142 research outputs found

    딥러닝 기반 군집화 방법을 이용하여 FDG PET에서 알츠하이머병의 공간적 뇌 대사 패턴의 특징적 아형 분류

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    학위논문(박사) -- 서울대학교대학원 : 융합과학기술대학원 분자의학 및 바이오제약학과, 2022.2. 이동수.알츠하이머병은 아밀로이드와 타우 침착과 같은 병리학적 특징을 공유함에도 불구하고 광범위한 임상병리학적 특성을 보인다. 본 연구에서는 딥러닝 기반 군집화 방법을 이용하여 FDG PET 영상에서 알츠하이머병 특징적 아형을 분류하여 신경 퇴행의 공간적 뇌 대사 패턴을 이해하고자 하였으며, 공간적 뇌 대사 패턴에 의해 정의된 아형의 임상병리학적 특징을 밝히고자 하였다. Alzheimer’s Disease Neuroimaging Initiative(ADNI) 데이터베이스로부터 첫번째 방문 및 추적 방문을 포함한 알츠하이머병, 경도인지장애, 인지 정상군의 총 3620개의 FDG 뇌 양전자단층촬영(PET) 영상을 수집하였다. 알츠하이머병에서 질병의 진행 외의 뇌 대사 패턴을 나타내는 표현(representation)을 찾기 위하여, 조건부 변이형 오토인코더(conditional variational autoencoder)를 사용하였으며, 인코딩된 표현으로부터 군집화(clustering)를 시행하였다. 알츠하이머병의 뇌 FDG PET (n=838)과 CDR-SB(Clinical Demetria Rating Scale Sum of Boxes) 점수가 cVAE 모델의 입력값으로 사용되었으며, 군집화에는 k-means 알고리즘이 사용되었다. 훈련된 딥러닝 모델은 경도인지장애군 (n=1761)의 뇌 FDG PET에 전이(transfer)되어 각 아형의 서로 다른 궤적(trajectory)과 예후를 밝히고자 하였다. 통계적 파라미터 지도작성법(Statistical Parametric Mapping, SPM)을 이용하여 각 군집의 공간적 패턴을 시각화 하였으며, 각 군집의 임상적 및 생물학적 특징을 비교하였다. 또한 아형 별 경도인지장애로부터 알츠하이머병으로 전환되는 비율을 비교하였다. 딥러닝 기반 군집화 방법으로 4개의 특징적 아형이 분류되었다. (i) S1 (angular): 모이랑(angular gyrus)에서 현저한 대사 저하를 보이며 분산된 피질의 대사 저하 패턴, 남성에서 빈도 높음, 더 많은 아밀로이드 침착, 더 적은 타우 침착, 더 심한 해마 위축, 초기 단계의 인지 저하의 특징을 보였다. (ii) S2 (occipital): 후두엽(occipital) 피질에서 현저한 대사 저하를 보이며 후부 우세한 대사 저하 패턴, 더 적은 연령, 더 많은 타우, 더 적은 해마 위축, 더 낮은 집행 및 시공간 점수, 경도인지장애로부터 알츠하이머병으로의 빠른 전환의 특징을 보였다. (iii) S3(orbitofrontal): 안와전두(orbitofrontal) 피질에서 현저한 대사 저하를 보이며 전방 우세한 대사 저하 패턴, 더 높은 연령, 더 적은 아밀로이드 침착, 더 심한 해마 위축, 더 높은 집행 및 시공간 점수의 특징을 보였다. (iv) S4(minimal): 최소의 대사 저하를 보임, 여성에서 빈도 높음, 더 적은 아밀로이드 침착, 더 많은 타우 침착, 더 적은 해마 위축, 더 높은 인지기능 점수의 특징을 보였다. 결론적으로, 본 연구에서 우리는 서로 다른 뇌 병리 및 임상 특성을 가진 알츠하이머병의 특징적 아형을 분류하였다. 또한 우리 딥러닝 모델은 경도인지장애군에 성공적으로 전이되어 아형 별 경도인지장애로부터 알츠하이머병으로 전환되는 예후를 예측할 수 있었다. 본 결과는 FDG PET에서 알츠하이머병의 특징적 아형은 개인의 임상 결과에 영향을 미칠 수 있고, 병태생리학 측면에서 알츠하이머병의 광범위한 스펙트럼을 이해하는데 단서를 제공할 수 있음을 시사한다.Alzheimer’s disease (AD) presents a broad spectrum of clinicopathologic profiles, despite common pathologic features including amyloid and tau deposition. Here, we aimed to identify AD subtypes using deep learning-based clustering on FDG PET images to understand distinct spatial patterns of neurodegeneration. We also aimed to investigate clinicopathologic features of subtypes defined by spatial brain metabolism patterns. A total of 3620 FDG brain PET images with AD, mild cognitive impairment (MCI), and cognitively normal controls (CN) at baseline and follow-up visits were obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. In order to identify representations of brain metabolism patterns different from disease progression in AD, a conditional variational autoencoder (cVAE) was used, followed by clustering using the encoded representations. FDG brain PET images with AD (n=838) and Clinical Demetria Rating Scale Sum of Boxes (CDR-SB) scores were used as inputs of cVAE model and the k-means algorithm was applied for the clustering. The trained deep learning model was also transferred to FDG brain PET image with MCI (n=1761) to identify differential trajectories and prognosis of subtypes. Statistical