Allogeneic NK cells induce the <i>in vitro</i> activation of monocyte-derived and conventional type-2 dendritic cells and trigger an inflammatory response under cancer-associated conditions

Natural killer (NK) cells are innate lymphocytes capable to recognize and kill virus-infected and cancer cells. In the past years, the use of allogeneic NK cells as anti-cancer therapy gained interest due to their ability to induce graft-versus-cancer responses without causing graft-versus-host disease and multiple protocols have been developed to produce high numbers of activated NK cells. While the ability of these cells to mediate tumor kill has been extensively studied, less is known about their capacity to influence the activity of other immune cells that may contribute to a concerted anti-tumor response in the tumor microenvironment (TME). In this study, we analyzed how an allogeneic off-the-shelf cord blood stem cell-derived NK-cell product influenced the activation of dendritic cells (DC). Crosstalk between NK cells and healthy donor monocyte-derived DC (MoDC) resulted in the release of IFNγ and TNF, MoDC activation, and the release of the T-cell-recruiting chemokines CXCL9 and CXCL10. Moreover, in the presence of prostaglandin-E2, NK cell/MoDC crosstalk antagonized the detrimental effect of IL-10 on MoDC maturation leading to higher expression of multiple (co-)stimulatory markers. The NK cells also induced activation of conventional DC2 (cDC2) and CD8 + T cells, and the release of TNF, GM-CSF, and CXCL9/10 in peripheral blood mononuclear cells of patients with metastatic colorectal cancer. The activated phenotype of MoDC/cDC2 and the increased release of pro-inflammatory cytokines and T-cell-recruiting chemokines resulting from NK cell/DC crosstalk should contribute to a more inflamed TME and may thus enhance the efficacy of T-cell-based therapies.</p

CRPropa: a public framework to propagate UHECRs in the universe

To answer the fundamental questions concerning the origin and nature of ultra-high energy cosmic rays (UHECRs), it is important to confront data with simulated astrophysical scenarios. These scenarios should include detailed information on particle interactions and astrophysical environments. To achieve this goal one should make use of computational tools to simulate the propagation of these particles. For this reason the CRPropa framework was developed. It allows the propagation of UHECRs with energies $\gtrsim$10$^{17}$ eV and secondary gamma rays and neutrinos. The newest version, CRPropa 3, reflects an efficient redesign of the code as well as several new features such as time dependent propagation in three dimensions, galactic magnetic field effects and improved treatment of interactions, among other enhancements.Comment: 6 pages, 6 figures; Proceedings of the International Symposium on Very High Energy Cosmic Ray Interactions (ISVHECRI 2014

Simulations of lattice animals and trees

The scaling behaviour of randomly branched polymers in a good solvent is studied in two to nine dimensions, using as microscopic models lattice animals and lattice trees on simple hypercubic lattices. As a stochastic sampling method we use a biased sequential sampling algorithm with re-sampling, similar to the pruned-enriched Rosenbluth method (PERM) used extensively for linear polymers. Essentially we start simulating percolation clusters (either site or bond), re-weigh them according to the animal (tree) ensemble, and prune or branch the further growth according to a heuristic fitness function. In contrast to previous applications of PERM, this fitness function is {\it not} the weight with which the actual configuration would contribute to the partition sum, but is closely related to it. We obtain high statistics of animals with up to several thousand sites in all dimension 2 <= d <= 9. In addition to the partition sum (number of different animals) we estimate gyration radii and numbers of perimeter sites. In all dimensions we verify the Parisi-Sourlas prediction, and we verify all exactly known critical exponents in dimensions 2, 3, 4, and >= 8. In addition, we present the hitherto most precise estimates for growth constants in d >= 3. For clusters with one site attached to an attractive surface, we verify the superuniversality of the cross-over exponent at the adsorption transition predicted by Janssen and Lyssy. Finally, we discuss the collapse of animals and trees, arguing that our present version of the algorithm is also efficient for some of the models studied in this context, but showing that it is {\it not} very efficient for the `classical' model for collapsing animals.Comment: 17 pages RevTeX, 29 figures include

