Helle Rootzén

Why did the breast cancer lymph node status distribution improve in Denmark in the pre-mammography screening period of 1978–1994?

Abstract Background. Danish breast cancer patients diagnosed in 1978–1994 experienced a trend over time towards a more favourable distribution of lymph node status at time of diagnosis, which was not due to mammography screening. We investigated how this trend could be explained by patient characteristics at diagnosis: age (biological processes), calendar period (e.g. environmental changes), birth cohort (living conditions over a life time), post-menopausal status (a predictor of less favourable nodal status), and tumour diameter (a marker of detection time). Material and methods. The data set consisted of 22 955 patients aged 30–69 years at time of diagnosis with known lymph node status, known tumour diameter, known menopausal status, and clinically detected tumours, available from the Danish Breast Cancer Cooperative Group (DBCG). Age, period, cohort, menopausal status, and tumour diameter were used as predictors in generalised linear models with either node-positive status (at least one of the excised lymph nodes being tumour-positive) or severely node-positive status (at least half of the excised lymph nodes being tumour-positive) as outcomes. Lymph node status was assessed both empirically and estimated using an EM algorithm in order to reduce misclassification. Results and discussion. We found that the improved lymph node status distribution was most likely a period effect due to a combination of earlier detection of clinical tumours, explaining most of the trend in node-positive breast cancer and half of the trend in severely node-positive breast cancer, and some unknown factor affecting lymph node status but not necessarily other tumour characteristics.

Space-time modeling of environmental monitoring data

This study describes and applies statistical methods for space-time modeling of data from environmental monitoring programs, e.g., within areas such as climate change, air pollution and aquatic environment. Such data are often characterized by sparse sampling in both the temporal and spatial dimensions. In order to improve the amount of information on the physical system in question we suggest using statistical modeling methods for monitoring data. Model predictions combined with observations could be analyzed directly to assess the environmental state or as forcing functions for time series models and deterministic, hydrodynamic models. To illustrate the approach we applied the proposed modeling methods to data from the Danish and Swedish marine monitoring programs. Time series with a weekly resolution were predicted from observations of dissolved inorganic nitrogen (DIN) from the Kattegat basin (1993–1997). DIN observations were sparse, irregularly distributed and comprised approximately 10% of the generated time series.

A Methodology for Development of a Pedagogical Simulation Tool used in Fermentation Applications

Abstract In this work, a holistic methodology was developed and implemented in a computeraided framework with the purpose of establishing a pedagogical simulation tool for bioprocess applications. The methodology integrates the development of a process simulator with the use of gamification elements to improve the pedagogical experience. Moreover, model development and reuse was incorporated into the framework through creating a generic model template. The application of the methodology was demonstrated by the simulation of a batch fermentation process of Saccharomyces cerevisiae cultivated under aerobic conditions with glucose as substrate, thereby, demonstrating mixed metabolism dynamics and considering the inhibition of ethanol consumption due to the presence of glucose with an integrated learning design and gamification elements. The learning experience, done with beta users with different previous levels of knowledge about fermentation processes, confirmed an interest for using gamification for training chemical engineering, biochemical engineering, and biotechnology students.

Statmaster and HEROS: Web-based Courses First and Second Generation

With the increasing focus on life-long learning, and with the convenience and accessibility of the Internet, the market for web-based courses has expanded vastly in recent times – in particular in connection with continuing education. However, teaching web-based courses presents various technical as well as pedagogical challenges. Some of these challenges are addressed, and means to dealing with them are suggested. A second generation of web-based courses is comprised of learning objects, which allows for tailoring courses for specialized groups of students, and accommodate individualized learning. The concept of learning objects and how they are used to form new courses are discussed.

Minisymposium Web Based Courses: Reaching a Distributed Audience

In this minisymposium we discussed the challenge of web based solutions in organizing education in modelling and applied mathematics. The cutting edge knowledge in the art of mathematical technology is located in small nodes, research groups on applied mathematics, mathematical physics, scientific computing etc. Web-technologies are a viable media for innovative processes and knowledge transfer. Virtual educational environments enable novel solutions to training and education, they help to facilitate distributed processes and provide access to educational resources. Interactive cross-media allows easy time- and location-independent access and portability, flexible updates and the benefits of media technology, hypertext properties, animations etc. An evolution of educational methods, materials and means of delivery is taking place.