We describe the development of a cyber-physical system (Rehab Tracker) for improving patient compliance with at-home physical rehabilitation using neuromuscular electrical stimulation (NMES) therapy. Rehab Tracker consists of three components: 1) hardware modifications to sense and store use data from an FDA-approved NMES therapy device and provide Bluetooth communication capability, 2) an iOS-based smartphone/tablet application to receive and transmit NMES use data and serve as a conduit for patient-provider interactions and 3) a back-end server platform to receive device use data, display compliance data for provider review and provide automated positive and remedial push notifications to patients to improve compliance. This system allows for near real-time compliance monitoring via a secure web portal and offers a novel conduit for patient-provider communication during at-home rehabilitation to improve compliance. The system was tested in patients (n=5) who suffered anterior cruciate ligament rupture and surgical repair to provide proof-of-principal evidence for system functionality and an initial assessment of system usability. The system functioned as designed, recording 89% of rehabilitation sessions. Thus, Rehab Tracker is a functionally correct system with the potential to be used as a tool for studying NMES and mobile communication methodologies at scale and improving compliance with at-home rehabilitation programs.

Although research has identified critical thinking (CT) as an objective of higher education, limited quantitative research has focused on how postsecondary instructors view using handheld devices for classroom collaboration to support CT. There are studies examining how the use of tablet technologies influence collaborative learning (CL), showing a link between CL and CT, and connecting CT to academic achievement. However, understanding how instructors perceive the intersection of these factors has not been well studied. Applying Vygotsky's social cognitive theory as a foundation of CL, using adapted questions from two questionnaires (Technology Acceptance Model and Cooperative Learning Implementation) and two frameworks, this quantitative survey study examined the relationship between tablet application and implementation of CL, and then between CL implementation and the development of CT dispositions (CTD). An email with a link to the survey was sent to a population of 1,932 instructors in a professional education technology organization. From a sample of 59, the key findings indicated instructors accepted the use and usefulness of tablets in the classroom, and used applications for completing collaborative tasks. The Pearson's product moment correlations between tablets and CL, acceptance and implementation appear to be affected by instructor's professional views and teaching practices. Perceptions about the development of CTD were positive with limitations of statistical significance. Results of this study may provide insights into using tablets in effective ways to enhance learning outcomes as one social benefit. Improving the CT of students may support developing citizens who contribute to communities and society in positive ways as lifelong learners.

The aim of this study was to investigate the perception of personalization on news applications and to examine to what extent it is seen as an optimal solution for users to receive information. Due to the growth of online news and digital journalism the amount of information that is being published online is significantly higher nowadays than it has previously been. Therefore, a recommendation system called personalization has been introduced to choose content for the reader. Many concerns of personalization have already been brought to light, these concerns are believed to be contributing to filter bubbles and echo chambers. This study will investigate these concerns further in order to understand the users. The methodology used in the study were semi-structured interviews and an analysis based on the concerns brought forward by Borgesius et al. Six interviews were conducted with users and two were conducted with major news organizations in Sweden. The results of the study indicate that users fear personalization will cause filter bubbles and polarization due to them only being subjected to one perspective. The users are unaware as to how personalization works and therefore question why it is being introduced into news applications. Due to personalization being a new phenomenon news applications it is not yet seen as an optimal solution by users or news organizations. There are, however, many factors that can assist in its development such as transparency and awareness of the phenomenon.

