京都大学 / 新制・論文博士 / 博士(医学) / 乙第13397号 / 論医博第2221号 / 新制||医||1051(附属図書館) / (主査)教授 伊佐 正, 教授 中本 裕士, 教授 渡邉 大 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

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The thesis deals with the lived everyday practice of patients with epileptic seizures and the types of knowledge they are working with in relation to seizures. Particular attention is paid to patients' embodied knowledge as the practical knowledge based on the experience of epileptic seizures and their bodies in general. The thesis shows how the types of knowledge (such as triggers, auras, forms of seizures or their management) are based on, created and learnt through the embodiment. Lifestyle regimens associated with seizure management are introduced as a link between general recommendations and individual regimens, with seizure management being negotiated with regard to other aspects of patient life. While adhering to management, there is some communication, cooperation and negotiation between the patient and his body. Finally, other forms of knowledge about seizures are outlined, such as those created by people close to the patient and those created by assistance dogs. (Furthermore), it is also explained what these forms of knowledge mean to the patient and how to work with them.

The selection of a representative sample is a delicate problem when drug seizures comprised of large number of units arrive at the Swedish National Forensic Centre (NFC). If deviating objects in the selected sample size are found, additional analyzes are required to investigate how representative the results are for the entire population. This generates further pressure on operational analysis flow. With the goal to provide a tool which forensic scientists at NFC can base their assessment of the representative nature of the selected sampling of large drug seizures on, this project investigated the possibilities of evaluating the level of homogeneity in drug seizures using near-infrared (NIR) hyperspectral imaging along with principal component analysis (PCA). A total of 27 sample groups (homogeneous, heterogeneous and seized sample groups) were analyzed and different predictive models were developed. The models were either based on quantifying the variation in NIR spectra or in PCA scores plots. It was shown that in the spectral range of 1300-2000 nm, using a pre-processing combination of area normalization, quadratic (second polynomial) detrending and mean centering, promising predictive abilities of the models in their evaluation of the level of homogeneity in drug seizures were achieved. A model where the approximated signal-dependent variation was related to the quotient of significant and noise explained variance given by PCA indicated most promising predictive abilities when quantifying the variation in NIR spectra. Similarly, a model where a rectangular area, defined by the maximum distances along PC1 and PC2, was related to the cumulative explained variance of the two PCs showed most promising predictive abilities when quantifying the variation in PCA scores plots. Different zones for which within sample groups are expected to appear based upon their degree of homogeneity could be established for both models. The two models differed in sensitivity. However, more comprehensive studies are required to evaluate the models applicability from an operational point-of-view.

Microglia are the resident macrophage in the central nervous system (CNS) that actively survey their environment and participate in shaping neuronal circuits. Among the transcription factors necessary for microglia development, interferon regulatory factor 8 (IRF8) is a known risk gene for multiple sclerosis and lupus and it has recently been shown to be downregulated in schizophrenia. These studies suggest that lack of microglial IRF8 can subsequently impact neuronal function in disease, but the mechanisms underlying these effects remain unknown. While most studies have focused on IRF8-dependent regulation of immune cell function, little is known about how it impacts neural circuits. To interrogate the impact of disrupted microglial IRF8 signaling on brain circuits, I first show by RNAseq that several genes known to regulate neuronal function are dysregulated basally in Irf8-/- brains. I then found that these molecular changes are reflected in heightened neural excitability and a profound increase in susceptibility to chemically-induced lethal seizures in Irf8-/- mice. Importantly, I also show that developmental synaptic pruning, a key function for microglia, proceeds normally in Irf8-/-mice. Finally, I identified that these IRF8-dependent effects on circuits are due to elevated TNF-α in the CNS as genetic or acute pharmacological blockade of TNF-α in the Irf8-/- CNS rescued the seizure phenotype. These results provide important insights into the consequences of IRF8 signaling and TNF-α on neural circuits. The next steps are to use cell-specific genetic approaches to manipulate this signaling, which I have further developed over the course of this project.

