In addition, we use a hierarchical model to determine the distribution of intrinsic cell periods, thereby separating the variability due to stochastic gene expression within each cell from the variability in period across the population of cells. (C) 2012 Elsevier Ltd. All rights reserved.”
“Background: Until recently, there was a lack of a uniform definition for acute kidney injury (AKI). The ‘acute renal injury/acute renal failure syndrome/severe acute renal failure syndrome’ criteria, the Risk – Injury – Failure

– Loss of kidney function End stage renal disease ( RIFLE) criteria and the Acute Kidney Injury Network ( AKIN) classification were the most recent proposals.

Aim: To compare the performance of the different AKI definitions.

Design and Methods: Application Epoxomicin in vivo of the three most recent AKI definitions to 41 972 critically ill ICU patients and comparison of their performance.

Results: Incidence and outcome of AKI varied depending on check details the criteria. The RIFLE and AKIN classification led to similar total incidences of AKI (35.9 vs. 35.4%) but different incidences and outcomes of the individual AKI stages. Multivariate analysis showed that the different stages of AKI were independently

associated with mortality. The worst stage of AKI was associated with an increased odds ratio for mortality of 1.59-2.27. Non-surgical admission, maximum number of associated failed organ systems, emergency surgery and mechanical ventilation were consistently associated with the highest risk of hospital mortality.

The proposed AKI definitions differ in the cut-off values Tryptophan synthase of serum creatinine, the suggested time frame, the approach towards patients with missing baseline values and the method of classifying patients on renal replacement therapy. All classifications can miss patients with definite AKI.

Conclusions: The three most recent definitions of AKI confirmed a correlation between severity of AKI and outcome but have limitations and the potential to miss patients

with definite AKI. These limitations need to be considered when using the criteria in clinical practice.”
“Understanding the emerging properties of complex biological systems is in the crux of systems biology studies. Computational methods for elucidating the role of each component in the synergetic interplay can be used to identify targets for genetic and metabolic engineering. In particular, we aim at determining the importance of reactions in a metabolic network with respect to a specific biological function. Therefore, we propose a novel game-theoretic framework which integrates restricted cooperative games with the outcome of flux balance analysis. We define productivity games on metabolic networks and present an analysis of their unrestricted and restricted variants based on the game-theoretic solution concept of the Shapley value.