scholarly journals Classifying Parkinson’s Disease Patients With Syntactic and Socio-emotional Verbal Measures

2020 ◽  
Vol 12 ◽  
Author(s):  
Sandra Baez ◽  
Eduar Herrera ◽  
Catalina Trujillo ◽  
Juan F. Cardona ◽  
Jesus A. Diazgranados ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Classification Accuracy ◽  
Functional Role ◽  
Affective State ◽  
Joint Analysis ◽  
Long Distance ◽  
Social Emotions ◽  
Role Assignment ◽  
Joint Assessment

Frontostriatal disorders, such as Parkinson’s disease (PD), are characterized by progressive disruption of cortico-subcortical dopaminergic loops involved in diverse higher-order domains, including language. Indeed, syntactic and emotional language tasks have emerged as potential biomarkers of frontostriatal disturbances. However, relevant studies and models have typically considered these linguistic dimensions in isolation, overlooking the potential advantages of targeting multidimensional markers. Here, we examined whether patient classification can be improved through the joint assessment of both dimensions using sentential stimuli. We evaluated 31 early PD patients and 24 healthy controls via two syntactic measures (functional-role assignment, parsing of long-distance dependencies) and a verbal task tapping social emotions (envy, Schadenfreude) and compared their classification accuracy when analyzed in isolation and in combination. Complementarily, we replicated our approach to discriminate between patients on and off medication. Results showed that specific measures of each dimension were selectively impaired in PD. In particular, joint analysis of outcomes in functional-role assignment and Schadenfreude improved the classification accuracy of patients and controls, irrespective of their overall cognitive and affective state. These results suggest that multidimensional linguistic assessments may better capture the complexity and multi-functional impact of frontostriatal disruptions, highlighting their potential contributions in the ongoing quest for sensitive markers of PD.

scholarly journals Identification of biomarkers for early diagnosis of Parkinson's disease by multi-omics joint analysis

2020 ◽  
Vol 27 (8) ◽  
pp. 2082-2088
Author(s):  
Chaokai Hu ◽  
Cherng Jyh Ke ◽  
Chungyu Wu
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Diagnosis ◽  
Joint Analysis

scholarly journals Complementary Transcriptomic and Proteomic Analysis in the Substantia Nigra of Parkinson’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bao-hua Dong ◽  
Zhao-qing Niu ◽  
Jing-tao Zhang ◽  
Yi-jing Zhou ◽  
Fan-mei Meng ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Proteomic Analysis ◽  
Mrna Level ◽  
Mitochondrial Damage ◽  
Vesicle Transport ◽  
Joint Analysis ◽  
Cell Aging ◽  
Sequencing Data ◽  
New Targets

Parkinson’s disease (PD) is a disease that involves brain damage and is associated with neuroinflammation, mitochondrial damage, and cell aging. However, the pathogenic mechanism of PD is still unknown. Sequencing data and proteomic data can describe the fluctuation of molecular abundance in diseases at the mRNA level and protein level, respectively. In order to explore new targets in the pathogenesis of PD, the study analyzed molecular changes from the database by combining transcriptomic and proteomic analysis. Differentially expressed genes and differentially abundant proteins were summarized and analyzed. Enrichment and cluster analysis emphasized the importance of neurotransmitter release, mitochondrial damage, and vesicle transport. The molecular network revealed a subnetwork of 9 molecules related to SCNA and TH and revealed hub gene with differential expression at both mRNA and protein levels. It found that ACHE and CADPS could be used as new targets in PD, emphasizing that impaired nerve signal transmission and vesicle transport affect the pathogenesis of PD. Our research emphasized that the joint analysis and verification of transcriptomics and proteomics were devoted to understanding the comprehensive views and mechanism of pathogenesis in PD.

scholarly journals Semantic Memory and Lexical Availability in Parkinson’s Disease: A Statistical Learning Study

2021 ◽  
Vol 13 ◽  
Author(s):  
Juan F. Cardona ◽  
Johan S. Grisales-Cardenas ◽  
Catalina Trujillo-Llano ◽  
Jesús A. Diazgranados ◽  
Hugo F. Urquina ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Semantic Memory ◽  
Classification Accuracy ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Semantic Fluency ◽  
Semantic Categories ◽  
Semantic Fields ◽  
Living Things

Parkinson’s disease (PD) is a neurodegenerative disorder that causes a progressive impairment in motor and cognitive functions. Although semantic fluency deficits have been described in PD, more specific semantic memory (SM) and lexical availability (LA) domains have not been previously addressed. Here, we aimed to characterize the cognitive performance of PD patients in a set of SM and LA measures and determine the smallest set of neuropsychological (lexical, semantic, or executive) variables that most accurately classify groups. Thirty early-stage non-demented PD patients (age 35–75, 10 females) and thirty healthy controls (age 36–76, 12 females) were assessed via general cognitive, SM [three subtests of the CaGi battery including living (i.e., elephant) and non-living things (i.e., fork)], and LA (eliciting words from 10 semantic categories related to everyday life) measures. Results showed that PD patients performed lower than controls in two SM global scores (picture naming and naming in response to an oral description). This impairment was particularly pronounced in the non-living things subscale. Also, the number of words in the LA measure was inferior in PD patients than controls, in both larger and smaller semantic fields, showing a more inadequate recall strategy. Notably, the classification algorithms indicated that the SM task had high classification accuracy. In particular, the denomination of non-living things had a classification accuracy of ∼80%. These results suggest that frontostriatal deterioration in PD leads to search strategy deficits in SF and the potential disruption in semantic categorization. These findings are consistent with the embodied view of cognition.

scholarly journals Delayed Clinical Manifestation of Parkinson’s Disease Among Physically Active: Do Participants in a Long-Distance Ski Race Have a Motor Reserve?

2020 ◽  
pp. 1-1
Author(s):  
Tomas T. Olsson ◽  
Martina Svensson ◽  
Ulf Hållmarker ◽  
Stefan James ◽  
Tomas Deierborg
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Manifestation ◽  
Long Distance ◽  
Physically Active

scholarly journals Bidirectional gut-to-brain and brain-to-gut propagation of synucleinopathy in non-human primates

Brain ◽  
2020 ◽  
Vol 143 (5) ◽  
pp. 1462-1475 ◽  
Author(s):  
Marie-Laure Arotcarena ◽  
Sandra Dovero ◽  
Alice Prigent ◽  
Mathieu Bourdenx ◽  
Sandrine Camus ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Nervous System ◽  
Vagus Nerve ◽  
Enteric Nervous System ◽  
General Circulation ◽  
Motor Nucleus ◽  
Long Distance ◽  
Primate Model ◽  
Systemic Mechanism

Abstract In Parkinson’s disease, synucleinopathy is hypothesized to spread from the enteric nervous system, via the vagus nerve, to the CNS. Here, we compare, in baboon monkeys, the pathological consequences of either intrastriatal or enteric injection of α-synuclein-containing Lewy body extracts from patients with Parkinson’s disease. This study shows that patient-derived α-synuclein aggregates are able to induce nigrostriatal lesions and enteric nervous system pathology after either enteric or striatal injection in a non-human primate model. This finding suggests that the progression of α-synuclein pathology might be either caudo-rostral or rostro-caudal, varying between patients and disease subtypes. In addition, we report that α-synuclein pathological lesions were not found in the vagal nerve in our experimental setting. This study does not support the hypothesis of a transmission of α-synuclein pathology through the vagus nerve and the dorsal motor nucleus of the vagus. Instead, our results suggest a possible systemic mechanism in which the general circulation would act as a route for long-distance bidirectional transmission of endogenous α-synuclein between the enteric and the central nervous systems. Taken together, our study provides invaluable primate data exploring the role of the gut-brain axis in the initiation and propagation of Parkinson’s disease pathology and should open the door to the development and testing of new therapeutic approaches aimed at interfering with the development of sporadic Parkinson’s disease.

Longterm outcome of cognition, affective state, and quality of life following subthalamic deep brain stimulation in Parkinson’s disease

2019 ◽  
Vol 126 (3) ◽  
pp. 309-318 ◽  
Author(s):  
Doreen Gruber ◽  
Lisa Calmbach ◽  
Andrea A. Kühn ◽  
Patricia Krause ◽  
Ute A. Kopp ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Affective State ◽  
Longterm Outcome ◽  
Deep Brain

scholarly journals A Multiple-Classifier Framework for Parkinson’s Disease Detection Based on Various Vocal Tests

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Mahnaz Behroozi ◽  
Ashkan Sami
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Classification Accuracy ◽  
Pattern Analysis ◽  
Majority Vote ◽  
Central Tendency ◽  
Classification Result ◽  
Sound Recordings ◽  
Multiple Classifier ◽  
New Framework

Recently, speech pattern analysis applications in building predictive telediagnosis and telemonitoring models for diagnosing Parkinson’s disease (PD) have attracted many researchers. For this purpose, several datasets of voice samples exist; the UCI dataset named “Parkinson Speech Dataset with Multiple Types of Sound Recordings” has a variety of vocal tests, which include sustained vowels, words, numbers, and short sentences compiled from a set of speaking exercises for healthy and people with Parkinson’s disease (PWP). Some researchers claim that summarizing the multiple recordings of each subject with the central tendency and dispersion metrics is an efficient strategy in building a predictive model for PD. However, they have overlooked the point that a PD patient may show more difficulty in pronouncing certain terms than the other terms. Thus, summarizing the vocal tests may lead into loss of valuable information. In order to address this issue, the classification setting must takewhathas been said into account. As a solution, we introduced a new framework that applies an independent classifier for each vocal test. The final classification result would be a majority vote from all of the classifiers. When our methodology comes with filter-based feature selection, it enhances classification accuracy up to15%.

Functional role of Barrington’s nucleus in the micturition reflex: Relevance in the surgical treatment of Parkinson’s disease

Neuroscience ◽  
2014 ◽  
Vol 266 ◽  
pp. 150-161 ◽  
Author(s):  
L. Blanco ◽  
C.M. Ros ◽  
E. Tarragón ◽  
E. Fernández-Villalba ◽  
M.T. Herrero
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Surgical Treatment ◽  
Functional Role ◽  
Micturition Reflex

scholarly journals Transfer Learning improves MI BCI models classification accuracy in Parkinson's disease patients

2021 ◽  
Author(s):  
Aleksandar Miladinovic ◽  
Milos Ajcevic ◽  
Pierpaolo Busan ◽  
Joanna Jarmolowska ◽  
Giulia Silveri ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Transfer Learning ◽  
Classification Accuracy
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