Le temps de mise sur le marché et les coûts d’implantation sont les deux critères principaux à prendre en compte dans l'automatisation du processus de conception de systèmes numériques. Les applications de traitement du signal utilisent majoritairement l'arithmétique virgule fixe en raison de leur coût d'implantation plus faible. Ainsi, une conversion en virgule fixe est nécessaire. Cette conversion est composée de deux parties correspondant à la détermination du nombre de bits pour la partie entière et pour la partie fractionnaire. Le raffinement d'un système en virgule fixe nécessite d'optimiser la largeur des données en vue de minimiser le coût d'implantation tout en évitant les débordements et un bruit de quantification excessif. Les applications dans les domaines du traitement d'image et du signal sont tolérantes aux erreurs si leur probabilité ou leur amplitude est suffisamment faible. De nombreux travaux de recherche se concentrent sur l'optimisation de la largeur de la partie fractionnaire sous contrainte de précision. La réduction du nombre de bits pour la partie fractionnaire conduit à une erreur d'amplitude faible par rapport à celle du signal. La théorie de la perturbation peut être utilisée pour propager ces erreurs à l'intérieur des systèmes à l'exception du cas des opérations un- smooth, comme les opérations de décision, pour lesquelles une erreur faible en entrée peut conduire à une erreur importante en sortie. De même, l'optimisation de la largeur de la partie entière peut réduire significativement le coût lorsque l'application est tolérante à une faible probabilité de débordement. Les débordements conduisent à une erreur d'amplitude élevée et leur occurrence doit donc être limitée. Pour l'optimisation des largeurs des données, le défi est d'évaluer efficacement l'effet des erreurs de débordement et de décision sur la métrique de qualité associée à l'application. L'amplitude élevée de l'erreur nécessite l'utilisation d'approches basées sur la simulation pour évaluer leurs effets sur la qualité. Dans cette thèse, nous visons à accélérer le processus d'évaluation de la métrique de qualité. Nous proposons un nouveau environnement logiciel utilisant des simulations sélectives pour accélérer la simulation des effets des débordements et des erreurs de décision. Cette approche peut être appliquée à toutes les applications de traitement du signal développées en langage C. Par rapport aux approches classiques basées sur la simulation en virgule fixe, où tous les échantillons d'entrée sont traités, l'approche proposée simule l'application uniquement en cas d'erreur. En effet, les dépassements et les erreurs de décision doivent être des événements rares pour maintenir la fonctionnalité du système. Par conséquent, la simulation sélective permet de réduire considérablement le temps requis pour évaluer les métriques de qualité des applications. De plus, nous avons travaillé sur l'optimisation de la largeur de la partie entière, qui peut diminuer considérablement le coût d'implantation lorsqu'une légère dégradation de la qualité de l'application est acceptable. Nous exploitons l'environnement logiciel proposé auparavant à travers un nouvel algorithme d'optimisation de la largeur des données. La combinaison de cet algorithme et de la technique de simulation sélective permet de réduire considérablement le temps d'optimisation. / Time-to-market and implementation cost are high-priority considerations in the automation of digital hardware design. Nowadays, digital signal processing applications use fixed-point architectures due to their advantages in terms of implementation cost. Thus, floating-point to fixed-point conversion is mandatory. The conversion process consists of two parts corresponding to the determination of the integer part word-length and the fractional part world-length. The refinement of fixed-point systems requires optimizing data word -length to prevent overflows and excessive quantization noises while minimizing implementation cost. Applications in image and signal processing domains are tolerant to errors if their probability or their amplitude is small enough. Numerous research works focus on optimizing the fractional part word-length under accuracy constraint. Reducing the number of bits for the fractional part word- length leads to a small error compared to the signal amplitude. Perturbation theory can be used to propagate these errors inside the systems except for unsmooth operations, like decision operations, for which a small error at the input can leads to a high error at the output. Likewise, optimizing the integer part word-length can significantly reduce the cost when the application is tolerant to a low probability of overflow. Overflows lead to errors with high amplitude and thus their occurrence must be limited. For the word-length optimization, the challenge is to evaluate efficiently the effect of overflow and unsmooth errors on the application quality metric. The high amplitude of the error requires using simulation based-approach to evaluate their effects on the quality. In this thesis, we aim at accelerating the process of quality metric evaluation. We propose a new framework using selective simulations to accelerate the simulation of overflow and un- smooth error effects. This approach can be applied on any C based digital signal processing applications. Compared to complete fixed -point simulation based approaches, where all the input samples are processed, the proposed approach simulates the application only when an error occurs. Indeed, overflows and unsmooth errors must be rare events to maintain the system functionality. Consequently, selective simulation allows reducing significantly the time required to evaluate the application quality metric. 1 Moreover, we focus on optimizing the integer part, which can significantly decrease the implementation cost when a slight degradation of the application quality is acceptable. Indeed, many applications are tolerant to overflows if the probability of overflow occurrence is low enough. Thus, we exploit the proposed framework in a new integer word-length optimization algorithm. The combination of the optimization algorithm and the selective simulation technique allows decreasing significantly the optimization time.

