Project description:BackgroundDifferent studies have shown that cellular enzymatic activities are able to self-organize spontaneously, forming a metabolic core of reactive processes that remain active under different growth conditions while the rest of the molecular catalytic reactions exhibit structural plasticity. This global cellular metabolic structure appears to be an intrinsic characteristic common to all cellular organisms. Recent work performed with dissipative metabolic networks has shown that the fundamental element for the spontaneous emergence of this global self-organized enzymatic structure could be the number of catalytic elements in the metabolic networks.Methodology/principal findingsIn order to investigate the factors that may affect the catalytic dynamics under a global metabolic structure characterized by the presence of metabolic cores we have studied different transitions in catalytic patterns belonging to a dissipative metabolic network. The data were analyzed using non-linear dynamics tools: power spectra, reconstructed attractors, long-term correlations, maximum Lyapunov exponent and Approximate Entropy; and we have found the emergence of self-regulation phenomena during the transitions in the metabolic activities.Conclusions/significanceThe analysis has also shown that the chaotic numerical series analyzed correspond to the fractional Brownian motion and they exhibit long-term correlations and low Approximate Entropy indicating a high level of predictability and information during the self-regulation of the metabolic transitions. The results illustrate some aspects of the mechanisms behind the emergence of the metabolic self-regulation processes, which may constitute an important property of the global structure of the cellular metabolism.
Project description:Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issues that are particularly damaging for the study of multifaceted constructs like self-regulation. Here, we derive a psychological ontology from a study of individual differences across a broad range of behavioral tasks, self-report surveys, and self-reported real-world outcomes associated with self-regulation. Though both tasks and surveys putatively measure self-regulation, they show little empirical relationship. Within tasks and surveys, however, the ontology identifies reliable individual traits and reveals opportunities for theoretic synthesis. We then evaluate predictive power of the psychological measurements and find that while surveys modestly and heterogeneously predict real-world outcomes, tasks largely do not. We conclude that self-regulation lacks coherence as a construct, and that data-driven ontologies lay the groundwork for a cumulative psychological science.
Project description:To fully understand the chemical structure of graphene oxide and the oxidation chemistry of sp2 carbon sites, we conducted a practical experiment and density functional theory combined study on the oxidation process of graphite. The nuclear magnetic resonance, thermogravimetric analysis, and X-ray photoelectron spectroscopy results of unhydrolyzed oxidized graphite indicate that the oxidation process involves the intercalating oxidation, where electrically neutral species is the oxidizing agent, and the diffusive-oxidation, where MnO3 + is the oxidizing agent. An intrinsic formation and conversion path of oxygen-containing functional groups is proposed based on the experimental results and further interpreted with the aid of frontier molecular orbital theory and density functional theory. Meanwhile, the two unique features of the oxidation process of graphite, the chemistry stability of oxygen-containing functional groups in the strong oxidizing medium, and the self-regulation of the oxidation process are theoretically reasoned.