Dynamics of social queues

This is the final version of the article. Available from the publisher via the DOI in this record.Queues formed by social wasps to inherit the dominant position in the nest are analyzed by using a transient quasi-birth-and-death (QBD) process. We show that the extended nest lifespan due to division of labor between queen and helpers has a big impact on nest productivity

The evolution of eusociality: no risk‐return tradeoff but the ecology matters

This is the final version. Available on open access from Wiley via the DOI in this recordata Availability Statement: No new data were created or analysed in this study.The origin of eusociality in the Hymenoptera is a question of major interest. Theory has tended to focus on genetic relatedness, but ecology can be just as important a determinant of whether eusociality evolves. Using the model of Fu et al. (2015), we show how ecological assumptions critically affect the conclusions drawn. Fu et al. inferred that eusociality rarely evolves because it faces a fundamental ‘risk‐return tradeoff’. The intuitive logic was that worker production represents an opportunity cost because it delays realising a reproductive payoff. However, making empirically justified assumptions that (1) workers take over egg‐laying following queen death and (2) productivity increases gradually with each additional worker, we find that the risk‐return tradeoff disappears. We then survey Hymenoptera with more specialised morphological castes, and show how the interaction between two common features of eusociality – saturating birth rates and group size‐dependent helping decisions – can determine whether eusociality outperforms other strategies

Direct and indirect control of the initiation of meiotic recombination by DNA damage checkpoint mechanisms in budding yeast

Meiotic recombination plays an essential role in the proper segregation of chromosomes at meiosis I in many sexually reproducing organisms. Meiotic recombination is initiated by the scheduled formation of genome-wide DNA double-strand breaks (DSBs). The timing of DSB formation is strictly controlled because unscheduled DSB formation is detrimental to genome integrity. Here, we investigated the role of DNA damage checkpoint mechanisms in the control of meiotic DSB formation using budding yeast. By using recombination defective mutants in which meiotic DSBs are not repaired, the effect of DNA damage checkpoint mutations on DSB formation was evaluated. The Tel1 (ATM) pathway mainly responds to unresected DSB ends, thus the sae2 mutant background in which DSB ends remain intact was employed. On the other hand, the Mec1 (ATR) pathway is primarily used when DSB ends are resected, thus the rad51 dmc1 double mutant background was employed in which highly resected DSBs accumulate. In order to separate the effect caused by unscheduled cell cycle progression, which is often associated with DNA damage checkpoint defects, we also employed the ndt80 mutation which permanently arrests the meiotic cell cycle at prophase I. In the absence of Tel1, DSB formation was reduced in larger chromosomes (IV, VII, II and XI) whereas no significant reduction was found in smaller chromosomes (III and VI). On the other hand, the absence of Rad17 (a critical component of the ATR pathway) lead to an increase in DSB formation (chromosomes VII and II were tested). We propose that, within prophase I, the Tel1 pathway facilitates DSB formation, especially in bigger chromosomes, while the Mec1 pathway negatively regulates DSB formation. We also identified prophase I exit, which is under the control of the DNA damage checkpoint machinery, to be a critical event associated with down-regulating meiotic DSB formation

How Gibbs distributions may naturally arise from synaptic adaptation mechanisms. A model-based argumentation

This paper addresses two questions in the context of neuronal networks dynamics, using methods from dynamical systems theory and statistical physics: (i) How to characterize the statistical properties of sequences of action potentials ("spike trains") produced by neuronal networks ? and; (ii) what are the effects of synaptic plasticity on these statistics ? We introduce a framework in which spike trains are associated to a coding of membrane potential trajectories, and actually, constitute a symbolic coding in important explicit examples (the so-called gIF models). On this basis, we use the thermodynamic formalism from ergodic theory to show how Gibbs distributions are natural probability measures to describe the statistics of spike trains, given the empirical averages of prescribed quantities. As a second result, we show that Gibbs distributions naturally arise when considering "slow" synaptic plasticity rules where the characteristic time for synapse adaptation is quite longer than the characteristic time for neurons dynamics.Comment: 39 pages, 3 figure