Indiana University-Purdue University Indianapolis (IUPUI) / Adolescents with a type of conversion disorder called psychogenic nonepileptic seizures (PNES) experience many school, relationship, and health care struggles as they attempt to manage their mental health condition with PNES events that strikingly resemble epileptic seizures. Considered one of the top three neuropsychiatric problems, health care providers and school personnel remain ill-informed regarding how to care for adolescents with PNES. Because of the unique multidisciplinary approach needed to address adolescent PNES, school nurses are uniquely positioned to bridge health care and education systems. A review of literature examined the concept of school nurse selfmanagement support for PNES, existing school nurse-led mental health interventions, and the relationships between concepts for a conceptual framework guiding adolescent PNES research. This review of literature reveals an absence of adolescents’ perspective and school emphasis in PNES research. This study was designed to investigate adolescents’ experience attending school and self-managing PNES. This was accomplished through a qualitative content analysis of data generated from semi-structured interviews and magnitude coding of select quantifiable data. Data were obtained from 10 adolescents, 12 to 19 years of age, with current or recent in-person school attendance. The results indicate adolescents from the sample had school experiences that involved stress, bullying, accusations of faking seizures, and feelings of isolation or exclusion. Their mostly effective proactive selfmanagement activities included seeking protection, persevering in life despite PNES struggles, and progress monitoring through seizure tracking. Reactive activities of mixed effectiveness included coping responses to seizure warnings. School nurses, school personnel, family members, and peers served as both facilitators and barriers for PNES self-management. Adolescents also contributed information for three emerging themes— family-management, school-management, and illness representation. These findings reveal the difficulties of attending school and self-managing PNES and inform future PNES interventions to improve academic, mental health, and quality of life outcomes.

Bakgrund Epilepsi är en kronisk sjukdom i hjärnan som drabbar cirka 50 miljoner personer runt om i världen. Sjukdomen kännetecknas av återkommande anfall. Stigmatisering och diskriminering är förekommande vilket kan göra att personer med epilepsi inte kan delta fullt ut i den sociala aspekten. Vårdpersonal har en viktig roll när det gäller att hjälpa personer med epilepsi att hantera ett brett spektrum av utmaningar som kommer med sjukdomen. Syfte Syftet är att belysa vuxna personers upplevelser av att leva med epilepsi med fokus på stresshantering. Metod Detta examensarbete är en strukturerad litteraturöversikt med inslag av den metodologi som används vid systematiska översikter. Tolv vetenskapliga studier ligger som grund för resultatet inhämtade ifrån databaserna APA PyscINFO och CINAHL. Litteraturöversikten har en deduktiv ansats baserat på vald teoretisk referensram kombinerat med induktiv ansats som utgår från de olika delar av studiernas resultat. Resultat Personer med epilepsi använder emotionsbaserad coping i form av acceptans och positivitet samt isolering och distansering. Problembaserad coping används genom att tillämpa interventioner, försiktighetsåtgärder, livsstilsförändringar, söka behandling och stöd hos andra. Slutsats Stressen av att leva med epilepsi visade sig ha stor påverkan på personernas livskvalité. Emotions- och problembaserad coping användes för att hantera stressen som kommer med sjukdomen. Tillämpningen av dessa metoder är individuella och ser olika ut från person till person. / Background Epilepsy is a chronic illness of the brain which affects around 50 million people around the world. The illness is characterized by recurrent seizures. Stigma and discrimination are rampant which makes persons with epilepsy unable to participate fully in the social aspects of life. Health care providers have an important role in helping persons with epilepsy in the broad spectrum of challenges that comes with the illness. Aim The study aims to describe the experiences of persons living with epilepsy with focus on stress management. Method This study is a structured literature review with elements of the methodology used in systematic reviews. Twelve scientific studies were used as the basis for the results taken from databases APA PsycINFO and CINAHL. This literature review has a deductive approach based on the chosen theoretical framework combined with an inductive approach taken from various parts of the result from the chosen scientific studies. Results Persons with epilepsy used emotional based coping in the form of acceptance and positivity as well as isolation and distancing. Problem based coping was used in the form of implementing interventions, precautionary measures, lifestyle changes, finding treatment regimens and support from others. Conclusions The stress of living with epilepsy had a big impact on the person's quality of life. Emotional- and problem based coping was used to handle the stress that comes with the illness. Application of these methods are from an individual’s standpoint and sees different from one person to another.

