Intensification of winter transatlantic aviation turbulence in response to climate change

Atmospheric turbulence causes most weather-related aircraft incidents1. Commercial aircraft encounter moderate-or-greater turbulence tens of thousands of times each year worldwide, injuring probably hundreds of passengers (occasionally fatally), costing airlines tens of millions of dollars and causing structural damage to planes1, 2, 3. Clear-air turbulence is especially difficult to avoid, because it cannot be seen by pilots or detected by satellites or on-board radar4, 5. Clear-air turbulence is linked to atmospheric jet streams6, 7, which are projected to be strengthened by anthropogenic climate change8. However, the response of clear-air turbulence to projected climate change has not previously been studied. Here we show using climate model simulations that clear-air turbulence changes significantly within the transatlantic flight corridor when the concentration of carbon dioxide in the atmosphere is doubled. At cruise altitudes within 50–75° N and 10–60° W in winter, most clear-air turbulence measures show a 10–40% increase in the median strength of turbulence and a 40–170% increase in the frequency of occurrence of moderate-or-greater turbulence. Our results suggest that climate change will lead to bumpier transatlantic flights by the middle of this century. Journey times may lengthen and fuel consumption and emissions may increase. Aviation is partly responsible for changing the climate9, but our findings show for the first time how climate change could affect aviation.

Bayesian model averaging and identification of structural breaks in time series

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

Experimental crop growing in Jordan to develop methodology for the identification of ancient crop irrigation

Crop irrigation has long been recognized as having been important for the evolution of social complexity in several parts of the world. Structural evidence for water management, as in the form of wells, ditches and dams, is often difficult to interpret and may be a poor indicator of past irrigation that may have had no need for such constructions. It would be of considerable value, therefore, to be able to infer past irrigation directly from archaeo-botanical remains, and especially the type of archaeo-botanical remains that are relatively abundant in the archaeological record, such as phytoliths. Building on the pioneering work of Rosen and Wiener (1994), this paper describes a crop-growing experiment designed to explore the impact of irrigation on the formation of phytoliths within cereals. If it can be shown that a systemic and consistent relationship exists between phytolith size, structure and the intensity of irrigation, and if various taphonomic and palaeoenvironmental processes can be controlled for, then the presence of past irrigation can feasibly be inferred from the phytoliths recovered from the archaeological record.

Rational conversion of substrate and product specificity in a Salvia monoterpene synthase: structural insights into the evolution of terpene synthase function

Terpene synthases are responsible for the biosynthesis of the complex chemical defense arsenal of plants and microorganisms. How do these enzymes, which all appear to share a common terpene synthase fold, specify the many different products made almost entirely from one of only three substrates? Elucidation of the structure of 1,8-cineole synthase from Salvia fruticosa (Sf-CinS1) combined with analysis of functional and phylogenetic relationships of enzymes within Salvia species identified active-site residues responsible for product specificity. Thus, Sf-CinS1 was successfully converted to a sabinene synthase with a minimum number of rationally predicted substitutions, while identification of the Asn side chain essential for water activation introduced 1,8-cineole and alpha-terpineol activity to Salvia pomifera sabinene synthase. A major contribution to product specificity in Sf-CinS1 appears to come from a local deformation within one of the helices forming the active site. This deformation is observed in all other mono- or sesquiterpene structures available, pointing to a conserved mechanism. Moreover, a single amino acid substitution enlarged the active-site cavity enough to accommodate the larger farnesyl pyrophosphate substrate and led to the efficient synthesis of sesquiterpenes, while alternate single substitutions of this critical amino acid yielded five additional terpene synthases.

Role of oxygen radicals in DNA damage and cancer incidence

The development of cancer in humans and animals is a multistep process. The complex series of cellular and molecular changes participating in cancer development are mediated by a diversity of endogenous and exogenous stimuli. One type of endogenous damage is that arising from intermediates of oxygen (dioxygen) reduction - oxygen-free radicals (OFR), which attacks not only the bases but also the deoxyribosyl backbone of DNA. Thanks to improvements in analytical techniques, a major achievement in the understanding of carcinogenesis in the past two decades has been the identification and quantification of various adducts of OFR with DNA. OFR are also known to attack other cellular components such as lipids, leaving behind reactive species that in turn can couple to DNA bases. Endogenous DNA lesions are genotoxic and induce mutations. The most extensively studied lesion is the formation of 8-OH-dG. This lesion is important because it is relatively easily formed and is mutagenic and therefore is a potential biomarker of carcinogenesis. Mutations that may arise from formation of 8-OH-dG involve GC. TA transversions. In view of these findings, OFR are considered as an important class of carcinogens. The effect of OFR is balanced by the antioxidant action of non-enzymatic antioxidants as well as antioxidant enzymes. Non-enzymatic antioxidants involve vitamin C, vitamin E, carotenoids (CAR), selenium and others. However, under certain conditions, some antioxidants can also exhibit a pro-oxidant mechanism of action. For example, beta-carotene at high concentration and with increased partial pressure of dioxygen is known to behave as a pro-oxidant. Some concerns have also been raised over the potentially deleterious transition metal ion-mediated (iron, copper) pro-oxidant effect of vitamin C. Clinical studies mapping the effect of preventive antioxidants have shown surprisingly little or no effect on cancer incidence. The epidemiological trials together with in vitro experiments suggest that the optimal approach is to reduce endogenous and exogenous sources of oxidative stress, rather than increase intake of anti-oxidants. In this review, we highlight some major achievements in the study of DNA damage caused by OFR and the role in carcinogenesis played by oxidatively damaged DNA. The protective effect of antioxidants against free radicals is also discussed.

