Kinetic Theory Approach to Modeling of Cellular Repair Mechanisms under Genome Stress

Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR) by using mathematical framework of kinetic theory of active particles (KTAP). Firstly, we focus on illustrating the profile of Cellular Repair System (CRS) instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs) and Repair Protein (RP) generating, DSB-protein complexes (DSBCs) synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances

f(R) theories

Over the past decade, f(R) theories have been extensively studied as one of the simplest modifications to General Relativity. In this article we review various applications of f(R) theories to cosmology and gravity - such as inflation, dark energy, local gravity constraints, cosmological perturbations, and spherically symmetric solutions in weak and strong gravitational backgrounds. We present a number of ways to distinguish those theories from General Relativity observationally and experimentally. We also discuss the extension to other modified gravity theories such as Brans-Dicke theory and Gauss-Bonnet gravity, and address models that can satisfy both cosmological and local gravity constraints.Comment: 156 pages, 14 figures, Invited review article in Living Reviews in Relativity, Published version, Comments are welcom

Crackling Noise

Crackling noise arises when a system responds to changing external conditions through discrete, impulsive events spanning a broad range of sizes. A wide variety of physical systems exhibiting crackling noise have been studied, from earthquakes on faults to paper crumpling. Because these systems exhibit regular behavior over many decades of sizes, their behavior is likely independent of microscopic and macroscopic details, and progress can be made by the use of very simple models. The fact that simple models and real systems can share the same behavior on a wide range of scales is called universality. We illustrate these ideas using results for our model of crackling noise in magnets, explaining the use of the renormalization group and scaling collapses. This field is still developing: we describe a number of continuing challenges

Applying critical systems thinking to social prescribing: a relational model of stakeholder “buy-in”

Background Social prescribing (SP) allows health professionals to refer primary care patients toward health and wellbeing interventions and activities in the local community. Now widely implemented across the UK and adopted in other nations, questions arise concerning the modelling of present and future schemes, including challenges to full engagement encountered by stakeholders, which lie beyond the scope of traditional evaluations. Critical Systems Thinking (CST) allows for holistic analysis of fields where multiple stakeholders hold diverse interests and unequal power. Methods We use CST to (a) critically examine a developing rural social prescribing scheme from multiple stakeholder perspectives and (b) present a relational model for local social prescribing schemes. Our fieldwork included 24 in-depth interviews, regular planning meetings with key stakeholders, and discussions with those involved with national and international SP landscaping. A modified grounded theory approach was used for the analysis, and to consider the core elements of social prescribing sustainability. Results Our study confirms that local social prescribing schemes must operate with numerous stakeholder interests in mind, seeking to address real life social complexity and offer integrated solutions to multifaceted issues. Three main areas are discussed: holistic vision and boundary judgments; barriers and facilitators; relational issues and “emotional buy in”. Problems for staff include selecting suitable clients, feedback and technological issues and funding and evaluation pressures. Barriers for clients include health, transport and expense issues, also lack of prior information and GP involvement. Emotional “buy-in” emerged as essential for all stakeholders, but hard to sustain. Based on our findings we propose a positive relational model comprising shared vision, confidence and commitment; motivation and encouragement, support and wellbeing focus, collaborative relationships, communication and feedback, access to information /resources, learning in and from action, with emotional “buy-in” at its heart. Conclusion Those implementing social prescribing in different localities inevitably face hard choices about what and whom to include. Research on the sustainability of social prescribing remains limited, studies are required to ascertain which “holistic” models of social prescribing work best for which communities, who are the main beneficiaries of these approaches and how “buy-in” is best sustained

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research

From discrete kinetic and stochastic game theory to modelling complex systems in applied sciences

This paper deals with some methodological aspects related to the discretization of a class of integro-differential equations modelling the evolution of the probability distribution over the microscopic state of a large system of interacting individuals. The microscopic state includes both mechanical and socio-biological variables. The discretization of the microscopic state generates a class of dynamical systems defining the evolution of the densities of the discretized state. In general, this yields a system of partial differential equations replacing the continuous integro-differential equation. As an example, a specific application is discussed, which refers to modelling in the field of social dynamics. The derivation of the evolution equation needs the development of a stochastic game theory

Modeling opinion formation in the kinetic theory of active particles I: spontaneous trend

The kinetic theory of active particles is used to model the formation and evolution of opinions in a structured population. The spatial structure is modeled by a network whose nodes mimic the geographic distribution of individuals, while the functional subsystems present in each node group together elements sharing a common orientation. In this paper we introduce a model, based on nonlinear and nonlinearly additive interactions among individuals. subsystems and nodes, related to the spontaneous evolution of opinion concerning given specific issues. Numerical solutions in a model situation not related with real data show how the mutual interactions are able to drive the subsystems opinion toward the emergence of collective structures characterizing this kind of complex systems