtree-size distribution depends on the symmetry of the branching rules governing arbor growth and that optimal morphologies are scale invariant. Thus, the subtree-size distribution is a topological property that recapitulates the functional morphology of dendrites.

Mental healthcare utilisation by patients before and after receiving paliperidone palmitate treatment: mirror image analyses.

OBJECTIVES: To compare mental healthcare use and healthcare professional (HCP) contacts for patients before and after initiation of paliperidone palmitate. SETTING: The South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre Clinical Record Interactive Search. PARTICIPANTS: We identified all adults with a diagnosis of schizophrenia (International Classification of Diseases 10th Revision: F20.x), who had received paliperidone palmitate prescription for at least 365 days and had at least 1 year of recorded treatment from SLAM, prior to the first recorded receipt of paliperidone palmitate. PRIMARY AND SECONDARY OUTCOME MEASURES: Inpatient and community mental healthcare service use, such as inpatient bed days, number of active days in the service, face-to-face and telephone HCP use in the 12 months before and after paliperidone palmitate initiation. RESULTS: We identified 664 patients initiated on paliperidone palmitate. Following initiation, inpatient bed days were lower, although patients remained active on the service case load longer for both mirror approach 1 (mean difference of inpatient bed days -10.48 (95% CI -15.75 to -5.22); days active 40.67 (95% CI 33.39 to 47.95)) and mirror approach 2 (mean difference of inpatient bed days -23.96 (95% CI -30.01 to -17.92); mean difference of days active 40.69 (95% CI 33.39 to 47.94)). The postinitiation period was further characterised by fewer face-to-face and telephone contacts with medical and social work HCPs, and an increased contact with clinical psychologists. CONCLUSIONS: Our findings indicate a change in the profile of HCP use, consistent with a transition from treatment to possible rehabilitation.

A general principle of dendritic constancy: A neuron's size- and shape-invariant excitability.

Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

Dendritic normalisation improves learning in sparsely connected artificial neural networks.

Artificial neural networks, taking inspiration from biological neurons, have become an invaluable tool for machine learning applications. Recent studies have developed techniques to effectively tune the connectivity of sparsely-connected artificial neural networks, which have the potential to be more computationally efficient than their fully-connected counterparts and more closely resemble the architectures of biological systems. We here present a normalisation, based on the biophysical behaviour of neuronal dendrites receiving distributed synaptic inputs, that divides the weight of an artificial neuron's afferent contacts by their number. We apply this dendritic normalisation to various sparsely-connected feedforward network architectures, as well as simple recurrent and self-organised networks with spatially extended units. The learning performance is significantly increased, providing an improvement over other widely-used normalisations in sparse networks. The results are two-fold, being both a practical advance in machine learning and an insight into how the structure of neuronal dendritic arbours may contribute to computation.

Risk of Recurrent Bleeding Events in Nonvalvular Atrial Fibrillation Treated with Vitamin K Antagonists: A Clinical Practice Research Datalink Study.

Background There is little evidence on how the occurrence of a bleed in individuals on vitamin K antagonists (VKAs) impacts the risk of subsequent bleeds, and thromboembolic and ischemic events. Such information would help to inform treatment decisions following bleeds. Objective To estimate the impact of bleeding events on the risk of subsequent bleeds, venous thromboembolism (VTE), stroke, and myocardial infarction (MI) among patients initiating VKA treatment for new-onset nonvalvular atrial fibrillation (NVAF). Methods We conducted an observational cohort study using a linked Clinical Practice Research Datalink-Hospital Episode Statistics dataset. Among a cohort of individuals with NVAF, the risk of clinically relevant bleeding, VTE, stroke, and MI was compared between the period prior to the first bleed and the periods following each subsequent bleed. The rate and cost of general practitioner (GP) consultations, prescriptions, and hospitalizations were also compared across these periods. Results The risk of clinically relevant bleeding events was observed to be elevated at least twofold in all periods following the first bleeding event. The risk of VTE, stroke, and MI was not found to differ according to the number of clinically relevant bleeding events. The rate and cost of GP consultations, GP prescriptions, and hospitalizations were increased in all periods relative to the period prior to the first bleed. Conclusions The doubling in the risk of bleeding following the first bleed, taken alongside the stable risk of MI, VTE, and stroke, suggests that the risk-benefit balance for VKA treatment should be reconsidered following the first clinically relevant bleed.

