Set up and run an objective structured clinical exam.

Objective structured clinical exams are increasingly used as a way of assessing a range of clinical skills at both undergraduate and postgraduate level. To those planning to introduce such assessments, this article provides basic guidance on their development and structure and the personnel required. For those already using the assessments, our article may provide new ideas or be the impetus for an exchange of ideas. For those who are facing such formal assessment as candidates, we hope this article shows the efforts that are made to achieve the necessary structure and objectivity in this type of examination.     

The objective structured interview for medical student selection

An objective structured interview is an integral part of the process of selecting and admitting applicants to study medicine at this university. During the nine years (to the end of 1986) that the interview has been used 1600 candidates were interviewed out of roughly 13 000 applicants, and from these, 584 students were admitted to the course. Analysis of the interview data was carried out based on two aspects of student progress: graduation with honours and failure to complete the course of study.The interview as a whole, and especially some of the subscales, appears to identify students who may fail to complete the course: it may also help to predict which students are likely to graduate with honours.     

Canadian experience with structured clinical examinations.

The use of structured clinical examinations to improve the evaluation of medical students and graduates has become significantly more common in the past 25 years. Many Canadian medical educators have contributed to the development of this technique. The Canadian experience is reviewed from the introduction of simulated-standardized patients and objective-structured clinical examinations to more recent developments and the use of such examinations for licensure and certification.     

Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data

MOTIVATION: Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challenges arise and these have not been addressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients. RESULTS: In this paper we describe a novel algorithm called Structured Analysis of Microarrays (StAM), which accounts for molecular heterogeneity of complex clinical phenotypes. Our algorithm goes beyond established methodology in several aspects: in addition to the expression data, it exploits functional annotations from the Gene Ontology database to build biologically focussed classifiers. These are used to uncover potential molecular disease subentities and associate them to biological processes without compromising overall prediction accuracy. AVAILABILITY: Bioconductor compliant R package SUPPLEMENTARY INFORMATION: Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/lottaz05.     

Assessment of sleep in subjects with visual impairment: Comparison using subjective and objective methods

The objective of the present study was to verify the agreement between objective and subjective measures of sleep in people with and without visual impairment. Thirty-seven subjects with visual impairment participated in the study (19 blind without light perception and 18 low-vision), as well as 34 subjects with normal vision, with paired age and gender characteristics. For the subjective sleep evaluation, we used the Sleep Quality Index—PSQI and for the objective evaluation we used the ActiGraph GT3X+. Among the three analyzed groups, the blind was the only ones who presented differences between subjective and objective sleep duration (p = 0.021). Furthermore, the concordance between subjective and objective sleep duration (ICC = 0.388; p = 0.108) was not observed in blind subjects, and a greater variability of differences in sleep duration between the two methods was observed by the Bland Altman scatter plot. We concluded that the sleep duration obtained by PSQI did not show agreement for the objective sleep duration in blind subjects without light perception.     

Assessment of sperm functional competence and sperm-egg interaction

A precise understanding in the functional competence of mammalian sperm is essential to generate clinical advances for the treatment of infertility and novel contraceptive strategies. The fundamental knowledge on the controlling parameters for spermatozoal activation process will help in the identifying the causes in fertilization failure due to male factor as well as in developing male contraceptive methodologies. The defects in the sperm-egg interaction seem to be one of the controlling mechanisms, however, none of the presently available methods for the evaluation of the fertilizing ability of sperm precisely indicates the reason for the failure or the success of sperm entry into egg. Adequate number of motile spermatozoa with normal morphology and timely occurrence of acrosome reaction are presumably the major prerequisites for the penetration through the egg investments. The present communication briefly reviews some of the main features of mammalian sperm which control the success or the failure of fertilization and existing clinical methods indicating the lack of fundamental knowledge on the sub-cellular and molecular aspects of this unique and species-specific cell-cell interaction.     

Assessment of lignocellulosic biorefineries in Germany using a hybrid LCA multi‐objective optimization model

In this study a tiered hybrid life cycle assessment (LCA) multi‐objective optimization model is developed and applied to determine the optimal choice of new biorefinery technologies in Germany. Thereby, several aspects can be explicitly addressed, including a regionally differentiated accountability of sustainable feedstock availability, identification of environmental impacts along global value chains, and identification of trade‐offs between different sustainability goals. The model is applied to assess the optimal choice between two lignocellulosic biorefinery concepts. Two optimization objectives are taken into account: maximizing the investor's profit and minimizing global impacts on climate change related to a specified demand for products. In terms of environmental impacts, the model also takes into account the comparison of new biorefineries with current available technologies producing the specified final demand. The results of the case study show that the biorefinery concept including the ethylene production is more beneficial in terms of reducing climate impacts, while on the other hand the biorefinery including the ethanol production is more cost‐effective. Depending on the decision‐maker's preference on weighting the two objectives, different capacities of biorefineries and optimal locations in Germany are identified. Furthermore, regions in Germany providing the necessary biomass feedstock can be identified on a county level. Finally, we argue that the extension of LCA by multi‐objective optimization is well suited guiding the way toward well‐informed decision‐making in the field of technological choices.     

Estimation of kinetic parameters in a structured yeast model using regularisation.

In this work, a procedure for estimating kinetic parameters in biochemically structured models was developed. The approach is applicable when the structure of a kinetic model has been set up and the kinetic parameters should be estimated. The procedure consists of five steps. First, initial values were found in or calculated from literature. Hereafter using sensitivity analysis the most sensitive parameters were identified. In the third step physiological knowledge was combined with the parameter sensitivities to manually tune the most sensitive parameters. In step four, a global optimisation routine was applied for simultaneous estimation of the most sensitive parameters identified during the sensitivity analysis. Regularisation was included in the simultaneous estimation to reduce the effect of insensitive parameters. Finally, confidence intervals for the estimated parameters were calculated. This parameter estimation approach was demonstrated on a biochemically structured yeast model containing 11 reactions and 37 kinetic constants as a case study.