Levodopa: History and therapeutic applications

Ovallath, Sujith; Sulthana, Bahiya

doi:10.4103/aian.aian_241_17

Cited by 24 publications

(10 citation statements)

References 30 publications

(27 reference statements)

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“…Our results showed that the score of the patients on part III of the UPDRS had the highest importance for the classification, indicating that the severity of PD motor symptoms was the most important feature for the Random Forest classifier when differentiating patients who are about to develop dyskinesia from those who are not. These findings are in accordance with the literature showing that dyskinesia appears as a result of the interaction between chronic dopaminergic therapy and the progression of striatal dopamine denervation 18 .…”

Section: Discussionsupporting

confidence: 93%

Prediction of dyskinesia in Parkinson’s disease patients using machine learning algorithms

Leal,

Dias,

Ramos

et al. 2023

Sci Rep

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Dyskinesias are non preventable abnormal involuntary movements that represent the main challenge of the long term treatment of Parkinson’s disease (PD) with the gold standard dopamine precursor levodopa. Applying machine learning techniques on the data extracted from the Parkinson’s Progression Marker Initiative (PPMI, Michael J. Fox Foundation), this study was aimed to identify PD patients who are at high risk of developing dyskinesias. Data regarding clinical, behavioral and neurological features from 697 PD patients were included in our study. Our results show that the Random Forest was the classifier with the best and most consistent performance, reaching an area under the receiver operating characteristic (ROC) curve of up to 91.8% with only seven features. Information regarding the severity of the symptoms, the semantic verbal fluency, and the levodopa treatment were the most important for the prediction, and were further used to create a Decision Tree, whose rules may guide the pharmacological management of PD symptoms. Our results contribute to the identification of PD patients who are prone to develop dyskinesia, and may be considered in future clinical trials aiming at developing new therapeutic approaches for PD.

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Section: Discussionsupporting

confidence: 93%

Prediction of dyskinesia in Parkinson’s disease patients using machine learning algorithms

Leal,

Dias,

Ramos

et al. 2023

Sci Rep

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“…An interesting fact is that a unique neurotransmitter found in L. fermentum U-21 but not L. fermentum 279 is l -DOPA. Since l -DOPA is the precursor of the neurotransmitters (dopamine, noradrenaline, and adrenaline), it is used in the therapeutic treatment of Parkinson’s disease and dopamine-responsive dystonia in medicine [ 31 ]. The culture supernatant contained a number of short-chain fatty acids, including acetic acid, propanoic acid, and butanoic acid.…”

Section: Discussionmentioning

confidence: 99%

Metabolites Potentially Determine the High Antioxidant Properties of Limosilactobacillus fermentum U-21

Grishina,

Vatlin,

Mavletova

et al. 2023

BioTech

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Many kinds of Lactobacillus are common occupants of humans’ digestive tract that support the preservation of a balanced microbial environment that benefits host health. In this study, the unique lactic acid bacterium strain Limosilactobacillus fermentum U-21, which was isolated from the feces of a healthy human, was examined for its metabolite profile in order to compare it to that of the strain L. fermentum 279, which does not have antioxidant (AO) capabilities. By using GC × GC−MS, the metabolite fingerprint of each strain was identified, and the data were then subjected to multivariate bioinformatics analysis. The L. fermentum U-21 strain has previously been shown to possess distinctive antioxidant properties in in vivo and in vitro studies, positioning it as a drug candidate for the treatment of Parkinsonism. The production of multiple distinct compounds is shown by the metabolite analysis, demonstrating the unique characteristics of the L. fermentum U-21 strain. According to reports, some of the L. fermentum U-21 metabolites found in this study have health-promoting properties. The GC × GC−MS-based metabolomic tests defined strain L. fermentum U-21 as a potential postbiotic with significant antioxidant potential.

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“…L-DOPA is the precursor of DA, introduced first in 1967 by George Cotzias as a therapeutic agent for PD [ 21 ]. Since then, it has been established as the gold standard treatment for PD and it has become an essential component of combination therapy [ 22 ].…”

Section: Clinically Approved Therapies For Pdmentioning

confidence: 99%

The Management of Parkinson’s Disease: An Overview of the Current Advancements in Drug Delivery Systems

Nakmode,

Day,

Song

et al. 2023

Pharmaceutics

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Parkinson’s disease (PD) has significantly affected a large proportion of the elderly population worldwide. According to the World Health Organization, approximately 8.5 million people worldwide are living with PD. In the United States, an estimated one million people are living with PD, with approximately 60,000 new cases diagnosed every year. Conventional therapies available for Parkinson’s disease are associated with limitations such as the wearing-off effect, on-off period, episodes of motor freezing, and dyskinesia. In this review, a comprehensive overview of the latest advances in DDSs used to reduce the limitations of current therapies will be presented, and both their promising features and drawbacks will be discussed. We are also particularly interested in the technical properties, mechanism, and release patterns of incorporated drugs, as well as nanoscale delivery strategies to overcome the blood–brain barrier.

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Levodopa: History and therapeutic applications

Cited by 24 publications

References 30 publications

Prediction of dyskinesia in Parkinson’s disease patients using machine learning algorithms

Prediction of dyskinesia in Parkinson’s disease patients using machine learning algorithms

Metabolites Potentially Determine the High Antioxidant Properties of Limosilactobacillus fermentum U-21

The Management of Parkinson’s Disease: An Overview of the Current Advancements in Drug Delivery Systems

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