Variability in gene expression underlies incomplete penetrance

The phenotypic differences between individual organisms can often be ascribed to underlying genetic and environmental variation. However, even genetically identical organisms in homogeneous environments vary, indicating that randomness in developmental processes such as gene expression may also generate diversity. To examine the consequences of gene expression variability in multicellular organisms, we studied intestinal specification in the nematode Caenorhabditis elegans in which wild-type cell fate is invariant and controlled by a small transcriptional network. Mutations in elements of this network can have indeterminate effects: some mutant embryos fail to develop intestinal cells, whereas others produce intestinal precursors. By counting transcripts of the genes in this network in individual embryos, we show that the expression of an otherwise redundant gene becomes highly variable in the mutants and that this variation is subjected to a threshold, producing an ON/OFF expression pattern of the master regulatory gene of intestinal differentiation. Our results demonstrate that mutations in developmental networks can expose otherwise buffered stochastic variability in gene expression, leading to pronounced phenotypic variation.National Institutes of Health (U.S.). Pioneer AwardMathematical Sciences Postdoctoral Research Fellowships (DMS-0603392)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (5F32GM080966

Upper atmospheres and ionospheres of planets and satellites

The upper atmospheres of the planets and their satellites are more directly exposed to sunlight and solar wind particles than the surface or the deeper atmospheric layers. At the altitudes where the associated energy is deposited, the atmospheres may become ionized and are referred to as ionospheres. The details of the photon and particle interactions with the upper atmosphere depend strongly on whether the object has anintrinsic magnetic field that may channel the precipitating particles into the atmosphere or drive the atmospheric gas out to space. Important implications of these interactions include atmospheric loss over diverse timescales, photochemistry and the formation of aerosols, which affect the evolution, composition and remote sensing of the planets (satellites). The upper atmosphere connects the planet (satellite) bulk composition to the near-planet (-satellite) environment. Understanding the relevant physics and chemistry provides insight to the past and future conditions of these objects, which is critical for understanding their evolution. This chapter introduces the basic concepts of upper atmospheres and ionospheres in our solar system, and discusses aspects of their neutral and ion composition, wind dynamics and energy budget. This knowledge is key to putting in context the observations of upper atmospheres and haze on exoplanets, and to devise a theory that explains exoplanet demographics.Comment: Invited Revie

Using high angular resolution diffusion imaging data to discriminate cortical regions

Brodmann's 100-year-old summary map has been widely used for cortical localization in neuroscience. There is a pressing need to update this map using non-invasive, high-resolution and reproducible data, in a way that captures individual variability. We demonstrate here that standard HARDI data has sufficiently diverse directional variation among grey matter regions to inform parcellation into distinct functional regions, and that this variation is reproducible across scans. This characterization of the signal variation as non-random and reproducible is the critical condition for successful cortical parcellation using HARDI data. This paper is a first step towards an individual cortex-wide map of grey matter microstructure, The gray/white matter and pial boundaries were identified on the high-resolution structural MRI images. Two HARDI data sets were collected from each individual and aligned with the corresponding structural image. At each vertex point on the surface tessellation, the diffusion-weighted signal was extracted from each image in the HARDI data set at a point, half way between gray/white matter and pial boundaries. We then derived several features of the HARDI profile with respect to the local cortical normal direction, as well as several fully orientationally invariant features. These features were taken as a fingerprint of the underlying grey matter tissue, and used to distinguish separate cortical areas. A support-vector machine classifier, trained on three distinct areas in repeat 1 achieved 80-82% correct classification of the same three areas in the unseen data from repeat 2 in three volunteers. Though gray matter anisotropy has been mostly overlooked hitherto, this approach may eventually form the foundation of a new cortical parcellation method in living humans. Our approach allows for further studies on the consistency of HARDI based parcellation across subjects and comparison with independent microstructural measures such as ex-vivo histology

Neural correlates of evidence accumulation during value-based decisions revealed via simultaneous EEG-fMRI

Current computational accounts posit that, in simple binary choices, humans accumulate evidence in favour of the different alternatives before committing to a decision. Neural correlates of this accumulating activity have been found during perceptual decisions in parietal and prefrontal cortex; however the source of such activity in value-based choices remains unknown. Here we use simultaneous EEG–fMRI and computational modelling to identify EEG signals reflecting an accumulation process and demonstrate that the within- and across-trial variability in these signals explains fMRI responses in posterior-medial frontal cortex. Consistent with its role in integrating the evidence prior to reaching a decision, this region also exhibits task-dependent coupling with the ventromedial prefrontal cortex and the striatum, brain areas known to encode the subjective value of the decision alternatives. These results further endorse the proposition of an evidence accumulation process during value-based decisions in humans and implicate the posterior-medial frontal cortex in this process

