126 research outputs found

    Distribution and female reproductive state differences in orexigenic and anorexigenic neurons in the brain of the mouth brooding African cichlid fish, Astatotilapia burtoni

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    © 2017 Wiley Periodicals, Inc. Integration of reproduction and metabolism is necessary for species survival. While the neural circuits controlling energy homeostasis are well-characterized, the signals controlling the relay of nutritional information to the reproductive axis are less understood. The cichlid fish Astatotilapia burtoni is ideal for studying the neural regulation of feeding and reproduction because females cycle between a feeding gravid state and a period of forced starvation while they brood developing young inside their mouths. To test the hypothesis that candidate neuropeptide-containing neurons known to be involved in feeding and energy homeostasis in mammals show conserved distribution patterns, we performed immunohistochemistry and in situ hybridization to localize appetite-stimulating (neuropeptide Y, NPY; agouti-related protein, AGRP) and appetite-inhibiting (cocaine and amphetamine-regulated transcript, CART; pro-opiomelanocortin, pomc1a) neurons in the brain. NPY, AGRP, CART, and pomc1a somata showed distribution patterns similar to other teleosts, which included localization to the lateral tuberal nucleus (NLT), the putative homolog of the mammalian arcuate nucleus. Gravid females also had larger NPY and AGRP neurons in the NLT compared to brooding females, but brooding females had larger pomc1a neurons compared to gravid females. Hypothalamic agrp mRNA levels were also higher in gravid compared to brooding females. Thus, larger appetite-stimulating neurons (NPY, AGRP) likely promote feeding while females are gravid, while larger pomc1a neurons may act as a signal to inhibit food intake during mouth brooding. Collectively, our data suggest a potential role for NPY, AGRP, POMC, and CART in regulating energetic status in A. burtoni females during varying metabolic and reproductive demands

    Robust Detection of Dynamic Community Structure in Networks

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    We describe techniques for the robust detection of community structure in some classes of time-dependent networks. Specifically, we consider the use of statistical null models for facilitating the principled identification of structural modules in semi-decomposable systems. Null models play an important role both in the optimization of quality functions such as modularity and in the subsequent assessment of the statistical validity of identified community structure. We examine the sensitivity of such methods to model parameters and show how comparisons to null models can help identify system scales. By considering a large number of optimizations, we quantify the variance of network diagnostics over optimizations (`optimization variance') and over randomizations of network structure (`randomization variance'). Because the modularity quality function typically has a large number of nearly-degenerate local optima for networks constructed using real data, we develop a method to construct representative partitions that uses a null model to correct for statistical noise in sets of partitions. To illustrate our results, we employ ensembles of time-dependent networks extracted from both nonlinear oscillators and empirical neuroscience data.Comment: 18 pages, 11 figure

    Localization of glutamatergic, GABAergic, and cholinergic neurons in the brain of the African cichlid fish, Astatotilapia burtoni

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    © 2016 Wiley Periodicals, Inc. Neural communication depends on release and reception of different neurotransmitters within complex circuits that ultimately mediate basic biological functions. We mapped the distribution of glutamatergic, GABAergic, and cholinergic neurons in the brain of the African cichlid fish Astatotilapia burtoni using in situ hybridization to label vesicular glutamate transporters (vglut1, vglut2.1, vglut3), glutamate decarboxylases (gad1, gad2), and choline acetyltransferase (chat). Cells expressing the glutamatergic markers vgluts 1–3 show primarily nonoverlapping distribution patterns, with the most widespread expression observed for vglut2.1, and more restricted expression of vglut1 and vglut3. vglut1 is prominent in granular layers of the cerebellum, habenula, preglomerular nuclei, and several other diencephalic, mesencephalic, and rhombencephalic regions. vglut2.1 is widely expressed in many nuclei from the olfactory bulbs to the hindbrain, while vglut3 is restricted to the hypothalamus and hindbrain. GABAergic cells show largely overlapping gad1 and gad2 expression in most brain regions. GABAergic expression dominates nuclei of the subpallial ventral telencephalon, while glutamatergic expression dominates nuclei of the pallial dorsal telencephalon. chat-expressing cells are prominent in motor cranial nerve nuclei, and some scattered cells lie in the preoptic area and ventral part of the ventral telencephalon. A localization summary of these markers within regions of the conserved social decision-making network reveals a predominance of either GABAergic or glutamatergic cells within individual nuclei. The neurotransmitter distributions described here in the brain of a single fish species provide an important resource for identification of brain nuclei in other fishes, as well as future comparative studies on circuit organization and function. J. Comp. Neurol. 525:610–638, 2017. © 2016 Wiley Periodicals, Inc

    Ultraviolet radiation significantly enhances the molecular response to dispersant and sweet crude oil exposure in Nematostella vectensis

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    Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Marine Environmental Research 134 (2018): 96-108, doi:10.1016/j.marenvres.2018.01.002.Estuarine organisms are subjected to combinations of anthropogenic and natural stressors, which together can reduce an organisms' ability to respond to either stress or can potentiate or synergize the cellular impacts for individual stressors. Nematostella vectensis (starlet sea anemone) is a useful model for investigating novel and evolutionarily conserved cellular and molecular responses to environmental stress. Using RNA-seq, we assessed global changes in gene expression in Nematostella in response to dispersant and/or sweet crude oil exposure alone or combined with ultraviolet radiation (UV). A total of 110 transcripts were differentially expressed by dispersant and/or crude oil exposure, primarily dominated by the down-regulation of 74 unique transcripts in the dispersant treatment. In contrast, UV exposure alone or combined with dispersant and/or oil resulted in the differential expression of 1133 transcripts, of which 436 were shared between all four treatment combinations. Most significant was the differential expression of 531 transcripts unique to one or more of the combined UV/chemical exposures. Main categories of genes affected by one or more of the treatments included enzymes involved in xenobiotic metabolism and transport, DNA repair enzymes, and general stress response genes conserved among vertebrates and invertebrates. However, the most interesting observation was the induction of several transcripts indicating de novo synthesis of mycosporine-like amino acids and other novel cellular antioxidants. Together, our data suggest that the toxicity of oil and/or dispersant and the complexity of the molecular response are significantly enhanced by UV exposure, which may co-occur for shallow water species like Nematostella.This material is based upon work supported by the National Science Foundation under Grant No. MCB1057152 (MJJ), MCB1057354 (AMT) and DEB1545539 (AMR)

    The Influence of Network Topology on Sound Propagation in Granular Materials

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    Granular materials, whose features range from the particle scale to the force-chain scale to the bulk scale, are usually modeled as either particulate or continuum materials. In contrast with either of these approaches, network representations are natural for the simultaneous examination of microscopic, mesoscopic, and macroscopic features. In this paper, we treat granular materials as spatially-embedded networks in which the nodes (particles) are connected by weighted edges obtained from contact forces. We test a variety of network measures for their utility in helping to describe sound propagation in granular networks and find that network diagnostics can be used to probe particle-, curve-, domain-, and system-scale structures in granular media. In particular, diagnostics of meso-scale network structure are reproducible across experiments, are correlated with sound propagation in this medium, and can be used to identify potentially interesting size scales. We also demonstrate that the sensitivity of network diagnostics depends on the phase of sound propagation. In the injection phase, the signal propagates systemically, as indicated by correlations with the network diagnostic of global efficiency. In the scattering phase, however, the signal is better predicted by meso-scale community structure, suggesting that the acoustic signal scatters over local geographic neighborhoods. Collectively, our results demonstrate how the force network of a granular system is imprinted on transmitted waves.Comment: 19 pages, 9 figures, and 3 table

    Cross-linked structure of network evolution

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    We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks

    Dynamic Network Centrality Summarizes Learning in the Human Brain

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    We study functional activity in the human brain using functional Magnetic Resonance Imaging and recently developed tools from network science. The data arise from the performance of a simple behavioural motor learning task. Unsupervised clustering of subjects with respect to similarity of network activity measured over three days of practice produces significant evidence of `learning', in the sense that subjects typically move between clusters (of subjects whose dynamics are similar) as time progresses. However, the high dimensionality and time-dependent nature of the data makes it difficult to explain which brain regions are driving this distinction. Using network centrality measures that respect the arrow of time, we express the data in an extremely compact form that characterizes the aggregate activity of each brain region in each experiment using a single coefficient, while reproducing information about learning that was discovered using the full data set. This compact summary allows key brain regions contributing to centrality to be visualized and interpreted. We thereby provide a proof of principle for the use of recently proposed dynamic centrality measures on temporal network data in neuroscience

    Interactions between marine megafauna and plastic pollution in Southeast Asia

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    Southeast (SE) Asia is a highly biodiverse region, yet it is also estimated to cumulatively contribute a third of the total global marine plastic pollution. This threat is known to have adverse impacts on marine megafauna, however, understanding of its impacts has recently been highlighted as a priority for research in the region. To address this knowledge gap, a structured literature review was conducted for species of cartilaginous fishes, marine mammals, marine reptiles, and seabirds present in SE Asia, collating cases on a global scale to allow for comparison, coupled with a regional expert elicitation to gather additional published and grey literature cases which would have been omitted during the structured literature review. Of the 380 marine megafauna species present in SE Asia, but also studied elsewhere, we found that 9.1 % and 4.5 % of all publications documenting plastic entanglement (n = 55) and ingestion (n = 291) were conducted in SE Asian countries. At the species level, published cases of entanglement from SE Asian countries were available for 10 % or less of species within each taxonomic group. Additionally, published ingestion cases were available primarily for marine mammals and were lacking entirely for seabirds in the region. The regional expert elicitation led to entanglement and ingestion cases from SE Asian countries being documented in 10 and 15 additional species respectively, highlighting the utility of a broader approach to data synthesis. While the scale of the plastic pollution in SE Asia is of particular concern for marine ecosystems, knowledge of its interactions and impacts on marine megafauna lags behind other areas of the world, even after the inclusion of a regional expert elicitation. Additional funding to help collate baseline data are critically needed to inform policy and solutions towards limiting the interactions of marine megafauna and plastic pollution in SE Asia
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