parametric maps were generated to visualize spatial patterns of clusters, and clinical and biological characteristics were compared among the clusters. The conversion rate from MCI to AD was also compared among the subtypes. Four distinct subtypes were identified by deep learning-based FDG PET clusters: (i) S1 (angular), showing prominent hypometabolism in the angular gyrus with a diffuse cortical hypometabolism pattern; frequent in males; more amyloid; less tau; more hippocampal atrophy; cognitive decline in the earlier stage. (ii) S2 (occipital), showing prominent hypometabolism in the occipital cortex with a posterior-predominant hypometabolism pattern; younger age; more tau; less hippocampal atrophy; lower executive and visuospatial scores; faster conversion from MCI to AD. (iii) S3 (orbitofrontal), showing prominent hypometabolism in the orbitofrontal cortex with an anterior-predominant hypometabolism pattern; older age; less amyloid; more hippocampal atrophy; higher executive and visuospatial scores. (iv) S4 (minimal), showing minimal hypometabolism; frequent in females; less amyloid; more tau; less hippocampal atrophy; higher cognitive scores. In conclusion, we could identify distinct subtypes in AD with different brain pathologies and clinical profiles. Also, our deep learning model was successfully transferred to MCI to predict the prognosis of subtypes for conversion from MCI to AD. Our results suggest that distinct AD subtypes on FDG PET may have implications for the individual clinical outcomes and provide a clue to understanding a broad spectrum of AD in terms of pathophysiology.1. Introduction 1 1.1 Heterogeneity of Alzheimer's disease 1 1.2 FDG PET as a biomarker of Alzheimer's disease 1 1.3 Biologic subtypes of Alzheimer's disease 2 1.4 Dimensionality reduction methods 5 1.5 Variational autoencoder for clustering 8 1.6 Final goal of the study 10 2. Methods 11 2.1 Subjects 11 2.2 FDG PET data acquisition and preprocessing 12 2.3 Deep learning-based model for representations of FDG PET in AD 12 2.4 Clustering method for AD subtypes on FDG PET 17 2.5 Transfer of deep learning-based FDG PET cluster model for MCI subtypes 17 2.6 Visualization of subtype-specific spatial brain metabolism pattern 21 2.7 Clinical and biological characterization 21 2.8 Prognosis prediction of MCI subtypes 22 2.9 Generation of subtype-specific FDG PET images 22 2.10 Statistical analysis 23 3. Results 24 3.1 Deep learning-based FDG PET clusters 24 3.2 Spatial brain metabolism pattern in AD subtypes 27 3.3 Clinical and biological characterization in AD subtypes 32 3.4 Subtype-specific spatial metabolism patterns resemble in MCI 43 3.5 Clinical and biological characterization in MCI subtypes 50 3.6 Prognosis prediction of subtypes for conversion from MCI to AD 56 3.7 Generating FDG PET images of AD subtypes 61 4. Discussion 66 4.1 Limitations of previous subtyping approach 68 4.2 Interpretation of results 68 4.3 Strength of our deep learning-based clustering approach 73 4.4 Strength of our deep learning-based AD subtypes 77 4.5 Limitations and future directions 82 5. Conclusion 83 References 84 Supplementary Figures 99 국문 초록 101박