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file

Budding Yeast Pch2, a Widely Conserved Meiotic Protein, Is Involved in the Initiation of Meiotic Recombination

Budding yeast Pch2 protein is a widely conserved meiosis-specific protein whose role is implicated in the control of formation and displacement of meiotic crossover events. In contrast to previous studies where the function of Pch2 was implicated in the steps after meiotic double-strand breaks (DSBs) are formed, we present evidence that Pch2 is involved in meiotic DSB formation, the initiation step of meiotic recombination. The reduction of DSB formation caused by the pch2 mutation is most prominent in the sae2 mutant background, whereas the impact remains mild in the rad51 dmc1 double mutant background. The DSB reduction is further pronounced when pch2 is combined with a hypomorphic allele of SPO11. Interestingly, the level of DSB reduction is highly variable between chromosomes, with minimal impact on small chromosomes VI and III. We propose a model in which Pch2 ensures efficient formation of meiotic DSBs which is necessary for igniting the subsequent meiotic checkpoint responses that lead to proper differentiation of meiotic recombinants

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations

Expression of RNA interference triggers from an oncolytic herpes simplex virus results in specific silencing in tumour cells in vitro and tumours in vivo

<p>Abstract</p> <p>Background</p> <p>Delivery of small interfering RNA (siRNA) to tumours remains a major obstacle for the development of RNA interference (RNAi)-based therapeutics. Following the promising pre-clinical and clinical results with the oncolytic herpes simplex virus (HSV) OncoVEX^GM-CSF, we aimed to express RNAi triggers from oncolytic HSV, which although has the potential to improve treatment by silencing tumour-related genes, was not considered possible due to the highly oncolytic properties of HSV.</p> <p>Methods</p> <p>To evaluate RNAi-mediated silencing from an oncolytic HSV backbone, we developed novel replicating HSV vectors expressing short-hairpin RNA (shRNA) or artificial microRNA (miRNA) against the reporter genes green fluorescent protein (eGFP) and β-galactosidase (lacZ). These vectors were tested in non-tumour cell lines <it>in vitro </it>and tumour cells that are moderately susceptible to HSV infection both <it>in vitro </it>and in mice xenografts <it>in vivo</it>. Silencing was assessed at the protein level by fluorescent microscopy, x-gal staining, enzyme activity assay, and western blotting.</p> <p>Results</p> <p>Our results demonstrate that it is possible to express shRNA and artificial miRNA from an oncolytic HSV backbone, which had not been previously investigated. Furthermore, oncolytic HSV-mediated delivery of RNAi triggers resulted in effective and specific silencing of targeted genes in tumour cells <it>in vitro </it>and tumours <it>in vivo</it>, with the viruses expressing artificial miRNA being comprehensibly more effective.</p> <p>Conclusions</p> <p>This preliminary data provide the first demonstration of oncolytic HSV-mediated expression of shRNA or artificial miRNA and silencing of targeted genes in tumour cells <it>in vitro </it>and <it>in vivo</it>. The vectors developed in this study are being adapted to silence tumour-related genes in an ongoing study that aims to improve the effectiveness of oncolytic HSV treatment in tumours that are moderately susceptible to HSV infection and thus, potentially improve response rates seen in human clinical trials.</p

A discrete time neural network model with spiking neurons II. Dynamics with noise

We provide rigorous and exact results characterizing the statistics of spike trains in a network of leaky integrate and fire neurons, where time is discrete and where neurons are submitted to noise, without restriction on the synaptic weights. We show the existence and uniqueness of an invariant measure of Gibbs type and discuss its properties. We also discuss Markovian approximations and relate them to the approaches currently used in computational neuroscience to analyse experimental spike trains statistics.Comment: 43 pages - revised version - to appear il Journal of Mathematical Biolog