The microbial and metazoan community associated with colonies of Trichodesmium spp.: a quantitative survey

Association with resource-rich particles may benefit a number of planktonic species in oligotriphic, open-ocean regimes. This study examined communities of microbes and Zooplankton associated with colonies of the cyanobacterium Trichodesmium spp. in the Sargasso Sea. Trichodesmium colonies and seawater controls were collected near Bermuda using SCUBA during September 1995, and June, July and August 1996. Organisms associated with the colonies and those in the surrounding seawater were enumerated using light and fluorescence microscopy. We found that 85% of the Trichodesmium puff and tuft colonies examined harbored associated organisms. Associated organisms included bacteria (rod and coccoid),fungi, pennate diatoms, centric diatoms, heterotrophic and autotriphic dinoflagellates, chrysophytes, hypotrich ciliates, amoebae, hydroids, juveniles and nauplii of harpacticoid copepods, and juvenile decapods. The most common associates (in addition to bacteria) were dinoflagellates (present in 74% of the colonies examined), amoebae (50%), ciliates (24%), and diatoms (24%). Numbers of bacteria per colony volume averaged 8.2x10(8) bacteria ml(-1) (range = 8.1x10(7) -3.5x10(9) bacteria ml(-1)), and the density of associated microzooplankton and metazoans averaged 6.8x10(4) organisms ml(-1) (range = 0-3.6-10(6) organisms ml-1). Associates of Tichodesmium colonies were enriched by two to five orders of magnitude over plankton in the surrounding water. This unique habitat allows for the association of primarily benthic ciliate, diatom and copepod species and could contribute significantly to plankton heterogeneity in the open-ocean. The distribution of associated organisms was affected by sample characteristics such as colony morphology, mucoid matrix structure and colony integrity. The influence of these factors indicates that succession or competition between heterotrophic microorganisms ultimately determines Tichodesmium microcommunity structure. Similar processes could regulate microbial and metazoan communities associated with other resource-rich microenvironments, such as marine snow particles

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

The Impact of Social Disparity on Prefrontal Function in Childhood

The prefrontal cortex (PFC) develops from birth through late adolescence. This extended developmental trajectory provides many opportunities for experience to shape the structure and function of the PFC. To date, a few studies have reported links between parental socioeconomic status (SES) and prefrontal function in childhood, raising the possibility that aspects of environment associated with SES impact prefrontal function. Considering that behavioral measures of prefrontal function are associated with learning across multiple domains, this is an important area of investigation. In this study, we used fMRI to replicate previous findings, demonstrating an association between parental SES and PFC function during childhood. In addition, we present two hypothetical mechanisms by which SES could come to affect PFC function of this association: language environment and stress reactivity. We measured language use in the home environment and change in salivary cortisol before and after fMRI scanning. Complexity of family language, but not the child's own language use, was associated with both parental SES and PFC activation. Change in salivary cortisol was also associated with both SES and PFC activation. These observed associations emphasize the importance of both enrichment and adversity-reduction interventions in creating good developmental environments for all children

A co-registration investigation of inter-word spacing and parafoveal preview: Eye movements and fixation-related potentials

Participants’ eye movements (EMs) and EEG signal were simultaneously recorded to examine foveal and parafoveal processing during sentence reading. All the words in the sentence were manipulated for inter-word spacing (intact spaces vs. spaces replaced by a random letter) and parafoveal preview (identical preview vs. random letter string preview). We observed disruption for unspaced text and invalid preview conditions in both EMs and fixation-related potentials (FRPs). Unspaced and invalid preview conditions received longer reading times than spaced and valid preview conditions. In addition, the FRP data showed that unspaced previews disrupted reading in earlier time windows of analysis, compared to string preview conditions. Moreover, the effect of parafoveal preview was greater for spaced relative to unspaced conditions, in both EMs and FRPs. These findings replicate well-established preview effects, provide novel insight into the neural correlates of reading with and without inter-word spacing and suggest that spatial selection precedes lexical processing

All different or all the same? Exploring the diversity of professional practices in Portuguese school psychology

"Published online: 29 March 2016"Studies have generally characterized school psychologists as a relative homogenous population. Understanding the differences in professional practices and related variables is important for the development of the profession. Using a sample of 446 Portuguese school psychologists, this study used cluster analysis to identify distinct profiles of professional activity, based on practitioners’ time distribution among different target audiences (i.e.,students, parents, teachers, school board members, school non-professional staff, and other professionals within the school community). Three distinct profiles emerged from the data: a group highly oriented to work with students, a group that distributes time almost equitably between adults and students, and a group that concentrates attention and professional expertise on adults. Practice setting variables, such as school-psychologists-to-student ratio, schoolpsychologists-to-school ratio, number of referrals per year, and school community level of demand for different activities, were found to be significantly related to cluster membership. No personal- or professional-background-related variables differentiated the three groups. The main implications of these findings are discussed in light of recent literature regarding the models of service delivery for school psychologists

Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding

The recognition of cryptic small-molecular binding sites in protein structures is important for understanding off-target side effects and for recognizing potential new indications for existing drugs. Current methods focus on the geometry and detailed chemical interactions within putative binding pockets, but may not recognize distant similarities where dynamics or modified interactions allow one ligand to bind apparently divergent binding pockets. In this paper, we introduce an algorithm that seeks similar microenvironments within two binding sites, and assesses overall binding site similarity by the presence of multiple shared microenvironments. The method has relatively weak geometric requirements (to allow for conformational change or dynamics in both the ligand and the pocket) and uses multiple biophysical and biochemical measures to characterize the microenvironments (to allow for diverse modes of ligand binding). We term the algorithm PocketFEATURE, since it focuses on pockets using the FEATURE system for characterizing microenvironments. We validate PocketFEATURE first by showing that it can better discriminate sites that bind similar ligands from those that do not, and by showing that we can recognize FAD-binding sites on a proteome scale with Area Under the Curve (AUC) of 92%. We then apply PocketFEATURE to evolutionarily distant kinases, for which the method recognizes several proven distant relationships, and predicts unexpected shared ligand binding. Using experimental data from ChEMBL and Ambit, we show that at high significance level, 40 kinase pairs are predicted to share ligands. Some of these pairs offer new opportunities for inhibiting two proteins in a single pathway

Genetic Differentiation, Structure, and a Transition Zone among Populations of the Pitcher Plant Moth Exyra semicrocea: Implications for Conservation

Pitcher plant bogs, or carnivorous plant wetlands, have experienced extensive habitat loss and fragmentation throughout the southeastern United States Coastal Plain, resulting in an estimated reduction to <3% of their former range. This situation has lead to increased management attention of these habitats and their carnivorous plant species. However, conservation priorities focus primarily on the plants since little information currently exists on other community members, such as their endemic arthropod biota. Here, we investigated the population structure of one of these, the obligate pitcher plant moth Exyra semicrocea (Lepidoptera: Noctuidae), using mitochondrial cytochrome c oxidase subunit I (COI) gene sequences. Examination of 221 individuals from 11 populations across eight southeastern US states identified 51 unique haplotypes. These haplotypes belonged to one of two divergent (∼1.9–3.0%) lineages separated by the Mississippi alluvial plain. Populations of the West Gulf Coastal Plain exhibited significant genetic structure, contrasting with similarly distanced populations east of the Mississippi alluvial plain. In the eastern portion of the Coastal Plain, an apparent transition zone exists between two regionally distinct population groups, with a well-established genetic discontinuity for other organisms coinciding with this zone. The structure of E. semicrocea appears to have been influenced by patchy pitcher plant bog habitats in the West Gulf Coastal Plain as well as impacts of Pleistocene interglacials on the Apalachicola-Chattahoochee-Flint River Basin. These findings, along with potential extirpation of E. semicrocea at four visited, but isolated, sites highlight the need to consider other endemic or associated community members when managing and restoring pitcher plant bog habitats

DPRESS: Localizing estimates of predictive uncertainty

<p>Abstract</p> <p>Background</p> <p>The need to have a quantitative estimate of the uncertainty of prediction for QSAR models is steadily increasing, in part because such predictions are being widely distributed as tabulated values disconnected from the models used to generate them. Classical statistical theory assumes that the error in the population being modeled is independent and identically distributed (IID), but this is often not actually the case. Such inhomogeneous error (heteroskedasticity) can be addressed by providing an individualized estimate of predictive uncertainty for each particular new object <it>u</it>: the standard error of prediction <it>s</it>_ucan be estimated as the non-cross-validated error <it>s</it>_t*for the closest object <it>t</it>* in the training set adjusted for its separation <it>d </it>from <it>u </it>in the descriptor space relative to the size of the training set.</p> <p><display-formula><graphic file="1758-2946-1-11-i1.gif"/></display-formula></p> <p>The predictive uncertainty factor <it>γ</it>_t*is obtained by distributing the internal predictive error sum of squares across objects in the training set based on the distances between them, hence the acronym: <it>D</it>istributed <it>PR</it>edictive <it>E</it>rror <it>S</it>um of <it>S</it>quares (DPRESS). Note that <it>s</it>_t*and <it>γ</it>_t*are characteristic of each training set compound contributing to the model of interest.</p> <p>Results</p> <p>The method was applied to partial least-squares models built using 2D (molecular hologram) or 3D (molecular field) descriptors applied to mid-sized training sets (<it>N </it>= 75) drawn from a large (<it>N </it>= 304), well-characterized pool of cyclooxygenase inhibitors. The observed variation in predictive error for the external 229 compound test sets was compared with the uncertainty estimates from DPRESS. Good qualitative and quantitative agreement was seen between the distributions of predictive error observed and those predicted using DPRESS. Inclusion of the distance-dependent term was essential to getting good agreement between the estimated uncertainties and the observed distributions of predictive error. The uncertainty estimates derived by DPRESS were conservative even when the training set was biased, but not excessively so.</p> <p>Conclusion</p> <p>DPRESS is a straightforward and powerful way to reliably estimate individual predictive uncertainties for compounds outside the training set based on their distance to the training set and the internal predictive uncertainty associated with its nearest neighbor in that set. It represents a sample-based, <it>a posteriori </it>approach to defining applicability domains in terms of localized uncertainty.</p