    Quantifying cognitive and mortality outcomes in older patients following acute illness using epidemiological and machine learning approaches

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    Introduction: Cognitive and functional decompensation during acute illness in older people are poorly understood. It remains unclear how delirium, an acute confusional state reflective of cognitive decompensation, is contextualised by baseline premorbid cognition and relates to long-term adverse outcomes. High-dimensional machine learning offers a novel, feasible and enticing approach for stratifying acute illness in older people, improving treatment consistency while optimising future research design. Methods: Longitudinal associations were analysed from the Delirium and Population Health Informatics Cohort (DELPHIC) study, a prospective cohort ≥70 years resident in Camden, with cognitive and functional ascertainment at baseline and 2-year follow-up, and daily assessments during incident hospitalisation. Second, using routine clinical data from UCLH, I constructed an extreme gradient-boosted trees predicting 600-day mortality for unselected acute admissions of oldest-old patients with mechanistic inferences. Third, hierarchical agglomerative clustering was performed to demonstrate structure within DELPHIC participants, with predictive implications for survival and length of stay. Results: i. Delirium is associated with increased rates of cognitive decline and mortality risk, in a dose-dependent manner, with an interaction between baseline cognition and delirium exposure. Those with highest delirium exposure but also best premorbid cognition have the “most to lose”. ii. High-dimensional multimodal machine learning models can predict mortality in oldest-old populations with 0.874 accuracy. The anterior cingulate and angular gyri, and extracranial soft tissue, are the highest contributory intracranial and extracranial features respectively. iii. Clinically useful acute illness subtypes in older people can be described using longitudinal clinical, functional, and biochemical features. Conclusions: Interactions between baseline cognition and delirium exposure during acute illness in older patients result in divergent long-term adverse outcomes. Supervised machine learning can robustly predict mortality in in oldest-old patients, producing a valuable prognostication tool using routinely collected data, ready for clinical deployment. Preliminary findings suggest possible discernible subtypes within acute illness in older people

    Executive function & semantic memory impairments in Alzheimer’s disease — investigating the decline of executive function and semantic memory in Alzheimer’s disease through computer-supported qualitative analysis of semantic verbal fluency and its applications in clinical decision support