[pt] Alexandre Plastino em sua tese de doutorado apresenta um ambiente de desenvolvimento de aplicações paralelas SPMD (Single Program, Multiple Data) denominado SAMBA que permite a geração de diferentes versões de uma aplicação paralela a partir da incorporação de diferentes algoritmos de balanceamento de carga disponíveis numa biblioteca própria. O presente trabalho apresenta uma ferramenta de geração de carga dinâmica integrada a este ambiente que possibilita criar, em tempo de execução, diferentes perfis de carga externa a serem aplicados a uma aplicação paralela em estudo. Dessa forma, pretende-se permitir que o desenvolvedor de uma aplicação paralela possa selecionar o algoritmo de balanceamento de carga mais apropriado frente a condições variáveis de carga externa. Com o objetivo de validar a integração da ferramenta ao ambiente SAMBA, foram obtidos resultados da execução de duas aplicações SPMD distintas. / [en] Alexandre Plastino s tesis presents a framework for the development of SPMD parallel applications, named SAMBA, that enables the generation of different versions of a parallel application by incorporating different load balancing algorithms from an internal library. This dissertation presents a dynamic workload generation s tool, integrated to SAMBA, that affords to create, at execution time, different external workload profiles to be applied over a parallel application in study. The objective is to enable that a parallel application developer selects the most appropriated load balancing algorithm based in its performance under variable conditions of external workload. In order to validate this integration, two SPMD applications were implemented.

Mobile sensing applications (MSAs) are an emerging class of applications that process continuous sensor data streams to make time-sensitive inferences. Representative application domains range from environmental monitoring, context-aware services to recognition of physical activities and social interactions. Example applications involve city air quality assessment, indoor localization, pedometer and speaker identification. The common application workflow is to read data streams from the sensors (e.g, accelerometers, microphone, GPS), extract statistical features, and then present the inferred high-level events to the user. MSAs in the healthcare domain especially draw a significant amount of attention in recent years because sensor-based data collection and assessment offer finer-granularity, timeliness, and higher accuracy in greater quantity than traditional, labor-intensive, data gathering mechanisms in use today, e.g., surveys methods. The higher fidelity and accuracy of the collected data expose new research opportunities, improve the reliability and accuracy of medical decisions, and empower users to manage personal health more effectively. Nonetheless, a critical challenge to practical deployment of MSAs in real-world is to effectively manage limited resources of mobile platforms to meet stringent quality of service (QoS) requirements in terms of processing throughput and delay while ensuring long term robustness. To address the challenge, we model MSAs in dataflows as a graph of processing elements that are connected by communication channels. The processing elements may execute in parallel as long as they have sufficient data to process. A key feature of the dataflow model is that it explicitly capture parallelism and data dependencies between processing elements. Based on the graph composition, we first proposed CSense, a stream-processing toolkit for robust and high-rate MSAs. In this work, CSense provide a simple language for developers to describe their sensing flow without the need to deal with system intricacy, such as memory allocation, concurrency control and power management. The results show up to 19X performance difference may be achieved automatically compared with a baseline using the default runtime concurrency and memory management. Following this direction, we saw the opportunities that MSAs can be significantly improved from the perspective of memory performance and energy efficiency in view of the iterative execution. Therefore, we next focus on optimizing the runtime memory management through compile time analysis. The contribution is a stream compiler that captures the whole program memory behavior to generate an efficient memory layout for runtime access. Experiments show that our memory optimizations reduce memory footprint by as much as 96% while matching or improving the performance of the StreamIt compiler with cache optimizations enabled. On the other hand, while there is a significant body of work that has focused on optimizing the throughput or latency of processing sensor streams, little to no attention has been given to energy efficiency. We proposed an accurate offline energy prediction model for MSAs that leverages the pipeline structure and iterative execution nature to search for the most energy saving batching configuration w.r.t. a deadline constraint. The developers are expected to visualize the energy delay trade-off in the parameter space without runtime profiling. The evaluation shows the worst-case prediction errors are about 7% and 15% for energy and latency respectively despite variable application workloads.

