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Orlov, P.

Publications and source records attributed to Orlov, P..

2 recordsLinked to original sources

Zooming into rearranged genome: applying pipeline of cytological, genomic, and transcriptomic methods for structural variant interpretation

Recent advances in genomic technologies have greatly enhanced our understanding of genotype-phenotype relationships and improved diagnostic of genetic diseases. However, the dissection of complex structural variants remains challenging due to the limitations of current methods in resolving their breakpoint and interpreting phenotypes involving multiple disrupted genes. In this study, we demonstrate how an integrative approach--combining cytological, genomic, and transcriptomic methods--enables the detection, structural and functional characterization of a complex structural variants affecting the MBD5, USP34, and XPO1 genes. Our findings underscore the utility of the Exo-C, a modified chromosome conformation capture technique, in resolving complex rearrangements. We also report, for the first time, a composite neurodevelopmental phenotype resulting from the combined effects of MBD5-associated intellectual disability and 2p15p16.1 microdeletion syndromes.

genomics↗

Natural Gaze Data Driven Wheelchair

Natural eye movements during navigation have long been considered to reflect planning processes and link to users future action intention. We investigate here whether natural eye movements during joystick-based navigation of wheel-chairs follow identifiable patterns that are predictive of joystick actions. To place eye movements in context with driving intentions, we combine our eye tracking with a 3D depth camera system, which allows us to identify which eye movements have the floor as gaze target and distinguish them from other non-navigation related eye movements. We find consistent patterns of eye movements on the floor predictive of steering commands issued by the driver in all subjects. Based on this empirical data we developed two gaze decoders using supervised machine learning techniques and enabled each of these drivers to then steer the wheelchair by imagining they were using a joystick to trigger appropriate natural eye movements via motor imagery. We show that all subjects are able to navigate their wheelchair \"by eye\" learning it within a short time span of minutes. Our work shows that simple gaze-based decoding without need for artificial user interfaces suffices to restore mobility and increasing participation in daily life.

bioengineering↗