Showing papers in "Proceedings of the National Academy of Sciences of the United States of America in 2007"
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TL;DR: Patient stratification by GI microbiota provides further evidence that CD represents a spectrum of disease states and suggests that treatment of some forms of IBD may be facilitated by redress of the detected microbiological imbalances.
Abstract: The two primary human inflammatory bowel diseases, Crohn's disease (CD) and ulcerative colitis (UC), are idiopathic relapsing disorders characterized by chronic inflammation of the intestinal tract. Although several lines of reasoning suggest that gastrointestinal (GI) microbes influence inflammatory bowel disease (IBD) pathogenesis, the types of microbes involved have not been adequately described. Here we report the results of a culture-independent rRNA sequence analysis of GI tissue samples obtained from CD and UC patients, as well as non-IBD controls. Specimens were obtained through surgery from a variety of intestinal sites and included both pathologically normal and abnormal states. Our results provide comprehensive molecular-based analysis of the microbiota of the human small intestine. Comparison of clone libraries reveals statistically significant differences between the microbiotas of CD and UC patients and those of non-IBD controls. Significantly, our results indicate that a subset of CD and UC samples contained abnormal GI microbiotas, characterized by depletion of commensal bacteria, notably members of the phyla Firmicutes and Bacteroidetes. Patient stratification by GI microbiota provides further evidence that CD represents a spectrum of disease states and suggests that treatment of some forms of IBD may be facilitated by redress of the detected microbiological imbalances.
3,454 citations
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TL;DR: In this paper, it was shown that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network and the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined.
Abstract: Detecting community structure is fundamental for uncovering the links between structure and function in complex networks and for practical applications in many disciplines such as biology and sociology. A popular method now widely used relies on the optimization of a quantity called modularity, which is a quality index for a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. This finding is confirmed through several examples, both in artificial and in real social, biological, and technological networks, where we show that modularity optimization indeed does not resolve a large number of modules. A check of the modules obtained through modularity optimization is thus necessary, and we provide here key elements for the assessment of the reliability of this community detection method.
2,658 citations
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TL;DR: This paper found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, while the vast majority of disease genes are non-essential and show no tendency to encoding hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network.
Abstract: A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.
2,592 citations
Journal Article•
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TL;DR: It is found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, suggesting that disease genes also would play a central role in the human interactome, and that diseases caused by somatic mutations should not be peripheral.
Abstract: A network of disorders and disease genes linked by known disorder–gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.
2,517 citations
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TL;DR: The rates of protein association and dissociation are determined using surface plasmon resonance technology with nanoparticles that are thiol-linked to gold, and through size exclusion chromatography of protein–nanoparticle mixtures, and this method is developed into a systematic methodology to isolate nanoparticle-associated proteins.
Abstract: Due to their small size, nanoparticles have distinct properties compared with the bulk form of the same materials. These properties are rapidly revolutionizing many areas of medicine and technology. Despite the remarkable speed of development of nanoscience, relatively little is known about the interaction of nanoscale objects with living systems. In a biological fluid, proteins associate with nanoparticles, and the amount and presentation of the proteins on the surface of the particles leads to an in vivo response. Proteins compete for the nanoparticle "surface," leading to a protein "corona" that largely defines the biological identity of the particle. Thus, knowledge of rates, affinities, and stoichiometries of protein association with, and dissociation from, nanoparticles is important for understanding the nature of the particle surface seen by the functional machinery of cells. Here we develop approaches to study these parameters and apply them to plasma and simple model systems, albumin and fibrinogen. A series of copolymer nanoparticles are used with variation of size and composition (hydrophobicity). We show that isothermal titration calorimetry is suitable for studying the affinity and stoichiometry of protein binding to nanoparticles. We determine the rates of protein association and dissociation using surface plasmon resonance technology with nanoparticles that are thiol-linked to gold, and through size exclusion chromatography of protein-nanoparticle mixtures. This method is less perturbing than centrifugation, and is developed into a systematic methodology to isolate nanoparticle-associated proteins. The kinetic and equilibrium binding properties depend on protein identity as well as particle surface characteristics and size.
2,441 citations
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TL;DR: The interactions of these regions are characterized by applying graph theory to resting state functional connectivity MRI data, suggesting the presence of two distinct task-control networks that appear to operate on different time scales and affect downstream processing via dissociable mechanisms.
Abstract: Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms.
2,130 citations
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TL;DR: The articles in this special feature challenge the presumption that scholars can make simple, predictive models of social–ecological systems (SESs) and deduce universal solutions, panaceas, to problems of overuse or destruction of resources.
Abstract: The articles in this special feature challenge the presumption that scholars can make simple, predictive models of social–ecological systems (SESs) and deduce universal solutions, panaceas, to problems of overuse or destruction of resources. Moving beyond panaceas to develop cumulative capacities to diagnose the problems and potentialities of linked SESs requires serious study of complex, multivariable, nonlinear, cross-scale, and changing systems. Many variables have been identified by researchers as affecting the patterns of interactions and outcomes observed in empirical studies of SESs. A step toward developing a diagnostic method is taken by organizing these variables in a nested, multitier framework. The framework enables scholars to organize analyses of how attributes of (i) a resource system (e.g., fishery, lake, grazing area), (ii) the resource units generated by that system (e.g., fish, water, fodder), (iii) the users of that system, and (iv) the governance system jointly affect and are indirectly affected by interactions and resulting outcomes achieved at a particular time and place. The framework also enables us to organize how these attributes may affect and be affected by larger socioeconomic, political, and ecological settings in which they are embedded, as well as smaller ones. The framework is intended to be a step toward building a strong interdisciplinary science of complex, multilevel systems that will enable future diagnosticians to match governance arrangements to specific problems embedded in a social–ecological context.
2,130 citations
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TL;DR: GF animals are protected from diet-induced obesity by two complementary but independent mechanisms that result in increased fatty acid metabolism: elevated levels of Fiaf, which induces Pgc-1α; and increased AMPK activity.
Abstract: The trillions of microbes that colonize our adult intestines function collectively as a metabolic organ that communicates with, and complements, our own human metabolic apparatus. Given the worldwide epidemic in obesity, there is interest in how interactions between human and microbial metabolomes may affect our energy balance. Here we report that, in contrast to mice with a gut microbiota, germ-free (GF) animals are protected against the obesity that develops after consuming a Western-style, high-fat, sugar-rich diet. Their persistently lean phenotype is associated with increased skeletal muscle and liver levels of phosphorylated AMP-activated protein kinase (AMPK) and its downstream targets involved in fatty acid oxidation (acetylCoA carboxylase; carnitine-palmitoyltransferase). Moreover, GF knockout mice lacking fasting-induced adipose factor (Fiaf), a circulating lipoprotein lipase inhibitor whose expression is normally selectively suppressed in the gut epithelium by the microbiota, are not protected from diet-induced obesity. Although GF Fiaf−/− animals exhibit similar levels of phosphorylated AMPK as their wild-type littermates in liver and gastrocnemius muscle, they have reduced expression of genes encoding the peroxisomal proliferator-activated receptor coactivator (Pgc-1α) and enzymes involved in fatty acid oxidation. Thus, GF animals are protected from diet-induced obesity by two complementary but independent mechanisms that result in increased fatty acid metabolism: (i) elevated levels of Fiaf, which induces Pgc-1α; and (ii) increased AMPK activity. Together, these findings support the notion that the gut microbiota can influence both sides of the energy balance equation, and underscore the importance of considering our metabolome in a supraorganismal context.
2,043 citations
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TL;DR: Data demonstrate that cells within the CD44+ population of human HNSCC possess the unique properties of cancer stem cells in functional assays for cancer stem cell self-renewal and differentiation and form unique histological microdomains that may aid in cancer diagnosis.
Abstract: Like many epithelial tumors, head and neck squamous cell carcinoma (HNSCC) contains a heterogeneous population of cancer cells. We developed an immunodeficient mouse model to test the tumorigenic potential of different populations of cancer cells derived from primary, unmanipulated human HNSCC samples. We show that a minority population of CD44(+) cancer cells, which typically comprise <10% of the cells in a HNSCC tumor, but not the CD44(-) cancer cells, gave rise to new tumors in vivo. Immunohistochemistry revealed that the CD44(+) cancer cells have a primitive cellular morphology and costain with the basal cell marker Cytokeratin 5/14, whereas the CD44(-) cancer cells resemble differentiated squamous epithelium and express the differentiation marker Involucrin. The tumors that arose from purified CD44(+) cells reproduced the original tumor heterogeneity and could be serially passaged, thus demonstrating the two defining properties of stem cells: ability to self-renew and to differentiate. Furthermore, the tumorigenic CD44(+) cells differentially express the BMI1 gene, at both the RNA and protein levels. By immunohistochemical analysis, the CD44(+) cells in the tumor express high levels of nuclear BMI1, and are arrayed in characteristic tumor microdomains. BMI1 has been demonstrated to play a role in self-renewal in other stem cell types and to be involved in tumorigenesis. Taken together, these data demonstrate that cells within the CD44(+) population of human HNSCC possess the unique properties of cancer stem cells in functional assays for cancer stem cell self-renewal and differentiation and form unique histological microdomains that may aid in cancer diagnosis.
