A recurrent neural model for proto-object based contour integration and figure-ground segregation

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects (“proto-objects”) based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594–6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492–1499 2007; Chen et al. Neuron, 82(3), 682–694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.     

Benthic ctenophores (Platyctenida: Coeloplanidae) in south Florida: environmental conditions,habitats, abundances,and behaviors

Two benthic ctenophores, Coeloplana waltoni and Vallicula multiformis, are contrasted in terms of their coastal environments, habitats, abundances, seasonal occurrences, and behavior in south Florida. Coeloplana waltoni occurs as an epibiont on octocorals in open water settings, and V. multiformis is present in bio‐fouling communities, associated with macroalgae, bryozoans, and inanimate substrates in protected, back‐water habitats. In our study, individuals of C. waltoni were found under moderate to strong current flow and relatively constant temperature and salinity (T/S) conditions, whereas individuals of V. multiformis occurred at sites of low current flow and more variable T/S conditions. In C. waltoni, individuals generally adhered tightly to host colony surfaces, whereas in V. multiformis, individuals often disassociated from substrates and floated free. Mean population densities of C. waltoni ranged ~500–850 individuals 100 mL^?1 (measured as the displacement volume of the octocoral habitat), and densities of V. multiformis ranged 5–360 individuals 100 mL^?1 (measured as the displacement volume of the biofouling habitat). Abundance of C. waltoni was significantly highest in the 2014 warm season (June–October) when numerous minute (≤0.5 mm body length) juveniles were present. Vallicula multiformis was abundant in the 2015 and 2016 warm seasons (July–October), and also relatively abundant in the 2016 cool season (March–April). Ctenophore abundance and surface seawater temperature indicate a significant positive response to warm‐season conditions in C. waltoni, whereas numbers of V. multiformis did not show any effect of seawater temperature. Recently settled individuals of V. multiformis (≤1.0 mm) occurred throughout the year. Individuals of V. multiformis recruited to fiber‐coated sponges during warm and cool periods, with mean body sizes increasing in one cohort from 1.41 to 6.46 mm over a 39‐d period, suggesting a growth rate of ~4% d^?1. Feeding in both species involves tentacle capture of water‐borne zooplankton and particulate organic matter. Individuals of C. waltoni were also observed inserting tentacles into octocoral polyps, possibly pilfering food. Chlorophyll a was detected in extracts of both ctenophore species. The high abundances and feeding behavior of benthic ctenophores could have a strong influence on octocoral and biofouling communities.     

The role of cAMP dependent protein kinase in modulating spontaneous intracellular Ca waves in interstitial cells of Cajal from the rabbit urethra

Interstitial cells of Cajal (ICC) serve as electrical pacemakers in the rabbit urethra. Pacemaking activity in ICC results from spontaneous intracellular Ca²⁺ waves that rely on Ca²⁺ release from endoplasmic reticulum (ER) stores. The purpose of this study was to investigate if the action of protein kinase A (PKA) affected the generation of Ca²⁺ waves in ICC. Intracellular [Ca²⁺] was measured in fluo-4 loaded ICC, freshly isolated from the rabbit urethra using a Nipkow spinning disc confocal microscope. Application of the PKA inhibitor H-89 (10 μM) significantly inhibited the generation of spontaneous Ca²⁺ waves in ICC and this was associated with a significant decrease in the ER Ca²⁺ load, measured with 10 mM caffeine responses. Ca²⁺ waves could be rescued in the presence of H-89 by stimulating ryanodine receptors (RyRs) with 1 mM caffeine but not by activation of inositol 1,4,5 tri-phosphate receptors (IP₃Rs) with 10 μM phenylephrine. Increasing intracellular PKA with the cAMP agonists forskolin and 8-bromo-cAMP failed to yield an increase in Ca²⁺ wave activity. We conclude that PKA may be maximally active under basal conditions in ICC and that inhibition of PKA with H-89 leads to a decreased ER Ca²⁺ load sufficient to inactivate IP₃Rs but not RyRs.     

Optimizing Dendritic Cell-Based Approaches for Cancer Immunotherapy

Dendritic cells (DC) are professional antigen-presenting cells uniquely suited for cancer immunotherapy. They induce primary immune responses, potentiate the effector functions of previously primed T-lymphocytes, and orchestrate communication between innate and adaptive immunity. The remarkable diversity of cytokine activation regimens, DC maturation states, and antigen-loading strategies employed in current DC-based vaccine design reflect an evolving, but incomplete, understanding of optimal DC immunobiology. In the clinical realm, existing DC-based cancer immunotherapy efforts have yielded encouraging but inconsistent results. Despite recent U.S. Federal and Drug Administration (FDA) approval of DC-based sipuleucel-T for metastatic castration-resistant prostate cancer, clinically effective DC immunotherapy as monotherapy for a majority of tumors remains a distant goal. Recent work has identified strategies that may allow for more potent “next-generation” DC vaccines. Additionally, multimodality approaches incorporating DC-based immunotherapy may improve clinical outcomes.     

Bld10/Cep135 stabilizes basal bodies to resist cilia-generated forces

Basal bodies nucleate, anchor, and organize cilia. As the anchor for motile cilia, basal bodies must be resistant to the forces directed toward the cell as a consequence of ciliary beating. The molecules and generalized mechanisms that contribute to the maintenance of basal bodies remain to be discovered. Bld10/Cep135 is a basal body outer cartwheel domain protein that has established roles in the assembly of nascent basal bodies. We find that Bld10 protein first incorporates stably at basal bodies early during new assembly. Bld10 protein continues to accumulate at basal bodies after assembly, and we hypothesize that the full complement of Bld10 is required to stabilize basal bodies. We identify a novel mechanism for Bld10/Cep135 in basal body maintenance so that basal bodies can withstand the forces produced by motile cilia. Bld10 stabilizes basal bodies by promoting the stability of the A- and C-tubules of the basal body triplet microtubules and by properly positioning the triplet microtubule blades. The forces generated by ciliary beating promote basal body disassembly in bld10Δ cells. Thus Bld10/Cep135 acts to maintain the structural integrity of basal bodies against the forces of ciliary beating in addition to its separable role in basal body assembly.     

A Predictive Framework for Integrating Disparate Genomic Data Types Using Sample-Specific Gene Set Enrichment Analysis and Multi-Task Learning

Understanding the root molecular and genetic causes driving complex traits is a fundamental challenge in genomics and genetics. Numerous studies have used variation in gene expression to understand complex traits, but the underlying genomic variation that contributes to these expression changes is not well understood. In this study, we developed a framework to integrate gene expression and genotype data to identify biological differences between samples from opposing complex trait classes that are driven by expression changes and genotypic variation. This framework utilizes pathway analysis and multi-task learning to build a predictive model and discover pathways relevant to the complex trait of interest. We simulated expression and genotype data to test the predictive ability of our framework and to measure how well it uncovered pathways with genes both differentially expressed and genetically associated with a complex trait. We found that the predictive performance of the multi-task model was comparable to other similar methods. Also, methods like multi-task learning that considered enrichment analysis scores from both data sets found pathways with both genetic and expression differences related to the phenotype. We used our framework to analyze differences between estrogen receptor (ER) positive and negative breast cancer samples. An analysis of the top 15 gene sets from the multi-task model showed they were all related to estrogen, steroids, cell signaling, or the cell cycle. Although our study suggests that multi-task learning does not enhance predictive accuracy, the models generated by our framework do provide valuable biological pathway knowledge for complex traits.     

Reporting on Marginal Lands for Bioenergy Feedstock Production: a Modest Proposal

Growing bioenergy feedstocks can provide a long-term sustainable production system for marginal land resources and is essential for minimizing food vs. fuel competition for prime croplands. However, the term “marginal” is too often used in research reports without being defined. We here suggest that clearly specifying the biophysical factors and agroeconomic context contributing to marginality will greatly enhance the utility and comparability of published research.     

HmuS and HmuQ of <Emphasis Type="Italic">Ensifer</Emphasis>/<Emphasis Type="Italic">Sinorhizobium meliloti</Emphasis> degrade heme in vitro and participate in heme metabolism in vivo

Ensifer meliloti is a nitrogen-fixing symbiont of the alfalfa legume able to use heme as an iron source. The transport mechanism involved in heme acquisition in E. meliloti has been identified and characterized, but the fate of heme once inside the cell is not known. In silico analysis of E. meliloti 1021 genome revealed no canonical heme oxygenases although two genes encoding putative heme degrading enzymes, smc01518 and hmuS, were identified. SMc01518 is similar to HmuQ of Bradyrhizobium japonicum, which is weakly homologous to the Staphylococcus aureus IsdG heme-degrading monooxygenase, whereas HmuS is homolog to Pseudomonas aeruginosa PhuS, a protein reported as a heme chaperone and as a heme degrading enzyme. Recombinant HmuQ and HmuS were able to bind hemin with a 1:1 stoichiometry and displayed a K_d value of 5 and 4 µM, respectively. HmuS degrades heme in vitro to the biliverdin isomers IX-β and IX-δ in an equimolar ratio. The HmuQ recombinant protein degrades heme to biliverdin IX-δ only. Additionally, in this work we demonstrate that humS and hmuQ gene expression is regulated by iron and heme in a RirA dependent manner and that both proteins are involved in heme metabolism in E. meliloti in vivo.     

Aerial dispersal of phytoseiid mites (Acari: Phytoseiidae): estimating falling speed and dispersal distance of adult females

Aerial dispersal is important to immigration and redistribution of phytoseiid mites that often can provide biological control of spider mite pests. Falling speed of a mite and wind largely determine dispersal distance of such a passively blown organism. A diffusion model of wind-blown phytoseiids could provide insight into their dispersal. To this end, we measured body weights and falling speeds of adult females of 13 phytoseiid and one tetranychid mite species. These data were then incorporated into seed dispersal models (Greene and Johnson, Okubo and Levin) and results were compared to mite dispersal distances in wind tunnel, greenhouse and field. Weights of phytoseiid species ranged from 5.25 to 2l.7 μg; starved mites weighed less than fed mites. Geometric diameters ( d _g ) of idiosomas were correlated to weights. Falling speeds for phytoseiids were 0.39–0.73 m/s, and less than for T. urticae (0.79 m/s) in still air. In some species, active mites had slower falling speeds than inactive (anesthetized) mites indicating that behavior may influence falling. Starved mites had significantly slower falling speeds than fed mites and dispersed farther. Equation-based estimates of falling speed were close to measured ones (2–8% deviation) for some species. There were significant relationships between falling speed and body weight and morphological traits. Greene and Johnson's seed dispersal model provided better fits to dispersal of mites in the wind tunnel, greenhouse and field studies than Okubo and Levin's model. Limits of models in describing mite dispersal distance and applications to IPM are discussed.