The extent and nature of physio-chemical changes that take place in detached leaves after harvest and during storage have been reviewed and discussed by Osborne (1962) and Rogers (1955). These changes include loss of moisture (Wittwer et al., 1962), chlorophyll degredation (Person et al., 1957), Protein loss (Thimann and Manmahan, 1960), and result in subsequent appearance of the visual manifestations of senescence of plant tissues. As lettuce, like most leafy vegetables, deteriorates rapidly and steadily after harvest. Loss of quality is inevitable and can only be minimized by rapid handling and with the best possible storage conditions (Pratt et al., 1954). In recent years, abundant work has been done to delay senescence by the use of various chemicals. Among the investigated chemicals, kinetin (6-furfurylarninopurine) and its related c ompounds show some promise. Van Overbeek et al. (1941) reported a potent new growthpromoting factor (kinetin) in coconut milk. This chemical is active in causing many of the growth reactions of c oconut milk at exceedingly small dosages. Subsequently several arninopurine compounds were synthesized. One of which is SD 4901 (Verdan), N6-benzyladenine, an experimental senescence inhibitor, was developed by Shell Development Company, Modesto, California in 1960. Many reports showed that this chemical is capable of delaying senescence of plant tissues on the basis of restoring protein molecules and respiration inhibition. On the other hand, others have shown stimulation of respiration and delaying of senescence. Paucity of scientific literature on the stability of those chemicals on leafy vegetables gave impetus to a study of the comparative influence of pre- and post-harvest applications of 6-furfurylaminopurine and N6-benzyladenine as related to successive harvest times. Such studies may have considerable economic bearing upon storing and shipping leafy vegetables to distant markets. This thesis presents effects of different concentrations (5, 10, and 20 ppm.) of pre- and post-harvest applications of 6-furfurylaminopurine and N6-benzyladenine as related to three successive harvest times (at one week intervals) on chlorophyll content, moisture content, total nitrogen, insoluble and soluble nitrogen, oxygen uptake, 0 and co2 production during storage (at 40 Fo and 85 percent RH) of "Great Lakes" variety of lettuce.

Database Auto Awesome is an approach to enhancing web applications comprised of forms used to interact with stored information. It was inspired by Google's Auto Awesome tool, which provides automatic enhancements for photos. Database Auto Awesome aims to automatically or semi-automatically provide improvements to an application by expanding the functionality of the application and improving the existing code. This thesis describes a tool that gathers information from the application and provides details on how the parts of the application work together. This information provides the details necessary to generate new portions of an application. These enhancements are directed by the web application administrator through specifying what they would like to have generated, in terms of functionality. Once the administrator has provided this direction, the new application code is generated and put in updated or new files. Using this approach, Database Auto Awesome provides a viable solution for semi-automatically generating enhancements to an existing web application.

The stability of the Internet is at risk if the amount of voice and video traffic continues to increase at the current pace. While current transport layer protocols do work well for most applications, they still present some problems. TCP is reliable, tracks the state of some network conditions and reacts drastically to an indication of congestion. TCP serves data-oriented applications very well but it can lead to unacceptably low quality for streaming applications by multiplicatively reducing the congestion window upon a sign of congestion. The other main transport layer protocol, UDP, provides good service for streaming applications but is not friendly to TCP and can cause the well-known existing congestion collapse problem in the Internet. This thesis proposes a new protocol to provide a good service for voice and video applications while being friendly to TCP and solving the congestion collapse problem. The protocol utilizes a fuzzy logic controller that considers network related information to govern the applications sending rate while satisfying the users needs. Using network information such as the available bandwidth, Packet Loss Rates (PLR), and Round Trip Times (RTT) a fuzzy inference system optimizes the applications send rate to meet the requested rate in a smooth manner without wasting network resources unnecessarily. The fuzzy logic controller is designed and its performance evaluated using MATLAB model simulations. The results indicate that the fuzzy controller solves the congestion collapse problem by reducing the number of undelivered packets into the network by nearly 100%. It provides smooth transition changes as demonstrated by the controlled UDP flow utilizing an estimated 44% more of the available bandwidth to smooth the send rate than the TCP flow in a highly varying bandwidth environment. The controller also remains friendly with TCP which was demonstrated to share the bandwidth at nearly 50% with one other competing controlled UDP flow.