Model-Based Inference of Synaptic Transmission.

Synaptic computation is believed to underlie many forms of animal behavior. A correct identification of synaptic transmission properties is thus crucial for a better understanding of how the brain processes information, stores memories and learns. Recently, a number of new statistical methods for inferring synaptic transmission parameters have been introduced. Here we review and contrast these developments, with a focus on methods aimed at inferring both synaptic release statistics and synaptic dynamics. Furthermore, based on recent proposals we discuss how such methods can be applied to data across different levels of investigation: from intracellular paired experiments to in vivo network-wide recordings. Overall, these developments open the window to reliably estimating synaptic parameters in behaving animals.

Dissecting Sholl Analysis into Its Functional Components.

Sholl analysis has been an important technique in dendritic anatomy for more than 60 years. The Sholl intersection profile is obtained by counting the number of dendritic branches at a given distance from the soma and is a key measure of dendritic complexity; it has applications from evaluating the changes in structure induced by pathologies to estimating the expected number of anatomical synaptic contacts. We find that the Sholl intersection profiles of most neurons can be reproduced from three basic, functional measures: the domain spanned by the dendritic arbor, the total length of the dendrite, and the angular distribution of how far dendritic segments deviate from a direct path to the soma (i.e., the root angle distribution). The first two measures are determined by axon location and hence microcircuit structure; the third arises from optimal wiring and represents a branching statistic estimating the need for conduction speed in a neuron.

Transmission of temporally correlated spike trains through synapses with short-term depression.

Short-term synaptic depression, caused by depletion of releasable neurotransmitter, modulates the strength of neuronal connections in a history-dependent manner. Quantifying the statistics of synaptic transmission requires stochastic models that link probabilistic neurotransmitter release with presynaptic spike-train statistics. Common approaches are to model the presynaptic spike train as either regular or a memory-less Poisson process: few analytical results are available that describe depressing synapses when the afferent spike train has more complex, temporally correlated statistics such as bursts. Here we present a series of analytical results-from vesicle release-site occupancy statistics, via neurotransmitter release, to the post-synaptic voltage mean and variance-for depressing synapses driven by correlated presynaptic spike trains. The class of presynaptic drive considered is that fully characterised by the inter-spike-interval distribution and encompasses a broad range of models used for neuronal circuit and network analyses, such as integrate-and-fire models with a complete post-spike reset and receiving sufficiently short-time correlated drive. We further demonstrate that the derived post-synaptic voltage mean and variance allow for a simple and accurate approximation of the firing rate of the post-synaptic neuron, using the exponential integrate-and-fire model as an example. These results extend the level of biological detail included in models of synaptic transmission and will allow for the incorporation of more complex and physiologically relevant firing patterns into future studies of neuronal networks.

Bayesian Inference of Synaptic Quantal Parameters from Correlated Vesicle Release.

Synaptic transmission is both history-dependent and stochastic, resulting in varying responses to presentations of the same presynaptic stimulus. This complicates attempts to infer synaptic parameters and has led to the proposal of a number of different strategies for their quantification. Recently Bayesian approaches have been applied to make more efficient use of the data collected in paired intracellular recordings. Methods have been developed that either provide a complete model of the distribution of amplitudes for isolated responses or approximate the amplitude distributions of a train of post-synaptic potentials, with correct short-term synaptic dynamics but neglecting correlations. In both cases the methods provided significantly improved inference of model parameters as compared to existing mean-variance fitting approaches. However, for synapses with high release probability, low vesicle number or relatively low restock rate and for data in which only one or few repeats of the same pattern are available, correlations between serial events can allow for the extraction of significantly more information from experiment: a more complete Bayesian approach would take this into account also. This has not been possible previously because of the technical difficulty in calculating the likelihood of amplitudes seen in correlated post-synaptic potential trains; however, recent theoretical advances have now rendered the likelihood calculation tractable for a broad class of synaptic dynamics models. Here we present a compact mathematical form for the likelihood in terms of a matrix product and demonstrate how marginals of the posterior provide information on covariance of parameter distributions. The associated computer code for Bayesian parameter inference for a variety of models of synaptic dynamics is provided in the Supplementary Material allowing for quantal and dynamical parameters to be readily inferred from experimental data sets.

Optimal Current Transfer in Dendrites.

