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1.
NPJ Parkinsons Dis ; 10(1): 38, 2024 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-38374278

RESUMO

Parkinson's disease (PD) is a neurodegenerative disease with both genetic and sporadic origins. In this study, we investigated the electrophysiological properties, synaptic activity, and gene expression differences in dopaminergic (DA) neurons derived from induced pluripotent stem cells (iPSCs) of healthy controls, sporadic PD (sPD) patients, and PD patients with E326K-GBA1 mutations. Our results demonstrate reduced sodium currents and synaptic activity in DA neurons derived from PD patients with E326K-GBA1 mutations, suggesting a potential contribution to PD pathophysiology. We also observed distinct electrophysiological alterations in sPD DA neurons, which included a decrease in synaptic currents. RNA sequencing analysis revealed unique dysregulated pathways in sPD neurons and E326K-GBA1 neurons, further supporting the notion that molecular mechanisms driving PD may differ between PD patients. In agreement with our previous reports, Extracellular matrix and Focal adhesion pathways were among the top dysregulated pathways in DA neurons from sPD patients and from patients with E326K-GBA1 mutations. Overall, our study further confirms that impaired synaptic activity is a convergent functional phenotype in DA neurons derived from PD patients across multiple genetic mutations as well as sPD. At the transcriptome level, we find that the brain extracellular matrix is highly involved in PD pathology across multiple PD-associated mutations as well as sPD.

2.
Int J Mol Sci ; 24(8)2023 Apr 18.
Artigo em Inglês | MEDLINE | ID: mdl-37108598

RESUMO

The extracellular matrix (ECM) of the brain is a dynamic structure made up of a vast network of bioactive macromolecules that modulate cellular events. Structural, organizational, and functional changes in these macromolecules due to genetic variation or environmental stressors are thought to affect cellular functions and may result in disease. However, most mechanistic studies to date usually focus on the cellular aspects of diseases and pay less attention to the relevance of the processes governing the dynamic nature of the extracellular matrix in disease pathogenesis. Thus, due to the ECM's diversified biological roles, increasing interest in its involvement in disease, and the lack of sufficient compiled evidence regarding its relationship with Parkinson's disease (PD) pathology, we aimed to compile the existing evidence to boost the current knowledge on the area and provide refined guidance for the future research. Here, in this review, we gathered postmortem brain tissue and induced pluripotent stem cell (iPSC)-related studies from PubMed and Google Scholar to identify, summarize and describe common macromolecular alterations in the expression of brain ECM components in Parkinson's disease (PD). A literature search was conducted up until 10 February 2023. The overall hits from the database and manual search for proteomic and transcriptome studies were 1243 and 1041 articles, respectively. Following a full-text review, 10 articles from proteomic and 24 from transcriptomic studies were found to be eligible for inclusion. According to proteomic studies, proteins such as collagens, fibronectin, annexins, and tenascins were recognized to be differentially expressed in Parkinson's disease. Transcriptomic studies displayed dysregulated pathways including ECM-receptor interaction, focal adhesion, and cell adhesion molecules in Parkinson's disease. A limited number of relevant studies were accessed from our search, indicating that much work remains to be carried out to better understand the roles of the ECM in neurodegeneration and Parkinson's disease. However, we believe that our review will elicit focused primary studies and thus support the ongoing efforts of the discovery and development of diagnostic biomarkers as well as therapeutic agents for Parkinson's disease.


Assuntos
Doença de Parkinson , Humanos , Doença de Parkinson/metabolismo , Proteômica , Encéfalo/metabolismo , Matriz Extracelular/metabolismo , Tenascina/metabolismo
3.
J Pharm Bioallied Sci ; 8(2): 124-9, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27134464

RESUMO

BACKGROUND: Diabetes mellitus is a major global health problem covering approximately 347 million persons worldwide. Glycemic control has a main role in its management which mainly depends upon patient adherence to the treatment plan. Accurate assessment of medication adherence is necessary for effective management of diabetes. OBJECTIVE: To assess nonadherence and factors affecting adherence of diabetic patients to anti-diabetic medication in Assela General Hospital (AGH), Oromia Region, Ethiopia. MATERIALS AND METHODS: A descriptive cross-sectional study was conducted on patients seeking anti-diabetic drug treatment and follow-up at AGH using structured questionnaire and reviewing the patient record card using check list from January 24, 2014 to February 7, 2014. Descriptive analysis was used to describe the percentages and number of distributions of the variables in the study; and association was identified for categorical data. P ≤ 0.05 was considered as statistically significant. RESULT: Of all respondents, 149 (52.3%) and 136 (47.7%) were female and male, respectively. The majority of the study participants 189 (66.3%) were in the age group of 30-60 years. Two-hundred nineteen (76.8%) of respondents were married currently. The majority, 237 (83.2%) of respondents did not have blood glucose self-monitoring equipment (glucometer). A total of 196 (68.8%) respondents were adhered to anti-diabetic medication. There was a significant association between adherence to the medication and side effect, level of education, monthly income and presence of glucometer at home (P < 0.05). CONCLUSION: The participants in the area of study were moderately adherent to their anti-diabetic medications with nonadherence rate of 31.2%. Different factors of medication nonadherence were identified such as side effect and complexity of regimen, failure to remember, and sociodemographic factors such as educational level and monthly income.

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