No Evidence for the Induction of Brown Algal Chemical Defense by the Phytohormones Jasmonic Acid and Methyl Jasmonate

Induced chemical defense reactions are widespread in marine brown algae. Despite the evidence that the biosynthesis of defense metabolites can be up-regulated upon herbivory, we do not know how this regulation of biosynthetic pathways to secondary metabolites is achieved in brown algae. In higher plants, the phytohormone jasmonic acid (JA) is crucial for the mediation of induced chemical defenses, and several findings of this metabolite from marine sources have been reported. We tested the hypothesis that JA or related metabolites play a role in induced brown algal defense. Quantification of oxylipins with a detection limit around 20ng g−1 algal tissue did not reveal the presence of JA in the seven examined brown algal species Dictyota dichotoma, Colpomenia peregrina, Ectocarpus fasciculatus, Fucus vesiculosus, Himanthalia elongata, Saccharina latissima (formerly Laminaria saccharina), and Sargassum muticum. Moreover, treatment with ecologically relevant concentrations of JA and methyl jasmonate did not lead to a significant change in the profile of medium- and non-polar metabolites of the tested algae. Only when high concentrations of ≥500μg ml−1 medium of the phytohormones were applied that a metabolic response which could be attributed to unspecific stress was observed. Bioassays with D. dichotoma that focused on medium- and non-polar compounds confirmed the lack of a biological role of JA and methyl jasmonate in the induction of algal induced chemical defenses. The phytohormone-treated samples did not exhibit any increased defense potential towards the amphipod Ampithoe longimana and the isopod Paracerceis caudata. JA and related phytohormones, known to be active in higher plants, thus appear to play no role in brown algae for induction of the defense chemicals studied her

jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints

<p>Abstract</p> <p>Background</p> <p>The decomposition of a chemical graph is a convenient approach to encode information of the corresponding organic compound. While several commercial toolkits exist to encode molecules as so-called fingerprints, only a few open source implementations are available. The aim of this work is to introduce a library for exactly defined molecular decompositions, with a strong focus on the application of these features in machine learning and data mining. It provides several options such as search depth, distance cut-offs, atom- and pharmacophore typing. Furthermore, it provides the functionality to combine, to compare, or to export the fingerprints into several formats.</p> <p>Results</p> <p>We provide a Java 1.6 library for the decomposition of chemical graphs based on the open source Chemistry Development Kit toolkit. We reimplemented popular fingerprinting algorithms such as depth-first search fingerprints, extended connectivity fingerprints, autocorrelation fingerprints (e.g. CATS2D), radial fingerprints (e.g. Molprint2D), geometrical Molprint, atom pairs, and pharmacophore fingerprints. We also implemented custom fingerprints such as the all-shortest path fingerprint that only includes the subset of shortest paths from the full set of paths of the depth-first search fingerprint. As an application of jCompoundMapper, we provide a command-line executable binary. We measured the conversion speed and number of features for each encoding and described the composition of the features in detail. The quality of the encodings was tested using the default parametrizations in combination with a support vector machine on the Sutherland QSAR data sets. Additionally, we benchmarked the fingerprint encodings on the large-scale Ames toxicity benchmark using a large-scale linear support vector machine. The results were promising and could often compete with literature results. On the large Ames benchmark, for example, we obtained an AUC ROC performance of 0.87 with a reimplementation of the extended connectivity fingerprint. This result is comparable to the performance achieved by a non-linear support vector machine using state-of-the-art descriptors. On the Sutherland QSAR data set, the best fingerprint encodings showed a comparable or better performance on 5 of the 8 benchmarks when compared against the results of the best descriptors published in the paper of Sutherland et al.</p> <p>Conclusions</p> <p>jCompoundMapper is a library for chemical graph fingerprints with several tweaking possibilities and exporting options for open source data mining toolkits. The quality of the data mining results, the conversion speed, the LPGL software license, the command-line interface, and the exporters should be useful for many applications in cheminformatics like benchmarks against literature methods, comparison of data mining algorithms, similarity searching, and similarity-based data mining.</p

Lyricum für das Schöne und Gute : Bd. 1. H. 1

http://tartu.ester.ee/record=b1715011~S1*es

Efficient extraction of canonical spatial relationships using a recursive enumeration of k-subsets

The spatial arrangement of a chemical compound plays an important role regarding the related properties or activities. A straightforward approach to encode the geometry is to enumerate pairwise spatial relationships between k substructures, like functional groups or subgraphs. This leads to a combinatorial explosion with th

Gait analysis in PSP and NPH Dual-task conditions make the difference

Objective To test whether quantitative gait analysis of gait under single- and dual-task conditions can be used for a differential diagnosis of progressive supranuclear palsy (PSP) and idiopathic normalpressure hydrocephalus (iNPH). Methods In this cross-sectional study, temporal and spatial gait parameters were analyzed in 38 patients with PSP (Neurological Disorders and Stroke and Society for Progressive Supranuclear Palsy diagnostic criteria), 27 patients with iNPH (international iNPH guidelines), and 38 healthy controls. A pressure-sensitive carpet was used to examine gait under 5 conditions: single task (preferred, slow, and maximal speed), cognitive dual task (walking with serial 7 subtractions), and motor dual task (walking while carrying a tray). Results The main results were as follows. First, both patients with PSP and those with iNPH exhibited significant gait dysfunction, which was worse in patients with iNPH with a more broad-based gait (p < 0.001). Second, stride time variability was increased in both patient groups, more pronounced in PSP (p = 0.009). Third, cognitive dual task led to a greater reduction of gait velocity in PSP (PSP 34.4% vs iNPH 16.9%, p = 0.002). Motor dual task revealed a dissociation of gait performance: patients with PSP considerably worsened, but patients with iNPH tended to improve. Conclusion Patients with PSP seem to be more sensitive to dual-task perturbations than patients with iNPH. An increased step width and anisotropy of the effect of dual-task conditions (cognitive vs motor) seem to be good diagnostic tools for iNPH