Integration of synaptic currents across an extensive dendritic tree is a prerequisite for computation in the brain. Dendritic tapering away from the soma has been suggested to both equalise contributions from synapses at different locations and maximise the current transfer to the soma. To find out how this is achieved precisely, an analytical solution for the current transfer in dendrites with arbitrary taper is required. We derive here an asymptotic approximation that accurately matches results from numerical simulations. From this we then determine the diameter profile that maximises the current transfer to the soma. We find a simple quadratic form that matches diameters obtained experimentally, indicating a fundamental architectural principle of the brain that links dendritic diameters to signal transmission.

Long-term plasticity determines the postsynaptic response to correlated afferents with multivesicular short-term synaptic depression.

Synchrony in a presynaptic population leads to correlations in vesicle occupancy at the active sites for neurotransmitter release. The number of independent release sites per presynaptic neuron, a synaptic parameter recently shown to be modified during long-term plasticity, will modulate these correlations and therefore have a significant effect on the firing rate of the postsynaptic neuron. To understand how correlations from synaptic dynamics and from presynaptic synchrony shape the postsynaptic response, we study a model of multiple release site short-term plasticity and derive exact results for the crosscorrelation function of vesicle occupancy and neurotransmitter release, as well as the postsynaptic voltage variance. Using approximate forms for the postsynaptic firing rate in the limits of low and high correlations, we demonstrate that short-term depression leads to a maximum response for an intermediate number of presynaptic release sites, and that this leads to a tuning-curve response peaked at an optimal presynaptic synchrony set by the number of neurotransmitter release sites per presynaptic neuron. These effects arise because, above a certain level of correlation, activity in the presynaptic population is overly strong resulting in wastage of the pool of releasable neurotransmitter. As the nervous system operates under constraints of efficient metabolism it is likely that this phenomenon provides an activity-dependent constraint on network architecture.

Systematic review, network meta-analysis and economic evaluation of biological therapy for the management of active psoriatic arthritis.

BACKGROUND: An updated economic evaluation was conducted to compare the cost-effectiveness of the four tumour necrosis factor (TNF)-α inhibitors adalimumab, etanercept, golimumab and infliximab in active, progressive psoriatic arthritis (PsA) where response to standard treatment has been inadequate. METHODS: A systematic review was conducted to identify relevant, recently published studies and the new trial data were synthesised, via a Bayesian network meta-analysis (NMA), to estimate the relative efficacy of the TNF-α inhibitors in terms of Psoriatic Arthritis Response Criteria (PsARC) response, Health Assessment Questionnaire (HAQ) scores and Psoriasis Area and Severity Index (PASI). A previously developed economic model was updated with the new meta-analysis results and current cost data. The model was adapted to delineate patients by PASI 50%, 75% and 90% response rates to differentiate between psoriasis outcomes. RESULTS: All four licensed TNF-α inhibitors were significantly more effective than placebo in achieving PsARC response in patients with active PsA. Adalimumab, etanercept and infliximab were significantly more effective than placebo in improving HAQ scores in patients who had achieved a PsARC response and in improving HAQ scores in PsARC non-responders. In an analysis using 1,000 model simulations, on average etanercept was the most cost-effective treatment and, at the National Institute for Health and Care Excellence willingness-to-pay threshold of between £20,000 to £30,000, etanercept is the preferred option. CONCLUSIONS: The economic analysis agrees with the conclusions from the previous models, in that biologics are shown to be cost-effective for treating patients with active PsA compared with the conventional management strategy. In particular, etanercept is cost-effective compared with the other biologic treatments.

Systematic review and network meta-analysis of combination and monotherapy treatments in disease-modifying antirheumatic drug-experienced patients with rheumatoid arthritis: analysis of American College of Rheumatology criteria scores 20, 50, and 70.

