Auxin-inducible degron technology allows rapid and controlled protein depletion. However, basal degradation without auxin and inefficient auxin-inducible depletion have limited its utility. We have identified a potent auxin-inducible degron system composed of auxin receptor F-box protein AtAFB2 and short degron minilAA7. The system showed minimal basal degradation and enabled rapid auxin-inducible depletion of endogenous human transmembrane, cytoplasmic and nuclear proteins in 1 h with robust functional phenotypes.

Azo dyes, such as azobenzene, are able to convert absorbed light into motion or deformation on the macroscopic scale on the basis of their remarkable ability to undergo repeatedly and in 100% yield reversibletrans-to-cisphotoisomerization. Current needs for multiresponsive and fast photoswitches have led to the development of heteroaryl azo dyes, such as azopyridine. This remarkable azo compound combines the photoresponse of the azo chromophore with the chemistry of the pyridine ring, in particular its responsiveness to changes in pH and its ability to form hydrogen- and halogen-bonds. This mini-review summarizes key features of the photoisomerization of polymer-tethered azopyridine in aqueous media and describes a few recent research accomplishments in emerging areas that have benefited of the fast thermalcis-to-transrelaxation characteristics of azopyridinium or H-bonded azopyridine. It also discusses the effects of the photoisomerization of azopyridine on the thermoresponsive properties of azopyridine-tethered heat-sensitive polymers. Overall, azopyridine is a highly versatile actuator to consider when designing photo/multiresponsive polymeric materials.

We present observations of similar to 10-60 min solar wind dynamic pressure structures that drive large-scale coherent similar to 20-100 keV electron loss from the outer radiation belt. A combination of simultaneous satellite and Balloon Array for Radiation-belt Relativistic Electron Losses (BARREL) observations on 11-12 January 2014 shows a close association between the pressure structures and precipitation as inferred from BARREL X-rays. Specifically, the structures drive radial ExB transport of electrons up to 1 Earth radii, modulating the free electron energy available for low-frequency plasmaspheric hiss growth, and subsequent hiss-induced loss cone scattering. The dynamic pressure structures, originating near the Sun and commonly observed advecting with the solar wind, are thus able to switch on scattering loss of electrons by hiss over a large spatial scale. Our results provide a direct link between solar wind pressure fluctuations and modulation of electron loss from the outer radiation belt and may explain long-period modulations and large-scale coherence of X-rays commonly observed in the BARREL data set. Plain Language Summary The Earth's low-density magnetosphere is a region of enclosed magnetic field lines that contains energetic electrons ranging from eV to MeV energies. These populations can be greatly enhanced in response to solar driving. Following enhancements, energetic electron populations are depleted on timescales of hours to days by various processes. One important depletion process occurs when an electromagnetic plasma wave called plasmaspheric hiss, which exists within a high plasma density region called the plasmasphere and its (occasional) radial extension called the plume, scatters energetic electrons into the atmosphere. In this paper, we show that these hiss waves can be switched on by compressions of the magnetosphere which occur in response to similar to 1 hr long pressure structures in the solar wind. These structures originate at or near the Sun and are very common in the solar wind at 1 AU. The newly excited hiss waves scatter electrons into the atmosphere where they are observed on balloon-borne X-ray detectors. Our results suggest that magnetospheric models that predict the loss of electrons from hiss waves may be improved by consideration of solar wind pressure-driven dynamics.

Context Mathematical models may help the analysis of biological systems by providing estimates of otherwise un-measurable quantities such as concentrations and fluxes. The variability in such systems makes it difficult to translate individual characteristics to group behavior. Mixed effects models offer a tool to simultaneously assess individual and population behavior from experimental data. Lipoproteins and plasma lipids are key mediators for cardiovascular disease in metabolic disorders such as diabetes mellitus type 2. By the use of mathematical models and tracer experiments fluxes and production rates of lipoproteins may be estimated. Results We developed a mixed effects model to study lipoprotein kinetics in a data set of 15 healthy individuals and 15 patients with type 2 diabetes. We compare the traditional and the mixed effects approach in terms of group estimates at various sample and data set sizes. Conclusion We conclude that the mixed effects approach provided better estimates using the full data set as well as with both sparse and truncated data sets. Sample size estimates showed that to compare lipoprotein secretion the mixed effects approach needed almost half the sample size as the traditional method.

In this study, we probed the importance of O-GlcNAc transferase (OGT) activity for the survival of tamoxifen-sensitive (TamS) and tamoxifen-resistant (TamR) breast cancer cells. Tamoxifen is an antagonist of estrogen receptor (ERa), a transcription factor expressed in over 50% of breast cancers. ERa-positive breast cancers are successfully treated with tamoxifen; however, a significant number of patients develop tamoxifen-resistant disease. We show that in vitro development of tamoxifenresistance is associated with increased sensitivity to the OGT small molecule inhibitor OSMI-1. Global transcriptome profiling revealed that TamS cells adapt to OSMI-1 treatment by increasing the expression of histone genes. This is known to mediate chromatin compaction. In contrast, TamR cells respond to OGT inhibition by activating the unfolded protein response and by significantly increasing ERRFI1 expression. ERRFI1 is an endogenous inhibitor of ERBB-signaling, which is a known driver of tamoxifen-resistance. We show that ERRFI1 is selectively downregulated in ERa-positive breast cancers and breast cancers driven by ERBB2. This likely occurs via promoter methylation. Finally, we show that increased ERRFI1 expression is associated with extended survival in patients with ERa-positive tumors (p = 9.2e-8). In summary, we show that tamoxifen-resistance is associated with sensitivity to OSMI-1, and propose that this is explained in part through an epigenetic activation of the tumor-suppressor ERRFI1 in response to OSMI-1 treatment.

We investigate the experimental setup proposed in [New J. Phys., 15, 115006 (2013)] for calorimetric measurements of thermodynamic indicators in an open quantum system. As theoretical model we consider a periodically driven qubit coupled with a large yet finite electron reservoir, the calorimeter. The calorimeter is initially at equilibrium with an infinite phonon bath. As time elapses, the temperature of the calorimeter varies in consequence of energy exchanges with the qubit and the phonon bath. We show how under weak coupling assumptions, the evolution of the qubit-calorimeter system can be described by a generalized quantum jump process including as dynamical variable the temperature of the calorimeter. We study the jump process by numeric and analytic methods. Asymptotically with the duration of the drive, the qubit-calorimeter attains a steady state. In this same limit, we use multiscale perturbation theory to derive a Fokker--Planck equation governing the calorimeter temperature distribution. We inquire the properties of the temperature probability distribution close and at the steady state. In particular, we predict the behavior of measurable statistical indicators versus the qubit-calorimeter coupling constant.

Aims. We model the energetic storm particle (ESP) event of 14 July 2012 using the energetic particle acceleration and transport model named 'PArticle Radiation Asset Directed at Interplanetary Space Exploration' (PARADISE), together with the solar wind and coronal mass ejection (CME) model named 'EUropean Heliospheric FORcasting Information Asset' (EUHFORIA). The simulation results illustrate both the capabilities and limitations of the utilised models. We show that the models capture some essential structural features of the ESP event; however, for some aspects the simulations and observations diverge. We describe and, to some extent, assess the sources of errors in the modelling chain of EUHFORIA and PARADISE and discuss how they may be mitigated in the future. Methods. The PARADISE model computes energetic particle distributions in the heliosphere by solving the focused transport equation in a stochastic manner. This is done using a background solar wind configuration generated by the ideal magnetohydrodynamic module of EUHFORIA. The CME generating the ESP event is simulated by using the spheromak model of EUHFORIA, which approximates the CME's flux rope as a linear force-free spheroidal magnetic field. In addition, a tool was developed to trace CME-driven shock waves in the EUHFORIA simulation domain. This tool is used in PARADISE to (i) inject 50 keV protons continuously at the CME-driven shock and (ii) include a foreshock and a sheath region, in which the energetic particle parallel mean free path, lambda(parallel to), decreases towards the shock wave. The value of lambda(parallel to) at the shock wave is estimated from in situ observations of the ESP event. Results. For energies below similar to 1 MeV, the simulation results agree well with both the upstream and downstream components of the ESP event observed by the Advanced Composition Explorer. This suggests that these low-energy protons are mainly the result of interplanetary particle acceleration. In the downstream region, the sharp drop in the energetic particle intensities is reproduced at the entry into the following magnetic cloud, illustrating the importance of a magnetised CME model.

Examining changes in abundance and demographic rates at species distribution margins may provide the first signs of broader species responses to environmental change. Still, the joint impact of space and time have remained relatively unstudied in most marginal regions. In order to examine the influence of climate variability on mussel distribution patterns, we monitored three sublittoral and marginal blue mussel (Mytilus trossulus) populations, spaced along a salinity gradient. Densities and biomasses peaked toward the saltier parts of the study area and showed relatively larger variations toward the low saline edge. Temporally, the areas showed a consistent increase in abundance after a synchronized large-scale recruitment event, which was followed by a decline in population size, occurring much faster toward the very range edge. Salinity, temperature, winter severity, and wave exposure explained most of the spatiotemporal variation in mussel abundances and adults showed positive effects on recruit abundance. We show empirically that the dynamics of edge populations are not driven by large changes in climate variables but that small spatial and temporal changes in key environmental variables have large and non-linear population level effects. Our results also show that fluctuating recruitment is a key factor for population stability affecting the storage potential of marginal populations, which dramatically decrease toward the edge. Our study provides a window into future population patterns and processes that drive marginal mussel populations in an altered sea characterized by rising temperature and declining salinity.

The sheaths of compressed solar wind that precede interplanetary coronal mass ejections (ICMEs) commonly display large-amplitude magnetic field fluctuations. As ICMEs propagate radially from the Sun, the properties of these fluctuations may evolve significantly. We have analyzed magnetic field fluctuations in an ICME sheath observed by MESSENGER at 0.47 au and subsequently by STEREO-B at 1.08 au while the spacecraft were close to radial alignment. Radial changes in fluctuation amplitude, compressibility, inertial-range spectral slope, permutation entropy, Jensen-Shannon complexity, and planar structuring are characterized. These changes are discussed in relation to the evolving turbulent properties of the upstream solar wind, the shock bounding the front of the sheath changing from a quasi-parallel to quasi-perpendicular geometry, and the development of complex structures in the sheath plasma.

To facilitate analysis of spatial tissue phenotypes, we created an open-source tool package named 'Spa-RQ' for 'Spatial tissue analysis: image Registration & Quantification'. Spa-RQ contains software for image registration (Spa-R) and quantitative analysis of DAB staining overlap (Spa-Q). It provides an easy-to-implement workflow for serial sectioning and staining as an alternative to multiplexed techniques. To demonstrate Spa-RQ's applicability, we analysed the spatial aspects of oncogenic KRAS-related signalling activities in non-small cell lung cancer (NSCLC). Using Spa-R in conjunction with ImageJ/Fiji, we first performed annotation-guided tumour-by-tumour phenotyping using multiple signalling markers. This analysis showed histopathology-selective activation of PI3K/AKT and MAPK signalling in Kras mutant murine tumours, as well as high p38MAPK stress signalling in p53 null murine NSCLC. Subsequently, Spa-RQ was applied to measure the co-activation of MAPK, AKT, and their mutual effector mTOR pathway in individual tumours. Both murine and clinical NSCLC samples could be stratified into 'MAPK/mTOR', 'AKT/mTOR', and 'Null' signature subclasses, suggesting mutually exclusive MAPK and AKT signalling activities. Spa-RQ thus provides a robust and easy to use tool that can be employed to identify spatially-distributed tissue phenotypes.