Prediction of intended career choice in family medicine using artificial neural networks.

Background: Due to the importance of family medicine and a relative shortage of doctors in this discipline, it is important to know how the decision to choose a career in this field is made.

Objective: Since this decision is closely linked to students' attitudes towards family medicine, we were interested in identifying those attitudes that predict intended career choice in family medicine.

Methods: A cross-sectional study was performed among 316 final-year medical students of the Ljubljana Medical Faculty in Slovenia.

Validation of the Slovenian version of patient assessment of chronic illness care (PACIC) in patients with coronary heart disease.

The Chronic Care Model (CCM) is a conceptual framework that supports the evidence-based proactive and planned care of chronic diseases. Our aim was to validate a Slovenian translation of Patient Assessment of Chronic Illness Care (PACIC)--a self-reported instrument designed to measure the extent to which patients with chronic illnesses receive care congruent with CCM--on a sample of patients with coronary heart disease. Secondary analysis of patients' evaluation of general practice care (EPA Cardio study) was done in patients with coronary heart disease in Slovenia.

Final year medical students' understanding of family medicine.

Objective: The European Academy of Teachers in General Practice / Family Medicine (EURACT) has developed an educational agenda, the key document for teaching family medicine in Europe. The aim of our study was to find out how final year medical students at the beginning of their family medicine clerkship understand the discipline of family medicine.

Methods: The attitudes toward family medicine were paraphrased and developed into a 164-item questionnaire, which was administered to 335 final-year medical students at the beginning of their clerkship.

Designable DNA-binding domains enable construction of logic circuits in mammalian cells.

Electronic computer circuits consisting of a large number of connected logic gates of the same type, such as NOR, can be easily fabricated and can implement any logic function. In contrast, designed genetic circuits must employ orthogonal information mediators owing to free diffusion within the cell. Combinatorial diversity and orthogonality can be provided by designable DNA- binding domains.

Markov random field model for segmenting large populations of lipid vesicles from micrographs.

Giant unilamellar lipid vesicles, artificial replacements for cell membranes, are a promising tool for in vitro assessment of interactions between products of nanotechnologies and biological membranes. However, the effect of nanoparticles can not be derived from observations on a single specimen, vesicle populations should be observed instead. We propose an adaptation of the Markov random field image segmentation model which allows detection and segmentation of numerous vesicles in micrographs.