The electroencephalogram (EEG) is the primary tool used for the diagnosis of a varietyof neural pathologies such as epilepsy. Identification of a critical event, such as an epileptic seizure, is difficult because the signals are collected by transducing extremely low voltages, and as a result, are corrupted by noise. Also, EEG signals often contain artifacts due to clinical phenomena such as patient movement. These artifacts are easily confused as seizure events. Factors such as slowly evolving morphologies make accurate marking of the onset and offset of a seizure event difficult. Precise segmentation, defined as the ability to detect start and stop times within a fraction of a second, is a challenging research problem. In this dissertation, we improve seizure segmentation performance by developing deep learning technology that mimics the human interpretation process. The central thesis of this work is that separation of the seizure detection problem into a two-phase problem – epileptiform activity detection followed by seizure detection – should improve our ability to detect and localize seizure events. In the first phase, we use a sequential neural network algorithm known as a long short-term memory (LSTM) network to identify channel-specific epileptiform discharges associated with seizures. In the second phase, the feature vector is augmented with posteriors that represent the onset and offset of ictal activities. These augmented features are applied to a multichannel convolutional neural network (CNN) followed by an LSTM network. The multiphase model was evaluated on a blind evaluation set and was shown to detect 106 segment boundaries within a 2-second margin of error. Our previous best system, which delivers state-of-the-art performance on this task, correctly detected only 9 segment boundaries. Our multiphase system was also shown to be robust by performing well on two blind evaluation sets. Seizure detection performance on the TU Seizure Detection (TUSZ) Corpus development set is 41.60% sensitivity with 5.63 false alarms/24 hours (FAs/24 hrs). Performance on the corresponding evaluation set is 48.21% sensitivity with 16.54 FAs/24 hrs. Performance on a previously unseen corpus, the Duke University Seizure (DUSZ) Corpus is 46.62% sensitivity with 7.86 FAs/24 hrs. Our previous best system yields 30.83% sensitivity with 6.74 FAs/24 hrs on the TUSZ development set, 33.11% sensitivity with 19.89 FAs/24 hrs on the TUSZ evaluation set and 33.71% sensitivity with 40.40 FAs/24 hrs on DUSZ. Improving seizure detection performance through better segmentation is an important step forward in making automated seizure detection systems clinically acceptable. For a real-time system, accurate segmentation will allow clinicians detect a seizure as soon as it appears in the EEG signal. This will allow neurologists to act during the early stages of the event which, in many cases, is essential to avoid permanent damage to the brain. In a similar way, accurate offset detection will help with delivery of therapies designed to mitigate postictal (after seizure) period symptoms. This will also help reveal the severity of a seizure and consequently provide guidance for medicating a patient. / Electrical and Computer Engineering

Individuals with epilepsy manage the clinical manifestations of the condition, primarily seizure-related activity, with daily use of pharmacologic agents, making it one of the most common neurological conditions treated with drug therapy for symptom management. Pharmacologic agents for epilepsy, also known as anti-epileptic drugs (AEDs), are commonly prescribed to treat seizures and neurologic conditions associated with epilepsy but can lead to a reduced quality of life and many unwanted side effects. Complementary and alternative treatments can also provide relief from seizures associated with epilepsy. The purpose of this literature review was to evaluate the effectiveness of complementary and alternative treatments compared to pharmacological treatment for individuals with epilepsy. A literature review examining different alternative treatments, such as physical activity, medical cannabis, neurostimulation, and various diets, and their benefits on seizure reduction, seizure frequency, and the quality of life was conducted from various online databases. Research articles published from 2003 to 2020 that focused on the benefits of complementary and alternative therapies in controlling the clinical manifestations of epilepsy were included for synthesis. Results from 10 studies that used a complementary or alternative therapy as a treatment for epilepsy, alone or in combination with pharmacological therapy, were compared for effectiveness on clinical manifestations. Seventy percent of the studies analyzed show at least a fifty percent reduction in seizure frequency. The studies suggest that complementary and alternative therapies can be effective as monotherapy or as adjuvant agents for reducing seizure frequency, reducing seizure duration, and improving quality of life. Although benefits were found in each study, many studies were performed on animals or had small sample sizes, indicating the need for further research.

京都大学 / 新制・論文博士 / 博士(医学) / 乙第13560号 / 論医博第2289号 / 新制||医||1067(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 森信 暁雄, 教授 村井 俊哉, 教授 林 康紀 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM