Mathematics difficulties in extremely preterm children : evidence of a specific deficit in basic mathematics processing

Background: Extremely preterm (EP, <26 wk gestation) children have been observed to have poor academic achievement in comparison to their term-born peers, especially in mathematics. This study investigated potential underlying causes of this difficulty. Methods: A total of 219 EP participants were compared with 153 term-born control children at 11 y of age. All children were assessed by a psychologist on a battery of standardized cognitive tests and a number estimation test assessing children’s numerical representations. Results: EP children underperformed in all tests in comparison with the term controls (the majority of Ps < 0.001). Different underlying relationships between performance on the number estimation test and mathematical achievement were found in EP as compared with control children. That is, even after controlling for cognitive ability, a relationship between number representations and mathematical performance persisted for EP children only (EP: r = 0.346, n = 186, P < 0.001; control: r = 0.095, n = 146, P = 0.256). Conclusion: Interventions for EP children may target improving children’s numerical representations in order to subsequently remediate their mathematical skills

BioPhysConnectoR: Connecting Sequence Information and Biophysical Models

<p>Abstract</p> <p>Background</p> <p>One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).</p> <p>A complete, theoretical picture of the selective advantage, and thus a functional annotation, of (co-)mutations is still lacking. Using sequence-based and information theoretical inspired methods we can identify coevolving residues in proteins without understanding the underlying biophysical properties giving rise to such coevolutionary dynamics. Detailed (atomistic) simulations are prohibitively expensive. At the same time reduced molecular models are an efficient way to determine the reduced dynamics around the native state. The combination of sequence based approaches with such reduced models is therefore a promising approach to annotate evolutionary sequence changes.</p> <p>Results</p> <p>With the <monospace>R</monospace> package <monospace>BioPhysConnectoR</monospace> we provide a framework to connect the information theoretical domain of biomolecular sequences to biophysical properties of the encoded molecules - derived from reduced molecular models. To this end we have integrated several fragmented ideas into one single package ready to be used in connection with additional statistical routines in <monospace>R</monospace>. Additionally, the package leverages the power of modern multi-core architectures to reduce turn-around times in evolutionary and biomolecular design studies. Our package is a first step to achieve the above mentioned annotation of coevolution by reduced dynamics around the native state of proteins.</p> <p>Conclusions</p> <p><monospace>BioPhysConnectoR</monospace> is implemented as an <monospace>R</monospace> package and distributed under GPL 2 license. It allows for efficient and perfectly parallelized functional annotation of coevolution found at the sequence level.</p

Barriers to the uptake and use of feedback in the context of summative assessment

Despite calls for feedback to be incorporated in all assessments, a dichotomy exists between formative and summative assessments. When feedback is provided in a summative context, it is not always used effectively by learners. In this study we explored the reasons for this. We conducted individual interviews with 17 students who had recently received web based feedback following a summative assessment. Constant comparative analysis was conducted for recurring themes. The summative assessment culture, with a focus on avoiding failure, was a dominant and negative influence on the use of feedback. Strong emotions were prevalent throughout the period of assessment and feedback, which reinforced the focus on the need to pass, rather than excel. These affective factors were heightened by interactions with others. The influence of prior learning experiences affected expectations about achievement and the need to use feedback. The summative assessment and subsequent feedback appeared disconnected from future clinical workplace learning. Socio-cultural influences and barriers to feedback need to be understood before attempting to provide feedback after all assessments. A move away from the summative assessment culture may be needed in order to maximise the learning potential of assessments

Social Facilitation Due to Online Inter-classrooms Tournaments

In this paper we explore the impact of an inter-classrooms math tournament implemented through internet. The strategy is to increase learning through intra-classroom collaboration generated by inter-classroom competition. Ten fourth grade classes with all their students from eight schools participated. During previous weeks students practiced on-line and played a cloud based board game designed to learn word problems. Afterwards, all students participated on an inter-classroom tournament. They played on-line synchronously during 60 min. The game was played in dyads formed from different schools. The list of each classroom average score was published every 5 min on each student computer. We found an important social facilitation effect: a significant improvement on the performance of male students weak on math, and therefore a reduction on the performance gap between mathematically weak and strong male students. The improvement of female students weak on math was also significant but lower

A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence

On computational approaches for size-and-shape distributions from sedimentation velocity analytical ultracentrifugation

Sedimentation velocity analytical ultracentrifugation has become a very popular technique to study size distributions and interactions of macromolecules. Recently, a method termed two-dimensional spectrum analysis (2DSA) for the determination of size-and-shape distributions was described by Demeler and colleagues (Eur Biophys J 2009). It is based on novel ideas conceived for fitting the integral equations of the size-and-shape distribution to experimental data, illustrated with an example but provided without proof of the principle of the algorithm. In the present work, we examine the 2DSA algorithm by comparison with the mathematical reference frame and simple well-known numerical concepts for solving Fredholm integral equations, and test the key assumptions underlying the 2DSA method in an example application. While the 2DSA appears computationally excessively wasteful, key elements also appear to be in conflict with mathematical results. This raises doubts about the correctness of the results from 2DSA analysis

The emerging role of magnetic resonance imaging and multidetector computed tomography in the diagnosis of dilated cardiomyopathy

Magnetic resonance imaging and multidetector computed tomography are new imaging methods that have much to offer clinicians caring for patients with dilated cardiomyopathy. In this article we briefly describe the clinical, pathophysiological and histological aspects of dilated cardiomyopathy. Then we discuss in detail the use of both imaging methods for measurement of chamber size, global and regional function, for myocardial tissue characterisation, including myocardial viability assessment, and determination of arrhythmogenic substrate, and their emerging role in cardiac resynchronisation therapy

Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families

Digital Versus Analogue Multiplayer Gaming: Comparing Learning Outcomes

In this study, we explore the similarities and differences in learning effects produced by playing a digital and an analogue version of the disruption management game for container terminal operations. We organized the analogue game sessions with students in the United States and digital game sessions with students from Greece. We analysed a postgame survey that captured the learning experiences of the participants to compare the differences and similarities of the learning effects of either game. Based on the results, we conclude that the type of game has limited effect on the learning experience, while incorporation or exclusion of learning principles does have.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Policy AnalysisOrganisation and GovernanceTransport and Plannin