2,019 citations
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TL;DR: The results validate the stem cell working model in human CRC and provide a highly robust surface marker profile for CRC stem cell isolation.
Abstract: Recent observations indicate that, in several types of human cancer, only a phenotypic subset of cancer cells within each tumor is capable of initiating tumor growth. This functional subset of cancer cells is operationally defined as the “cancer stem cell” (CSC) subset. Here we developed a CSC model for the study of human colorectal cancer (CRC). Solid CRC tissues, either primary tissues collected from surgical specimens or xenografts established in nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice, were disaggregated into single-cell suspensions and analyzed by flow cytometry. Surface markers that displayed intratumor heterogeneous expression among epithelial cancer cells were selected for cell sorting and tumorigenicity experiments. Individual phenotypic cancer cell subsets were purified, and their tumor-initiating properties were investigated by injection in NOD/SCID mice. Our observations indicate that, in six of six human CRC tested, the ability to engraft in vivo in immunodeficient mice was restricted to a minority subpopulation of epithelial cell adhesion molecule (EpCAM)high/CD44+ epithelial cells. Tumors originated from EpCAMhigh/CD44+ cells maintained a differentiated phenotype and reproduced the full morphologic and phenotypic heterogeneity of their parental lesions. Analysis of the surface molecule repertoire of EpCAMhigh/CD44+ cells led to the identification of CD166 as an additional differentially expressed marker, useful for CSC isolation in three of three CRC tested. These results validate the stem cell working model in human CRC and provide a highly robust surface marker profile for CRC stem cell isolation.
2,007 citations
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TL;DR: Transformed cells exhibit a high rate of glutamine consumption that cannot be explained by the nitrogen demand imposed by nucleotide synthesis or maintenance of nonessential amino acid pools, and glutamine metabolism provides a carbon source that facilitates the cell's ability to use glucose-derived carbon and TCA cycle intermediates as biosynthetic precursors.
Abstract: Tumor cell proliferation requires rapid synthesis of macromolecules including lipids, proteins, and nucleotides. Many tumor cells exhibit rapid glucose consumption, with most of the glucose-derived carbon being secreted as lactate despite abundant oxygen availability (the Warburg effect). Here, we used 13C NMR spectroscopy to examine the metabolism of glioblastoma cells exhibiting aerobic glycolysis. In these cells, the tricarboxylic acid (TCA) cycle was active but was characterized by an efflux of substrates for use in biosynthetic pathways, particularly fatty acid synthesis. The success of this synthetic activity depends on activation of pathways to generate reductive power (NADPH) and to restore oxaloacetate for continued TCA cycle function (anaplerosis). Surprisingly, both these needs were met by a high rate of glutamine metabolism. First, conversion of glutamine to lactate (glutaminolysis) was rapid enough to produce sufficient NADPH to support fatty acid synthesis. Second, despite substantial mitochondrial pyruvate metabolism, pyruvate carboxylation was suppressed, and anaplerotic oxaloacetate was derived from glutamine. Glutamine catabolism was accompanied by secretion of alanine and ammonia, such that most of the amino groups from glutamine were lost from the cell rather than incorporated into other molecules. These data demonstrate that transformed cells exhibit a high rate of glutamine consumption that cannot be explained by the nitrogen demand imposed by nucleotide synthesis or maintenance of nonessential amino acid pools. Rather, glutamine metabolism provides a carbon source that facilitates the cell's ability to use glucose-derived carbon and TCA cycle intermediates as biosynthetic precursors.
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TL;DR: Empirical evidence is presented indicating that the processes relating urbanization to economic development and knowledge creation are very general, being shared by all cities belonging to the same urban system and sustained across different nations and times.