Corporate governance and financial constraints on strategic turnarounds

The paper extends the Robbins and Pearce (1992) two-stage turnaround response model to include governance factors. In addition to the retrenchment and recovery, the paper proposes the addition of a realignment stage, referring specifically to the re-alignment of expectations of principal and agent groups. The realignment stage imposes a threshold that must be crossed before the retrenchment and hence recovery stage can be entered. Crossing this threshold is problematic to the extent that the interests of governance-stakeholder groups diverge in a crisis situation. The severity of the crisis impacts on the bases of strategy contingent asset valuation leading to the fragmentation of stakeholder interests. In some cases the consequence may be that management are prevented from carrying out turnarounds by governance constraints. The paper uses a case study to illustrate these dynamics, and like the Robbins and Pearce study, it focuses on the textile industry. A longitudinal approach is used to show the impact of the removal of governance constraints. The empirical evidence suggests that such financial constraints become less serious to the extent that there is a functioning market for corporate control. Building on governance research and turnaround literature, the paper also outlines the general case necessary and sufficient conditions for successful turnarounds

Lifestyle and clinical determinants of skin autofluorescence in a population-based cohort study

BACKGROUND: Skin autofluorescence (SAF) is a non-invasive marker of advanced glycation end products (AGEs). In diabetes, higher SAF levels has been positively associated with long-term complications, cardiovascular morbidity and mortality. Because little is known about the factors that influence SAF in non-diabetic individuals, we assessed the association of clinical and lifestyle parameters with SAF as well as their interactions in a large-scale, non-diabetic population and performed the same analyses in a type 2 diabetic subgroup. METHODS: In a cross-sectional study in participants from the LifeLines Cohort Study, extensive clinical and biochemical phenotyping, including SAF measurement, was assessed in 9009 subjects of whom 314 (3.5%) subjects with type 2 diabetes. RESULTS: Mean SAF was 2.04 ± 0.44 arbitrary units (AU) in non-diabetic individuals and 2.44 ± 0.55 AU in type 2 diabetic subjects (p<0.0001). Multivariate backward regression analysis showed that in the non-diabetic population, SAF was significantly and independently associated with age, BMI, HbA1c, creatinine clearance, genetic polymorphism in NAT2 (rs4921914), current smoking, pack-years of smoking and coffee consumption. In the type 2 diabetic group, a similar set of factors was associated with SAF, except for coffee consumption. CONCLUSIONS: In addition to the established literature on type 2 diabetes, we have demonstrated that SAF levels are associated with several clinical and lifestyle factors in the non-diabetic population. These parameters should be taken into consideration when using SAF as a screening or prediction tool for populations at risk for cardiovascular disease and diabetes. This article is protected by copyright. All rights reserved

Mathematical morphology on tensor data using the Loewner ordering

The notions of maximum and minimum are the key to the powerful tools of greyscale morphology. Unfortunately these notions do not carry over directly to tensor-valued data. Based upon the Loewner ordering for symmetric matrices this paper extends the maximum and minimum operation to the tensor-valued setting. This provides the ground to establish matrix-valued analogues of the basic morphological operations ranging from erosion/dilation to top hats. In contrast to former attempts to develop a morphological machinery for matrices, the novel definitions of maximal/minimal matrices depend continuously on the input data, a property crucial for the construction of morphological derivatives such as the Beucher gradient or a morphological Laplacian. These definitions are rotationally invariant and preserve positive semidefiniteness of matrix fields as they are encountered in DT-MRI data. The morphological operations resulting from a component-wise maximum/minimum of the matrix channels disregarding their strong correlation fail to be rotational invariant. Experiments on DT-MRI images as well as on indefinite matrix data illustrate the properties and performance of our morphological operators