Robust nonlinear model identification methods using forward regression

In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on either experimental design criteria that optimizes model adequacy, or the predicted residual sums of squares (PRESS) statistic that optimizes model generalization capability, respectively. Three robust identification algorithms are introduced, i.e., combined A- and D-optimality with regularized orthogonal least squares algorithm, respectively; and combined PRESS statistic with regularized orthogonal least squares algorithm. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalization scheme in orthogonal least squares or regularized orthogonal least squares has been extended such that the new algorithms are computationally efficient. Numerical examples are included to demonstrate effectiveness of the algorithms.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

The role of corticospinal tract damage in chronic motor recovery and neurorehabilitation: a pilot study

Background. With diffusion-tensor imaging (DTi) it is possible to estimate the structural characteristics of fiber bundles in vivo. This study used DTi to infer damage to the corticospinal tract (CST) and relates this parameter to (a) the level of residual motor ability at least 1 year poststroke and (b) the outcome of intensive motor rehabilitation with constraint-induced movement therapy (CIMT). Objective. To explore the role of CST damage in recovery and CIMT efficacy. Methods. Ten patients with low-functioning hemiparesis were scanned and tested at baseline, before and after CIMT. Lesion overlap with the CST was indexed as reduced anisotropy compared with a CST variability map derived from 26 controls. Residual motor ability was measured through the Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL) acquired at baseline. CIMT benefit was assessed through the pre—post treatment comparison of WMFT and MAL performance. Results. Lesion overlap with the CST correlated with residual motor ability at baseline, with greater deficits observed in patients with more extended CST damage. Infarct volume showed no systematic association with residual motor ability. CIMT led to significant improvements in motor function but outcome was not associated with the extent of CST damage or infarct volume. Conclusion. The study gives in vivo support for the proposition that structural CST damage, not infarct volume, is a major predictor for residual functional ability in the chronic state. The results provide initial evidence for positive effects of CIMT in patients with varying, including more severe, CST damage.

Identification of critical residues in the active site of porcine membrane-bound aminopeptidase P

The membrane-bound form of mammalian aminopeptidase P (AP-P; EC 3.4. 11.9) is a mono-zinc-containing enzyme that lacks any of the typical metal binding motifs found in other zinc metalloproteases. To identify residues involved in metal binding and catalysis, sequence and structural information was used to align the sequence of porcine membrane-bound AP-P with other members of the peptidase clan MG, including Escherichia coli AP-P and methionyl aminopeptidases. Residues predicted to be critical for activity were mutated and the resultant proteins were expressed in COS-1 cells. Immunoelectrophoretic blot analysis was used to compare the levels of expression of the mutant proteins, and their ability to hydrolyze bradykinin and Gly-Pro-hydroxyPro was assessed. Asp449, Asp460, His523, Glu554, and Glu568 are predicted to serve as metal ion ligands in the active site, and mutagenesis of these residues resulted in fully glycosylated proteins that were catalytically inactive. Mutation of His429 and His532 also resulted in catalytically inactive proteins, and these residues, by analogy with E. coli AP-P, are likely to play a role in shuttling protons during catalysis. These studies indicate that mammalian membrane-bound AP-P has an active-site configuration similar to that of other members of the peptidase clan MG, which is compatible with either a dual metal ion model or a single metal ion in the active site. The latter model is consistent, however, with the known metal stoichiometry of both the membrane-bound and cytosolic forms of AP-P and with a recently proposed model for methionyl aminopeptidase.

