Tackling thermosensation with multidimensional phenotyping.

Most if not all animals sense temperature using specialized thermosensory neurons. Genetic studies in simple organisms have been used to identify gene products required for detecting temperature changes or for mediating the effects of temperature on behaviour. A recent study has used automated imaging and multidimensional phenotyping to characterize behavioural responses to aversive temperature changes and to identify mutants with specific defects in these processes.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

From Gain Score t to ANCOVA F (and vice versa)

Although they test somewhat different hypotheses, analysis of gain scores (or its repeated-measures analog) and analysis of covariance are both common methods that researchers use for pre-post data. The results of the two approaches yield non-comparable outcomes, but since the same generic data are used, it is possible to transform the test statistic of one into that of the other. We derive a formula that can be used to accomplish a conversion between the two and give an example. Such a result could be helpful to meta-analysts, where the outcomes in different research reports may be of either of the two types, yet need to be synthesized. Suggestions for additional research that can improve the usefulness of the formula are offered. Accessed 30,293 times on https://pareonline.net from March 20, 2009 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Distinct roles for innexin gap junctions and hemichannels in mechanosensation.

Mechanosensation is central to a wide range of functions, including tactile and pain perception, hearing, proprioception, and control of blood pressure, but identifying the molecules underlying mechanotransduction has proved challenging. In Caenorhabditis elegans, the avoidance response to gentle body touch is mediated by six touch receptor neurons (TRNs), and is dependent on MEC-4, a DEG/ENaC channel. We show that hemichannels containing the innexin protein UNC-7 are also essential for gentle touch in the TRNs, as well as harsh touch in both the TRNs and the PVD nociceptors. UNC-7 and MEC-4 do not colocalize, suggesting that their roles in mechanosensory transduction are independent. Heterologous expression of unc-7 in touch-insensitive chemosensory neurons confers ectopic touch sensitivity, indicating a specific role for UNC-7 hemichannels in mechanosensation. The unc-7 touch defect can be rescued by the homologous mouse gene Panx1 gene, thus, innexin/pannexin proteins may play broadly conserved roles in neuronal mechanotransduction

A circuit model of the temporal pattern generator of Caenorhabditis egg-laying behavior.

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.BACKGROUND: Egg-laying behavior in the nematode C. elegans displays a distinct clustered temporal pattern: egg-laying events occur primarily in bursts or active phases, separated by inactive phases during which eggs are retained. The onset of the active phase can be modeled as a Poisson process with a time constant of approximately 20 minutes, while egg-laying events within an active phase occur with a faster time constant of approximately 20 seconds. Here we propose a cellular model for how the temporal pattern of egg-laying might be generated, based on genetic and cell-biological experiments and statistical analyses. RESULTS: We suggest that the HSN neuron is the executive neuron driving egg-laying events. We propose that the VC neurons act as "single egg counters" that inhibit HSN activity for short periods in response to individual egg-laying events. We further propose that the uv1 neuroendocrine cells are "cluster counters", which inhibit HSN activity for longer periods and are responsible for the time constant of the inactive phase. Together they form an integrated circuit that drives the clustered egg-laying pattern. CONCLUSIONS: The detailed predictions derived from this model can now be tested by straightforward validation experiments.Published versio

Magnetic field generation in finite beam plasma system

For finite systems boundaries can introduce remarkable novel features. A well known example is the Casimir effect [1, 2] that is observed in quantum electrodynamic systems. In classical systems too novel effects associated with finite boundaries have been observed, for example the surface plasmon mode [3] that appears when the plasma has a finite extension. In this work a novel instability associated with the finite transverse size of a beam owing through a plasma system has been shown to exist. This instability leads to distinct characteristic features of the associated magnetic field that gets generated. For example, in contrast to the well known unstable Weibel mode of a beam plasma system which generates magnetic field at the skin depth scale, this instability generates magnetic field at the scales length of the transverse beam dimension [4]. The existence of this new instability is demonstrated by analytical arguments and by simulations conducted with the help of a variety of Particle - In - Cell (PIC) codes (e.g. OSIRIS, EPOCH, PICPSI). Two fluid simulations have also been conducted which confirm the observations. Furthermore, laboratory experiments on laser plasma system also provides evidence of such an instability mechanism at work

Performance Limits of Stochastic Sub-Gradient Learning, Part II: Multi-Agent Case

The analysis in Part I revealed interesting properties for subgradient learning algorithms in the context of stochastic optimization when gradient noise is present. These algorithms are used when the risk functions are non-smooth and involve non-differentiable components. They have been long recognized as being slow converging methods. However, it was revealed in Part I that the rate of convergence becomes linear for stochastic optimization problems, with the error iterate converging at an exponential rate $\alpha^i$ to within an $O(\mu)-$neighborhood of the optimizer, for some $\alpha \in (0,1)$ and small step-size $\mu$. The conclusion was established under weaker assumptions than the prior literature and, moreover, several important problems (such as LASSO, SVM, and Total Variation) were shown to satisfy these weaker assumptions automatically (but not the previously used conditions from the literature). These results revealed that sub-gradient learning methods have more favorable behavior than originally thought when used to enable continuous adaptation and learning. The results of Part I were exclusive to single-agent adaptation. The purpose of the current Part II is to examine the implications of these discoveries when a collection of networked agents employs subgradient learning as their cooperative mechanism. The analysis will show that, despite the coupled dynamics that arises in a networked scenario, the agents are still able to attain linear convergence in the stochastic case; they are also able to reach agreement within $O(\mu)$ of the optimizer

Solar wind collisional heating

To properly describe heating in weakly collisional turbulent plasmas such as the solar wind, inter-particle collisions should be taken into account. Collisions can convert ordered energy into heat by means of irreversible relaxation towards the thermal equilibrium. Recently, Pezzi et al. (Phys. Rev. Lett., vol. 116, 2016, p. 145001) showed that the plasma collisionality is enhanced by the presence of fine structures in velocity space. Here, the analysis is extended by directly comparing the effects of the fully nonlinear Landau operator and a linearized Landau operator. By focusing on the relaxation towards the equilibrium of an out of equilibrium distribution function in a homogeneous force-free plasma, here it is pointed out that it is significant to retain nonlinearities in the collisional operator to quantify the importance of collisional effects. Although the presence of several characteristic times associated with the dissipation of different phase space structures is recovered in both the cases of the nonlinear and the linearized operators, the influence of these times is different in the two cases. In the linearized operator case, the recovered characteristic times are systematically larger than in the fully nonlinear operator case, this suggesting that fine velocity structures are dissipated slower if nonlinearities are neglected in the collisional operator

Locus model for space-time fabric and quantum indeterminacies

A simple locus model for the space-time fabric is presented and is compared with quantum foam and random walk models. The induced indeterminacies in momentum are calculated and it is shown that these space-time fabric indeterminacies are, in most cases, negligible compared with the quantum mechanical indeterminacies. This result restricts the possibilities of an experimental observation of the space-time fabric

Some Remarks about the Complexity of Epidemics Management

Recent outbreaks of Ebola, H1N1 and other infectious diseases have shown that the assumptions underlying the established theory of epidemics management are too idealistic. For an improvement of procedures and organizations involved in fighting epidemics, extended models of epidemics management are required. The necessary extensions consist in a representation of the management loop and the potential frictions influencing the loop. The effects of the non-deterministic frictions can be taken into account by including the measures of robustness and risk in the assessment of management options. Thus, besides of the increased structural complexity resulting from the model extensions, the computational complexity of the task of epidemics management - interpreted as an optimization problem - is increased as well. This is a serious obstacle for analyzing the model and may require an additional pre-processing enabling a simplification of the analysis process. The paper closes with an outlook discussing some forthcoming problems