Understanding human functioning using graphical models

<p>Abstract</p> <p>Background</p> <p>Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning. The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications.</p> <p>Methods</p> <p>We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations. Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure.</p> <p>Results</p> <p>In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected components which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with chronic health conditions, we found that the five ICF categories that showed the strongest effect were plausible.</p> <p>Conclusions</p> <p>Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models.</p

Endothelial dysfunction of bypass graft: Direct comparison of In Vitro and In Vivo models of ischemia-reperfusion injury

BACKGROUND: Although, ischemia/reperfusion induced vascular dysfunction has been widely described, no comparative study of in vivo- and in vitro-models exist. In this study, we provide a direct comparison between models (A) ischemic storage and in-vitro reoxygenation (B) ischemic storage and in vitro reperfusion (C) ischemic storage and in-vivo reperfusion. METHODS AND RESULTS: Aortic arches from rats were stored for 2 hours in saline. Arches were then (A) in vitro reoxygenated (B) in vitro incubated in hypochlorite for 30 minutes (C) in vivo reperfused after heterotransplantation (2, 24 hours and 7 days reperfusion). Endothelium-dependent and independent vasorelaxations were assessed in organ bath. DNA strand breaks were assessed by TUNEL-method, mRNA expressions (caspase-3, bax, bcl-2, eNOS) by quantitative real-time PCR, proteins by Western blot analysis and the expression of CD-31 by immunochemistry. Endothelium-dependent maximal relaxation was drastically reduced in the in-vivo models compared to ischemic storage and in-vitro reperfusion group, and no difference showed between ischemic storage and control group. CD31-staining showed significantly lower endothelium surface ratio in-vivo, which correlated with TUNEL-positive ratio. Increased mRNA and protein levels of pro- and anti-apoptotic gens indicated a significantly higher damage in the in-vivo models. CONCLUSION: Even short-period of ischemia induces severe endothelial damage (in-vivo reperfusion model). In-vitro models of ischemia-reperfusion injury can be limitedly suited for reliable investigations. Time course of endothelial stunning is also described

IGL-1 solution reduces endoplasmic reticulum stress and apoptosis in rat liver transplantation

Injury due to cold ischemia reperfusion (I/R) is a major cause of primary graft non-function following liver transplantation. We postulated that I/R-induced cellular damage during liver transplantation might affect the secretory pathway, particularly at the endoplasmic reticulum (ER). We examined the involvement of ER stress in organ preservation, and compared cold storage in University of Wisconsin (UW) solution and in Institute Georges Lopez-1 (IGL-1) solution. In one group of rats, livers were preserved in UW solution for 8 h at 4 °C, and then orthotopic liver transplantation was performed according to Kamada's cuff technique. In another group, livers were preserved in IGL-1 solution. The effect of each preservation solution on the induction of ER stress, hepatic injury, mitochondrial damage and cell death was evaluated. As expected, we found increased ER stress after liver transplantation. IGL-1 solution significantly attenuated ER damage by reducing the activation of three pathways of unfolded protein response and their effector molecules caspase-12, C/EBP homologous protein-10, X-box-binding protein 1, tumor necrosis factor-associated factor 2 and eukaryotic translation initiation factor 2. This attenuation of ER stress was associated with a reduction in hepatic injury and cell death. Our results show that IGL-1 solution may be a useful means to circumvent excessive ER stress reactions associated with liver transplantation, and may optimize graft quality

The Contribution of Occult Precipitation to Nutrient Deposition on the West Coast of South Africa

The Strandveld mediterranean-ecosystem of the west coast of South Africa supports floristically diverse vegetation growing on mostly nutrient-poor aeolian sands and extending from the Atlantic Ocean tens of kilometers inland. The cold Benguela current upwelling interacts with warm onshore southerly winds in summer causing coastal fogs in this region. We hypothesized that fog and other forms of occult precipitation contribute moisture and nutrients to the vegetation. We measured occult precipitation over one year along a transect running inland in the direction of the prevailing wind and compared the nutrient concentrations with those in rainwater. Occult deposition rates of P, N, K, Mg, Ca, Na, Al and Fe all decreased with distance from the ocean. Furthermore, ratios of cations to Na were similar to those of seawater, suggesting a marine origin for these. In contrast, N and P ratios in occult precipitation were higher than in seawater. We speculate that this is due to marine foam contributing to occult precipitation. Nutrient loss in leaf litter from dominant shrub species was measured to indicate nutrient demand. We estimated that occult precipitation could meet the demand of the dominant shrubby species for annual N, P, K and Ca. Of these species, those with small leaves intercepted more moisture and nutrients than those with larger leaves and could take up foliar deposits of glycine, NO3-, NH4 + and Li (as tracer for K) through leaf surfaces. We conclude that occult deposition together with rainfall deposition are potentially important nutrient and moisture sources for the Strandveld vegetation that contribute to this vegetation being floristically distinct from neighbouring nutrient-poor Fynbos vegetation

Inferring causal molecular networks: empirical assessment through a community-based effort.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871