Abstract: ‡§ ¶ Humanity has just crossed a major landmark in its history with the majority of people now living in cities. Cities have long been known to be society’s predominant engine of innovation and wealth creation, yet they are also its main source of crime, pollution, and disease. The inexorable trend toward urbanization worldwide presents an urgent challenge for developing a predictive, quantitative theory of urban organization and sustainable development. Here we present empirical evidence indicating that the processes relating urbanization to economic development and knowledge creation are very general, being shared by all cities belonging to the same urban system and sustained across different nations and times. Many diverse properties of cities from patent production and personal income to electrical cable length are shown to be power law functions of population size with scaling exponents, , that fall into distinct universality classes. Quantities reflecting wealth creation and innovation have 1.2 >1 (increasing returns), whereas those accounting for infrastructure display 0.8 <1 (economies of scale). We predict that the pace of social life in the city increases with population size, in quantitative agreement with data, and we discuss how cities are similar to, and differ from, biological organisms, for which <1. Finally, we explore possible consequences of these scaling relations by deriving growth equations, which quantify the dramatic difference between growth fueled by innovation versus that driven by economies of scale. This difference suggests that, as population grows, major innovation cycles must be generated at a continually accelerating rate to sustain growth and avoid stagnation or collapse. population sustainability urban studies increasing returns economics of scale
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TL;DR: The growth rate of atmospheric carbon dioxide (CO2), the largest human contributor to human-induced climate change, is increasing rapidly and three processes contribute to this rapid increase: emissions, global economic activity, carbon intensity of the global economy, and the increase in airborne fraction of CO2 emissions.
Abstract: The growth rate of atmospheric carbon dioxide (CO2), the largest human contributor to human-induced climate change, is increasing rapidly. Three processes contribute to this rapid increase. Two of these processes concern emissions. Recent growth of the world economy combined with an increase in its carbon intensity have led to rapid growth in fossil fuel CO2 emissions since 2000: comparing the 1990s with 2000 –2006, the emissions growth rate increased from 1.3% to 3.3% y 1 . The third process is indicated by increasing evidence (P 0.89) for a long-term (50-year) increase in the airborne fraction (AF) of CO2 emissions, implying a decline in the efficiency of CO2 sinks on land and oceans in absorbing anthropogenic emissions. Since 2000, the contributions of these three factors to the increase in the atmospheric CO2 growth rate have been65 16% from increasing global economic activity, 17 6% from the increasing carbon intensity of the global economy, and 18 15% from the increase in AF. An increasing AF is consistent with results of climate– carbon cycle models, but the magnitude of the observed signal appears larger than that estimated by models. All of these changes characterize a carbon cycle that is generating stronger-than-expected and sooner-than-expected climate forcing. airborne fraction anthropogenic carbon emissions carbon‐climate feedback terrestrial and ocean carbon emissions vulnerabilities of the carbon cycle
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TL;DR: It is found that, when it comes to information diffusion, weak and strong ties are both simultaneously ineffective, and this coupling significantly slows the diffusion process, resulting in dynamic trapping of information in communities.
Abstract: ncovering the structure and function of communication networks has always been constrained by the practical difficulty of mapping out interactions among a large number of individuals. Indeed, most of our current understanding of com- munication and social networks is based on questionnaire data, reaching typically a few dozen individuals and relying on the individual's opinion to reveal the nature and the strength of the ties. The fact that currently an increasing fraction of human interactions are recorded, from e-mail (1-3) to phone records (4), offers unprecedented opportunities to uncover and explore the large scale characteristics of communication and social networks (5). Here we take a first step in this direction by exploiting the widespread use of mobile phones to construct a map of a society-wide communication network, capturing the mobile interaction patterns of millions of individuals. The data set allows us to explore the relationship between the topology of the network and the tie strengths between individuals, informa- tion that was inaccessible at the societal level before. We demonstrate a local coupling between tie strengths and network topology, and show that this coupling has important conse- quences for the network's global stability if ties are removed, as well as for the spread of news and ideas within the network. A significant portion of a country's communication network wasreconstructedfrom18weeksofallmobilephonecallrecords among 20% of the country's entire population, 90% of whose
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TL;DR: The data indicate that AMPK phosphorylation of PGC-1α initiates many of the important gene regulatory functions of AMPK in skeletal muscle.
Abstract: Activation of AMP-activated kinase (AMPK) in skeletal muscle increases glucose uptake, fatty acid oxidation, and mitochondrial biogenesis by increasing gene expression in these pathways. However, the transcriptional components that are directly targeted by AMPK are still elusive. The peroxisome-proliferator-activated receptor γ coactivator 1α (PGC-1α) has emerged as a master regulator of mitochondrial biogenesis; furthermore, it has been shown that PGC-1α gene expression is induced by exercise and by chemical activation of AMPK in skeletal muscle. Using primary muscle cells and mice deficient in PGC-1α, we found that the effects of AMPK on gene expression of glucose transporter 4, mitochondrial genes, and PGC-1α itself are almost entirely dependent on the function of PGC-1α protein. Furthermore, AMPK phosphorylates PGC-1α directly both in vitro and in cells. These direct phosphorylations of the PGC-1α protein at threonine-177 and serine-538 are required for the PGC-1α-dependent induction of the PGC-1α promoter. These data indicate that AMPK phosphorylation of PGC-1α initiates many of the important gene regulatory functions of AMPK in skeletal muscle.
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TL;DR: It is shown that chronic exposure of fathead minnow (Pimephales promelas) to low concentrations of the potent 17α-ethynylestradiol led to feminization of males through the production of vitellogenin mRNA and protein, impacts on gonadal development as evidenced by intersex in males and altered oogenesis in females, and, ultimately, a near extinction of this species from the lake.
Abstract: Municipal wastewaters are a complex mixture containing estrogens and estrogen mimics that are known to affect the reproductive health of wild fishes. Male fishes downstream of some wastewater outfalls produce vitellogenin (VTG) (a protein normally synthesized by females during oocyte maturation) and early-stage eggs in their testes, and this feminization has been attributed to the presence of estrogenic substances such as natural estrogens [estrone or 17β-estradiol (E2)], the synthetic estrogen used in birth-control pills [17α-ethynylestradiol (EE2)], or weaker estrogen mimics such as nonylphenol in the water. Despite widespread evidence that male fishes are being feminized, it is not known whether these low-level, chronic exposures adversely impact the sustainability of wild populations. We conducted a 7-year, whole-lake experiment at the Experimental Lakes Area (ELA) in northwestern Ontario, Canada, and showed that chronic exposure of fathead minnow (Pimephales promelas) to low concentrations (5–6 ng·L−1) of the potent 17α-ethynylestradiol led to feminization of males through the production of vitellogenin mRNA and protein, impacts on gonadal development as evidenced by intersex in males and altered oogenesis in females, and, ultimately, a near extinction of this species from the lake. Our observations demonstrate that the concentrations of estrogens and their mimics observed in freshwaters can impact the sustainability of wild fish populations.
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TL;DR: This study uses microarray technology to identify miRNAs induced in primary murine macrophages after exposure to polyriboinosinic:polyribocytidylic acid or the cytokine IFN-β and characterize miR-155 as a common target of a broad range of inflammatory mediators.
Abstract: The mammalian inflammatory response to infection involves the induction of several hundred genes, a process that must be carefully regulated to achieve pathogen clearance and prevent the consequences of unregulated expression, such as cancer. Recently, microRNAs (miRNAs) have emerged as a class of gene expression regulators that has also been linked to cancer. However, the relationship between inflammation, innate immunity, and miRNA expression is just beginning to be explored. In the present study, we use microarray technology to identify miRNAs induced in primary murine macrophages after exposure to polyriboinosinic:polyribocytidylic acid or the cytokine IFN-β. miR-155 was the only miRNA of those tested that was substantially up-regulated by both stimuli. It also was induced by several Toll-like receptor ligands through myeloid differentiation factor 88- or TRIF-dependent pathways, whereas up-regulation by IFNs was shown to involve TNF-α autocrine signaling. Pharmacological inhibition of the kinase JNK blocked induction of miR-155 in response to either polyriboinosinic:polyribocytidylic acid or TNF-α, suggesting that miR-155-inducing signals use the JNK pathway. Together, these findings characterize miR-155 as a common target of a broad range of inflammatory mediators. Importantly, because miR-155 is known to function as an oncogene, these observations identify a potential link between inflammation and cancer.
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TL;DR: The efficiency, ease-of-use, and versatility obtained here with the φC31-based integration system represents an important advance in transgenesis and opens up the possibility of systematic, high-throughput screening of large cDNA sets and regulatory elements.
