933 research outputs found

    Understanding drivers of aquatic ecosystem metabolism in freshwater subtropical ridge and slough wetlands

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    How climate and habitat drive variation in aquatic metabolism in wetlands remains uncertain. To quantify differences in seasonal aquatic metabolism among wetlands, we estimated aquatic ecosystem metabolism (gross primary productivity, GPP; ecosystem respiration, ER; net aquatic productivity, NAP) in subtropical ridge and slough wetlands of the Florida Everglades from more than 2 yr of continuously measured water column dissolved oxygen, photosynthetically active radiation (PAR), water temperature, and water depth. Gross primary productivity and ER were modeled from light, temperature, and water depth using non-linear minimization and maximum likelihood. Reaeration rates were estimated from wind speed. Dissolved oxygen was below saturation at all sites during both wet and dry seasons. Water depth interacted with vegetation to influence PAR, water temperature, and spatiotemporal patterns in aquatic metabolism. Gross primary productivity and ER were highest at the slough with lowest submerged aquatic vegetation (low-SAV slough), intermediate in the sawgrass (Cladium jamaicense) ridge site, and lowest at the slough with highest submerged aquatic vegetation (high-SAV slough). Ecosystem respiration was strongly positively correlated with GPP at the sawgrass ridge and low-SAV slough sites. Gross primary productivity increased with water temperature and PAR across all habitat types, whereas ER decreased (more respiration) with water temperature and PAR. Net aquatic productivity was negatively correlated with water temperature and positively correlated with PAR, suggesting that ER was more sensitive than GPP to water temperature. Aquatic metabolism was largely net heterotrophic in all wetlands, and high-SAV appeared to buffer seasonal variation in PAR and water temperatures that drive NAP in subtropical wetlands. Our results suggest that aquatic ecosystem metabolism in wetlands with seasonal hydrology is sensitive to changes in water depth and vegetation density that influence temperature and light. Expanding our understanding of how metabolic processes and carbon cycling in wetland ecosystems vary across gradients in hydrology, vegetation, and organic matter could enhance our understanding and protection of conditions that maximize carbon storage

    Structural basis for mechanotransduction in a potassium-dependent mechanosensitive ion channel

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    Mechanosensitive channels of small conductance, found in many living organisms, open under elevated membrane tension and thus play crucial roles in biological response to mechanical stress. Amongst these channels, MscK is unique in that its activation also requires external potassium ions. To better understand this dual gating mechanism by force and ligand, we elucidate distinct structures of MscK along the gating cycle using cryo-electron microscopy. The heptameric channel comprises three layers: a cytoplasmic domain, a periplasmic gating ring, and a markedly curved transmembrane domain that flattens and expands upon channel opening, which is accompanied by dilation of the periplasmic ring. Furthermore, our results support a potentially unifying mechanotransduction mechanism in ion channels depicted as flattening and expansion of the transmembrane domain

    Don't bleach chaotic data

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    A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.Comment: 12 dense pages (82K) of ordinary LaTeX; uses macro psfig.tex for inclusion of figures in text; figures are uufile'd into a single file of size 306K; the final dvips'd postscript file is about 1.3mb Replaced 9/30/93 to incorporate final changes in the proofs and to make the LaTeX more portable; the paper will appear in CHAOS 4 (Dec, 1993

    A biophysical model of prokaryotic diversity in geothermal hot springs

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    Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms

    Lifespan extension and the doctrine of double effect

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    Recent developments in biogerontology—the study of the biology of ageing—suggest that it may eventually be possible to intervene in the human ageing process. This, in turn, offers the prospect of significantly postponing the onset of age-related diseases. The biogerontological project, however, has met with strong resistance, especially by deontologists. They consider the act of intervening in the ageing process impermissible on the grounds that it would (most probably) bring about an extended maximum lifespan—a state of affairs that they deem intrinsically bad. In a bid to convince their deontological opponents of the permissibility of this act, proponents of biogerontology invoke an argument which is grounded in the doctrine of double effect. Surprisingly, their argument, which we refer to as the ‘double effect argument’, has gone unnoticed. This article exposes and critically evaluates this ‘double effect argument’. To this end, we first review a series of excerpts from the ethical debate on biogerontology in order to substantiate the presence of double effect reasoning. Next, we attempt to determine the role that the ‘double effect argument’ is meant to fulfil within this debate. Finally, we assess whether the act of intervening in ageing actually can be justified using double effect reasoning

    Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context

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    Epigenetic control of gene transcription is critical for normal human development and cellular differentiation. While alterations of epigenetic marks such as DNA methylation have been linked to cancers and many other human diseases, interindividual epigenetic variations in normal tissues due to aging, environmental factors, or innate susceptibility are poorly characterized. The plasticity, tissue-specific nature, and variability of gene expression are related to epigenomic states that vary across individuals. Thus, population-based investigations are needed to further our understanding of the fundamental dynamics of normal individual epigenomes. We analyzed 217 non-pathologic human tissues from 10 anatomic sites at 1,413 autosomal CpG loci associated with 773 genes to investigate tissue-specific differences in DNA methylation and to discern how aging and exposures contribute to normal variation in methylation. Methylation profile classes derived from unsupervised modeling were significantly associated with age (P<0.0001) and were significant predictors of tissue origin (P<0.0001). In solid tissues (n = 119) we found striking, highly significant CpG island–dependent correlations between age and methylation; loci in CpG islands gained methylation with age, loci not in CpG islands lost methylation with age (P<0.001), and this pattern was consistent across tissues and in an analysis of blood-derived DNA. Our data clearly demonstrate age- and exposure-related differences in tissue-specific methylation and significant age-associated methylation patterns which are CpG island context-dependent. This work provides novel insight into the role of aging and the environment in susceptibility to diseases such as cancer and critically informs the field of epigenomics by providing evidence of epigenetic dysregulation by age-related methylation alterations. Collectively we reveal key issues to consider both in the construction of reference and disease-related epigenomes and in the interpretation of potentially pathologically important alterations

    Variance in Centrality within Rock Hyrax Social Networks Predicts Adult Longevity

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    BACKGROUND: In communal mammals the levels of social interaction among group members vary considerably. In recent years, biologists have realized that within-group interactions may affect survival of the group members. Several recent studies have demonstrated that the social integration of adult females is positively associated with infant survival, and female longevity is affected by the strength and stability of the individual social bonds. Our aim was to determine the social factors that influence adult longevity in social mammals. METHODOLOGY/PRINCIPAL FINDINGS: As a model system, we studied the social rock hyrax (Procavia capensis), a plural breeder with low reproductive skew, whose groups are mainly composed of females. We applied network theory using 11 years of behavioral data to quantify the centrality of individuals within groups, and found adult longevity to be inversely correlated to the variance in centrality. In other words, animals in groups with more equal associations lived longer. Individual centrality was not correlated with longevity, implying that social tension may affect all group members and not only the weakest or less connected ones. CONCLUSIONS/SIGNIFICANCE: Our novel findings support previous studies emphasizing the adaptive value of social associations and the consequences of inequality among adults within social groups. However, contrary to previous studies, we suggest that it is not the number or strength of associations that an adult individual has (i.e. centrality) that is important, but the overall configuration of social relationships within the group (i.e. centrality SD) that is a key factor in influencing longevity

    Anti-cancer effects and mechanism of actions of aspirin analogues in the treatment of glioma cancer

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    INTRODUCTION: In the past 25 years only modest advancements in glioma treatment have been made, with patient prognosis and median survival time following diagnosis only increasing from 3 to 7 months. A substantial body of clinical and preclinical evidence has suggested a role for aspirin in the treatment of cancer with multiple mechanisms of action proposed including COX 2 inhibition, down regulation of EGFR expression, and NF-κB signaling affecting Bcl-2 expression. However, with serious side effects such as stroke and gastrointestinal bleeding, aspirin analogues with improved potency and side effect profiles are being developed. METHOD: Effects on cell viability following 24 hr incubation of four aspirin derivatives (PN508, 517, 526 and 529) were compared to cisplatin, aspirin and di-aspirin in four glioma cell lines (U87 MG, SVG P12, GOS – 3, and 1321N1), using the PrestoBlue assay, establishing IC50 and examining the time course of drug effects. RESULTS: All compounds were found to decrease cell viability in a concentration and time dependant manner. Significantly, the analogue PN517 (IC50 2mM) showed approximately a twofold increase in potency when compared to aspirin (3.7mM) and cisplatin (4.3mM) in U87 cells, with similar increased potency in SVG P12 cells. Other analogues demonstrated similar potency to aspirin and cisplatin. CONCLUSION: These results support the further development and characterization of novel NSAID derivatives for the treatment of glioma

    N-body simulations of gravitational dynamics

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    We describe the astrophysical and numerical basis of N-body simulations, both of collisional stellar systems (dense star clusters and galactic centres) and collisionless stellar dynamics (galaxies and large-scale structure). We explain and discuss the state-of-the-art algorithms used for these quite different regimes, attempt to give a fair critique, and point out possible directions of future improvement and development. We briefly touch upon the history of N-body simulations and their most important results.Comment: invited review (28 pages), to appear in European Physics Journal Plu
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