Kaasasündinud N-glükosüülimise haigused Eestis

Väitekirja elektrooniline versioon ei sisalda publikatsiooneKaasasündinud glükosüülimise haigused (KGH) moodustavad kiirelt areneva ainevahetushaiguste grupi ning on põhjustatud valkude ja lipiididega seotud glükaanide häirunud sünteesist. Erinevad valkude N-glükosüülimise haigused on enim diagnoositavad KGH-d ja PMM2-CDG on kõige sagedasem N-glükosüülimise haigus. KGH sümptomid on mittespetsiifilised ja multisüsteemsed. Valikmeetod KGH skriinimiseks on seerumi transferriini isoelektriline fokuseerimine (IEF). Käesoleva uuringu eesmärk oli juurutada Eestis KGH diagnostikaks transferriini IEF ja hinnata kolme aasta jooksul N-glükosüülimise haiguste esinemist meie patsientide hulgas. Kuuel patsiendil 1230-st esines KGH skriiningul positiivne tulemus, mis leidis molekulaarse kinnituse. Esmalt näitasime, et kõige sagedasem KGH Eestis on PMM2-CDG, mida diagnoositi neljal patsiendil kahest perekonnast. Ühe pere lastel väljendub haigus kerge neuroloogilise vormina, kuid normaalse kognitiivse arenguga, mida PMM2-CDG patsientide hulgas esineb harva. Eesti PMM2-CDG patsientidel oli kõige sagedasem variant PMM2 geenis p.Val131Met. Teiseks, esitasime tulemused PMM2-CDG eeldatava sageduse kohta, kasutades Tartu Ülikooli Eesti Geenivaramu andmeid. Leidsime viis erinevat PMM2 heterosügootset mutatsiooni. Kõige sagedasem geenivariant on p.Arg141His kandlussagedusega 1/224. p.Val131Met kandlussagedus on 1/449. Eeldatav PMM2-CDG sagedus Eestis on 1/77,000. Kolmandaks, kirjeldasime patsienti KGH alatüübiga SLC35A2-CDG ning võrdlesime tema fenotüüpi ja genotüüpi 14 rahvusvahelise patsiendi kliiniliste andmetega. Patsientidele on iseloomulik mittespetsiifiline neuroloogiline haigus üldise arengu hilistumise, lihashüpotoonia, krampide ning epileptilise entsefalopaatiaga, düsmorfsed tunnused ja lühike kasv. Lisaks võib transferriini IEF olla vale-negatiivne. Neljandaks, kirjeldasime multisüsteemsete kliiniliste sümptomitega ning uue, seni kirjeldamata KGH alatüübiga patsienti, kellel on KGH alatüübi põhjuseks tõenäoliselt haiguspõhjuslik homosügootne muutus STX5 geenis. Käesolev uuring näitas, et Eesti patsientide puhul on transferriini IEF on tulemuslik meetod KGH diagnostikas. Skriiningu rakendamine võimaldas lisada uusi kliinilisi ja epidemioloogilisi andmeid erinevate teadaolevate ning uue KGH alatüübi kohta.Congenital disorders of glycosylation (CDG) are an expanding group of inherited metabolic diseases caused by impaired synthesis and attachment of glycans on proteins and lipids. Disorders affecting the N-glycosylation pathway form the most common CDG subgroup, and the most common N-glycosylation disorder is PMM2-CDG. The symptoms of different CDG are often non-specific and multisystem. Serum transferrin isoelectric focusing (Tf IEF) is a routine method to screen CDG. The aim of this study was to implement Tf IEF in Estonian clinical practice and to study the presence of N-glycosylation defects among Estonian patients in a three-year screening period. Altogether, positive CDG screening with subsequent molecular confirmation was detected in six patients among 1230 subjects screened. First, the most frequent CDG in Estonia is PMM2-CDG as we diagnosed this disorder in four patients from two families. In one family, the siblings show a mild neurological phenotype with normal-borderline cognitive development, which has previously been seldom described. Among PMM2-CDG patients, the most common variant in PMM2 gene is p.Val131Met. Second, we reported the expected frequency of PMM2-CDG based on the Estonian population data. In this cohort, we identified five different heterozygous variants in PMM2 gene. The most frequent variant is p.Arg141His with carrier frequency 1/224. The carrier frequency for p.Val131Met based on the Estonian population data is 1/449. The expected frequency of PMM2-CDG is 1/77,000. Third, we described a patient with SLC35A2-CDG and compared his phenotype-genotype with 14 international SLC35A2-CDG patients. This type of CDG presents as a non-specific neurological syndrome with global developmental delay, hypotonia, seizures and epileptic encephalopathy, together with dysmorphic features and short stature. In addition, Tf IEF can show a normal profile. Fourth, we presented a patient with multisystem clinical CDG features and a novel type II CDG likely caused by homozygous variant in STX5. In conclusion, Tf IEF proved to be an effective method to detect CDG among Estonian patients. Our results led to many findings, which have helped to add new clinical and epidemiological data about different known types of CDG, but also to expand the group of CDG by the discovery of a new type of CDG

Architecting Smart Home Environments for Healthcare : A Database-Centric Approach

