Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Underperforming policy networks : the biopesticides network in the United Kingdom

Loosely integrated and incomplete policy networks have been neglected in the literature. They are important to consider in terms of understanding network underperformance. The effective delivery and formulation of policy requires networks that are not incomplete or underperforming. The biopesticides policy network in the United Kingdom is considered and its components identified with an emphasis on the lack of integration of retailers and environmental groups. The nature of the network constrains the actions of its agents and frustrates the achievement of policy goals. A study of this relatively immature policy network also allows for a focus on network formation. The state, via an external central government department, has been a key factor in the development of the network. Therefore, it is important to incorporate such factors more systematically into understandings of network formation. Feedback efforts from policy have increased interactions between productionist actors but the sphere of consumption remains insufficiently articulated

Prognostic significance of tumor-infiltrating lymphocytes in ductal carcinoma in situ of the breast

Tumor-infiltrating lymphocytes (TILs) provide prognostic value in invasive breast cancer and guidelines for their assessment have been published. This study aims to evaluate: (a) methods of TILs assessment, and (b) their prognostic significance in breast ductal carcinoma in situ (DCIS). Hematoxylin and eosin sections from two clinically annotated DCIS cohorts; a training set (n = 150 pure DCIS) and a validation set (n = 666 comprising 534 pure DCIS and 132 cases wherein DCIS and invasive breast carcinoma were co-existent) were assessed. Seven different scoring methods were applied to the training set to identify the most optimal reproducible method associated with strongest prognostic value. Among different methods, TILs touching ducts' basement membrane or away from it by one lymphocyte cell thickness provided the strongest significant association with outcome and highest concordance rate [inter-cluster correlation coefficient = 0.95]. Assessment of periductal TILs at increasing distances from DCIS (0.2 , 0.5 , and 1 mm) as well as percent of stromal TILs were practically challenging and showed lower concordance rates than touching TILs. TILs hotspots and lymphoid follicles did not show prognostic significance. Within the pure DCIS validation set, dense TILs were associated with younger age, symptomatic presentation, larger size, higher nuclear grade, comedo necrosis and estrogen receptor negativity as well as shorter recurrence-free interval (p = 0.002). In multivariate survival analysis, dense TILs were independent predictor of shorter recurrence-free interval (p = 0.002) in patients treated with breast conservation. DCIS associated with invasive carcinoma showed denser TILs than pure DCIS (p = 9.0 × 10-13). Dense TILs is an independent prognostic variable in DCIS. Touching TILs provides a reproducible method for their assessment that can potentially be used to guide management

Low adherent cancer cell subpopulations are enriched in tumorigenic and metastatic epithelial-to-mesenchymal transition-induced cancer stem-like cells

Cancer stem cells are responsible for tumor progression, metastasis, therapy resistance and cancer recurrence, doing their identification and isolation of special relevance. Here we show that low adherent breast and colon cancer cells subpopulations have stem-like properties. Our results demonstrate that trypsin-sensitive (TS) breast and colon cancer cells subpopulations show increased ALDH activity, higher ability to exclude Hoechst 33342, enlarged proportion of cells with a cancer stem-like cell phenotype and are enriched in sphere- and colony-forming cells in vitro. Further studies in MDA-MB-231 breast cancer cells reveal that TS subpopulation expresses higher levels of SLUG, SNAIL, VIMENTIN and N-CADHERIN while show a lack of expression of E-CADHERIN and CLAUDIN, being this profile characteristic of the epithelial-to-mesenchymal transition (EMT). The TS subpopulation shows CXCL10, BMI-1 and OCT4 upregulation, differing also in the expression of several miRNAs involved in EMT and/or cell self-renewal such as miR-34a-5p, miR-34c-5p, miR-21-5p, miR-93-5p and miR-100-5p. Furthermore, in vivo studies in immunocompromised mice demonstrate that MDA-MB-231 TS cells form more and bigger xenograft tumors with shorter latency and have higher metastatic potential. In conclusion, this work presents a new, non-aggressive, easy, inexpensive and reproducible methodology to isolate prospectively cancer stem-like cells for subsequent biological and preclinical studies.Ministry of Economy and Competitiveness, Instituto de Salud Carlos III (FEDER funds) PI10/02295 PI10/02149Fundacion Progreso y Salud, Consejeria de Salud, Junta de Andalucia (Ministry of Health, Government of Andalucia) PI-0533-2014Consejeria Economia, Innovacion, Ciencia y Empleo, Junta de Andalucia (Ministry of Economy, Innovation, Science and Employment, Government of Andalucia) CTS-656

Contribution mapping: a method for mapping the contribution of research to enhance its impact.

