Experimental toolbox for quantitative evaluation of clathrin-mediated endocytosis in the plant model Arabidopsis

Clathrin-mediated endocytosis (CME) is a crucial cellular process implicated in many aspects of plant growth, development, intra- and inter-cellular signaling, nutrient uptake and pathogen defense. Despite these significant roles, little is known about the precise molecular details of how it functions in planta. In order to facilitate the direct quantitative study of plant CME, here we review current routinely used methods and present refined, standardized quantitative imaging protocols which allow the detailed characterization of CME at multiple scales in plant tissues. These include: (i) an efficient electron microscopy protocol for the imaging of Arabidopsis CME vesicles in situ, thus providing a method for the detailed characterization of the ultra-structure of clathrin-coated vesicles; (ii) a detailed protocol and analysis for quantitative live-cell fluorescence microscopy to precisely examine the temporal interplay of endocytosis components during single CME events; (iii) a semi-automated analysis to allow the quantitative characterization of global internalization of cargos in whole plant tissues; and (iv) an overview and validation of useful genetic and pharmacological tools to interrogate the molecular mechanisms and function of CME in intact plant samples

Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke recurrence.

BackgroundPatients with symptomatic intracranial atherosclerosis (ICAS) of ≥ 70% luminal stenosis are at high risk of stroke recurrence. We aimed to evaluate the relationships between hemodynamics of ICAS revealed by computational fluid dynamics (CFD) models and risk of stroke recurrence in this patient subset.MethodsPatients with a symptomatic ICAS lesion of 70-99% luminal stenosis were screened and enrolled in this study. CFD models were reconstructed based on baseline computed tomographic angiography (CTA) source images, to reveal hemodynamics of the qualifying symptomatic ICAS lesions. Change of pressures across a lesion was represented by the ratio of post- and pre-stenotic pressures. Change of shear strain rates (SSR) across a lesion was represented by the ratio of SSRs at the stenotic throat and proximal normal vessel segment, similar for the change of flow velocities. Patients were followed up for 1 year.ResultsOverall, 32 patients (median age 65; 59.4% males) were recruited. The median pressure, SSR and velocity ratios for the ICAS lesions were 0.40 (-2.46-0.79), 4.5 (2.2-20.6), and 7.4 (5.2-12.5), respectively. SSR ratio (hazard ratio [HR] 1.027; 95% confidence interval [CI], 1.004-1.051; P = 0.023) and velocity ratio (HR 1.029; 95% CI, 1.002-1.056; P = 0.035) were significantly related to recurrent territorial ischemic stroke within 1 year by univariate Cox regression, respectively with the c-statistics of 0.776 (95% CI, 0.594-0.903; P = 0.014) and 0.776 (95% CI, 0.594-0.903; P = 0.002) in receiver operating characteristic analysis.ConclusionsHemodynamics of ICAS on CFD models reconstructed from routinely obtained CTA images may predict subsequent stroke recurrence in patients with a symptomatic ICAS lesion of 70-99% luminal stenosis

The existence of global weak solutions for a weakly dissipative Camassa-Holm equation in H1(R)

The existence of global weak solutions to the Cauchy problem for a weakly dissipative Camassa-Holm equation is established in the space C([0,∞)×R)nL∞([0,∞);H1(R)) under the assumption that the initial value u 0 (x) only belongs to the space H 1 (R) . The limit of viscous approximations, a one-sided super bound estimate and a space-time higher-norm estimate for the equation are established to prove the existence of the global weak solution

Oral cancer: role of the basement membrane in invasion

The document attached has been archived with permission from the Australian Dental Association. An external link to the publisher’s copy is included.Invasive growth of cancer cells is a complex process involving specific interactions between tumour cells and the orderly, integrated complexes of the extracellular matrix. Basement membranes have been proposed as one constituent of extra-cellular matrix which carries responsibility for regulating invasion and metastasis.David F. Wilson, Jiang De-Jun, Angela M. Pierce and Ole W. Wiebki

Deep Reinforcement Learning for DER Cyber-Attack Mitigation

The increasing penetration of DER with smart-inverter functionality is set to transform the electrical distribution network from a passive system, with fixed injection/consumption, to an active network with hundreds of distributed controllers dynamically modulating their operating setpoints as a function of system conditions. This transition is being achieved through standardization of functionality through grid codes and/or international standards. DER, however, are unique in that they are typically neither owned nor operated by distribution utilities and, therefore, represent a new emerging attack vector for cyber-physical attacks. Within this work we consider deep reinforcement learning as a tool to learn the optimal parameters for the control logic of a set of uncompromised DER units to actively mitigate the effects of a cyber-attack on a subset of network DER

Single to Double Hump Transition in the Equilibrium Distribution Function of Relativistic Particles

We unveil a transition from single peaked to bimodal velocity distribution in a relativistic fluid under increasing temperature, in contrast with a non-relativistic gas, where only a monotonic broadening of the bell-shaped distribution is observed. Such transition results from the interplay between the raise in thermal energy and the constraint of maximum velocity imposed by the speed of light. We study the Bose-Einstein, the Fermi-Dirac, and the Maxwell-J\"uttner distributions, all exhibiting the same qualitative behavior. We characterize the nature of the transition in the framework of critical phenomena and show that it is either continuous or discontinuous, depending on the group velocity. We analyze the transition in one, two, and three dimensions, with special emphasis on two-dimensions, for which a possible experiment in graphene, based on the measurement of the Johnson-Nyquist noise, is proposed.Comment: 5 pages, 5 figure

Computational and Mathematical Modelling of the EGF Receptor System

This chapter gives an overview of computational and mathematical modelling of the EGF receptor system. It begins with a survey of motivations for producing such models, then describes the main approaches that are taken to carrying out such modelling, viz. differential equations and individual-based modelling. Finally, a number of projects that applying modelling and simulation techniques to various aspects of the EGF receptor system are described

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Exploring the Bounds of Pygmalion Effects: Congruence of Implicit Followership Theories Drives and Binds Leader Performance Expectations and Follower Work Engagement

The topic of work engagement is moving up on the managerial agenda as it sets the stage for numerous beneficial outcomes for both organizations and their employees. It is clear, however, that not all employees are equally engaged in their job. The current study taps into theory on positive self-fulfilling prophecies induced by leaders’ high expectations of followers (i.e., the Pygmalion effect) and examines their potential to facilitate follower work engagement. By integrating literature on implicit followership theories with the Pygmalion model, we investigate the assumption that leaders’ high expectations are universally perceived as and therefore foster the same desirable results for all employees. We argue and find that the extent to which followers’ work engagement benefits from high leader expectations de