Problem formulation by medical students: an observation study

<p>Abstract</p> <p>Background</p> <p>Medical problems are often complex and ill-structured. In formulating the problem, one has to discriminate pertinent elements from irrelevant information in order to effectively find a solution. In this observation study, we describe how medical students formulate the problem of a complex case.</p> <p>Methods</p> <p>32 third year medical students were presented with a complex case of endocarditis. They were asked to synthesize the case and give the best formulation of the problem. They were then asked to provide a diagnosis. A subsequent group of 25 students were presented with the problem already formulated and were also asked for the diagnosis. We analyzed the student's problem formulations using the presence or absence of essential elements of the case, the use of higher-order concepts and the use of relations between concepts.</p> <p>Results</p> <p>12/32 students presented with the case made the correct diagnosis. Diagnostic accuracy was significantly associated with the use of higher-order concepts and relations between concepts. Establishing explicit relations was particularly important. Almost all students who missed the diagnosis could not elicit any relations between concepts but only reported factual observations. When presented with an already formulated problem, 19/25 students made the correct diagnosis. (p < 0.05)</p> <p>Conclusion</p> <p>When faced with a complex new case, students may not have the structured knowledge to recognize the nature of the problem. They have to build new schema or problem representation. Our observations suggest that this process involves using higher-order concepts and establishing new relations between concepts. The fact that students could recognize the disease when presented with a formulated problem but had more difficulty when presented with the original complex case indicates that knowledge of the clinical features may be necessary but not sufficient for problem formulation. Our hypothesis is that problem formulation represents a distinct ability.</p

Medulloblastoma Exome Sequencing Uncovers Subtype-Specific Somatic Mutations

Medulloblastomas are the most common malignant brain tumors in children1. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles2–5. Here, we utilized whole exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, novel findings in medulloblastoma. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma

Dynamic landscape modelling: The quest for a unifying theory

International audienceIn the past 30 years, the notion of landscape has emerged in ecology as a result of both theoretical considerations and practical aspects of land use and land cover. This has generated a variety of numerical models addressing both methodological and thematic objectives. Scientists model landscapes for at least two reasons: to better understand the landscape dynamics themselves (called intrinsic needs) and to offer a realistic frame to support other ecological processes (extrinsic needs). This paper mainly concerns the intrinsic needs; it reviews and discusses the way the socioeconomic and/or ecological mechanisms of various landscapes have been explored through modelling approaches in the past. Our objective is to identify the possible lack of understanding in landscape dynamics and to propose a unified view of this complex object. We outline the links between the concepts of landscape and of models using a double-entry matrix, focusing on one hand on the four main terrestrial landscapes (agricultural, forested, arid and urban) and on the other hand on the main landscape model characteristics (explicit or neutral, patchy or continuous, and multi- or mono-scale). The patterns and processes of each of the four landscape types, in particular, are analysed within a coherent framework. The heterogeneity of this yet coherent analytical matrix implies the need for unifying concepts and formalisms. The complexity theory and related concepts such as self-organization or formal grammar applied to landscape mosaics could help to further develop the mathematical formalisms necessary to assemble the various inner landscape processes. The discipline can now offer a theoretical dimension to dynamic landscape modelling aiming at understanding the mechanism unity underlying this complex objec

Innovative Methodology Normalizing genes for quantitative RT-PCR in differentiating human intestinal epithelial cells and adenocarcinomas of the colon

quantitative RT-PCR in differentiating human intestinal epithelial cells and adenocarcinomas of the colon. Am J Physiol Gastrointest Liver Physiol 290: G1067–G1074, 2006. First published January 6, 2006; doi:10.1152/ajpgi.00234.2005.—As for other mRNA measurement methods, quantitative RT-PCR results need to be normalized relative to stably expressed genes. Widely used normalizing genes include �-actin and glyceraldehyde-3-phosphate dehydrogenase. It has, however, become clear that these and other normalizing genes can display modulated patterns of expression across tissue types and during complex cellular processes such as cell differentiation and cancer progression. Our objective was to set the basis for identifying normalizing genes that displayed stable expression during enterocytic differentiation and between healthy tissue and adenocarcinomas of the human colon. We thus identified novel potential normalizing genes using previously generated cDNA microarray data and examined th

Nigral Glutamatergic Neurons Control the Speed of Locomotion

The mesencephalic locomotor region (MLR) plays a crucial role in locomotor control. In vertebrates, stimulation of the MLR at increasing intensities elicits locomotion of growing speed. This effect has been presumed to result from higher brain inputs activating the MLR like a dimmer switch. Here, we show in lampreys (Petromyzon marinus) of either sex that incremental stimulation of a region homologous to the mammalian substantia nigra pars compacta (SNc) evokes increasing activation of MLR cells with a graded increase in the frequency of locomotor movements. Neurons co-storing glutamate and dopamine were found to project from the primal SNc to the MLR. Blockade of glutamatergic transmission largely diminished MLR cell responses and locomotion. Local blockade of D-1 receptors in the MLR decreased locomotor frequency, but did not disrupt the SNc-evoked graded control of locomotion. Our findings revealed the presence of a glutamatergic input to the MLR originating from the primal SNc that evokes graded locomotor movements