How citation boosts promote scientific paradigm shifts and Nobel Prizes

Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the "boosting effect" of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying "boost factor" is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain, how social influence comes about and why the value of goods depends so strongly on the attention they attract.Comment: 6 pages, 6 figure

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Structure and Molecular Evolution of CDGSH Iron-Sulfur Domains

The recently discovered CDGSH iron-sulfur domains (CISDs) are classified into seven major types with a wide distribution throughout the three domains of life. The type 1 protein mitoNEET has been shown to fold into a dimer with the signature CDGSH motif binding to a [2Fe-2S] cluster. However, the structures of all other types of CISDs were unknown. Here we report the crystal structures of type 3, 4, and 6 CISDs determined at 1.5 Å, 1.8 Å and 1.15 Å resolution, respectively. The type 3 and 4 CISD each contain one CDGSH motif and adopt a dimeric structure. Although similar to each other, the two structures have permutated topologies, and both are distinct from the type 1 structure. The type 6 CISD contains tandem CDGSH motifs and adopts a monomeric structure with an internal pseudo dyad symmetry. All currently known CISD structures share dual iron-sulfur binding modules and a β-sandwich for either intermolecular or intramolecular dimerization. The iron-sulfur binding module, the β-strand N-terminal to the module and a proline motif are conserved among different type structures, but the dimerization module and the interface and orientation between the two iron-sulfur binding modules are divergent. Sequence analysis further shows resemblance between CISD types 4 and 7 and between 1 and 2. Our findings suggest that all CISDs share common ancestry and diverged into three primary folds with a characteristic phylogenetic distribution: a eukaryote-specific fold adopted by types 1 and 2 proteins, a prokaryote-specific fold adopted by types 3, 4 and 7 proteins, and a tandem-motif fold adopted by types 5 and 6 proteins. Our comprehensive structural, sequential and phylogenetic analysis provides significant insight into the assembly principles and evolutionary relationship of CISDs

The influence of metabolically engineered glucosinolates profiles in Arabidopsis thaliana on Plutella xylostella preference and performance

The oviposition preference and larval performance of the diamondback moth (DBM), Plutella xylostella, was studied using Arabidopsis thaliana plants with modified glucosinolate (GS) profiles containing novel GSs as a result of the introduction of individual CYP79 genes. The insect parameters were determined in a series of bioassays. The GS content of the plants as well as the number of trichomes were measured. Multivariate analysis was used to determine the possible relationships among insect and plant variables. The novel GSs in the tested lines did not appear to have any unequivocal effect on the DBM. Instead, the plant characteristics that affected larval performance and larval preference did not influence oviposition preference. Trichomes did not affect oviposition, but influenced larval parameters negatively. Although the tested A. thaliana lines had earlier been shown to influence disease resistance, in this study no clear results were found for P. xylostella

Activation of PPARγ in Myeloid Cells Promotes Lung Cancer Progression and Metastasis

Activation of peroxisome proliferator-activated receptor-γ (PPARγ) inhibits growth of cancer cells including non-small cell lung cancer (NSCLC). Clinically, use of thiazolidinediones, which are pharmacological activators of PPARγ is associated with a lower risk of developing lung cancer. However, the role of this pathway in lung cancer metastasis has not been examined well. The systemic effect of pioglitazone was examined in two models of lung cancer metastasis in immune-competent mice. In an orthotopic model, murine lung cancer cells implanted into the lungs of syngeneic mice metastasized to the liver and brain. As a second model, cancer cells injected subcutaneously metastasized to the lung. In both models systemic administration of pioglitazone increased the rate of metastasis. Examination of tissues from the orthotopic model demonstrated increased numbers of arginase I-positive macrophages in tumors from pioglitazone-treated animals. In co-culture experiments of cancer cells with bone marrow-derived macrophages, pioglitazone promoted arginase I expression in macrophages and this was dependent on the expression of PPARγ in the macrophages. To assess the contribution of PPARγ in macrophages to cancer progression, experiments were performed in bone marrow-transplanted animals receiving bone marrow from Lys-M-Cre+/PPARγflox/flox mice, in which PPARγ is deleted specifically in myeloid cells (PPARγ-Macneg), or control PPARγflox/flox mice. In both models, mice receiving PPARγ-Macneg bone marrow had a marked decrease in secondary tumors which was not significantly altered by treatment with pioglitazone. This was associated with decreased numbers of arginase I-positive cells in the lung. These data support a model in which activation of PPARγ may have opposing effects on tumor progression, with anti-tumorigenic effects on cancer cells, but pro-tumorigenic effects on cells of the microenvironment, specifically myeloid cells

Psychosis risk as a function of age at onset: A comparison between early- and late-onset psychosis in a general population sample

This paper proposes a partial-order semantics for a stochastic process algebra that supports general (non-memoryless) distributions and combines this with an approach to numerically analyse the first passage time of an event. Based on an adaptation of McMillan's complete finite prefix approach tailored to event structures and process algebra, finite representations are obtained for recursive processes. The behaviour between two events is now captured by a partial order that is mapped on a stochastic task graph, a structure amenable to numerical analysis. Our approach is supported by the (new) tool FOREST for generating the complete prefix and the (existing) tool PEPP for analysing the generated task graph. As a case study, the delay of the first resolution in the root contention phase of the IEEE 1394 serial bus protocol is analysed

Therapeutic effects of the mitochondrial ROS-redox modulator KH176 in a mammalian model of Leigh Disease

Leigh Disease is a progressive neurometabolic disorder for which a clinical effective treatment is currently still lacking. Here, we report on the therapeutic efficacy of KH176, a new chemical entity derivative of Trolox, in Ndufs4 (-/-) mice, a mammalian model for Leigh Disease. Using in vivo brain diffusion tensor imaging, we show a loss of brain microstructural coherence in Ndufs4 (-/-) mice in the cerebral cortex, external capsule and cerebral peduncle. These findings are in line with the white matter diffusivity changes described in mitochondrial disease patients. Long-term KH176 treatment retained brain microstructural coherence in the external capsule in Ndufs4 (-/-) mice and normalized the increased lipid peroxidation in this area and the cerebral cortex. Furthermore, KH176 treatment was able to significantly improve rotarod and gait performance and reduced the degeneration of retinal ganglion cells in Ndufs4 (-/-) mice. These in vivo findings show that further development of KH176 as a potential treatment for mitochondrial disorders is worthwhile to pursue. Clinical trial studies to explore the potency, safety and efficacy of KH176 are ongoing

Managing sedentary behavior to reduce the risk of diabetes and cardiovascular disease

Modern human environments are vastly different from those of our forebears. Rapidly advancing technology in transportation, communications, workplaces, and home entertainment confer a wealth of benefits, but increasingly come with costs to human health. Sedentary behavior—too much sitting as distinct from too little physical activity—contributes adversely to cardiometabolic health outcomes and premature mortality. Findings from observational epidemiology have been synthesized in meta-analyses, and evidence is now shifting into the realm of experimental trials with the aim of identifying novel mechanisms and potential causal relationships. We discuss recent observational and experimental evidence that makes a compelling case for reducing and breaking up prolonged sitting time in both the primary prevention and disease management contexts. We also highlight future research needs, the opportunities for developing targeted interventions, and the potential of population-wide initiatives designed to address too much sitting as a health risk

Ants in a Labyrinth: A Statistical Mechanics Approach to the Division of Labour

Division of labour (DoL) is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic) interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments