Using High-Content Screening to Generate Single-Cell Gene-Corrected Patient-Derived iPS Clones Reveals Excess Alpha-Synuclein with Familial Parkinson's Disease Point Mutation A30P.

in Cells (2020), 9(9),

The generation of isogenic induced pluripotent stem cell (iPSC) lines using CRISPR-Cas9 technology is a technically challenging, time-consuming process with variable efficiency. Here we use fluorescence ... [more ▼]

The generation of isogenic induced pluripotent stem cell (iPSC) lines using CRISPR-Cas9 technology is a technically challenging, time-consuming process with variable efficiency. Here we use fluorescence-activated cell sorting (FACS) to sort biallelic CRISPR-Cas9 edited single-cell iPSC clones into high-throughput 96-well microtiter plates. We used high-content screening (HCS) technology and generated an in-house developed algorithm to select the correctly edited isogenic clones for continued expansion and validation. In our model we have gene-corrected the iPSCs of a Parkinson's disease (PD) patient carrying the autosomal dominantly inherited heterozygous c.88G>C mutation in the SNCA gene, which leads to the pathogenic p.A30P form of the alpha-synuclein protein. Undertaking a PCR restriction-digest mediated clonal selection strategy prior to sequencing, we were able to post-sort validate each isogenic clone using a quadruple screening strategy prior to generating footprint-free isogenic iPSC lines, retaining a normal molecular karyotype, pluripotency and three germ-layer differentiation potential. Directed differentiation into midbrain dopaminergic neurons revealed that SNCA expression is reduced in the gene-corrected clones, which was validated by a reduction at the alpha-synuclein protein level. The generation of single-cell isogenic clones facilitates new insights in the role of alpha-synuclein in PD and furthermore is applicable across patient-derived disease models. [less ▲]

Using Hypothetical Vacancies in Factorial Surveys to Study Employers' Hiring Decisions – A Valid Approach?

Presentation (2019, July 18)

Factorial survey experiments are increasingly employed by scholars interested in understanding the general mechanisms underlying employers' hiring decisions in relation to specific applicant ... [more ▼]

Factorial survey experiments are increasingly employed by scholars interested in understanding the general mechanisms underlying employers' hiring decisions in relation to specific applicant characteristics. Usually, a sample of human resource professionals is asked to rate the hiring chances of hypothetical applicants for a hypothetical job. However, using hypothetical job descriptions for the evaluation of applicants in factorial surveys may reduce the internal and external validity of the results. For example, employers might apply different evaluation standards when assessing the quality of applicant profiles for a hypothetical job (put less/more weight on certain characteristics) because it is difficult to put themselves in the actual hiring situation – affecting the internal validity. In this paper, we contextualize prior factorial survey experiments by examining whether there is a difference in employers' hiring intentions when confronted with real versus hypothetical hiring problems. Despite the growing number of factorial surveys and the potential implications for the validity of these data, this question has been widely neglected so far. We employ a factorial survey experiment among recruiters in different occupational sectors in Luxembourg. Recruiters evaluate the hiring chances of several profiles of hypothetical applicants with varying characteristics either referring to a real vacancy in their company or to a hypothetical (but similar) job type. Preliminary findings suggest no differences in employers hiring decisions based on the type of evaluation used in the factorial survey. The results partly contradict previous findings from pretest data which showed significant differences between the average hiring chances in the two groups. By examining the internal validity of presenting hypothetical vacancies, this study contributes to methodological research on factorial surveys as well as to the literature studying employers' hiring decisions. [less ▲]

Using interactive items in arithmetic problems to help Grade 3 students shift from intuitive to arithmetic-based strategies and create mental representation.

Poster (2016, July 29)

In 2014, 32% of Grade 3 students in fundamental schools in Luxembourg failed to attain the minimum required skill level in mathematics; rising from 30% of students in 2015, as measured by the Ep.Stan ... [more ▼]

In 2014, 32% of Grade 3 students in fundamental schools in Luxembourg failed to attain the minimum required skill level in mathematics; rising from 30% of students in 2015, as measured by the Ep.Stan examination, a standardized assessment of students at national level. These results have been rather stable since 2011, suggesting that almost 1 in 3 students in grade 3 do not possess the mathematical skills they would need to successfully progress in school. Most students in this bottom tier of performance in mathematics are also found to have low scores in reading skills in the German language (these students also tend to be recent arrivals with a low socio-economic profile) (Martin et al 2014), which as we will see has a compounding effect on their mathematics performance. At the beginning of grade 3 in the fundamental schools in Luxembourg, students begin to delve into the skills needed to solve arithmetic wording problems. That students encounter more barriers to perform highly in the resolution of arithmetic wording problems than in those problems presented in a numeric form is however a well-known fact (Reusser 1990). The needed skills are not only mathematical, but well-developed skills in reading the language are needed, to solve an arithmetic wording problem (LeBlanc & Weber-Russel 1996). Both conditions do not allow the low performing students, who also perform less well in Ep.Stan, to succeed. The purpose of this PhD study will be to measure the impact on the test results from Ep. Stan of the grade 3 students by letting students learn on wording problems that require intuitive strategies at first, up to those needing a more arithmetic strategy through interactive animated items in the digital learning environment MathemaTIC. [less ▲]

Using iterative design and development for mobile learning systems in school projects

in Proceedings of ICEC CELDA 2007 (2007)

Using Log-File Data to Uncover Strategy Use in Complex Problem Solving

Scientific Conference (2018, September 18)

The aim of the current project is to utilize log-file data to enhance the understanding of strategy use in Complex Problem Solving (CPS). CPS can be defined as the ability to manipulate the existing ... [more ▼]

The aim of the current project is to utilize log-file data to enhance the understanding of strategy use in Complex Problem Solving (CPS). CPS can be defined as the ability to manipulate the existing variables of a particular novel, complex, intransparent, and dynamic environment successfully in order to reach a predefined goal. In order to successfully solve a CPS task, the goal-directed application and variation of certain strategies is necessary. To uncover the systematic use of these strategies, log-files have been deemed a fruitful resource as they contain not only the final results of a computer-based CPS item, but also the individual steps undertaken while solving such a task. Recent studies using log-files have highlighted the importance of some strategies for CPS, like the varying one variable at a time (VOTAT) strategy, or of engaging in noninterfering observations (i.e., idle rounds). In addition, other strategies have also been shown to be relevant in neighboring fields of CPS. However, comprehensive studies investigating a broad repertoire of strategies applied in CPS are scarce. Hence, on the basis of existing large-scale assessment data sets, the present project set out to investigate which strategies hidden in log-files are relevant for solving a CPS task in order to gain a more thorough understanding of how CPS tasks are being approached. Preliminary findings indicate that, in addition to VOTAT and idle rounds, particularly the flexibility of switching between strategies should be taken into account. [less ▲]

Using Machine Learning to Speed Up the Design Space Exploration of Ethernet TSN networks

Report (2019)

In this work, we ask if Machine Learning (ML) can provide a viable alternative to conventional schedulability analysis to determine whether a real-time Ethernet network meets a set of timing constraints ... [more ▼]

In this work, we ask if Machine Learning (ML) can provide a viable alternative to conventional schedulability analysis to determine whether a real-time Ethernet network meets a set of timing constraints. Otherwise said, can an algorithm learn what makes it difficult for a system to be feasible and predict whether a configuration will be feasible without executing a schedulability analysis? In this study, we apply standard supervised and unsupervised ML techniques and compare them, in terms of their accuracy and running times, with precise and approximate schedulability analyses in Network-Calculus. We show that ML techniques are efficient at predicting the feasibility of realistic TSN networks and offer new trade-offs between accuracy and computation time especially interesting for design-space exploration algorithms. [less ▲]

Using metabolic networks to resolve ecological properties of microbiomes

in Current Opinion in Systems Biology (2018)

The systematic collection, integration and modelling of high-throughput molecular data (multi-omics) allows the detailed characterisation of microbiomes in situ. Through metabolic trait inference ... [more ▼]

The systematic collection, integration and modelling of high-throughput molecular data (multi-omics) allows the detailed characterisation of microbiomes in situ. Through metabolic trait inference, metabolic network reconstruction and modelling, we are now able to define ecological interactions based on metabolic exchanges, identify keystone genes, functions and species, and resolve ecological niches of constituent microbial populations. The resulting knowledge provides detailed information on ecosystem functioning. However, as microbial communities are dynamic in nature the field needs to move towards the integration of time- and space-resolved multi-omic data along with detailed environmental information to fully harness the power of community- and population-level metabolic network modelling. Such approaches will be fundamental for future targeted management strategies with wide-ranging applications in biotechnology and biomedicine. [less ▲]

Using mobile phone data for urban network state estimation

Scientific Conference (2018, June)

Using modern technology to support museum activities. Case study: Estonians Deported to Siberia: Soviet Red Terror 1940-1960

in Proceedings of ICOM, Milano 2016 (2016)

Using multi-member panels to tackle RSD complexities

in Forced Migration Review (2020), (65), 32-35