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    Alzheimer’s Disease (AD) has a huge impact on an ever-aging society in highly developed industrialized countries such as the EU member states: according to the World Alzheimer’s Association the number one risk factor for AD is age. AD patients suffer from neurodegenerative processes driving cognitive decline which eventually results in the loss of patients’ ability of independent living. Episodic memory impairment is the most prominent cognitive symptom of AD in its clinical stage. In addition, also executive function and semantic memory impairments significantly affect activities of daily living and are discussed as important cognitive symptoms during prodromal as well as acute clinical stages of AD. Most of the research on semantic memory impairments in AD draws evidence from the Semantic Verbal Fluency (SVF) task which evidentially also places high demands on the executive function level. At the same time, the SVF is one of the most-applied routine assessments in clinical neuropsychology especially in the diagnosis of AD. Therefore, the SVF is a prime task to study semantic memory and executive function impairment side-by-side and draw conclusions about their parallel or successive impairments across the clinical trajectory of AD. To effectively investigate semantic memory and executive function processes in the SVF, novel computational measures have been proposed that tap into data-driven semantic as well as temporal metrics scoring an SVF performance on the item-level. With a better and more differentiated understanding of AD-related executive function and semantic memory impairments in the SVF, the SVF can grow from a well-established screening into a more precise diagnostic tool for early AD. As the SVF is one of the most-applied easy-to-use and low-burden neurocognitive assessments in AD, such advancements have a direct impact on clinical practice as well. For the last decades huge efforts have been put on the discovery of disease-modifying compounds responding to specific AD biomarker-related cognitive decline characteristics. However, as most pharmaceutical trials failed, the focus has shifted towards population-wide early screening with cost-effective and scalable cognitive tests representing an effective mid-term strategy. Computer-supported SVF analysis responds to this demand. This thesis pursues a two-fold objective: (1) improve our understanding of the progressive executive function and semantic memory impairments and their interplay in clinical AD as measured by the SVF and (2) harness those insights for applied early and specific AD screening. To achieve both objectives, this thesis comprises work on subjects from different clinical stages of AD (Healthy Aging, amnestic Mild Cognitive Impairment—aMCI, and AD dementia) and in different languages (German & French). All results are based on SVF speech data generated either as a one-time assessment or a repeated within-participant testing. From these SVF speech samples, qualitative markers are extracted with different amount of computational support (ranging from manual processing of speech to fully automated evaluation). The results indicate, that semantic memory is structurally affected from an early clinical—amnestic Mild Cognitive Impairment (aMCI)—stage on and is even more affected in the later acute dementia stage. The semantic memory impairment in AD is particularly worsened through the patients’ inability to compensate by engaging executive functions. Hence, over the course of the disease, hampered executive functioning and therefore the inability to compensate for corrupt semantic memory structures might be the main driver of later-stage AD patients’ notably poor cognitive performance. These insights generated on the SVF alone are only made possible through computer-supported qualitative analysis on an item-per-item level which leads the way towards potential applications in clinical decision support. The more fine-grained qualitative analysis of the SVF is clinically valuable for AD diagnosis and screening but very time-consuming if performed manually. This thesis shows though that automatic analysis pipelines can reliably and validly generate this diagnostic information from the SVF. Automatic transcription of speech plus automatic extraction of the novel qualitative SVF features result in clinical interpretation comparable to manual transcripts and improved diagnostic decision support simulated through machine learning classification experiments. This indicates that the computer-supported SVF could ultimately be used for cost-effective fully automated early clinical AD screening. This thesis advances current AD research in a two-fold manner. First it improves the understanding of the decline of executive function and semantic memory in AD as measured through computational qualitative analysis of the SVF. Secondly, this thesis embeds these theoretical advances into practical clinical decision support concepts that help screen population-wide and cost-effective for early-stage AD.Die Alzheimer-Krankheit (AD) stellt eine enorme Herausforderung für die immer älter werdende Gesellschaft in hochentwickelten Industrieländern wie den EU-Mitgliedsstaaten dar. Nach Angaben der World Alzheimer's Association ist der größte Risikofaktor für AD das Alter. Alzheimer-Patienten leiden unter neurodegenerativen Prozessen, die kognitiven Abbau verursachen und schließlich dazu führen, dass Patienten nicht länger selbstbestimmt