A Proof of Concept Study on Real-Pime LiMAx CYP1A2 Liver Function Assessment of Donor Grafts During Normothermic Machine Perfusion

No single reliable parameter exists to assess liver graft function of extended criteria donors during ex-vivo normothermic machine perfusion (NMP). The liver maximum capacity (LiMAx) test is a clinically validated cytochromal breath test, measuring liver function based on 13CO2 production. As an innovative concept, we aimed to integrate the LiMAx breath test with NMP to assess organ function. Eleven human livers were perfused using NMP. After one hour of stabilization, LiMAx testing was performed. Injury markers (ALT, AST, miR-122, FMN, and Suzuki-score) and lactate clearance were measured and related to LiMAx values. LiMAx values ranged between 111 and 1838 µg/kg/h, and performing consecutive LiMAx tests during longer NMP was feasible. No correlation was found between LiMAx value and miR-122 and FMN levels in the perfusate. However, a significant inverse correlation was found between LiMAx value and histological injury (Suzuki-score, R = − 0.874, P < 0.001), AST (R = − 0.812, P = 0.004) and ALT (R = − 0.687, P = 0.028). Furthermore, a significant correlation was found with lactate clearance (R = 0.683, P = 0.043). We demonstrate, as proof of principle, that liver function during NMP can be quantified using the LiMAx test, illustrating a positive correlation with traditional injury markers. This new breath-test application separates livers with adequate cytochromal liver function from inadequate ones and may support decision-making in the safe utilization of extended criteria donor grafts

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

TREEPLAN� - A Genetic Evaluation System for Forest Trees

The TREEPLAN� genetic evaluation system is designed specifically for the efficient and accurate prediction of breeding and other genetic values in trees. TREEPLAN� uses the preferred statistical method of best linear unbiased prediction (BLUP) using an individual tree additive genetic effect. Although BLUP methods are well developed theoretically, other software is suitable only for breeding value estimation and prediction on small and/or highly structured (balanced) data sets. Packages such as ASREML and SAS have hardware and software limitations that make them unsuitable for routine prediction on large data sets with complex pedigree structures and overlapping generations. TREEPLAN� fits a reduced individual tree model for purposes of efficiency. TREEPLAN� can model multiple genetic groups, handle clonal data, fit multi-trait models with more than 50 traits, accommodate heterogeneous variances, fit site specific statistical and genetic models, and also weights information across environments (accounts for genotype by environment interaction) and time (allows for age:age correlations). The Southern Tree Breeding Association (STBA) is routinely using TREEPLAN� for genetic evaluation in Australian tree improvement programs for Pinus radiata, Eucalyptus globulus and E. nitens. TREEPLAN� has allowed data across generations and years to be combined in a multi-trait analysis to produce single lists of breeding values for each trait and environment combination. TREEPLAN� is easy to use and has the �industrial strength� to handle large amounts of unbalanced data with the complex pedigree structures that are usually associated with national or regional tree improvement programs. TREEPLAN� is fully integrated with a web based data management system that efficiently handles data and pedigree information. The analytical power and flexibility of the TREEPLAN� system has made routine genetic evaluation in trees a straightforward process.Papers and abstracts from the 27th Southern Forest Tree Improvement Conference held at Oklahoma State University in Stillwater, Oklahoma on June 24-27, 2003

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure

Utilization of livers donated after circulatory death for transplantation - An international comparison.

