1,720,994 research outputs found
An automatic Alzheimer’s disease classifier based on spontaneous spoken English
Full text linkAccording to the World Health Organization, the number of people suffering from dementia worldwide will grow to 150 million by mid-century, and Alzheimer’s disease is the most common form of dementia contributing to 60%–70% of cases. The problem is compounded by the fact that current pharmacologic treatments are only symptomatic, and therapies are ineffective in slow down or cure the degenerative process. An automatic and standardize classifier for Alzheimer’s disease is thereby extremely important to rapidly respond and deliver as preventive as possible interventions. Speech alterations might be one of the earliest signs of cognitive defect and, recently, the researchers showed that they can be observable well in advance other cognitive deficits become manifest. In this paper, we propose a full automated method able to classify the spontaneous spoken production of the subjects. In particular, we trained an artificial neural network using the spectrogram of the audio signal, which is the visual representation of the speech of the subject. Moreover, to overcome the problem of the large amount of annotated data usually required for training deep learning models, we used a specific data augmentation approach that avoids distorting the original samples. We evaluated the proposed method using the English Pitt Corpus from DementiaBank. The used dataset consists of 180 subjects: 43 healthy controls and 137 Alzheimer’s disease patients. The proposed method outperformed the other approaches in the literature based on manual and semi-automatic transcription and annotation of speech, improving the classification capability by 5.93%, and obtained good classification results compared to the state-of-the-art neuropsychological screening tests (i.e., the Mini-Mental State Examination and the Activities of Daily Living portion of the Blessed Dementia Rating Scale) exhibiting an accuracy of 93.30% and an F1 score of 88.50%
Automatic Speech Classifier for Mild Cognitive Impairment and Early Dementia
Full text linkThe World Health Organization estimates that 50 million people are currently living with dementia worldwide and this figure will almost triple by 2050. Current pharmacological treatments are only symptomatic, and drugs or other therapies are ineffective in slowing down or curing the neurodegenerative process at the basis of dementia. Therefore, early detection of cognitive decline is of the utmost importance to respond significantly and deliver preventive interventions. Recently, the researchers showed that speech alterations might be one of the earliest signs of cognitive defect, observable well in advance before other cognitive deficits become manifest. In this article, we propose a full automated method able to classify the audio file of the subjects according to the progress level of the pathology. In particular, we trained a specific type of artificial neural network, called autoencoder, using the visual representation of the audio signal of the subjects, that is, the spectrogram. Moreover, we used a data augmentation approach to overcome the problem of the large amount of annotated data usually required during the training phase, which represents one of the most major obstacles in deep learning. We evaluated the proposed method using a dataset of 288 audio files from 96 subjects: 48 healthy controls and 48 cognitively impaired participants. The proposed method obtained good classification results compared to the state-of-the-art neuropsychological screening tests and, with an accuracy of 90.57%, outperformed the methods based on manual transcription and annotation of speech
Nuclear receptors and differentiation of oligodendrocyte precursor cells
No full textOligodendrocytes are the cells responsible for myelin formation during development and in adulthood, both for normal myelin turnover and myelin repair. These highly specialized cells derive from the oligodendrocyte precursor cells (OPCs), through a complex differentiation process involving genetic and epigenetic regulation mechanisms, which switch the phenotype from a migratory and replicative precursor to a mature post-mitotic cell. The process is regulated by a plethora of molecules, involving neurotransmitters, growth factors, hormones and other small molecules, and is mainly driven by nuclear receptors (NRs). NRs are transcription factors with heterogeneous ligand-dependent and independent actions which differ for the cell target, the responsive gene and the formation of NR homo- or heterodimers. This chapter highlights the role of NRs in regulating OPC differentiation, also in view of drug discovery strategies aimed at targeting pathological conditions which interfere with both developmental myelination and remyelination in adulthood
NGF and Retinitis Pigmentosa: Structural and Molecular Studies
No full textNerve growth factor (NGF) is a neuroprotective molecule performing not only on central and peripheral neurons but also on cells of the visual system. Human retinitis pigmentosa (RP) is a major cause of blindness worldwide, and a resolute therapy is still lacking. Recent studies have shown that ocular NGF administration exerts a protective action on damaged retinal cells of mammalians, including human beings, although whether NGF also protects photoreceptors is not clear.We used the Royal College of Surgeons (RCS) strain in this study. The RCS is a rodent affected by inherited retinitis pigmentosa (RP) during postnatal life. For this study, we investigated whether ocular NGF treatment reduces/stops the progression of photoreceptor degeneration of rats with RP.This study was carried out in vitro on isolated photoreceptors to further investigate the action on these cells and whether the action is direct or mediated.The results indicate that ocular NGF administration can protect photoreceptors from degeneration into a model developing inherited RP and that the NGF action is direct. In this regard, we observed that binding of NGF to its receptor modulates expression of rhodopsin, a specific biological marker for photoreceptor survival and functionality.Part of the data reported in this chapter has been published in a previous study
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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