leben können. Die Beeinträchtigung des episodischen Gedächtnisses ist das prominenteste kognitive Symptom von AD im klinischen Stadium. Darüber hinaus führen auch Störungen der Exekutivfunktionen sowie der semantischen Gedächtnisleistung zu erheblichen Einschränkungen bei Aktivitäten des täglichen Lebens und werden als wichtige kognitive Symptome sowohl im Prodromal- als auch im akuten klinischen Stadium von AD diskutiert. Der Großteil der Forschung zu semantischen Gedächtnisbeeinträchtigungen bei AD stützt sich auf Ergebnisse aus dem Semantic Verbal Fluency Tests (SVF), der auch die Exekutivfunktionen stark fordert. In der Praxis ist die SVF eines der am häufigsten eingesetzten Routine- Assessments in der klinischen Neuropsychologie, insbesondere bei der Diagnose von AD. Daher ist die SVF eine erstklassige Aufgabe, um die Beeinträchtigung des semantischen Gedächtnisses und der exekutiven Funktionen Seite an Seite zu untersuchen und Rückschlüsse auf ihre parallelen oder sukzessiven Beeinträchtigungen im klinischen Verlauf von AD zu ziehen. Um semantische Gedächtnis- und Exekutivfunktionsprozesse in der SVF effektiv zu untersuchen, wurden jüngst neuartige computergestützte Verfahren vorgeschlagen, die sowohl datengetriebene semantische als auch temporäre Maße nutzen, die eine SVF-Leistung auf Item-Ebene bewerten. Mit einem besseren und differenzierteren Verständnis von ADbedingten Beeinträchtigungen der Exekutivfunktionen und des semantischen Gedächtnisses in der SVF kann sich die SVF von einem gut etablierten Screening zu einem präziseren Diagnoseinstrument für frühe AD entwickeln. Da die SVF eines der am häufigsten angewandten, einfach zu handhabenden und wenig belastenden neurokognitiven Assessments bei AD ist, haben solche Fortschritte auch einen direkten Einfluss auf die klinische Praxis. In den letzten Jahrzehnten wurden enorme Anstrengungen unternommen, um krankheitsmodifizierende Substanzen zu finden, die auf spezifische, mit AD-Biomarkern verbundene Merkmale des kognitiven Abbaus reagieren. Da jedoch die meisten pharmazeutischen Studien in jüngster Vergangenheit fehlgeschlagen sind, wird heute als mittelfristige Strategie bevölkerungsweite Früherkennung mit kostengünstigen und skalierbaren kognitiven Tests gefordert. Die computergestützte SVF-Analyse ist eine Antwort auf diese Forderung. Diese Arbeit verfolgt deshalb zwei Ziele: (1) Verbesserung des Verständnisses der fortschreitenden Beeinträchtigungen der Exekutivfunktionen und des semantischen Gedächtnisses und ihres Zusammenspiels bei klinischer AD, gemessen durch die SVF, und (2) Nutzung dieser Erkenntnisse für angewandte AD-Früherkennung. Um beide Ziele zu erreichen, umfasst diese Thesis Forschung mit Probanden aus verschiedenen klinischen AD Stadien (gesundes Altern, amnestisches Mild Cognitive Impairment-aMCI, und AD-Demenz) und in verschiedenen Sprachen (Deutsch & Französisch). Alle Ergebnisse basieren auf SVF Sprachdaten, erhoben im Querschnittdesign oder als wiederholte Testung in einem Längsschnittdesign. Aus diesen SVF-Sprachproben werden mit unterschiedlicher rechnerischer Unterstützung qualitative Marker extrahiert (von manueller Verarbeitung der Sprache bis hin zu vollautomatischer Auswertung). Die Ergebnisse zeigen, dass das semantische Gedächtnis bereits im frühen aMCI Stadium strukturell beeinträchtigt ist und im späteren akuten Demenzstadium noch stärker betroffen ist. Die strukturelle Beeinträchtigung des semantischen Gedächtnisses bei Alzheimer wird insbesondere dadurch verschlimmert, dass die Patienten nicht in der Lage sind, dies durch den Einsatz exekutiver Funktionen zu kompensieren. Daher könnten im Verlauf der Erkrankung eingeschränkte Exekutivfunktionen und damit die Unfähigkeit, degenerierte semantische Gedächtnisstrukturen zu kompensieren, die Hauptursache für die auffallend schlechten kognitiven Leistungen von AD-Patienten im Akutstadium sein. Diese Erkenntnisse basierend auf der SVF alleine werden erst durch die computergestützte qualitative Analyse auf Item-per-Item-Ebene möglich und weisen den Weg zu möglichen Anwendungen in der klinischen Entscheidungsunterstützung. Die feinkörnigere qualitative Analyse der SVF ist klinisch wertvoll für die AD-Diagnose und das Screening, aber sehr zeitaufwändig, wenn sie manuell durchgeführt wird. Diese Arbeit zeigt jedoch, dass automatische Analysepipelines diese diagnostischen Informationen zuverlässig und valide aus der SVF generieren können. Die automatische Transkription von Sprache plus die automatische Extraktion der neuartigen qualitativen SVF-Merkmale führen zu einer klinischen Interpretation, die mit manuellen Analysen vergleichbar ist. Diese Verarbeitung führt auch zu einer verbesserten diagnostischen Entscheidungsunterstützung, die durch Klassifikationsexperimente mit maschinellem Lernen simuliert wurde. Dies deutet darauf hin, dass die computergestützte SVF letztendlich für ein kostengünstiges vollautomatisches klinisches AD-Frühscreening eingesetzt werden könnte. Diese Arbeit bringt die aktuelle AD-Forschung auf zweifache Weise voran. Erstens verbessert sie unser Verständnis der kognitiven Einschränkungen im Bereich der Exekutivfunktionen und des semantischen Gedächtnisses bei AD, gemessen durch die computergestützte qualitative Analyse der SVF. Zweitens bettet diese Arbeit diese theoretischen Fortschritte in ein praktisches Konzept zur klinischen Entscheidungsunterstützung ein, das zukünftig ein bevölkerungsweites und kosteneffektives Screening für AD im Frühstadium ermöglichen könnte

    Identification of a fluid-based microglial activation-dependent biomarker panel

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    Advancing knowledge into the clinical assessment of dementia.

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    The aim of the present thesis was to identify and measure cognitive and social abilities in people with dementia and learning disabilities. In Chapter 1, normal agemg was discussed, distinguishing it from abnormal ageing and highlighting the problems it brings in terms of physical and psychological factors. Normal memory was also discussed and how the processes involved may be effected by dementia. Definitions of dementia were discussed in detail, outlining the neuropathology, neuropsychology and clinical signs of Alzheimer's disease, and the neuropsychology of multi-infarct dementia. The psychology of pseudodementia was presented and discussed and reference was made to the difficulties of a differential diagnosis. This was placed in the context of defining learning disabilities, such as Down's syndrome, and the complexity of assessing people who have both a learning disability and dementia. Social and cultural differences were discussed together with the influence of environmental factors in measuring dementia. Theoretical considerations about the difficulties in assessing people with learning disabilities, particularly people who have Down's syndrome and dementia, were presented and discussed. These issues arose from the abnormalities in intellectual development and therefore, impacted upon subsequent cognitive rehabilitation and integration into the community of such individuals. A description and critique of the instruments used in the clinical studies ensued with important reference to the reliability, validity, and standard error and norms of each tool used. Finally, the goals of the study series were presented and discussed. Part I: Empirical Studies (Published Papers) Clinical studies were presented in chapters 2 - 5. All clients participating in the studies were randomly selected from consultant psychiatrists' lists ofpeople living in their own homes or in voluntary sector group homes in England. In Chapter 2, a neuropsychological test battery was devised in order to identify dementia in people with Down's syndrome. This battery comprised a series of standardised neuropsychological tests and rating scales measuring intellectual profiling, cognitive and social functioning and ability, and anxiety and depression. In addition to gathering biographical information, self-care information was also gathered. The Dementia Questionnaire for Mentally Retarded Persons proved to be a useful tool for indicating general areas of clients' skills that had declined; however, there is still a need for a definitive assessment of depression for these clients in order to discriminate between the effects of depression and those ofdementia. In Chapter 3, clients with Down's syndrome and non-Down's syndrome learning disabilities were assessed usmg specially selected neuropsychological assessment tools at two points separated by twelve months. Evidence was found to support hypothesis 1 which suggested that people with Down's syndrome show a greater decline in social abilities with age, compared with other groups ofpeople with learning disabilities. Statistically, score changes reflecting the social abilities of the Down's syndrome clients were found to be significantly greater (p < .002) than those of the non-Down's syndrome clients. Findings were explained in terms of poor language abilities in the Down's syndrome people generally, and the link between declining social abilities and dementia. In Chapter 4, forty-one clients with learning disabilities were assessed using specially selected neuropsychological assessment tools at two time points separated by twelve months. Evidence for hypothesis 1 suggested that people with Down's syndrome show a greater decline in cognitive abilities with age, compared with other groups of people with learning disabilites. A weak linear association (p < .004; r = .625; 2-tailed) between cognitive performance and social abilities was also found for the Down's syndrome clients, supporting hypothesis 2. Findings were explained in terms of the link between declining cognitive abilities and dementia. In Chapter 5, a clinical investigation was undertaken to determine the rate of decline in cognitive and social abilities in 16 clients with learning disabilities, 8 of which had Down's syndrome. Clients assessed at 6 months using specially selected neuropsychological tests and rating scales measuring cognitive and social abilities as well as intellectual profiling. Both Down's syndrome and non-Down's syndrome clients were found to decline in cognitive abilities (Down's syndrome: p <.005; I-tailed); NonDown's syndrome: p <.01; I-tailed; p <.005; I-tailed). The Down's syndrome clients also showed decline in social abilities (p <.005; I-tailed) over 6 months suggesting that changes between the two client groups may be significantly greater over a longer period, ie 12 months. Hence, the rate of change in cognitive abilities for the Down's syndrome clients was faster. Part 11: Evaluation of Treatment and Services (Published Papers) In Chapter 6, a new version of the Benton Visual Retention Test for assessing people's memory functioning was evaluated. Findings showed that the conventional method of testing was preferred and not significantly different in terms of efficacy and reliability of measurement. In Chapter 7, the potential benefits of Aricept, an acetylcholine esterase inhibitor, was investigated. There were significant effects and benefits for patients who had mild-to-moderate Alzheimer's disease over a short period of time. However, the results were encouraging as they signalled the first documentation of the effect and a promising future for a possible remission of the disease. In Chapter 8, a support group for wives of husbands with dementia was presented and discussed. The psychoeducation support group was shown to be an effective way of supporting newly diagnosed people with dementia and their carers. In Chapter 9, a new interdisciplinary clinic for people with cognitive abilities was discussed. Importance in the constitution of the clinic personnel as well as the fbcus on assessment and follow-up treatment was emphasised. Part Ill: Future Direction (Published Papers) In Chapter 10, the importance of assessing people with dementia in the early stages of diagnosis and at particular intervals was demonstrated in the context of the legal process. Suggestions were made for improving the test for testamentary capacity. Part IV: In Summary Discussion in Chapter 11 covers the empirical work presented together with suggestions for future research, namely considering the differences between discrete types of dementias such as multi-infarct (vascular) dementia versus Alzheimer's disease and also longitudinal studies. Interesting findings from the clinical studies revealed a greater decline in social abilities of Down's syndrome clients versus non-Down's syndrome clients. These findings were explained in terms of poor language abilities in Down's syndrome clients generally, and the link between declining social abilities and dementia. A link between cognitive performance and social abilities was also found for the Down's syndrome clients. Findings of declining cognitive abilities in both groups of clients were associated with dementia; and in particular, with a failure of the Central Executive System and Articulatory Loop System, considered to be important in nonnal memory. Modifying assessment techniques such as by computerisation is presented and treatment efficacy using the acetycholinesterase inhibitor, Aricept, is presented and discussed. The establishment of cognitive assessment clinics is also presented as a way of providing a comprehensive service for people with early onset dementia. Service implications for people with learning disabilities is discussed and finally, ways of improving the test for testamentary capacity for people with dementia is detailed. Collectively, these writings significantly contribute to our academic and clinical knowledge of assessing dementia. We have learned a great deal from studying and helping people with Down's syndrome; however, perhaps more importantly, this work should contribute significantly to our rather limited knowledge of assessing dementia in people with Down's syndrome and thus may step towards improving and widening access to service provision for these valued people