Malonato complexes of oxidovanadium(IV): synthesis, structural characterization and exploration of their insulin mimetic properties

Several bis-malonatooxidovanadium(IV) complexes of the general type [M(2)(H2(O))(n)][VO(mal)(2)(H(2)O)] (where M = Li(1), Na(2), K(3), Cs(4) and NH4(5); n = 3.5, 1, 3, 1 and 1, respectively) were isolated in good yield and high purity. These complexes were fully characterized by various physicochemical techniques (elemental analysis, UV- Vis, IR, EPR, CV, etc.) complexes 1, 2 and 3 were structurally characterized by single crystal X- ray diffraction technique. In vivo antidiabetic properties of bis- malonato complexes 1, 2, 3 and 5 have been studied using Streptozotocin induced diabetic rats. Significant lowering of blood sugar level has been noticed. At the same time these complexes were found to regulate secondary pathophysiological complications like liver damage and lowering of the total antioxidant status (TAS) in diabetic rats. Results of these study are expected to a expand the possibility of designing new oxidovanadium(IV) complexes of O, O chelating ligands with significant antidiabetic properties

Direct anthelmintic effects of condensed tannins from diverse plant sources against Ascaris suum

Ascaris suum is one of the most prevalent nematode parasites in pigs and causes significant economic losses, and also serves as a good model for A. lumbricoides, the large roundworm of humans that is ubiquitous in developing countries and causes malnutrition, stunted growth and compromises immunity to other pathogens. New treatment options for Ascaris infections are urgently needed, to reduce reliance on the limited number of synthetic anthelmintic drugs. In areas where Ascaris infections are common, ethno-pharmacological practices such as treatment with natural plant extracts are still widely employed. However, scientific validation of these practices and identification of the active compounds are lacking, although observed effects are often ascribed to plant secondary metabolites such as tannins. Here, we extracted, purified and characterised a wide range of condensed tannins from diverse plant sources and investigated anthelmintic effects against A. suum in vitro. We show that condensed tannins can have potent, direct anthelmintic effects against A. suum, as evidenced by reduced migratory ability of newly hatched third-stage larvae and reduced motility and survival of fourth-stage larvae recovered from pigs. Transmission electron microscopy showed that CT caused significant damage to the cuticle and digestive tissues of the larvae. Furthermore, we provide evidence that the strength of the anthelmintic effect is related to the polymer size of the tannin molecule. Moreover, the identity of the monomeric structural units of tannin polymers may also have an influence as gallocatechin and epigallocatechin monomers exerted significant anthelmintic activity whereas catechin and epicatechin monomers did not. Therefore, our results clearly document direct anthelmintic effects of condensed tannins against Ascaris and encourage further in vivo investigation to determine optimal strategies for the use of these plant compounds for the prevention and/or treatment of ascariosis.

Genetic, structural, and molecular insights into the function of ras of complex proteins domains

Ras of complex proteins (ROC) domains were identified in 2003 as GTP binding modules in large multidomain proteins from Dictyostelium discoideum. Research into the function of these domains exploded with their identification in a number of proteins linked to human disease, including leucine-rich repeat kinase 2 (LRRK2) and death-associated protein kinase 1 (DAPK1) in Parkinson’s disease and cancer, respectively. This surge in research has resulted in a growing body of data revealing the role that ROC domains play in regulating protein function and signaling pathways. In this review, recent advances in the structural informa- tion available for proteins containing ROC domains, along with insights into enzymatic function and the integration of ROC domains as molecular switches in a cellular and organismal context, are explored.

The structural effect of Methyl substitution on the binding of Polypyridyl Ru-dppz Complexes to DNA

ABSTRACT: Polypyridyl ruthenium complexes have been intensively studied and possess photophysical properties which are both interesting and useful. They can act as probes for DNA, with a substantial enhancement in emission when bound, and can induce DNA damage upon photoirradiation and therefore, the synthesis and characterization of DNA binding of new complexes is an area of intense research activity. Whilst knowledge of how the binding of derivatives compares to the parent compound is highly desirable, this information can be difficult to obtain. Here we report the synthesis of three new methylated complexes, [Ru(TAP)2(dppz-10-Me).2Cl, [Ru(TAP)2(dppz-10,12-Me2)].2Cl and [Ru(TAP)2(dppz-11-Me)].2Cl, and examine the consequences for DNA binding through the use of atomic resolution X-ray crystallography. We find that the methyl groups are located in discrete positions with a complete directional preference. This may help to explain the quenching behavior which is found in solution for analogous [Ru(phen)2(dppz)]2+ derivatives.

OX133, a monoclonal antibody recognizing protein-bound N-ethylmaleimide for the identification of reduced disulfide bonds in proteins

In vivo, enzymatic reduction of some protein disulfide bonds, allosteric disulfide bonds, provides an important level of structural and functional regulation. The free cysteine residues generated can be labeled by maleimide reagents, including biotin derivatives, allowing the reduced protein to be detected or purified. During the screening of monoclonal antibodies for those specific for the reduced forms of proteins, we isolated OX133, a unique antibody that recognizes polypeptide resident, N-ethylmaleimide (NEM)-modified cysteine residues in a sequence-independent manner. OX133 offers an alternative to biotin-maleimide reagents for labeling reduced/alkylated antigens and capturing reduced/alkylated proteins with the advantage that NEM-modified proteins are more easily detected in mass spectrometry, and may be more easily recovered than is the case following capture with biotin based reagents.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.