Patient-specific induced pluripotent stem cells (iPSCs) emerged as a promising cell source for disease modeling and drug screening as well as a virtually unlimited source for restorative therapy. The thesis deals with three major topics to help realizing biomedical applications with neural stem cells. To enable the generation of transgene-free iPSCs, alternatives to retroviral reprogramming were developed. Hence, the adaptation and evaluation of reprogramming using excisable lentiviral constructs, Sendai virus (SeV) and synthetic mRNA-based methods was assessed in the first part of this thesis. hiPSCs exhibit the pluripotency markers OCT4, SSEA-4, TRA1-60 which were confirmed by immunofluorescence and flow cytometry. Besides, the potential to differentiate in cell types of all three germ layers was detected, confirming pluripotent identity of proliferating colonies resulting from various reprogramming strategies. However, major differences such as high efficiency with SeV in contrast to a relatively low efficiency with mRNA in regard to passage number and the phenotype of starting fibroblasts were observed. Furthermore, a prolonged clone- and passage-dependent residual presence of viral RNA genes was identified in SeV-iPSCs for up to 23 passages using RT-PCR underlining the importance of careful monitoring of clone selection. In contrast, viral-free reprogramming by synthetic mRNA represents a fully non-integrative approach but requires further refinement to be efficiently applicable to all fibroblasts. The second part of this thesis deals with the establishment of a rapid monolayer approach to differentiate neural progenitor cells from iPSCs. To achieve this, a two-step protocol was developed allowing first the formation of a stable, primitive NPC line within 7 days which was expanded for 2-3 passages. In a second step, a subsequent adaptation to conditions yielding neural rosette-like NPCs followed. Both neural lines were demonstrated to be expandable, cryopreservable and negative for the pluripotency marker OCT4. Furthermore, a neural precursor identity including SOX1, SOX2, PAX6, Nestin was confirmed by immunofluorescence and quantitative RT-PCR. Moreover, the differentiation resulted in TUJ1-positive neurons and GFAP-positive astrocytes. Nonetheless, the outcome of glial differentiation from primitive NSCs remained low, whereas FGF/EGF-NPCs were efficiently differentiated into GFAP-positive astrocytes which were implicated in a cellular model of the blood brain barrier. The third and major objective of this study was to generate human early neural progenitor cells from fetal brain tissue with a wide neural differentiation capacity. Therefore, a defined medium composition including small molecules and growth factors capable of modulation of crucial signaling pathways orchestrating early human development such as SHH and FGF was assessed. Indeed, specific culture conditions containing TGFβ inhibitor SB431542, SHH agonist Purmorphamine, GSK3β inhibitor CHIR99021 and basic FGF, but no EGF enabled robust formation of early neuroepithelial progenitor (eNEP) colonies displaying a homogeneous morphology and a high proliferation rate. Moreover, primary eNEPs exhibit a relatively high clonogenicity of more than 23 % and can be monoclonally expanded for more than 45 passages carrying a normal karyotype. Characterization by immunofluorescence, flow cytometry and quantitative RT-PCR revealed a distinct NPC profile including SOX1, PAX6, Nestin and SOX2 and Prominin. Furthermore, primary eNEPs show NOTCH and HES5 activation in combination with non-polarized morphology, indicative of an early neuroepithelial identity. Microarray analysis unraveled