The development of system architectures and applications for smart homes and ambient assisted living has been the main activity of a number of academic and industrial research projects around the world. Existing system architectures for smart environments usually employ different architectural styles in a multi-layer logical architecture to support the integration and interoperation of heterogeneous hardware and software technologies, which are subsequently used to provide two major functionalities: monitoring and assistance. It is also usual among existing architectures that the database management system is the most common but the least exploited architectural component, existing in the periphery of the system and devoted exclusively for data storage and retrieval. However, database technology has advanced and matured considerably over the years, and, as a result, current database management systems can be and do more. This thesis considers the hypothesis of several features of modern database management systems being employed to address functional (e.g. well-being and security monitoring, automated control, data processing) and non-functional (e.g. interoperability, extensibility, data security and privacy) requirements of smart environments, i.e. the database management system serves as a platform for smart environments. The scope of this thesis is therefore to investigate the possibility of using different features supported by database management systems to create a database-centric system architecture for the development of smart home environments and ambient assisted living. The thesis also investigates the development of applications for health monitoring and assistance: 1) a serious game for fall prevention that assists people in practicing Tai Chi at home, and 2) a non-intrusive home-based method for sleep assessment. These features are explored in this thesis to address general functional aspects of smart environments, such as monitoring, processing, coordination and control of various types of events in a given environment. Extensibility and security features and cross-platform capabilities of database management systems are employed to accommodate non-functional, but still technical, properties of smart environments, including interoperability, extensibility, portability, scalability, security and privacy. Heterogeneous technologies are integrated into the system using programming language and platform independent software resource adapters. Interoperation among integrated technologies is mediated in an active database. The feasibility of the proposed database-centric system architecture was pragmatically investigated with the development of a "smart bedroom'' demonstrator and with the implementation of a number of short-term and long-term types of services to support active aging, aging in place and ambient assisted living. In the proposed architecture, active in-database processing maintains sensitive data within the database. This increases data security and independence from external software applications for data analysis. Changes in the system are managed during runtime, which improves flexibility and avoids system downtime. The proposed system architecture was evaluated taking into account different application scenarios and heterogeneous computing platforms. As a conclusion, modern database management systems support features that can be successfully employed in a database-centric system architecture to effectively and efficiently address functional and non-functional requirements of smart environments

Dynamic Management of Input/Output Devices for Wearable Computers

At first, God bless us all. I would like to thank my advisor, Jean-Yves Tigli for his guidance, support and encouragement during the preparation of this dissertation and articles. Words cannot express my appreciation and deepest gratitude to my father, my mother and my brother for their love and emotional support. Thanks to all my family. My special thanks to Diane Lingrand for her support and for the articles. I want to express my gratitude to my friends from Brazil and to my new friends here in France to the moral support. I would like also to thank Celio Trois for his friendship. Finally, thank for all people involved during the academic year. "If the future's looking dark We're the ones who have to shine If there's no one in control"

Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments

Advances in database technology allow modern database systems to serve as a platform for the development, deployment and management of smart home environments and ambient assisted living systems. This work investigates non-functional issues of a database-centric system architecture for smart home environments when: (i) extending the system with new functionalities other than data storage, such as on-line reactive behaviors and advanced processing of longitudinal information, (ii) porting the whole system to different operating systems on distinct hardware platforms, and (iii) scaling the system by incrementally adding new instances of a given functionality. The outcome of the evaluation is demonstrated, and analyzed, for three test functionalities on three heterogeneous computing platforms. As a contribution, this work can help developers in identifying which architectural components in the database-centric system architecture that may become performance bottlenecks when extending, porting and scaling the system

Gait Unsteadiness Analysis from Motion Primitives

The development of intelligent ambulatory monitoring systems and smart living environments is important when considering the aging of society and its implications. This work concerns the use of human motion analysis as a tool for supporting elderly life. Movement recognition has so far been achieved through some form of template matching after manual segmentation or modeling of important features. However, previous works have failed to generalize movement and have only been able to recognize few predetermined activities. To cope with those limitations, this work suggests a new “motion language” approach. To demonstrate the viability and usefulness of this methodology, the concept of “motion primitives” was used to quantitatively analyze gait unsteadiness, which relates to physical condition and cognitive performance. The variability of stride time and temporal walk symmetry between the two feet were measured. Accelerometers were chosen as motion sensors since they offer desirable features in monitoring human movements such as response to both movement frequency and intensity, miniaturization and low power consumption. This study shows that a motion language methodology is capable of quantitatively measuring temporal gait characteristics and providing tools for continuous, unobtrusive, home-based gait analysis.SELIE

Using Smart Virtual-Sensor Nodes to Improve the Robustness of Indoor Localization Systems

Young, older, frail, and disabled individuals can require some form of monitoring or assistance, mainly when critical situations occur, such as falling and wandering. Healthcare facilities are increasingly interested in e-health systems that can detect and respond to emergencies on time. Indoor localization is an essential function in such e-health systems, and it typically relies on wireless sensor networks (WSN) composed of fixed and mobile nodes. Nodes in the network can become permanently or momentarily unavailable due to, for example, power failures, being out of range, and wrong placement. Consequently, unavailable sensors not providing data can compromise the system’s overall function. One approach to overcome the problem is to employ virtual sensors as replacements for unavailable sensors and generate synthetic but still realistic data. This paper investigated the viability of modelling and artificially reproducing the path of a monitored target tracked by a WSN with unavailable sensors. Particularly, the case with just a single sensor was explored. Based on the coordinates of the last measured positions by the unavailable node, a neural network was trained with 4 min of not very linear data to reproduce the behavior of a sensor that become unavailable for about 2 min. Such an approach provided reasonably successful results, especially for areas close to the room’s entrances and exits, which are critical for the security monitoring of patients in healthcare facilities