Inositol 1,3,4,5,6-pentakisphosphate 2-kinase is a distant IPK member with a singular inositide binding site for axial 2-OH recognition

Inositol phosphates (InsPs) are signaling molecules with multiple roles in cells. In particular Graphic (InsP6) is involved in mRNA export and editing or chromatin remodeling among other events. InsP6 accumulates as mixed salts (phytate) in storage tissues of plants and plays a key role in their physiology. Human diets that are exclusively grain-based provide an excess of InsP6 that, through chelation of metal ions, may have a detrimental effect on human health. Ins(1,3,4,5,6)P5 2-kinase (InsP5 2-kinase or Ipk1) catalyses the synthesis of InsP6 from InsP5 and ATP, and is the only enzyme that transfers a phosphate group to the axial 2-OH of the myo-inositide. We present the first structure for an InsP5 2-kinase in complex with both substrates and products. This enzyme presents a singular structural region for inositide binding that encompasses almost half of the protein. The key residues in substrate binding are identified, with Asp368 being responsible for recognition of the axial 2-OH. This study sheds light on the unique molecular mechanism for the synthesis of the precursor of inositol pyrophosphates

Alternative Splicing of Circadian Clock Genes Correlates With Temperature in Field-Grown Sugarcane

Alternative Splicing (AS) is a mechanism that generates different mature transcripts from precursor mRNAs (pre-mRNAs) of the same gene. In plants, a wide range of physiological and metabolic events are related to AS, as well as fast responses to changes in temperature. AS is present in around 60% of intron-containing genes in Arabidopsis, 46% in rice, and 38% in maize and it is widespread among the circadian clock genes. Little is known about how AS influences the circadian clock of C4 plants, like commercial sugarcane, a C4 crop with a complex hybrid genome. This work aims to test if the daily dynamics of AS forms of circadian clock genes are regulated by environmental factors, such as temperature, in the field. A systematic search for AS in five sugarcane clock genes, ScLHY, ScPRR37, ScPRR73, ScPRR95, and ScTOC1 using different organs of sugarcane sampled during winter, with 4 months old plants, and during summer, with 9 months old plants, revealed temperature- and organ-dependent expression of at least one alternatively spliced isoform in all genes. Expression of AS isoforms varied according to the season. Our results suggest that AS events in circadian clock genes are correlated with temperature.</p

Doublet structures in quantum well absorption spectra due to Fano-related interference

In this theoretical investigation we predict an unusual interaction between a discrete state and a continuum of states, which is closely related to the case of Fano-interference. It occurs in a GaAs/AlxGa1-xAs quantum well between the lowest light-hole exciton and the continuum of the second heavy-hole exciton. Unlike the typical case for Fano-resonance, the discrete state here is outside the continuum; we use uniaxial stress to tune its position with respect to the onset of the continuum. State-of-the art calculations of absorption spectra show that as the discrete state approaches the continuum, a doublet structure forms which reveals anticrossing behaviour. The minimum separation energy of the anticrossing depends characteristically on the well width and is unusually large for narrow wells. This offers striking evidence for the strong underlying valence-band mixing. Moreover, it proves that previous explanations of similar doublets in experimental data, employing simple two-state models, are incomplete.Comment: 21 pages, 5 figures and 5 equations. Accepted for publication in Physical Review

Accurate cell tracking and lineage construction in live-cell imaging experiments with deep learning

Live-cell imaging experiments have opened an exciting window into the behavior of living systems. While these experiments can produce rich data, the computational analysis of these datasets is challenging. Single-cell analysis requires that cells be accurately identified in each image and subsequently tracked over time. Increasingly, deep learning is being used to interpret microscopy image with single cell resolution. In this work, we apply deep learning to the problem of tracking single cells in live-cell imaging data. Using crowdsourcing and a human-in-the-loop approach to data annotation, we constructed a dataset of over 11,000 trajectories of cell nuclei that includes lineage information. Using this dataset, we successfully trained a deep learning model to perform cell tracking within a linear programming framework. Benchmarking tests demonstrate that our method achieves state-of-the-art performance on the task of cell tracking with respect to multiple accuracy metrics. Further, we show that our deep learning-based method generalizes to perform cell tracking for both fluorescent and brightfield images of the cell cytoplasm, despite having never been trained those data types. This enables analysis of live-cell imaging data collected across imaging modalities. A persistent cloud deployment of our cell tracker is available at http://www.deepcell.org

Book Reviews

LEGAL RIGHTS OF THE MENTALLY HANDICAPPED. Edited by Bruce J. Ennis and Paul R. Friedman, with assistance by Bonnie Gitlin. New York: Practising Law Institute-Mental Health Law Project, 1973. Pp. 1533 in three volumes. 20.00. THE LAW OF ADVERTISING. By George Eric Rosden and Peter Eric Rosden. New York: Matthew Bender & Co., 1974. Loose Leaf, in two volumes. 100.00

The Evolution of Bat Vestibular Systems in the Face of Potential Antagonistic Selection Pressures for Flight and Echolocation

PMCID: PMC3634842This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Microhabitats of benthic foraminifera - a static concept or a dynamic adaption to optimize food aquisition?

In situ observations of microhabitat preferences of living benthic foraminifera are presented from sediments of the Norwegian-Greenland Sea, the upwelling area off northwestern Africa and the shallow-water Kiel Bight (Baltic Sea). Certain foraminiferal species (e.g.Cibicidoides wuellerstorfi andRupertina stabilis) can be regarded as strictly epibenthic species, colonizing elevated habitats that are strongly affected by bottom water hydrodynamics. Large epibenthic foraminifera (e.g.Rhabdammina abyssorum andHyperammina crassatina) colonize the sediment surface in areas where strong bottom currents occur and might have by virtue of their own size an impact on the small-scale circulation patterns of the bottom water. Motile species changing from epifaunal to infaunal habitats (e.g.Pyrgo rotalaria, Melonis barleeanum, Elphidium excavatum clavatum, Elphidium incertum, Ammotium cassis andSphaeroidina bulloides) are regarded here as highly adaptable to changes in food availability and/or changing environmental conditions. This flexible behaviour is regarded as a dynamic adaptation to optimize food acquisition, rather than a static concept leading to habitat classification of these ubiquitous rhizopods

Recent advances in methodology for clinical trials in small populations : the InSPiRe project

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods

Search for the disappearance of muon antineutrinos in the NuMI neutrino beam

We report constraints on antineutrino oscillation parameters that were obtained by using the two MINOS detectors to measure the 7% muon antineutrino component of the NuMI neutrino beam. In the Far Detector, we select 130 events in the charged-current muon antineutrino sample, compared to a prediction of 136.4 ± 11.7(stat)^(+10.2)_(-8.9)(syst) events under the assumption │Δm^2│ = 2.32 X 10^(-3) eV^2, sin^2(2θ) = 1.0

Measurement of the underground atmospheric muon charge ratio using the MINOS Near Detector

The magnetized MINOS Near Detector, at a depth of 225 mwe, is used to measure the atmospheric muon charge ratio. The ratio of observed positive to negative atmospheric muon rates, using 301 days of data, is measured to be 1.266±0.001(stat)_(-0.014)^(+0.015)(syst). This measurement is consistent with previous results from other shallow underground detectors and is 0.108±0.019(stat+syst) lower than the measurement at the functionally identical MINOS Far Detector at a depth of 2070 mwe. This increase in charge ratio as a function of depth is consistent with an increase in the fraction of muons arising from kaon decay for increasing muon surface energie