Continuum percolation for Gibbs point processes

We consider percolation properties of the Boolean model generated by a Gibbs point process and balls with deterministic radius. We show that for a large class of Gibbs point processes there exists a critical activity, such that percolation occurs a.s. above criticality. For locally stable Gibbs point processes we show a converse result, i.e. they do not percolate a.s. at low activity.

Bounds for the probability generating functional of a Gibbs point process

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics such as the F function. For pairwise interaction processes we obtain further estimates for the G and K functions, the intensity, and higher-order correlation functions. The proof of the main result is based on Stein's method for Poisson point process approximation.

Gibbs point process approximation: Total variation bounds using Stein's method

We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and statistical physics, including the comparison of two Lennard-Jones processes, hard core approximation of an area interaction process and the approximation of lattice processes by a continuous Gibbs process. Our proof of the main results is based on Stein's method. We construct an explicit coupling between two spatial birth-death processes to obtain Stein factors, and employ the Georgii-Nguyen-Zessin equation for the total bound.

Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Age-modulated association between prefrontal NAA and the BDNF gene

Brain-derived neurotrophic factor (BDNF) has been implicated in the pathophysiology of psychiatric and neurological disorders and in the mechanisms of antidepressant pharmacotherapy. Psychiatric and neurological conditions have also been associated with reduced brain levels of N-acetyl-aspartate (NAA), which has been used as a putative marker of neural integrity. However, few studies have explored the relationship between BDNF polymorphisms and NAA levels directly. Here, we present data from a single-voxel proton magnetic resonance spectroscopy study of 64 individuals and explore the relationship between BDNF polymorphisms and prefrontal NAA level. Our results indicate an association between a single nucleotide polymorphism (SNP) within BDNF, known as rs1519480, and reduced NAA level (p = 0.023). NAA levels were further predicted by age and Asian ancestry. There was a significant rs1519480 × age interaction on NAA level (p = 0.031). Specifically, the effect of rs1519480 on NAA level became significant at age ⩾34.17 yr. NAA level decreased with advancing age for genotype TT (p = 0.001) but not for genotype CT (p = 0.82) or CC (p = 0.34). Additional in silico analysis of 142 post-mortem brain samples revealed an association between the same SNP and reduced BDNF mRNA expression in the prefrontal cortex. The rs1519480 SNP influences BDNF mRNA expression and has an impact on prefrontal NAA level over time. This genetic mechanism may contribute to inter-individual variation in cognitive performance seen during normal ageing, as well as contributing to the risk for developing psychiatric and neurological conditions.

An examination of the metabolic processes underpinning critical swimming in Atlantic cod (Gadus morhua L.) using in vivo 31P-NMR spectroscopy.

Traditionally, critical swimming speed has been defined as the speed when a fish can no longer propel itself forward, and is exhausted. To gain a better understanding of the metabolic processes at work during a U(crit) swim test, and that lead to fatigue, we developed a method using in vivo (31)P-NMR spectroscopy in combination with a Brett-type swim tunnel. Our data showed that a metabolic transition point is reached when the fish change from using steady state aerobic metabolism to non-steady state anaerobic metabolism, as indicated by a significant increase in inorganic phosphate levels from 0.3+/-0.3 to 9.5+/-3.4 mol g(-1), and a drop in intracellular pH from 7.48+/-0.03 to 6.81+/-0.05 in muscle. This coincides with the point when the fish change gait from subcarangiform swimming to kick-and-glide bursts. As the number of kicks increased, so too did the Pi concentration, and the pH(i) dropped. Both changes were maximal at U(crit). A significant drop in Gibbs free energy change of ATP hydrolysis from -55.6+/-1.4 to -49.8+/-0.7 kJ mol(-1) is argued to have been involved in fatigue. This confirms earlier findings that the traditional definition of U(crit), unlike other critical points that are typically marked by a transition from aerobic to anaerobic metabolism, is the point of complete exhaustion of both aerobic and anaerobic resources.

Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo

Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

Towards the introduction of the 'Immunoscore' in the classification of malignant tumours.

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named 'Immunoscore' has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).