    Perspectives of People with Dementia: Experiencing Shame. An Interpretative Phenomenological Analysis

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    Background People with dementia who have participated in research have reported experiencing shame (Cheston, in press; Mitchell, McCollum & Monaghan, 2013), and other uncomfortable self-conscious experiences, such as self-criticism (Langdon, Eagle & Warner, 2006), embarrassment (Imhof, Wallhagen, Mahrer-Imhof & Monsch, 2006), and fears of stigma (Harman & Clare, 2006). Public Health guidance has emphasised the importance of addressing the stigma and marginalisation of people with dementia (Department of Health, 2009; World Health Organisation & Alzheimer’s Disease International, 2012). Methodology This study uses Interpretative Phenomenological Analysis to explore experiences of shame for six people in the early stages of dementia, living independently in the community. Data was collected through the use of individual, semi-structured interviews conducted within participants’ homes. The interviews were transcribed by the primary researcher and analysed through an in-depth, interpretive examination. Results Four superordinate themes emerged from the data. Firstly, Avoidance reveals how the participants made several levels of attempts to hide and distance themselves from shaming experiences. Secondly, the participants’ accounts highlight Negative Self-Perceptions, including a weakening sense of self, a loss of value, and meaninglessness. Thirdly, Relationship Matters involve issues around trust, feeling a burden, and the impact of past relationships on current levels of shame. Fourthly, Uncertainty and loss of control highlights the participants’ search for an understanding of their experiences, and fears about an unknown future and losing control. Conclusion The study contributes ideas for developing both public and professional awareness for promoting non-shaming experiences for people with dementia. In particular, suggestions are provided for improving communication during the assessment and diagnosis process, as well as options for responding to shame through psychological therapies

    Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

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    On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

    Biomarker-And Pathway-Informed Polygenic Risk Scores for Alzheimer's Disease and Related Disorders

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    Indiana University-Purdue University Indianapolis (IUPUI)Determining an individual’s genetic susceptibility in complex diseases like Alzheimer’s disease (AD) is challenging as multiple variants each contribute a small portion of the overall risk. Polygenic Risk Scores (PRS) are a mathematical construct or composite that aggregates the small effects of multiple variants into a single score. Potential applications of PRS include risk stratification, biomarker discovery and increased prognostic accuracy. A systematic review demonstrated that methodological refinement of PRS is an active research area, mostly focused on large case-control genome-wide association studies (GWAS). In AD, where there is considerable phenotypic and genetic heterogeneity, we hypothesized that PRS based on endophenotypes, and pathway-relevant genetic information would be particularly informative. In the first study, data from the NIA Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used to develop endophenotype-based PRS based on amyloid (A), tau (T), neurodegeneration (N) and cerebrovascular (V) biomarkers, as well as an overall/combined endophenotype-PRS. Results indicated that combined phenotype-PRS predicted neurodegeneration biomarkers and overall AD risk. By contrast, amyloid and tau-PRSs were strongly linked to the corresponding biomarkers. Finally, extrinsic significance of the PRS approach was demonstrated by application of AD biological pathway-informed PRS to prediction of cognitive changes among older women with breast cancer (BC). Results from PRS analysis of the multicenter Thinking and Living with Cancer (TLC) study indicated that older BC patients with high AD genetic susceptibility within the immune-response and endocytosis pathways have worse cognition following chemotherapy±hormonal therapy rather than hormonal-only therapy. In conclusion, PRSs based on biomarker- or pathway- specific genetic information may provide mechanistic insights beyond disease susceptibility, supporting development of precision medicine with potential application to AD and other age-associated cognitive disorders

    On the representation of semantic and motor knowledge. Evidence from brain damaged patients

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    When we think of an apple, do we actually feel the same as when we eat it? The central theme of this work is to understand whether the permanent representation of an object corresponds to a reactivation of sensations we perceived when we actually had it in our hands. A recent debate in cognitive neuroscience, in fact, is concerned with the possibility that the neural systems that mediate overt action and sensory experience are causally involved in the neural representation of actions and real objects. On the other hand, more classical models postulate a relative separation between the how system and the what system, the former being more related to action, the latter more related to visual and semantic object representation. Such a classical view does not deny that the two streams normally have a close interaction but, based on neuropsychological and behavioral evidence, it holds that they can work separately in the case of selective brain damage or in particular experimental conditions. In this thesis I will explore the possible role of the motor processes in understanding objects and actions by studying brain damaged patients performing a series of action- and object-related tasks. In Chapter I, I will briefly introduce the literature on the relationship between actions and concepts of both healthy and brain damaged subjects. Chapter II reports a study on a group of 37 stroke patients who have been tested for their ability to recognize and use objects, as well as to recognize and imitate actions. In this group I found double dissociations suggesting that these tasks depend on separable cognitive processes. In Chapter III, I will describe a double dissociation study in which we compared the performance of two patients with apraxia with that of two patients with semantic impairment, and I will show how the object knowledge of the latter patients decline in time although they maintained relatively good ability to use objects. Finally, in Chapter IV I will analyze the performance of a new series of apraxic patients on a set of tasks aimed at testing a computational model which accounts for the errors that apraxic patients make when using objects. The results will not completely fit with the embodied theories of knowledge. Rather, they are compatible with \u201cdisembodied\u201d models that postulate a separation between the object conceptual knowledge and the sensory-motor input and output systems
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