BACKGROUND AND AIM Liver graft utilization rates are a hot topic due to the worldwide organ shortage and an increasing number of transplant candidates on waiting lists. Liver perfusion techniques have been introduced in several countries, and may help to increase the organ supply, as they potentially allow the assessment of livers before use. METHODS Liver offers were counted from donation after circulatory death (DCD) donors (Maastricht-type-III) arising during the past decade in eight countries, including Belgium, France, Italy, the Netherlands, Spain, Switzerland, UK, and US. Initial DCD-type-III liver offers were correlated with accepted, recovered and implanted livers. RESULTS A total number of 34`269 DCD livers were offered, resulting in 9`780 liver transplants (28.5%). The discard rates were highest in UK and US, ranging between 70 and 80%. In contrast, much lower DCD liver discard rates, e.g., between 30-40%, were found in Belgium, France, Italy, Spain and Switzerland. In addition, large differences were recognized in the use of various machine perfusion techniques, and in terms of risk factors in the cohorts of implanted livers. For example, the median donor age and functional donor warm ischemia were highest in Italy, e.g., >40minutes, followed by Switzerland, France, and the Netherlands. Importantly, such varying risk profiles of accepted DCD livers between countries did not translate into large differences in five-year graft survival rates, which ranged between 60-82% in this analysis. CONCLUSIONS We highlight a significant number of discarded and consequently unused DCD liver offers. Countries with more routine use of in- and ex-situ machine perfusion strategies showed better DCD utilization rates without compromised outcome. IMPACT AND IMPLICATIONS A significant number of Maastricht type III DCD livers are discarded across Europe and North America today. The overall utilization rate among eight Western countries is 28.5%, but varies significantly between 18.9% and 74.2%. For example, the median DCD III liver utilization in five countries, e.g., Belgium, France, Italy, Switzerland, and Spain is 65%, in contrast to 24% in the Netherlands, UK and US. Despite this, and despite different rules and strategies for organ acceptance and preservation, the one and five-year graft survival remains currently relatively comparable among all participating countries. Factors which impact on DCD liver acceptance rates include the national pre-selections of donors, before the offer is made, as well as cutoffs for key risk factors, including donor age and donor warm ischemia time. In addition, a highly varying experience with modern machine perfusion technology is noticed. In situ and ex situ liver perfusion concepts, and assessment tools for type III DCD livers before transplantation may be one key part for the observed differences in better DCD III utilization

A Switch in the Control of Growth of the Wing Imaginal Disks of Manduca sexta

Background: Insulin and ecdysone are the key extrinsic regulators of growth for the wing imaginal disks of insects. In vitro tissue culture studies have shown that these two growth regulators act synergistically: either factor alone stimulates only limited growth, but together they stimulate disks to grow at a rate identical to that observed in situ. It is generally thought that insulin signaling links growth to nutrition, and that starvation stops growth because it inhibits insulin secretion. At the end of larval life feeding stops but the disks continue to grow, so at that time disk growth has become uncoupled from nutrition. We sought to determine at exactly what point in development this uncoupling occurs. Methodology: Growth and cell proliferation in the wing imaginal disks and hemolymph carbohydrate concentrations were measured at various stages in the last larval instar under experimental conditions of starvation, ligation, rescue, and hormone treatment. Principal Findings: Here we show that in the last larval instar of M. sexta, the uncoupling of nutrition and growth occurs as the larva passes the critical weight. Before this time, starvation causes a decline in hemolymph glucose and trehalose and a cessation of wing imaginal disks growth, which can be rescued by injections of trehalose. After the critical weight the trehalose response to starvation disappears, and the expression of insulin becomes decoupled from nutrition. After the critical weight the wing disks loose their sensitivity to repression by juvenile hormone, and factors from the abdomen, bu

Genetic parameters for growth, wood density and pulp yield in Eucalyptus globulus

Genetic variation and co-variation among the key pulpwood selection traits for Eucalyptus globulus were estimated for a range of sites in Portugal, with the aim of improving genetic parameters used to predict breeding values and correlated response to selection. The trials comprised clonally replicated full-sib families (eight trials) and unrelated clones (17 trials), and exhibited varying levels of pedigree connectivity. The traits studied were stem diameter at breast height, Pilodyn penetration (an indirect measure of wood basic density) and near infrared reflectance predicted pulp yield. Univariate and multivariate linear mixed models were fitted within and across sites, and estimates of additive genetic, total genetic, environmental and phenotypic variances and covariances were obtained. All traits studied exhibited significant levels of additive genetic variation. The average estimated within-site narrowsense heritability was 0.19±0.03 for diameter and 0.29± 0.03 for Pilodyn penetration, and the pooled estimate for predicted pulp yield was 0.42±0.14. When they could be tested, dominance and epistatic effects were generally not statistically significant, although broad-sense heritability estimates were slightly higher than narrow-sense heritability estimates. Averaged across trials, positive additive (0.64±0.08), total genetic (0.58±0.04), environmental (0.38±0.03) and phenotypic (0.43±0.02) correlation estimates were consistently obtained between diameter and Pilodyn penetration. This data argues for at least some form of pleiotropic relationship between these two traits and that selection for fast growth will adversely affect wood density in this population. Estimates of the across-site genetic correlations for diameter and Pilodyn penetration were high, indicating that the genotype by environment interaction is low across the range of sites tested. This result supports the use of single aggregated selection criteria for growth and wood density across planting environments in Portugal, as opposed to having to select for performance in different environment

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution