Introduction to the mathematical theory of knowledge conceptualization: Conceptual systems and structures

The paper departs from the general problem of knowledge integration and the basic strategies that can be adopted to confront this challenge. With the purpose of providing a sound meta-theoretical framework to facilitate knowledge conceptualization and integration, as well as assessment criteria to evaluate achievements regarding knowledge integration, the paper first reviews the previous work in the field of conceptual spaces. It subsequently gives an overview of structural tools and mechanisms for knowledge representation, recapped in the modal stratified bond model of global knowledge. On these groundings, a novel formalized representation of conceptual systems, structures, spaces and algebras is developed through a set of definitions which goes beyond the exploration of mental knowledge representation and the semantics of natural languages. These two components provide a sound framework for the development of the glossaLAB international project with respect to its two basic objectives, namely (i) facilitating knowledge integration in general and particularly in the context of the general study of information and systems; (ii) facilitating the assessment of the achievements as regards knowledge integration in interdisciplinary settings. An additional article tackles the solutions adopted to integrate these results in the elucidation of the conceptual network of the general study of information and systems.2019-2

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

The human role in the age of information

Age of automation entails freedom from most of the common working roles. Signs are changes in employment, unemployment, professional structures, relevance of services, entertainment industry, working hours, and the nature of social relations. Warnings are suggested against voluntaristic interventions, neglect of social, historical relations. New approaches are required in the fields of lifelong education and in the education of socially disadvantaged people. The changes in evolutionary inherited motivations and life styles are critical challenges to mankind. Open society and lessons of system control are recommended. © 2013 Springer-Verlag London

Treatment response in Kawasaki disease is associated with sialylation levels of endogenous but not therapeutic intravenous immunoglobulin G.

OBJECTIVES: Although intravenous immunoglobulin (IVIG) is highly effective in Kawasaki disease (KD), mechanisms are not understood and 10-20% of patients are treatment-resistant, manifesting a higher rate of coronary artery aneurysms. Murine models suggest that α2-6-linked sialic acid (α2-6Sia) content of IVIG is critical for suppressing inflammation. However, pro-inflammatory states also up-regulate endogenous levels of β-galactoside:α2-6 sialyltransferase-I (ST6Gal-I), the enzyme that catalyzes addition of α2-6Sias to N-glycans. We asked whether IVIG failures correlated with levels of α2-6Sia on infused IVIG or on the patient's own endogenous IgG. METHODS: We quantified levels of α2-6Sia in infused IVIG and endogenous IgG from 10 IVIG-responsive and 10 resistant KD subjects using multiple approaches. Transcript levels of ST6GAL1, in patient whole blood and B cell lines were evaluated by RT-PCR. Plasma soluble (s)ST6Gal-I levels were measured by ELISA. RESULTS: There was no consistent difference in median sialylation levels of infused IVIG between groups. However, α2-6Sia levels in endogenous IgG, ST6GAL1 transcript levels, and ST6Gal-I protein in serum from IVIG-resistant KD subjects were lower than in responsive subjects at both pre-treatment and one-year time points (p <0.001, respectively). CONCLUSIONS: Our data indicate sialylation levels of therapeutic IVIG are unrelated to treatment response in KD. Rather, lower sialylation of endogenous IgG and lower blood levels of ST6GALI mRNA and ST6Gal-I enzyme predict therapy resistance. These differences were stable over time, suggesting a genetic basis. Because IVIG-resistance increases risk of coronary artery aneurysms, our findings have important implications for the identification and treatment of such individuals