Background: At a time of growing emphasis on both the use of research and accountability, it is important for research funders, researchers and other stakeholders to monitor and evaluate the extent to which research contributes to better action for health, and find ways to enhance the likelihood that beneficial contributions are realized. Past attempts to assess research 'impact' struggle with operationalizing 'impact', identifying the users of research and attributing impact to research projects as source. In this article we describe Contribution Mapping, a novel approach to research monitoring and evaluation that aims to assess contributions instead of impacts. The approach focuses on processes and actors and systematically assesses anticipatory efforts that aim to enhance contributions, so-called alignment efforts. The approach is designed to be useful for both accountability purposes and for assisting in better employing research to contribute to better action for health.Methods: Contribution Mapping is inspired by a perspective from social studies of science on how research and knowledge utilization processes evolve. For each research project that is assessed, a three-phase process map is developed that includes the main actors, activities and alignment efforts during research formulation, production and knowledge extension (e.g. dissemination and utilization). The approach focuses on the actors involved in, or interacting with, a research project (the linked actors) and the most likely influential users, who are referred to as potential key users. In the first stage, the investigators of the assessed project are interviewed to develop a preliminary version of the process map and first estimation of research-related contributions. In the second stage, potential key-users and other informants are interviewed to trace, explore and triangulate possible contributions. In the third stage, the presence and role of alignment efforts is analyzed and the preliminary results are shared with relevant stakeholders for feedback and validation. After inconsistencies are clarified or described, the results are shared with stakeholders for learning, improvement and accountability purposes.Conclusion: Contribution Mapping provides an interesting alternative to existing methods that aim to assess research impact. The method is expected to be useful for research monitoring, single case studies, comparing multiple cases and indicating how research can better be employed to contribute to better action for health. © 2012 Kok and Schuit; licensee BioMed Central Ltd

Realising the European network of biodosimetry: RENEB-status quo

Creating a sustainable network in biological and retrospective dosimetry that involves a large number of experienced laboratories throughout the European Union (EU) will significantly improve the accident and emergency response capabilities in case of a large-scale radiological emergency. A well-organised cooperative action involving EU laboratories will offer the best chance for fast and trustworthy dose assessments that are urgently needed in an emergency situation. To this end, the EC supports the establishment of a European network in biological dosimetry (RENEB). The RENEB project started in January 2012 involving cooperation of 23 organisations from 16 European countries. The purpose of RENEB is to increase the biodosimetry capacities in case of large-scale radiological emergency scenarios. The progress of the project since its inception is presented, comprising the consolidation process of the network with its operational platform, intercomparison exercises, training activities, proceedings in quality assurance and horizon scanning for new methods and partners. Additionally, the benefit of the network for the radiation research community as a whole is addressed

A clinically relevant gene signature in triple negative and basal-like breast cancer

Introduction: Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple negative breast cancers (TNBC) are clinically heterogeneous and prognostic markers and biology-based therapies are needed to better treat this disease. Methods: We assembled Affymetrix gene expression data for 579 TNBC and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n = 394 cases for discovery and n = 185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations, including immune cells, blood, adipocytes, stroma, angiogenesis and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed, including routine clinical and pathological variables. Results: Seventy-three percent of TNBC displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (hazard ratio (HR) 0.37, 95% CI 0.22 to 0.61; P < 0.001) and was the only significant predictor in multivariate analysis including routine clinicopathological variables. Conclusions: We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease

Homogeneous Datasets of Triple Negative Breast Cancers Enable the Identification of Novel Prognostic and Predictive Signatures

Background: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes. Methodology/Principal Findings: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases). Conclusions/Significance: Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures