Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer--comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial.

Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age <35 years, (ii) grade 3, (iii) human epithelial growth factor receptor-2 positivity, (iv) vascular invasion, (v) progesterone receptor negativity, (vi) grade 2 tumors >2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as OS

Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial

Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age 2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as O

Анализ применимости численных алгоритмов для моделирования процессов в топке котла с циркулирующим кипящим слоем

Моделирование различных задач связано с решением систем дифференциальных уравнений с большим числом неизвестных, что приводит к их упрощению и соответственно отражается на качестве расчета. Данная работа направлена на оценку применимости тех или иных математических алгоритмов для получения качественного моделирования процессов в энергетических котлах с циркулирующим кипящим слоемModeling of various tasks related to the solution of systems of differential equations with a large number of unknowns, which leads to their simplification and, accordingly, affect the quality of the calculation. This work aims to assess the applicability of those or other mathematical algorithms to obtain a quantitative simulation of processes in power boilers with circulating fluidized bed

Kinetic oxygen measurements by CVC96 in L-929 cell cultures

Generally animal and human cells use oxygen during their whole life. Consequently the oxygen use is a simple indicator to test the vitality of cells. When the vitality decreases by the delivery of toxic substances the decrease can be observed directly by the oxygen-use of the cells. To get fast information of the vitality of cells we have measured the O(2)-tension by testing a new model of a bioreactor, the Cell Vitality Checker 96 (CVC96), in practical application. With this CVC96, soon a simple test will exist for the measurement of the oxygen use. In this respect the question had to be answered whether the use in the laboratory is easy and whether oxygen as a parameter in the vitality test can also be applied in future for problems in the field of material testing

The interpretations and uses of fitness landscapes in the social sciences

__Abstract__ This working paper precedes our full article entitled “The evolution of Wright’s (1932) adaptive field to contemporary interpretations and uses of fitness landscapes in the social sciences” as published in the journal Biology & Philosophy (http://link.springer.com/article/10.1007/s10539-014-9450-2). The working paper features an extended literature overview of the ways in which fitness landscapes have been interpreted and used in the social sciences, for which there was not enough space in the full article. The article features an in-depth philosophical discussion about the added value of the various ways in which fitness landscapes are used in the social sciences. This discussion is absent in the current working paper. Th

The Digital Transformation of Search and Recombination in the Innovation Function: Tensions and an Integrative Framework*

Search and recombination are important mechanisms in the creativity phase of innovation. Digital transformation and the resulting pervasive digitalization of the innovation function have often been associated with increasing possibilities for search and recombination. In this paper, by systematically integrating the search and recombination literature with the literature on digitalization, we demonstrate that digitalization may engender new idiosyncratic tensions in the organizational antecedents of search and recombination and, by implication, in their likely outcomes. We propose that, depending on the interactions among the idiosyncratic tensions identified herein, knowledge recombination might spur very different outcomes, including knowledge layering, knowledge integration, knowledge grafting, or even no recombination at all (which we label “search for the sake of search”). These outcomes may not always be the initially planned desired outcomes. Finally, we provide implications of our integrative framework pertaining to product development and to organizing for innovation

From green technology development to green innovation: inducing regulatory adoption of pathogen detection technology for sustainable forestry

Technological entrepreneurship has been widely acknowledged as a key driver of modern industrial economies, and more recently, a panacea for environmental and social problems. However, our current understanding of how green-technology ventures emerge and diffuse more sustainable innovations remains limited. We advance theory on green entrepreneurship by drawing on institutional work to refine and extend our understanding of how entrepreneurs may influence government policies and practices in their attempts to diffuse green technology. We develop a theoretical framework that combines institutional work with a search tool, the technological, commercial, organizational, and societal (TCOS) framework of innovative uncertainties, which identifies key opportunities, hurdles, and potential unintended consequences at early stages of technology development. We present a detailed case study of a potential university-based green-tech venture developing pathogen detection technology for forestry protection. Foreign pathogens spread by international trade can have major detrimental impacts on forests and the industries that rely on them. Our analysis found that green technology demonstrating technological feasibility is necessary but not sufficient; green-tech ventures must also engage in institutional work, in this case, articulating the technology’s benefits to regulators to establish legitimacy and avoid misuse that can hinder its adoption. We thus add to previous studies by emphasizing that institutional work could be a main activity for a green-tech venture, a core entrepreneurial strategy rather than an afterthought