An improvement in clear-air turbulence forecasting based on spontaneous imbalance theory: the ULTURB algorithm

Recent research has shown that Lighthill–Ford spontaneous gravity wave generation theory, when applied to numerical model data, can help predict areas of clear-air turbulence. It is hypothesized that this is the case because spontaneously generated atmospheric gravity waves may initiate turbulence by locally modifying the stability and wind shear. As an improvement on the original research, this paper describes the creation of an ‘operational’ algorithm (ULTURB) with three modifications to the original method: (1) extending the altitude range for which the method is effective downward to the top of the boundary layer, (2) adding turbulent kinetic energy production from the environment to the locally produced turbulent kinetic energy production, and, (3) transforming turbulent kinetic energy dissipation to eddy dissipation rate, the turbulence metric becoming the worldwide ‘standard’. In a comparison of ULTURB with the original method and with the Graphical Turbulence Guidance second version (GTG2) automated procedure for forecasting mid- and upper-level aircraft turbulence ULTURB performed better for all turbulence intensities. Since ULTURB, unlike GTG2, is founded on a self-consistent dynamical theory, it may offer forecasters better insight into the causes of the clear-air turbulence and may ultimately enhance its predictability.

Gap junction-mediated spontaneous Ca(2+) waves in differentiated cholinergic SN56 cells

Neuronal gap junctions are receiving increasing attention as a physiological means of intercellular communication, yet our understanding of them is poorly developed when compared to synaptic communication. Using microfluorimetry, we demonstrate that differentiation of SN56 cells (hybridoma cells derived from murine septal neurones) leads to the spontaneous generation of Ca(2+) waves. These waves were unaffected by tetrodotoxin (1microM), but blocked by removal of extracellular Ca(2+), or addition of non-specific Ca(2+) channel inhibitors (Cd(2+) (0.1mM) or Ni(2+) (1mM)). Combined application of antagonists of NMDA receptors (AP5; 100microM), AMPA/kainate receptors (NBQX; 20microM), nicotinic AChR receptors (hexamethonium; 100microM) or inotropic purinoceptors (brilliant blue; 100nM) was also without effect. However, Ca(2+) waves were fully prevented by carbenoxolone (200microM), halothane (3mM) or niflumic acid (100microM), three structurally diverse inhibitors of gap junctions, and mRNA for connexin 36 was detected by PCR. Whole-cell patch-clamp recordings revealed spontaneous inward currents in voltage-clamped cells which we inhibited by Cd(2+), Ni(2+) or niflumic acid. Our data suggest that differentiated SN56 cells generated spontaneous Ca(2+) waves which are propagated by intercellular gap junctions. We propose that this system can be exploited conveniently for the development of neuronal gap junction modulators.

Distribution of calcium (Ca) and magnesium (Mg) in the leaves of Brassica rapa under varying exogenous Ca and Mg supply

Background and Aims Leafy vegetable Brassica crops are an important source of dietary calcium (Ca) and magnesium (Mg) and represent potential targets for increasing leaf Ca and Mg concentrations through agronomy or breeding. Although the internal distribution of Ca and Mg within leaves affects the accumulation of these elements, such data are not available for Brassica. The aim of this study was to characterize the internal distribution of Ca and Mg in the leaves of a vegetable Brassica and to determine the effects of altered exogenous Ca and Mg supply on this distribution. Methods Brassica rapa ssp. trilocularis ‘R-o-18’ was grown at four different Ca:Mg treatments for 21 d in a controlled environment. Concentrations of Ca and Mg were determined in fully expanded leaves using inductively coupled plasma-mass spectrometry (ICP-MS). Internal distributions of Ca and Mg were determined in transverse leaf sections at the base and apex of leaves using energy-dispersive X-ray spectroscopy (EDS) with cryo-scanning electron microscopy (cryo-SEM). Key Results Leaf Ca and Mg concentrations were greatest in palisade and spongy mesophyll cells, respectively, although this was dependent on exogenous supply. Calcium accumulation in palisade mesophyll cells was enhanced slightly under high Mg supply; in contrast, Mg accumulation in spongy mesophyll cells was not affected by Ca supply. Conclusions The results are consistent with Arabidopsis thaliana and other Brassicaceae, providing phenotypic evidence that conserved mechanisms regulate leaf Ca and Mg distribution at a cellular scale. The future study of Arabidopsis gene orthologues in mutants of this reference B. rapa genotype will improve our understanding of Ca and Mg homeostasis in plants and may provide a model-to-crop translation pathway for targeted breeding.

Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs

Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca2+ transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca2+ transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.