Abstract: Germ-line transformation via transposable elements is a powerful tool to study gene function in Drosophila melanogaster. However, some inherent characteristics of transposon-mediated transgenesis limit its use for transgene analysis. Here, we circumvent these limitations by optimizing a phiC31-based integration system. We generated a collection of lines with precisely mapped attP sites that allow the insertion of transgenes into many different predetermined intergenic locations throughout the fly genome. By using regulatory elements of the nanos and vasa genes, we established endogenous sources of the phiC31 integrase, eliminating the difficulties of coinjecting integrase mRNA and raising the transformation efficiency. Moreover, to discriminate between specific and rare nonspecific integration events, a white gene-based reconstitution system was generated that enables visual selection for precise attP targeting. Finally, we demonstrate that our chromosomal attP sites can be modified in situ, extending their scope while retaining their properties as landing sites. The efficiency, ease-of-use, and versatility obtained here with the phiC31-based integration system represents an important advance in transgenesis and opens up the possibility of systematic, high-throughput screening of large cDNA sets and regulatory elements.
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TL;DR: It is argued that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains,such as sustainable development.
Abstract: The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.
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TL;DR: This work has identified six widely distributed resting state networks and supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.
Abstract: Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1–80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.
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TL;DR: Global emissions growth since 2000 was driven by a cessation or reversal of earlier declining trends in the energy intensity of gross domestic product (GDP) and the carbon intensity of energy (emissions/energy), coupled with continuing increases in population and per-capita GDP.
Abstract: CO2 emissions from fossil-fuel burning and industrial processes have been accelerating at a global scale, with their growth rate increasing from 1.1% y(-1) for 1990-1999 to >3% y(-1) for 2000-2004. The emissions growth rate since 2000 was greater than for the most fossil-fuel intensive of the Intergovernmental Panel on Climate Change emissions scenarios developed in the late 1990s. Global emissions growth since 2000 was driven by a cessation or reversal of earlier declining trends in the energy intensity of gross domestic product (GDP) (energy/GDP) and the carbon intensity of energy (emissions/energy), coupled with continuing increases in population and per-capita GDP. Nearly constant or slightly increasing trends in the carbon intensity of energy have been recently observed in both developed and developing regions. No region is decarbonizing its energy supply. The growth rate in emissions is strongest in rapidly developing economies, particularly China. Together, the developing and least-developed economies (forming 80% of the world's population) accounted for 73% of global emissions growth in 2004 but only 41% of global emissions and only 23% of global cumulative emissions since the mid-18th century. The results have implications for global equity.
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TL;DR: It is found that of the four main elements of food security, i.e., availability, stability, utilization, and access, only the first is routinely addressed in simulation studies, indicating the potential for further negative impacts beyond those currently assessed with models.
Abstract: This article reviews the potential impacts of climate change on food security. It is found that of the four main elements of food security, i.e., availability, stability, utilization, and access, only the first is routinely addressed in simulation studies. To this end, published results indicate that the impacts of climate change are significant, however, with a wide projected range (between 5 million and 170 million additional people at risk of hunger by 2080) strongly depending on assumed socio-economic development. The likely impacts of climate change on the other important dimensions of food security are discussed qualitatively, indicating the potential for further negative impacts beyond those currently assessed with models. Finally, strengths and weaknesses of current assessment studies are discussed, suggesting improvements and proposing avenues for new analyses.
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TL;DR: Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, this work finds structure–function relations at multiple temporal scales.
Abstract: Neuronal dynamics unfolding within the cerebral cortex exhibit complex spatial and temporal patterns even in the absence of external input. Here we use a computational approach in an attempt to relate these features of spontaneous cortical dynamics to the underlying anatomical connectivity. Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, we find structure-function relations at multiple temporal scales. Functional networks recovered from long windows of neural activity (minutes) largely overlap with the underlying structural network. As a result, hubs in these long-run functional networks correspond to structural hubs. In contrast, significant fluctuations in functional topology are observed across the sequence of networks recovered from consecutive shorter (seconds) time windows. The functional centrality of individual nodes varies across time as interregional couplings shift. Furthermore, the transient couplings between brain regions are coordinated in a manner that reveals the existence of two anticorrelated clusters. These clusters are linked by prefrontal and parietal regions that are hub nodes in the underlying structural network. At an even faster time scale (hundreds of milliseconds) we detect individual episodes of interregional phase-locking and find that slow variations in the statistics of these transient episodes, contingent on the underlying anatomical structure, produce the transfer entropy functional connectivity and simulated blood oxygenation level-dependent correlation patterns observed on slower time scales.
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TL;DR: The enforced expression of miR-29s in lung cancer cell lines restores normal patterns of DNA methylation, induces reexpression of methylation-silenced tumor suppressor genes, and inhibits tumorigenicity in vitro and in vivo.
