DRASTIC—INSIGHTS:querying information in a plant gene expression database

DRASTIC––Database Resource for the Analysis of Signal Transduction In Cells (http://www.drastic.org.uk/) has been created as a first step towards a data-based approach for constructing signal transduction pathways. DRASTIC is a relational database of plant expressed sequence tags and genes up- or down-regulated in response to various pathogens, chemical exposure or other treatments such as drought, salt and low temperature. More than 17700 records have been obtained from 306 treatments affecting 73 plant species from 512 peer-reviewed publications with most emphasis being placed on data from Arabidopsis thaliana. DRASTIC has been developed by the Scottish Crop Research Institute and the Abertay University and allows rapid identification of plant genes that are up- or down-regulated by multiple treatments and those that are regulated by a very limited (or perhaps a single) treatment. The INSIGHTS (INference of cell SIGnaling HypoTheseS) suite of web-based tools allows intelligent data mining and extraction of information from the DRASTIC database. Potential response pathways can be visualized and comparisons made between gene expression patterns in response to various treatments. The knowledge gained informs plant signalling pathways and systems biology investigations

Spatiotemporal patterns in the ecological community of the nearshore Mid-Atlantic Bight

Recognition of the need for a more holistic, ecosystem approach to the assessment and management of living marine resources has renewed interest in quantitative community eco logy and fueled efforts to develop ecosystem metrics to gain insight into system status. This investigation utilized 12 years (2008 to 2019) of fisheries-independent bottom trawl survey data to quantify and synthesize the spatiotemporal patterns of species assemblages inhabiting the nearshore Mid-Atlantic Bight (MAB). Assemblages were delineated by ecomorphotype (EMT), and all species collected by the survey were allocated among 9 EMTs: demersal fishes; pelagic fishes; flatfishes; skates; rays; dogfishes; other sharks; cephalopods; and benthic arthropods. Annual time series and seasonal spatial distributions of relative aggregate biomass were quantified for each EMT using delta-generalized additive models. Dynamic factor analysis (DFA) revealed that the information content of the 9 annual time series was effectively summarized by 3 common trends, and DFA model fits to each EMT time series represented a new suite of ecosystem indicators for this system. Mean sea surface temperature during winter in the MAB was included in the selected DFA model, suggesting that winter environmental conditions influence the structure of this system at an annual scale. Principal component analysis uncovered a north-to-south gradient in the seasonal spatial distributions of these EMTs and identified a distinct area of elevated biomass for several assemblages along the south shore of Long Island, NY. Taken together, these results characterize the community structure of the nearshore MAB and yield requisite information to support ongoing ecosystem-scale assessment and management activities for this region

Automatic Spectroscopic Data Categorization by Clustering Analysis (ASCLAN): A Data-Driven Approach for Distinguishing Discriminatory Metabolites for Phenotypic Subclasses

We propose a novel data-driven approach aiming to reliably distinguish discriminatory metabolites from nondiscriminatory metabolites for a given spectroscopic data set containing two biological phenotypic subclasses. The automatic spectroscopic data categorization by clustering analysis (ASCLAN) algorithm aims to categorize spectral variables within a data set into three clusters corresponding to noise, nondiscriminatory and discriminatory metabolites regions. This is achieved by clustering each spectral variable based on the r(2) value representing the loading weight of each spectral variable as extracted from a orthogonal partial least-squares discriminant (OPLS-DA) model of the data set. The variables are ranked according to r(2) values and a series of principal component analysis (PCA) models are then built for subsets of these spectral data corresponding to ranges of r(2) values. The Q(2)X value for each PCA model is extracted. K-means clustering is then applied to the Q(2)X values to generate two clusters based on minimum Euclidean distance criterion. The cluster consisting of lower Q(2)X values is deemed devoid of metabolic information (noise), while the cluster consists of higher Q(2)X values is then further subclustered into two groups based on the r(2) values. We considered the cluster with high Q(2)X but low r(2) values as nondiscriminatory, while the cluster with high Q(2)X and r(2) values as discriminatory variables. The boundaries between these three clusters of spectral variables, on the basis of the r(2) values were considered as the cut off values for defining the noise, nondiscriminatory and discriminatory variables. We evaluated the ASCLAN algorithm using six simulated (1)H NMR spectroscopic data sets representing small, medium and large data sets (N = 50, 500, and 1000 samples per group, respectively), each with a reduced and full resolution set of variables (0.005 and 0.0005 ppm, respectively). ASCLAN correctly identified all discriminatory metabolites and showed zero false positive (100% specificity and positive predictive value) irrespective of the spectral resolution or the sample size in all six simulated data sets. This error rate was found to be superior to existing methods for ascertaining feature significance: univariate t test by Bonferroni correction (up to 10% false positive rate), Benjamini-Hochberg correction (up to 35% false positive rate) and metabolome wide significance level (MWSL, up to 0.4% false positive rate), as well as by various OPLS-DA parameters: variable importance to projection, (up to 15% false positive rate), loading coefficients (up to 35% false positive rate), and regression coefficients (up to 39% false positive rate). The application of ASCLAN was further exemplified using a widely investigated renal toxin, mercury II chloride (HgCl2) in rat model. ASCLAN successfully identified many of the known metabolites related to renal toxicity such as increased excretion of urinary creatinine, and different amino acids. The ASCLAN algorithm provides a framework for reliably differentiating discriminatory metabolites from nondiscriminatory metabolites in a biological data set without the need to set an arbitrary cut off value as applied to some of the conventional methods. This offers significant advantages over existing methods and the possibility for automation of high-throughput screening in "omics" data

Mycobacteriosis-associated mortality in wild striped bass (Morone saxatilis) from Chesapeake Bay, USA

The striped bass (Morone saxatilis) is an economically and ecologically important finfish species along the Atlantic seaboard of the United States. Recent stock assessments in Chesapeake Bay (USA) indicate that non-fishing mortality in striped bass has increased since 1999, concomitant with very high (\u3e50%) prevalence of visceral and dermal disease caused by Mycobacterium spp. Current fishery assessment models do not differentiate between disease and other components of non-fishing mortality (e. g., senescence, predation); therefore, disease impact on the striped bass population has not been established. Specific measurement of mortality associated with mycobacteriosis in wild striped bass is complicated because the disease is chronic and mortality is cryptic. Epidemiological models have been developed to estimate disease-associated mortality from cross-sectional prevalence data and have recently been generalized to represent disease processes more realistically. Here, we used this generalized approach to demonstrate disease-associated mortality in striped bass from Chesapeake Bay. To our knowledge this is the first demonstration of cryptic mortality associated with a chronic infectious disease in a wild finfish. This finding has direct implications for management and stock assessment of striped bass, as it demonstrates population-level negative impacts of a chronic disease. Additionally, this research provides a framework by which disease-associated mortality may be specifically addressed within fisheries models for resource management

P2 receptors in macrophage fusion and osteoclast formation

Cells of the mononuclear phagocyte lineage fuse to form multinucleated giant cells and osteoclasts. Several lines of evidence suggest that P2 receptors, in particular P2X7, are involved in this process, although P2X7 is not absolutely required for fusion because P2X7-null mice form multinucleated osteoclasts. Extracellular ATP may be an important regulator of macrophage fusion

Hexaaqua­zinc(II) dipicrate

In the title compound, [Zn(H2O)6](C6H2N3O7)2, the ZnII ion is located on an inversion center and is coordinated by six water mol­ecules in an octa­hedral geometry. The picrate anions have no coordination inter­actions with the ZnII atom. The three nitro groups are twisted away from the attached benzene ring by19.8 (3), 6.5 (4) and 28.6 (3)°. There are numerous O—H⋯O hydrogen bonds in the crystal structure

Many Body Theory of Charge Transfer in Hyperthermal Atomic Scattering

We use the Newns-Anderson Hamiltonian to describe many-body electronic processes that occur when hyperthermal alkali atoms scatter off metallic surfaces. Following Brako and Newns, we expand the electronic many-body wavefunction in the number of particle-hole pairs (we keep terms up to and including a single particle-hole pair). We extend their earlier work by including level crossings, excited neutrals and negative ions. The full set of equations of motion are integrated numerically, without further approximations, to obtain the many-body amplitudes as a function of time. The velocity and work-function dependence of final state quantities such as the distribution of ion charges and excited atomic occupancies are compared with experiment. In particular, experiments that scatter alkali ions off clean Cu(001) surfaces in the energy range 5 to 1600 eV constrain the theory quantitatively. The neutralization probability of Na$^+$ ions shows a minimum at intermediate velocity in agreement with the theory. This behavior contrasts with that of K$^+$, which shows ... (7 figures, not included. Figure requests: [email protected])Comment: 43 pages, plain TeX, BUP-JBM-

Hexaaqua­cadmium(II) dipicrate monohydrate

In the structure of the title compound, [Cd(H2O)6](C6H2N3O7)2·H2O, the CdII ion is located on an inversion center and is coordinated by six water mol­ecules in an octa­hedral geometry. The picrate anions have no coordination inter­actions with the CdII ion. The three nitro groups are twisted away from the attached benzene ring, making dihedral angles of 17.89 (3), 27.94 (4) and 13.65 (3)°. There are numerous O—H⋯O hydrogen bonds in the crystal structure, involving coordinated and uncoordinated water molecules