SOX11, BRN2 and other HES-genes as characteristic upregulated genes. Interestingly, eNEPs were detected to display ventral midbrain/hindbrain regional identity. The validation of yielded cell types upon differentiation indicates a strong neurogenic potential with more than 90 % of TUJ1-positive neurons. Moreover, astrocytes marked by GFAP and putative myelin structures indicating oligodendrocytes were identified. Electrophysiological recordings revealed functionally active neurons and immunofluorescence indicate GABAergic, glutamatergic, dopaminergic and serotonergic subtypes. Additionally, putative physiological synapse formation was observed by the presence of Synapsin and PSD-95 as well as by ultrastructural examination. Notably, rare neurons stained positive for the peripheral neuronal marker Peripherin suggesting the potential of eNEPS to give rise to cells of neural tube and neural crest origin. By the application of specific differentiation protocols an increase of TH-positive neurons or neural crest-derivatives such as putative A- and C-sensory neurons and mesenchymal cells was identified. Taken together, primary eNEPs might help to elucidate mechanisms of early human neurodevelopment and will serve as a novel source for cell replacement and further biomedical applications. / Patientenspezifische induziert pluripotente Zellen (iPSZ) haben sich als eine vielversprechende Möglichkeit erwiesen Zellen zu gewinnen, die für Krankheitsmodellierung, Arzneimitteltests und Zellersatztherapie in Frage kommen. In dieser Arbeit wurden drei wichtige Fragestellungen adressiert, die für potenzielle biomedizinische Anwendungen von neuralen Stammzellen von großem Interesse sind. Um die Generierung von transgenfreien iPSZ zu ermöglichen, wurden Alternativen zur retroviralen Reprogrammierung entwickelt. Im ersten Teil dieser Arbeit wurden Reprogrammierungsmethoden, die auf deletierbaren, lentiviralen Konstrukten oder nichtintegrativen Verfahren wie Sendaivirus (SeV)-Transduktion und Transfektion synthetischer mRNA basieren, adaptiert und evaluiert. Die daraus resultierenden iPSZ exprimieren die Pluripotenzmarker OCT4, SSEA-4 und TRA1-60. Weiterhin wurde das Potenzial in Zelltypen aller drei Keimblätter zu differenzieren nachgewiesen. Dadurch konnte die pluripotente Identität der proliferativen Kolonien bestätigt werden. Beim Vergleich der angewandten Methoden fielen, bezüglich der generierten iPSZ-Linien, sowohl qualitative als auch quantitative Unterschiede auf. Bei der Verwendung von SeV-Partikeln wurde eine hohe Reprogrammierungseffizienz festgestellt. Bei der Transfektion von mRNAs hingegen war die Reprogrammierungseffizienz deutlich niedriger. Diese war darüber hinaus abhängig von der Passage und dem Genotyp der Ausgangsfibroblasten. Des Weiteren konnte eine klon- und passagenabhängige Präsenz viraler Gene in SeV-iPSZ bis zu 23 Passagen lang beobachtet werden, während bei der mRNA-Transfektion keine Spuren der genetischen Manipulation zurückblieben. Dies verdeutlicht die Bedeutung einer sorgfältigen Qualitätskontrolle bei der Klonselektion im Falle der SeV-iPSZ. Im Gegensatz dazu stellt die Reprogrammierung durch Transfektion synthetischer mRNAs eine völlig nicht-integrative Strategie dar, erfordert allerdings weitere Verfeinerung um das Verfahren effizient und vor allem für alle Fibroblastenpräparationen anwendbar zu machen. Der zweite Teil der Arbeit behandelt die Etablierung eines schnellen, adhärenten Protokolls, um neurale Vorläuferpopulation aus iPSZ zu differenzieren. Um dies zu erreichen, wurde ein zweiphasiges Protokoll entwickelt, welches zunächst die Generierung einer primitiven neuralen Vorläuferzellpopulation innerhalb von 7 Tagen