Abstract: MicroRNAs (miRNAs) are small, noncoding RNAs that regulate expression of many genes. Recent studies suggest roles of miRNAs in carcinogenesis. We and others have shown that expression profiles of miRNAs are different in lung cancer vs. normal lung, although the significance of this aberrant expression is poorly understood. Among the reported down-regulated miRNAs in lung cancer, the miRNA (miR)-29 family (29a, 29b, and 29c) has intriguing complementarities to the 3′-UTRs of DNA methyltransferase (DNMT)3A and -3B (de novo methyltransferases), two key enzymes involved in DNA methylation, that are frequently up-regulated in lung cancer and associated with poor prognosis. We investigated whether miR-29s could target DNMT3A and -B and whether restoration of miR-29s could normalize aberrant patterns of methylation in non-small-cell lung cancer. Here we show that expression of miR-29s is inversely correlated to DNMT3A and -3B in lung cancer tissues, and that miR-29s directly target both DNMT3A and -3B. The enforced expression of miR-29s in lung cancer cell lines restores normal patterns of DNA methylation, induces reexpression of methylation-silenced tumor suppressor genes, such as FHIT and WWOX, and inhibits tumorigenicity in vitro and in vivo. These findings support a role of miR-29s in epigenetic normalization of NSCLC, providing a rationale for the development of miRNA-based strategies for the treatment of lung cancer.
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TL;DR: Analysis of tumor samples from multiple independent patient cohorts and array-based comparative genomic hybridization suggest that MET amplification occurs independently of EGFRT790M mutations and that MET may be a clinically relevant therapeutic target for some patients with acquired resistance to gefitinib or erlotinib.
Abstract: In human lung adenocarcinomas harboring EGFR mutations, a second-site point mutation that substitutes methionine for threonine at position 790 (T790M) is associated with approximately half of cases of acquired resistance to the EGFR kinase inhibitors, gefitinib and erlotinib. To identify other potential mechanisms that contribute to disease progression, we used array-based comparative genomic hybridization (aCGH) to compare genomic profiles of EGFR mutant tumors from untreated patients with those from patients with acquired resistance. Among three loci demonstrating recurrent copy number alterations (CNAs) specific to the acquired resistance set, one contained the MET proto-oncogene. Collectively, analysis of tumor samples from multiple independent patient cohorts revealed that MET was amplified in tumors from 9 of 43 (21%) patients with acquired resistance but in only two tumors from 62 untreated patients (3%) (P = 0.007, Fisher's Exact test). Among 10 resistant tumors from the nine patients with MET amplification, 4 also harbored the EGFRT790M mutation. We also found that an existing EGFR mutant lung adenocarcinoma cell line, NCI-H820, harbors MET amplification in addition to a drug-sensitive EGFR mutation and the T790M change. Growth inhibition studies demonstrate that these cells are resistant to both erlotinib and an irreversible EGFR inhibitor (CL-387,785) but sensitive to a multikinase inhibitor (XL880) with potent activity against MET. Taken together, these data suggest that MET amplification occurs independently of EGFRT790M mutations and that MET may be a clinically relevant therapeutic target for some patients with acquired resistance to gefitinib or erlotinib.
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TL;DR: The six articles of the special feature are introduced and situated within these components of study of land change: observation and monitoring; understanding the coupled system—causes, impacts, and consequences; modeling; and synthesis issues.
Abstract: Land change science has emerged as a fundamental component of global environmental change and sustainability research. This interdisciplinary field seeks to understand the dynamics of land cover and land use as a coupled human-environment system to address theory, concepts, models, and applications relevant to environmental and societal problems, including the intersection of the two. The major components and advances in land change are addressed: observation and monitoring; understanding the coupled system-causes, impacts, and consequences; modeling; and synthesis issues. The six articles of the special feature are introduced and situated within these components of study.
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TL;DR: A Cu-free variant of click chemistry that can label biomolecules rapidly and selectively in living systems, overcoming the intrinsic toxicity of the canonical Cu-catalyzed reaction is reported.
Abstract: Dynamic imaging of proteins in live cells is routinely performed by using genetically encoded reporters, an approach that cannot be extended to other classes of biomolecules such as glycans and lipids. Here, we report a Cu-free variant of click chemistry that can label these biomolecules rapidly and selectively in living systems, overcoming the intrinsic toxicity of the canonical Cu-catalyzed reaction. The critical reagent, a substituted cyclooctyne, possesses ring strain and electron-withdrawing fluorine substituents that together promote the [3 + 2] dipolar cycloaddition with azides installed metabolically into biomolecules. This Cu-free click reaction possesses comparable kinetics to the Cu-catalyzed reaction and proceeds within minutes on live cells with no apparent toxicity. With this technique, we studied the dynamics of glycan trafficking and identified a population of sialoglycoconjugates with unexpectedly rapid internalization kinetics.
