Biology subjects

Konstantinidis, E.

Publications and source records attributed to Konstantinidis, E..

2 recordsLinked to original sources

bioRxiv2017

Targeted gene correction of FKRP by CRISPR/Cas9 restores functional glycosylation of α-dystroglycan in cortical neurons derived from human induced pluripotent stem cells

Mutations in genes required for functional glycosylation of -dystroglycan cause a group of congenital muscular dystrophies associated with brain malformations, referred to as dystroglycanopathies. The lack of isogenic, physiology-relevant human cellular models has limited our understanding of the cortical abnormalities in dystroglycanopathies. Here we generate induced pluripotent stem cells (iPSCs) from a severe dystroglycanopathy patient with homozygous mutations in the ribitol-5-phosphate transferase gene, FKRP. We carry out targeted gene correction in FKRP-iPSCs using CRISPR/Cas9-mediated genome editing. We characterise the directed differentiation of FKRP- and corrected-iPSCs to neural stem cells, cortical progenitors and cortical neurons. Importantly, we show that targeted gene correction of FKRP restores functional glycosylation of -dystroglycan in iPSC-derived cortical neurons. We independently validate this result by showing targeted gene mutation of FKRP disrupts functional glycosylation of -dystroglycan. This work demonstrates the feasibility of using CRISPR/Cas9-engineered human iPSCs for modelling dystroglycanopathies and provides a foundation for therapeutic development.\n\nHighlightsO_LIGeneration of FKRP-iPSCs for modelling cortical abnormalities in dystroglycanopathies\nC_LIO_LIPrecise gene correction by CRISPR/Cas9-mediated genome editing\nC_LIO_LIDirected differentiation of isogenic control and FKRP-iPSC to cortical neurons\nC_LIO_LIFunctional glycosylation of -dystroglycan is restored in cortical neurons derived from CRISPR/Cas9-corrected iPSCs\nC_LIO_LITargeted gene mutation of FKRP disrupts functional glycosylation of -dystroglycan in cortical neurons\nC_LI

molecular biology↗

bioRxiv2016

Putting bandits into context: How function learning supports decision making

We introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximise their rewards. The options are described by a number of contextual features which are predictive of the rewards through initially unknown functions. From their experience with choosing options and observing the consequences of their decisions, participants can learn about the functional relation between contexts and rewards and improve their decision strategy over time. In three experiments, we explore participants behaviour in such learning environments. We predict participants behaviour by context-blind (mean-tracking, Kalman filter) and contextual (Gaussian process and linear regression) learning approaches combined with different choice strategies. Participants are mostly able to learn about the context-reward functions and their behaviour is best described by a Gaussian process learning strategy which generalizes previous experience to similar instances. In a relatively simple task with binary features, they seem to combine this learning with a \"probability of improvement\" decision strategy which focuses on alternatives that are expected to lead to an improvement upon a current favourite option. In a task with continuous features that are linearly related to the rewards, participants seem to more explicitly balance exploration and exploitation. Finally, in a difficult learning environment where the relation between features and rewards is non-linear, some participants are again well-described by a Gaussian process learning strategy, whereas others revert to context-blind strategies.

animal behavior and cognition↗