Coupled daily streamflow and water temperature modelling in large river basins

Realistic estimates of daily streamflow and water temperature are required for effective management of water resources (e.g. for electricity and drinking water production) and freshwater ecosystems. Although hydrological and process-based water temperature modelling approaches have been successfully applied to small catchments and short time periods, much less work has been done at large spatial and temporal scales. We present a physically based modelling framework for daily river discharge and water temperature simulations applicable to large river systems on a global scale. Model performance was tested globally at 1/2 × 1/2° spatial resolution and a daily time step for the period 1971–2000. We made specific evaluations on large river basins situated in different hydro-climatic zones and characterized by different anthropogenic impacts. Effects of anthropogenic heat discharges on simulated water temperatures were incorporated by using global gridded thermoelectric water use datasets and representing thermal discharges as point sources into the heat advection equation. This resulted in a significant increase in the quality of the water temperature simulations for thermally polluted basins (Rhine, Meuse, Danube and Mississippi). Due to large reservoirs in the Columbia which affect streamflow and thermal regimes, a reservoir routing model was used. This resulted in a significant improvement in the performance of the river discharge and water temperature modelling. Overall, realistic estimates were obtained at daily time step for both river discharge (median normalized BIAS = 0.3; normalized RMSE = 1.2; r = 0.76) and water temperature (median BIAS = -0.3 °C; RMSE = 2.8 °C; r = 0.91) for the entire validation period, with similar performance during warm, dry periods. Simulated water temperatures are sensitive to headwater temperature, depending on resolution and flow velocity. A high sensitivity of water temperature to river discharge (thermal capacity) was found during warm, dry conditions. The modelling approach has potential to be used for risk analyses and studying impacts of climate change and other anthropogenic effects (e.g. thermal pollution, dams and reservoir regulation) on large rivers

Upstream transcription factor 1 (USF1) in risk of type 2 diabetes:Association study in 2000 Dutch Caucasians

Type 2 diabetes shares substantial genetic and phenotypic overlap with familial combined hyperlipidemia. Upstream stimulatory factor 1 (USF7), a well-established susceptibility gene for familial combined hyperlipidemia, is postulated to be such a shared genetic determinant. We evaluated two established variants in familial combined hyperlipidemia (rs2073658 and rs3737787) for association with type 2 diabetes in two Dutch case-control samples (N=2011). The first case-control sample comprised 501 subjects with type 2 diabetes from the Breda cohort and 920 healthy blood bank donors of Dutch Caucasian origin. The second case-control sample included 211 subjects with type 2 diabetes, and 379 normoglycemic controls. SNP rs2073658 and SNP rs3737787 were in perfect linkage disequilibrium. In the first case-control sample, prevalence of the major allele was higher in patients than in controls (75% versus 71%, OR=1.25, p=0.018). A similar effect-size and -direction was observed in the second case-control sample (76% versus 72%, OR=1.22, p=0.16). A combined analysis strengthened the evidence for association (OR=1.23, p=0.006). Notably, the increased risk for type 2 diabetes could be ascribed to the major allele, and its high frequency translated to a substantial population attributable risk of 14.5%. In conclusion, the major allele of rs2073658 in the USF1 gene is associated with a modestly increased risk to develop type 2 diabetes in Dutch Caucasians, with considerable impact at the population level. (c) 2008 Elsevier Inc. All rights reserved

Activating transcription factor 6 polymorphisms and haplotypes are associated with impaired glucose homeostasis and type 2 diabetes in dutch Caucasians

Context: Activating transcription factor 6 (ATF6) is critical for initiation and full activation of the unfolded protein response. An association between genetic variation in ATF6 and type 2 diabetes (DM2) was recently reported in Pima Indians. Objectives: To investigate the broader significance of this association for DM2, replication studies in distinct ethic populations are required. We investigated ATF6 for its association with DM2 in Dutch Caucasians. Design/Setting: A genetic association study was conducted at an academic research laboratory. Study Participants: Two independent Dutch cohorts were studied. Cohort 1 (n = 154) was used to evaluate genetic variation in the ATF6 gene in relation to glucose homeostasis in the general population. Cohort 2 (n = 798) consisted of patients with DM2, impaired glucose tolerance, impaired fasting glucose, and normoglycemic control subjects, and was used to investigate ATF6 polymorphisms for their contribution to disturbed glucose homeostasis and DM2. Main Outcome Measures: There were 16 tag single nucleotide polymorphisms genotyped in all subjects of both cohorts. Those single nucleotide polymorphisms included three nonsynonymous coding variants and captured all common allelic variation of ATF6. Results: Our data show that common ATF6 variants are associated with elevated glucose levels in the general population (cohort 1, P = 0.005-0.05). Furthermore, the majority of these variants, and haplotypes thereof, were significantly associated with impaired fasting glucose, impaired glucose tolerance, and DM2 ( cohort 2, P = 0.006-0.05). Associated variants differ from those identified in Pima Indians. Conclusions: Our results strengthen the evidence that one or more variants in ATF6 are associated with disturbed glucose homeostasis and DM2