Characteristics of Jupiter’s X‐ray auroral hot spot emissions using Chandra

To help understand and determine the driver of jovian auroral X-rays, we present the first statistical study to focus on the morphology and dynamics of the jovian northern hot spot (NHS) using Chandra data. The catalogue we explore dates from 18 December 2000 up to and including 8 September 2019. Using a numerical criterion, we characterize the typical and extreme behaviour of the concentrated NHS emissions across the catalogue. The mean power of the NHS is found to be 1.91 GW with a maximum brightness of 2.02 Rayleighs (R), representing by far the brightest parts of the jovian X-ray spectrum. We report a statistically significant region of emissions at the NHS center which is always present, the averaged hot spot nucleus (AHSNuc), with mean power of 0.57 GW and inferred average brightness of ∼ 1.2 R. We use a flux equivalence mapping model to link this distinct region of X-ray output to a likely source location and find that the majority of mappable NHS photons emanate from the pre-dusk to pre-midnight sector, coincident with the dusk flank boundary. A smaller cluster maps to the noon magnetopause boundary, dominated by the AHSNuc, suggesting that there may be multiple drivers of X-ray emissions. On application of timing analysis techniques (Rayleigh, Monte Carlo, Jackknife), we identify several instances of statistically significant quasi-periodic oscillations (QPOs) in the NHS photons ranging from ∼ 2.3-min to 36.4-min, suggesting possible links with ultra-low frequency activity on the magnetopause boundary (e.g. dayside reconnection, Kelvin-Helmholtz instabilities)

Can we prevent or treat multiple sclerosis by individualised vitamin D supply?

Apart from its principal role in bone metabolism and calcium homeostasis, vitamin D has been attributed additional effects including an immunomodulatory, anti-inflammatory, and possibly even neuroprotective capacity which implicates a possible role of vitamin D in autoimmune diseases like multiple sclerosis (MS). Indeed, several lines of evidence including epidemiologic, preclinical, and clinical data suggest that reduced vitamin D levels and/or dysregulation of vitamin D homeostasis is a risk factor for the development of multiple sclerosis on the one hand, and that vitamin D serum levels are inversely associated with disease activity and progression on the other hand. However, these data are not undisputable, and many questions regarding the preventive and therapeutic capacity of vitamin D in multiple sclerosis remain to be answered. In particular, available clinical data derived from interventional trials using vitamin D supplementation as a therapeutic approach in MS are inconclusive and partly contradictory. In this review, we summarise and critically evaluate the existing data on the possible link between vitamin D and multiple sclerosis in light of the crucial question whether optimization of vitamin D status may impact the risk and/or the course of multiple sclerosis

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

Protein kinase C and cardiac dysfunction: a review

Heart failure (HF) is a physiological state in which cardiac output is insufficient to meet the needs of the body. It is a clinical syndrome characterized by impaired ability of the left ventricle to either fill or eject blood efficiently. HF is a disease of multiple aetiologies leading to progressive cardiac dysfunction and it is the leading cause of deaths in both developed and developing countries. HF is responsible for about 73,000 deaths in the UK each year. In the USA, HF affects 5.8 million people and 550,000 new cases are diagnosed annually. Cardiac remodelling (CD), which plays an important role in pathogenesis of HF, is viewed as stress response to an index event such as myocardial ischaemia or imposition of mechanical load leading to a series of structural and functional changes in the viable myocardium. Protein kinase C (PKC) isozymes are a family of serine/threonine kinases. PKC is a central enzyme in the regulation of growth, hypertrophy, and mediators of signal transduction pathways. In response to circulating hormones, activation of PKC triggers a multitude of intracellular events influencing multiple physiological processes in the heart, including heart rate, contraction, and relaxation. Recent research implicates PKC activation in the pathophysiology of a number of cardiovascular disease states. Few reports are available that examine PKC in normal and diseased human hearts. This review describes the structure, functions, and distribution of PKCs in the healthy and diseased heart with emphasis on the human heart and, also importantly, their regulation in heart failure

Identifying the Variety of Jovian X-Ray Auroral Structures: Tying the Morphology of X-Ray Emissions to Associated Magnetospheric Dynamics

We define the spatial clustering of X-rays within Jupiter's northern auroral regions by classifying their distributions into “X-ray auroral structures.” Using data from Chandra during Juno's main mission observations (24 May 2016 to 8 September 2019), we define five X-ray structures based on their ionospheric location and calculate the distribution of auroral photons. The morphology and ionospheric location of these structures allow us to explore the possibility of numerous X-ray auroral magnetospheric drivers. We compare these distributions to Hubble Space Telescope (HST) and Juno (Waves and MAG) data, and a 1D solar wind propagation model to infer the state of Jupiter's magnetosphere. Our results suggest that the five sub-classes of “X-ray structures” fall under two broad morphologies: fully polar and low latitude emissions. Visibility modeling of each structure suggests the non-uniformity of the photon distributions across the Chandra intervals are likely associated with the switching on/off of magnetospheric drivers as opposed to geometrical effects. The combination of ultraviolet (UV) and X-ray morphological structures is a powerful tool to elucidate the behavior of both electrons and ions and their link to solar wind/magnetospheric conditions in the absence of an upstream solar monitor. Although much work is still needed to progress the use of X-ray morphology as a diagnostic tool, we set the foundations for future studies to continue this vital research