BACKGROUND: Biologic disease-modifying antirheumatic drugs (bDMARDs) extend the treatment choices for rheumatoid arthritis patients with suboptimal response or intolerance to conventional DMARDs. The objective of this systematic review and meta-analysis was to compare the relative efficacy of EU-licensed bDMARD combination therapy or monotherapy for patients intolerant of or contraindicated to continued methotrexate. METHODS: Comprehensive, structured literature searches were conducted in Medline, Embase, and the Cochrane Library, as well as hand-searching of conference proceedings and reference lists. Phase II or III randomized controlled trials reporting American College of Rheumatology (ACR) criteria scores of 20, 50, and 70 between 12 and 30 weeks' follow-up and enrolling adult patients meeting ACR classification criteria for rheumatoid arthritis previously treated with and with an inadequate response to conventional DMARDs were eligible. To estimate the relative efficacy of treatments whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using fixed and random-effects, logit-link models fitted to the binomial ACR 20/50/70 trial data. RESULTS: The systematic review identified 10,625 citations, and after a review of 2450 full-text papers, there were 29 and 14 eligible studies for the combination and monotherapy meta-analyses, respectively. In the combination analysis, all licensed bDMARD combinations had significantly higher odds of ACR 20/50/70 compared to DMARDs alone, except for the rituximab comparison, which did not reach significance for the ACR 70 outcome (based on the 95% credible interval). The etanercept combination was significantly better than the tumor necrosis factor-α inhibitors adalimumab and infliximab in improving ACR 20/50/70 outcomes, with no significant differences between the etanercept combination and certolizumab pegol or tocilizumab. Licensed-dose etanercept, adalimumab, and tocilizumab monotherapy were significantly better than placebo in improving ACR 20/50/70 outcomes. Sensitivity analysis indicated that including studies outside the target population could affect the results. CONCLUSION: Licensed bDMARDs are efficacious in patients with an inadequate response to conventional therapy, but tumor necrosis factor-α inhibitor combination therapies are not equally effective.

Topotecan for relapsed small cell lung cancer: a systematic review and economic evaluation.

BACKGROUND: Topotecan is a relatively new drug for use as a second-line treatment in patients with relapsed small cell lung cancer (SCLC). We performed a systematic review and economic evaluation of topotecan, and consider it here in relation to the NICE end of life criteria. METHODS: Seventeen bibliographic databases (including Cochrane library, Medline and Embase) were searched from 1990 to February 2009, and experts and manufacturers were consulted, to identify relevant randomised controlled trials (RCTs) which were selected according to prospectively defined criteria. An economic evaluation was undertaken to assess cost effectiveness compared with best supportive care (BSC) in the UK. RESULTS: Five RCTs were included. The clinical evidence indicates a statistically significant benefit of oral topotecan plus BSC compared to BSC alone for overall survival. Intravenous topotecan was similar in efficacy to both oral topotecan and CAV (cyclophosphamide, doxorubicin and vincristine). In the survival model, oral topotecan plus BSC was associated with an average gain in life expectancy of approximately 4 months, resulting in a gain of 0.183 quality-adjusted life years (QALYs). At an incremental cost of approximately £6200 the incremental cost effectiveness ratio (ICER) is £33,851 per QALY gained. CONCLUSIONS: Compared with BSC alone, oral topotecan for patients with relapsed SCLC was associated with improved health outcomes but at increased cost. The ICER is at the upper extreme of the range conventionally regarded as cost effective from an NHS decision making perspective. However, this treatment may fall under supplementary guidance for life extending, end of life treatments.

The mammalian SPD-2 ortholog Cep192 regulates centrosome biogenesis.

Centrosomes are the major microtubule-organizing centers of mammalian cells. They are composed of a centriole pair and surrounding microtubule-nucleating material termed pericentriolar material (PCM). Bipolar mitotic spindle assembly relies on two intertwined processes: centriole duplication and centrosome maturation. In the first process, the single interphase centrosome duplicates in a tightly regulated manner so that two centrosomes are present in mitosis. In the second process, the two centrosomes increase in size and microtubule nucleation capacity through PCM recruitment, a process referred to as centrosome maturation. Failure to properly orchestrate centrosome duplication and maturation is inevitably linked to spindle defects, which can result in aneuploidy and promote cancer progression. It has been proposed that centriole assembly during duplication relies on both PCM and centriole proteins, raising the possibility that centriole duplication depends on PCM recruitment. In support of this model, C. elegans SPD-2 and mammalian NEDD-1 (GCP-WD) are key regulators of both these processes. SPD-2 protein sequence homologs have been identified in flies, mice, and humans, but their roles in centrosome biogenesis until now have remained unclear. Here, we show that Cep192, the human homolog of C. elegans and D. melanogaster SPD-2, is a major regulator of PCM recruitment, centrosome maturation, and centriole duplication in mammalian cells. We propose a model in which Cep192 and Pericentrin are mutually dependent for their localization to mitotic centrosomes during centrosome maturation. Both proteins are then required for NEDD-1 recruitment and the subsequent assembly of gamma-TuRCs and other factors into fully functional centrosomes.