Institutional fields as linked arenas: Inter-field resource dependence, institutional work and institutional change

Theories of institutional change have paid limited attention to the ways in which relations between institutional fields might facilitate or hinder institutional change. I introduce inter-field resource dependence as an important condition explaining institutional change between fields. Building on resource dependence theory, I conceptualize two dimensions of inter-field resource dependence: mutual dependence and power imbalance. I argue that these two dimensions have opposite effects on the likelihood of institutional change between fields. Mutual dependence between two fields increases the chances of institutional change by inducing actors in both the fields to work at creating new shared institutions in order to regulate their mutual dependence. Power imbalance between two fields decreases the chances of institutional change by inducing actors in the dominant field to work at maintaining existing institutions in order to preserve their power. Thus, different types of inter-field resource dependence motivate actors to undertake different forms of institutional work, which in turn shape the likelihood of institutional change between fields. Developing this core argument, I theorize that whether the institutional change occurring between two fields is radical or incremental is a function of the type of resource dependence linking the two fields; for example, when power imbalance is high, institutional change is unlikely but when it occurs it tends to be radical

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD

A combined model reduction algorithm for controlled biochemical systems

Background: Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest. Methods: In this paper a model reduction algorithm bringing together the complementary aspects of proper lumping and empirical balanced truncation is presented. Additional contributions include the development of a criterion for the selection of state-variable elimination via conservation analysis and use of an ‘averaged’ lumping inverse. This combined algorithm is highly automatable and of particular applicability in the context of ‘controlled’ biochemical networks. Results: The algorithm is demonstrated here via application to two examples; an 11 dimensional model of bacterial chemotaxis in Escherichia coli and a 99 dimensional model of extracellular regulatory kinase activation (ERK) mediated via the epidermal growth factor (EGF) and nerve growth factor (NGF) receptor pathways. In the case of the chemotaxis model the algorithm was able to reduce the model to 2 state-variables producing a maximal relative error between the dynamics of the original and reduced models of only 2.8% whilst yielding a 26 fold speed up in simulation time. For the ERK activation model the algorithm was able to reduce the system to 7 state-variables, incurring a maximal relative error of 4.8%, and producing an approximately 10 fold speed up in the rate of simulation. Indices of controllability and observability are additionally developed and demonstrated throughout the paper. These provide insight into the relative importance of individual reactants in mediating a biochemical system’s input-output response even for highly complex networks. Conclusions: Through application, this paper demonstrates that combined model reduction methods can produce a significant simplification of complex Systems Biology models whilst retaining a high degree of predictive accuracy. In particular, it is shown that by combining the methods of proper lumping and empirical balanced truncation it is often possible to produce more accurate reductions than can be obtained by the use of either method in isolation

Un modèle mathématico-statistique simulant le processus du diagnostic médical

Doctorat en sciences médicalesinfo:eu-repo/semantics/nonPublishe

Not impossible vs.guaranted possible in fusion and revision

International audienceIn daily life we have two kinds of knowledge at our disposal, pieces of information ruling out what is known to be impossible on the one hand, and case reports pointing out things which are indeed possible.The fusion of the first type of information is basically conjunctive, while it is disjunctive in the other case. The second type of information has been largely neglected by the logical tradition. Both types can be pervaded with uncertainty.The paper first describes how the two types of information can be accommodated in the possibility theory and in the evidence theory frameworks. Then it is shown how the existence of the two types of information can shed new light on the revision of a knowledge base when receiving new information