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TL;DR: A facile approach for designing families of GPCRs with engineered ligand specificities will prove to be powerful tools for selectively modulating signal-transduction pathways in vitro and in vivo.
Abstract: We evolved muscarinic receptors in yeast to generate a family of G protein-coupled receptors (GPCRs) that are activated solely by a pharmacologically inert drug-like and bioavailable compound (clozapine-N-oxide) Subsequent screening in human cell lines facilitated the creation of a family of muscarinic acetylcholine GPCRs suitable for in vitro and in situ studies We subsequently created lines of telomerase-immortalized human pulmonary artery smooth muscle cells stably expressing all five family members and found that each one faithfully recapitulated the signaling phenotype of the parent receptor We also expressed a Gi-coupled designer receptor in hippocampal neurons (hM4D) and demonstrated its ability to induce membrane hyperpolarization and neuronal silencing We have thus devised a facile approach for designing families of GPCRs with engineered ligand specificities Such reverse-engineered GPCRs will prove to be powerful tools for selectively modulating signal-transduction pathways in vitro and in vivo
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TL;DR: Maturation to progress in a similar manner regionally in both children with and without ADHD, with primary sensory areas attaining peak cortical thickness before polymodal, high-order association areas, and there was a marked delay in ADHD in attainingpeak thickness throughout most of the cerebrum.
Abstract: There is controversy over the nature of the disturbance in brain development that underpins attention-deficit/hyperactivity disorder (ADHD). In particular, it is unclear whether the disorder results from a delay in brain maturation or whether it represents a complete deviation from the template of typical development. Using computational neuroanatomic techniques, we estimated cortical thickness at >40,000 cerebral points from 824 magnetic resonance scans acquired prospectively on 223 children with ADHD and 223 typically developing controls. With this sample size, we could define the growth trajectory of each cortical point, delineating a phase of childhood increase followed by adolescent decrease in cortical thickness (a quadratic growth model). From these trajectories, the age of attaining peak cortical thickness was derived and used as an index of cortical maturation. We found maturation to progress in a similar manner regionally in both children with and without ADHD, with primary sensory areas attaining peak cortical thickness before polymodal, high-order association areas. However, there was a marked delay in ADHD in attaining peak thickness throughout most of the cerebrum: the median age by which 50% of the cortical points attained peak thickness for this group was 10.5 years (SE 0.01), which was significantly later than the median age of 7.5 years (SE 0.02) for typically developing controls (log rank test χ(1)2 = 5,609, P < 1.0 × 10−20). The delay was most prominent in prefrontal regions important for control of cognitive processes including attention and motor planning. Neuroanatomic documentation of a delay in regional cortical maturation in ADHD has not been previously reported.
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TL;DR: The ability to differentially order particles of different sizes, continuously, at high rates, and without external forces in microchannels is expected to have a broad range of applications in continuous bioparticle separation, high-throughput cytometry, and large-scale filtration systems.
Abstract: Under laminar flow conditions, when no external forces are applied, particles are generally thought to follow fluid streamlines. Contrary to this perspective, we observe that flowing particles migrate across streamlines in a continuous, predictable, and accurate manner in microchannels experiencing laminar flows. The migration is attributed to lift forces on particles that are observed when inertial aspects of the flow become significant. We identified symmetric and asymmetric channel geometries that provide additional inertial forces that bias particular equilibrium positions to create continuous streams of ordered particles precisely positioned in three spatial dimensions. We were able to order particles laterally, within the transverse plane of the channel, with >80-nm accuracy, and longitudinally, in regular chains along the direction of flow. A fourth dimension of rotational alignment was observed for discoidal red blood cells. Unexpectedly, ordering appears to be independent of particle buoyant direction, suggesting only minor centrifugal contributions. Theoretical analysis indicates the physical principles are operational over a range of channel and particle length scales. The ability to differentially order particles of different sizes, continuously, at high rates, and without external forces in microchannels is expected to have a broad range of applications in continuous bioparticle separation, high-throughput cytometry, and large-scale filtration systems.