erlaubt. In einem zweiten Schritt erfolgte die Adaptierung an Kulturbedingungen, die eine neurale, rosettenähnliche Zellpopulation induzieren. Beide neuralen Zellpopulationen konnten weiter expandiert und eingefroren werden und waren negativ für den Pluripotenz-assoziierten Transkriptionsfaktor OCT4. Darüber hinaus konnte die neurale Vorläuferidentität mittels positiver Expression von SOX1, SOX2, PAX6 und Nestin bestätigt werden. Eine weitere Differenzierung dieser Zellen resultierte in TUJ1-positiven Neuronen und GFAP-positiven Astrozyten, die die Verwendung der Zellpopulation beispielsweise in einem zellulären Modell der Blut-Hirn-Schranke erlaubten. Das Hauptprojekt dieser Dissertation war es, frühe humane neurale Vorläuferzellen aus fetalem Hirngewebe zu isolieren und in Kultur zu stabilisieren. Diese Population sollte eine breite Differenzierungskapazität aufweisen. Zu diesem Zweck wurde eine chemisch definierte Medienzusammensetzung gewählt, die zusätzlich pharmakologisch wirksame Verbindungen und Wachstumsfaktoren beinhaltet. Hierdurch konnten Signaltransduktionswege wie zum Beispiel der Sonic-Hedgehog- (SHH) oder FGF-Signalweg, die bei der frühen neuralen Entwicklung eine bedeutende Rolle spielen, moduliert werden. In der Tat ermöglichten spezifische Kultivierungsbedingungen, die den TGFβ-Inhibitor SB431542, den SHH-Agonisten Purmorphamin, den GSK3β-Inhibitor CHIR99021 und basisches FGF, jedoch kein EGF enthielten, die robuste Bildung einer früheren neuroepithelialen Vorläuferpopulation (eNEP). Die so stabilisierten Kolonien wiesen eine homogene Morphologie und eine hohe Proliferationsrate auf. Außerdem zeigten sie eine hohe Klonogenitätsrate von 23%, die es ermöglichte monoklonale Zelllinien zu isolieren und für mehr als 45 Passagen zu expandieren. Dabei blieb ein normaler Karyotyp erhalten. Die Zellen zeigten ein eindeutiges neurales Profil, gekennzeichnet durch SOX1, PAX6, Nestin, SOX2 und Prominin-Expression. Weiterhin wiesen eNEPs NOTCH und HES5-Aktivierung in Kombination mit nicht-polarisierter Morphologie auf, was auf eine frühe neuropitheliale Identität hinweist. Eine Microarray-Analyse demonstrierte weiterhin SOX11, BRN2 und einige HES-Gene als charakteristisch hochregulierte Gene. Interessanterweise zeigen eNEPs eine regionale Identität, die auf eine Mittelhirn/Hinterhirn-Regionalisierung hinweist. Die Validierung ungerichtet ausdifferenzierter Zelltypen offenbarte mit einem Kulturanteil von 90% TUJ1-positiven Neuronen ein stark neurogenes Potenzial. Zusätzlich konnten GFAPpositive Astrozyten sowie mögliche Myelinstrukturen, die auf Oligodendrozyten hinweisen, nachgewiesen werden. Elektrophysiologische Aufzeichnungen deuten auf funktionell aktive Neurone hin und Immunofluoreszenzfärbungen zeigten GABAerge, glutamaterge, dopaminerge und serotonerge neuronale Subtypen. Außerdem wurden mittels Immunfluoreszenzanalyse Synapsin- und PSD-95- positive synaptische Strukturen nachgewiesen. Ultrastrukturelle Analysen mittels Transmissionselektronenmikroskopie bestätigten das Ergebnis. Hervorzuheben ist, dass einige Neurone positiv für den peripheren Neuronenmarker Peripherin gefärbt wurden, was darauf hinweist, dass eNEPs das Potenzial besitzen, in Zellen der Neuralleiste zu differenzieren. Durch die Verwendung von spezifischen Differenzierungsprotokollen konnte das Vorkommen TH-positiver und auch möglicher A- und C-sensorischer Fasern, sowie mesenchymaler Zellen nachgewiesen werden. Zusammenfassend lässt sich sagen, dass primäre eNEPs dazu beitragen könnten, die frühe humane Gehirnentwicklung zu verstehen. Darüber hinaus stellen eNEPs eine potentielle zelluläre Quelle für Zellersatztherapien und weitere biomedizinische Anwendungen dar.