Hypothesis testing in animal social networks

Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.     

Synaptic plasticity at the cerebellum input stage: mechanisms and functional implications

The mf-GrC relay provides the case of a synapse at which elementary neurotransmission mechanisms are particularly well understood allowing a precise investigation of synaptic plasticity. An interesting consequence is that a presynaptic mechanism of LTP could be precisely documented on the basis of quantal analysis. By being presynaptically expressed, LTP becomes instrumental to regulation of short-term synaptic dynamics thereby controlling time-dependent transformations of the incoming mossy fiber input. It is unknown to what extent these considerations could be generalized, but early observations were provided for comparable concepts and mechanisms in neocortical synapses (Tsodyks and Markram, 1997). Although several aspects remain to be investigated, mf-GrC LTP provides a wide substrate for information storage in the cerebellum. In the rat cerebellum, there are 10(11) GrCs and 4 times as many mf-GrC synapses. Mathematical models have suggested that mf-GrC LTP improves mutual information transfer, and that the combination of synaptic and non-synaptic changes improves sparse representation of the mf input (Schweighofer et al., 2000; Philipona et al., 2003). Moreover, mf-GrC LTP could play a key role in regulating neurotransmission dynamics, implementing adaptability in delay lines early envisioned by Breitenberg (1967) and then revisited by Medina and Mauk (2002). These observations challenge the simple view of spatial pattern separation proposed by Marr (1969). The potential consequences of mf-GrC LTP need to be further investigated and confronted with computational models of the cerebellar network.     

Functional Vascular Changes of the Kidney during Pregnancy in Animals: A Systematic Review and Meta-Analysis

Renal vascular responses to pregnancy have frequently been studied, by investigating renal vascular resistance (RVR), renal flow, glomerular filtration rate (GFR), and renal artery responses to stimuli. Nonetheless, several questions remain: 1. Which vasodilator pathways are activated and to what extent do they affect RVR, renal flow and GFR across species, strains and gestational ages, 2. Are these changes dependent on renal artery adaptation, 3. At which cellular level does pregnancy affect the involved pathways? In an attempt to answer the questions raised, we performed a systematic review and meta-analysis on animal data. We included 37 studies (116 responses). At mid-gestation, RVR and GFR change to a similar degree across species and strains, accompanied by variable change in renal flow. At least in rats, changes depend on NO activation. At late gestation, changes in RVR, renal flow and GFR vary between species and strains. In rats, these changes are effectuated by sympathetic stimulation. Overall, renal artery responsiveness to stimuli is unaffected by pregnancy, except for Sprague Dawley rats in which pregnancy enhances renal artery vascular compliance and reduces renal artery myogenic reactivity. Our meta-analysis shows that: 1. Pregnancy changes RVR, renal flow and GFR dependent on NO-activation and sympathetic de-activation, but adjustments are different among species, strains and gestational ages; 2. These changes do not depend on adaptation of renal artery responsiveness; 3. It remains unknown at which cellular level pregnancy affects the pathways. Our meta-analysis suggests that renal changes during pregnancy in animals are qualitatively similar, even in comparison to humans, but quantitatively different.     

Electrogenicity of sodium/L-glutamate cotransport in rabbit renal brush-border membranes: a reevaluation

In order to clarify contradictory reports on the electrogenicity of sodium/L-glutamate cotransport, this cotransport was studied using brush-border membrane vesicles isolated from rabbit renal cortex. Beforehand, the claim that the symport of L-glutamate with Na+ is linked to simultaneous antiport with K+ has been confirmed by the demonstration that equilibrium exchange of L-glutamate is inhibited by potassium. Concerning the electrogenicity of the system, the following results are reported: net uptake of sodium-dependent L-glutamate uptake was stimulated when the transmembranal electrical potential difference was increased by replacing a sodium sulfate gradient by a sodium nitrate gradient. At 100 mM Na+ the 'relative electrogenicity' of the initial uptake in the presence of intravesicular potassium was 2-times higher than in its absence. At a sodium concentration of 20 mM, when overall uptake was reduced, the relative electrogenicity in the presence of K+ was even 3-fold higher than in K+-free media. The relative electrogenicity of sodium/D-glucose cotransport measured under the same experimental conditions was not affected by K+. These results are discussed in terms of a model where the apparent electrogenicity of a cotransport system is dependent on the extent to which the charge translocating step is rate limiting ('rate limitancy'). It is proposed that potassium antiport, while decreasing charge stoichiometry of Na+/glutamate transport, increases the relative rate limitancy of the transport step translocating three cations (probably two Na+, one H+) together with one glutamate. Thereby the positive electrogenicity of glutamate uptake increases, in complete contrast to what would be expected from simple considerations of charge stoichiometry.     

Mathematical analysis and modeling of motion direction selectivity in the retina

Motion detection is one of the most important and primitive computations performed by our visual system. Specifically in the retina, ganglion cells producing motion direction-selective responses have been addressed by different disciplines, such as mathematics, neurophysiology and computational modeling, since the beginnings of vision science. Although a number of studies have analyzed theoretical and mathematical considerations for such responses, a clear picture of the underlying cellular mechanisms is only recently emerging. In general, motion direction selectivity is based on a non-linear asymmetric computation inside a receptive field differentiating cell responses between preferred and null direction stimuli. To what extent can biological findings match these considerations? In this review, we outline theoretical and mathematical studies of motion direction selectivity, aiming to map the properties of the models onto the neural circuitry and synaptic connectivity found in the retina. Additionally, we review several compartmental models that have tried to fill this gap. Finally, we discuss the remaining challenges that computational models will have to tackle in order to fully understand the retinal motion direction-selective circuitry.     

Connectomic constraints on computation in feedforward networks of spiking neurons

Several efforts are currently underway to decipher the connectome or parts thereof in a variety of organisms. Ascertaining the detailed physiological properties of all the neurons in these connectomes, however, is out of the scope of such projects. It is therefore unclear to what extent knowledge of the connectome alone will advance a mechanistic understanding of computation occurring in these neural circuits, especially when the high-level function of the said circuit is unknown. We consider, here, the question of how the wiring diagram of neurons imposes constraints on what neural circuits can compute, when we cannot assume detailed information on the physiological response properties of the neurons. We call such constraints—that arise by virtue of the connectome—connectomic constraints on computation. For feedforward networks equipped with neurons that obey a deterministic spiking neuron model which satisfies a small number of properties, we ask if just by knowing the architecture of a network, we can rule out computations that it could be doing, no matter what response properties each of its neurons may have. We show results of this form, for certain classes of network architectures. On the other hand, we also prove that with the limited set of properties assumed for our model neurons, there are fundamental limits to the constraints imposed by network structure. Thus, our theory suggests that while connectomic constraints might restrict the computational ability of certain classes of network architectures, we may require more elaborate information on the properties of neurons in the network, before we can discern such results for other classes of networks.     

Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis

MOTIVATION: Pathway knowledge in public databases enables us to examine how individual metabolites are connected via chemical reactions and what genes are implicated in those processes. For two given (sets of) compounds, the number of possible paths between them in a metabolic network can be intractably large. It would be informative to rank these paths in order to differentiate between them. RESULTS: Focusing on adjacent pairwise coexpression, we developed an algorithm which, for a specified k, efficiently outputs the top k paths based on a probabilistic scoring mechanism, using a given metabolic network and microarray datasets. Our idea of using adjacent pairwise coexpression is supported by recent studies that local coregulation is predominant in metabolism. We first evaluated this idea by examining to what extent highly correlated gene pairs are adjacent and how often they are consecutive in a metabolic network. We then applied our algorithm to two examples of path ranking: the paths from glucose to pyruvate in the entire metabolic network of yeast and the paths from phenylalanine to sinapyl alcohol in monolignols pathways of arabidopsis under several different microarray conditions, to confirm and discuss the performance analysis of our method.     

Inhibition of glutamine synthetase in the mouse kidney: a novel mechanism of adaptation to metabolic acidosis

As part of a study on the regulation of renal ammoniagenesis in the mouse kidney, we investigated the effect of chronic metabolic acidosis on glutamine synthesis by isolated mouse renal proximal tubules. The results obtained reveal that, in tubules from control mice, glutamine synthesis occurred at high rates from glutamate and proline and, to a lesser extent, from ornithine, alanine, and aspartate. A 48 h, metabolic acidosis caused a marked inhibition of glutamine synthesis from near-physiological concentrations of both alanine and proline that were avidly metabolized by the tubules; metabolic acidosis also greatly stimulated glutamine utilization and metabolism. These effects were accompanied by a large increase (i) in alanine, proline, and glutamine gluconeogenesis and (ii) in ammonia accumulation from proline and glutamine. In the renal cortex of acidotic mice, the activity of phosphoenolpyruvate carboxykinase increased 4-fold, but that of glutamate dehydrogenase did not change; in contrast with what is known in the rat renal cortex, metabolic acidosis markedly diminished the glutamine synthetase activity and protein level, but not the glutamine synthetase mRNA level in the mouse renal cortex. These results strongly suggest that, in the mouse kidney, glutamine synthetase is an important regulatory component of the availability of the ammonium ions to be excreted for defending systemic acid-base balance. Furthermore, they show that, in rodents, the regulation of renal glutamine synthetase is species-specific.     

Effects of aging on the kidney.

A host of abnormalities of renal structure and function accompany advancing age. This presentation briefly surveys the renal anatomical and functional changes associated with senescence. Four areas of renal functional change have been selected for in-depth discussion: a) renal blood flow; b) glomerular filtration rate; c) renal sodium handling; and d) renal concentrating ability. The methodologic considerations including population selection which confound the assessment of the effects of aging on renal function are discussed. In addition, the functional changes associated with senescence are discussed in the context of longitudinal studies and studies utilizing appropriate patient cohorts, including potential kidney transplant donors. The clinical implications of senescent changes with regard to adjusting "normative" standards to fit the age of the patient are addressed. Furthermore, the implications of age-related renal functional alterations in predisposing the elderly patient to a number of fluid and electrolyte derangements are considered.--Epstein, M. Effects of aging on the kidney.     

Coevolution is a short-distance force at the protein interaction level and correlates with the modular organization of protein networks

We investigated what roles coevolution plays in shaping yeast protein interaction network (PIN). We found that the extent of coevolution between two proteins decreases rapidly as their interacting distance on the PIN increases, suggesting coevolutionary constraint is a short-distance force at the molecular level. We also found that protein-protein interactions (PPIs) with strong coevolution tend to be enriched in interconnected clusters, whereas PPIs with weak coevolution are more frequently present at inter-cluster region. The findings indicate the close relationship between coevolution and modular organization of PINs, and may provide insights into evolution and modularity of cellular networks.     

Multilayer network analyses as a toolkit for measuring social structure

The formalization of multilayer networks allows for new ways to measure sociality in complex social systems,including groups of animals.The same mathematical representation and methods are widely applicable across fields and study systems,and a network can represent drastically different types of data.As such,in order to apply analyses and interpret the results in a meaningful way the researcher must have a deep understanding of what their network is representing and what parts of it are being measured by a given analysis.Multilayer social networks can represent social structure with more detail than is often present in single layer networks,including multiple"types"of individuals,interactions,or relationships,and the extent to which these types are interdependent.Multilayer networks can also encompass a wider range of social scales,which can help overcome complications that are inherent to measuring sociality.In this paper,I dissect multilayer networks into the parts that correspond to different components of social structures.I then discuss common pitfalls to avoid across different stages of multilayer network analyses-some novel and some that always exist in social network analysis but are magnified in multi-layer representations.This paper serves as a primer for building a customized toolkit of multilayer network analyses,to probe components of social structure in animal social systems.     

Generalized Gene Adjacencies, Graph Bandwidth, and Clusters in Yeast Evolution

We present a parameterized definition of gene clusters that allows us to control the emphasis placed on conserved order within a cluster. Though motivated by biological rather than mathematical considerations, this parameter turns out to be closely related to the bandwidth parameter of a graph. Our focus will be on how this parameter affects the characteristics of clusters: how numerous they are, how large they are, how rearranged they are, and to what extent they are preserved from ancestor to descendant in a phylogenetic tree. We infer the latter property by dynamic programming optimization of the presence of individual edges at the ancestral nodes of the phylogeny. We apply our analysis to a set of genomes drawn from the Yeast Gene Order Browser.     

Stock Portfolio Structure of Individual Investors Infers Future Trading Behavior

Although the understanding of and motivation behind individual trading behavior is an important puzzle in finance, little is known about the connection between an investor''s portfolio structure and her trading behavior in practice. In this paper, we investigate the relation between what stocks investors hold, and what stocks they buy, and show that investors with similar portfolio structures to a great extent trade in a similar way. With data from the central register of shareholdings in Sweden, we model the market in a similarity network, by considering investors as nodes, connected with links representing portfolio similarity. From the network, we find investor groups that not only identify different investment strategies, but also represent individual investors trading in a similar way. These findings suggest that the stock portfolios of investors hold meaningful information, which could be used to earn a better understanding of stock market dynamics.     

THE NATURE OF THE FLESHY SHOOT OF ALLENROLFEA AND ALLIED GENERA

James , Lois E. (Whittier Coll., Whittier, Calif.), and Donald W. Kyhos . The nature of the fleshy shoot of Allenrolfea and allied genera. Amer. Jour. Bot. 48(2): 101–108. Illus. 1961.—A number of genera of the Chenopodiaceae are characterized by what have been called fleshy internodes which make them appear jointed. The fleshy tissue comprises on the average the outer ⅔ of what superficially appears to be the stem. This fleshy tissue contains a vascular network which is continuous with and similar to the vascular network in what has commonly been called the scalelike leaf. The problem is whether this fleshy vascularized tissue is the result of a downward prolongation of the base of the leaf or whether it is actually the true cortex of the stem. The present authors have found that Allenrolfea is uniquely suited to solving the problem of the so-called fleshy internodes of these allied genera. The origin and development of the fleshy tissue indicate it to be foliar. This conclusion is further substantiated by the shape of the fleshy tissue, its phyllotactic arrangement, the extent of the palisade tissue and underlying vascular network, the pattern of branching of the leaf traces, and the effect of secondary thickening and suberization.     

Complexities and uncertainties of neuronal network function

The nervous system generates behaviours through the activity in groups of neurons assembled into networks. Understanding these networks is thus essential to our understanding of nervous system function. Understanding a network requires information on its component cells, their interactions and their functional properties. Few networks come close to providing complete information on these aspects. However, even if complete information were available it would still only provide limited insight into network function. This is because the functional and structural properties of a network are not fixed but are plastic and can change over time. The number of interacting network components, their (variable) functional properties, and various plasticity mechanisms endows networks with considerable flexibility, but these features inevitably complicate network analyses. This review will initially discuss the general approaches and problems of network analyses. It will then examine the success of these analyses in a model spinal cord locomotor network in the lamprey, to determine to what extent in this relatively simple vertebrate system it is possible to claim detailed understanding of network function and plasticity.     

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms—Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)—that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.     

Stability from Structure: Metabolic Networks Are Unlike Other Biological Networks

In recent work, attempts have been made to link the structure of biochemical networks to their complex dynamics. It was shown that structurally stable network motifs are enriched in such networks. In this work, we investigate to what extent these findings apply to metabolic networks. To this end, we extend a previously proposed method by changing the null model for determining motif enrichment, by using interaction types directly obtained from structural interaction matrices, by generating a distribution of partial derivatives of reaction rates and by simulating enzymatic regulation on metabolic networks. Our findings suggest that the conclusions drawn in previous work cannot be extended to metabolic networks, that is, structurally stable network motifs are not enriched in metabolic networks.     

Global solidarity, migration and global health inequity

The grounds for global solidarity have been theorized and conceptualized in recent years, and many have argued that we need a global concept of solidarity. But the question remains: what can motivate efforts of the international community and nation-states? Our focus is the grounding of solidarity with respect to global inequities in health. We explore what considerations could motivate acts of global solidarity in the specific context of health migration, and sketch briefly what form this kind of solidarity could take. First, we argue that the only plausible conceptualization of persons highlights their interdependence. We draw upon a conception of persons as 'ecological subjects' and from there illustrate what such a conception implies with the example of nurses migrating from low and middle-income countries to more affluent ones. Next, we address potential critics who might counter any such understanding of current international politics with a reference to real-politik and the insights of realist international political theory. We argue that national governments--while not always or even often motivated by moral reasons alone--may nevertheless be motivated to acts of global solidarity by prudential arguments. Solidarity then need not be, as many argue, a function of charitable inclination, or emergent from an acknowledgment of injustice suffered, but may in fact serve national and transnational interests. We conclude on a positive note: global solidarity may be conceptualized to helpfully address global health inequity, to the extent that personal and transnational interdependence are enough to motivate national governments into action.     

Management of childhood urinary tract infection in family practice.

To find out to what extent doctors appreciate the potential damage that bacteriuria may cause, we sent questionnaires to 195 family practitioners and trainees in one health board in Northern Ireland. The results of the survey showed that, though doctors seemed to be aware of the risk of renal disease, this was not reflected in practice.