Potential Regulation of the Long Non-Coding RNA Metastasis-Associated Lung Adenocarcinoma Transcript1 by Estrogen in Parkinson’s Disease DOI Creative Commons

Eman Adel,

Maya Nicolas

Life, Journal Year: 2024, Volume and Issue: 14(12), P. 1662 - 1662

Published: Dec. 16, 2024

Parkinson’s disease (PD) is the second-leading cause of death among neurodegenerative after Alzheimer’s (AD), affecting around 2% population. It expected that incidence PD will exceed 12 million by 2040. Meanwhile, there a recognized difference in phenotypical expression and response to treatment between men women. Men have twice compared women, who late onset worse prognosis usually associated with menopause. In addition, women cumulative estrogen levels their bodies. These differences are suggested be due protective effect on brain, which cannot given clinical practice improve symptoms because its peripheral side effects, causing cancer both males females addition feminizing it has males. As pathophysiology involves alteration multiple LncRNAs, including metastatic-associated lung adenocarcinoma transcript 1 (MALAT1), as been illustrated control MALAT1 conditions, worth investigating estrogen–MALAT1 interaction mimic brain while avoiding effects. The following literature review suggests potential regulation PD, would enhance our understanding disease, improving development more tailored effective treatments.

Language: Английский

Role of GABA pathway in motor and non-motor symptoms in Parkinson's disease: a bidirectional circuit DOI Creative Commons

Bandar Alharbi,

Hayder M. Al‐kuraishy, Ali I. Al‐Gareeb

et al.

European journal of medical research, Journal Year: 2024, Volume and Issue: 29(1)

Published: March 27, 2024

Abstract Parkinson's disease (PD) is a progressive neurodegenerative as result of the degeneration dopaminergic neurons in substantia nigra pars compacta (SNpc). The fundamental features PD are motor and non-motor symptoms. symptoms develop due to disruption neurotransmitters other such γ-aminobutyric acid (GABA). potential role GABA neuropathology concerning was not precisely discussed. Therefore, this review intended illustrate possible regarding pathway essential regulating inhibitory tone prevent excessive stimulation cerebral cortex. Degeneration linked with reducing GABAergic neurotransmission. Decreasing activity promotes mitochondrial dysfunction oxidative stress, which highly related neuropathology. Hence, restoring by agonists may attenuate progression dysregulation SNpc contributes developing Besides, also pathway, amelioration reduce In conclusion, deregulation might be intricate Improving novel, beneficial approach control

Language: Английский

Citations

16
The mechanism of cuproptosis in Parkinson’s disease DOI
Min Huang,

Yong Zhang,

Xuehong Liu

et al.

Ageing Research Reviews, Journal Year: 2024, Volume and Issue: 95, P. 102214 - 102214

Published: Feb. 2, 2024

Language: Английский

Citations

14
Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements DOI

Aananya Reddy,

Ruhananhad P. Reddy,

Aryan Kia Roghani

et al.

Ageing Research Reviews, Journal Year: 2024, Volume and Issue: 99, P. 102410 - 102410

Published: July 6, 2024

Language: Английский

Citations

13
Prevalence of Parkinson’s disease among adults aged 45 years and older in China: a cross-sectional study based on the China health and retirement longitudinal study DOI Creative Commons

Detao Meng,

Jiayu Wu, Xinyu Huang

et al.

BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: May 2, 2024

In recent decades, China has experienced a rapid increase in the number of elderly individuals and life expectancy, as well industrialization, which is associated with an increased prevalence Parkinson's disease (PD). However, inconsistent results have recently been reported. Therefore, this study aimed to investigate distribution characteristics PD among aged 45 years older.

Language: Английский

Citations

6
National and Regional Rates of Chronic Diseases and All-Cause Mortality in Saudi Arabia—Analysis of the 2018 Household Health Survey Data DOI Open Access
MAJED SAEED ALZAHRANI,

Yaser Saad Alharthi,

Jamal Khaled S Aljamal

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2023, Volume and Issue: 20(7), P. 5254 - 5254

Published: March 24, 2023

The disease burden and mortality were estimated in Saudi Arabia between 2010 2017 but unknown 2018. This study aims to assess the 2018 national regional rates of chronic diseases all-cause among total populations. In this descriptive cross-sectional study, we obtained data from 24,012 households household health survey. We included doctor-diagnosed conditions such as diabetes mellitus (DM), hypertension (HTN), cardiovascular (CAD), cancer (CN). A secondary analysis was performed by Both citizens residents comprised population. Makkah Al-Medina had greater population; however, Al-Baha Ha'il high related Age-adjusted 286 per 100,000 population-year. age-adjusted rate those aged 65 above 3428 population same age group. Men a 1779 men, which higher than 1649 for women. 2018, most DM, HTN CAD, Al-Qassim CN. People older highest death rate.

Language: Английский

Citations

16
Insights into Parkinson’s Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis DOI Creative Commons
Hagar Elbatanouny, Natasa Kleanthous, Hayssam Dahrouj

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(12), P. 3959 - 3959

Published: June 18, 2024

Parkinson’s Disease (PD) is a complex neurodegenerative disorder characterized by spectrum of motor and non-motor symptoms, prominently featuring the freezing gait (FOG), which significantly impairs patients’ quality life. Despite extensive research, precise mechanisms underlying FOG remain elusive, posing challenges for effective management treatment. This paper presents comprehensive meta-analysis prediction detection methodologies, with focus on integration wearable sensor technology machine learning (ML) approaches. Through an exhaustive review literature, this study identifies key trends, datasets, preprocessing techniques, feature extraction methods, evaluation metrics, comparative analyses between ML non-ML The analysis also explores utilization cueing devices. limited adoption explainable AI (XAI) approaches in research represents significant gap. Improving user acceptance comprehension requires understanding logic algorithm predictions. Current has number limitations, are identified discussion. These include issues devices, dataset constraints, ethical privacy concerns, financial accessibility restrictions, requirement multidisciplinary collaboration. Future avenues center refining explainability, expanding diversifying adhering to requirements, increasing accuracy. findings contribute advancing offer valuable guidance development more ultimately benefiting individuals affected PD.

Language: Английский

Citations

5
Migraine headache (MH) classification using machine learning methods with data augmentation DOI Creative Commons
Lal Khan,

Moudasra Shahreen,

Atika Qazi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 2, 2024

Abstract Migraine headache, a prevalent and intricate neurovascular disease, presents significant challenges in its clinical identification. Existing techniques that use subjective pain intensity measures are insufficiently accurate to make reliable diagnosis. Even though headaches common condition with poor diagnostic specificity, they have negative influence on the brain, body, general human function. In this era of deeply intertwined health technology, machine learning (ML) has emerged as crucial force transforming every aspect healthcare, utilizing advanced facilities ML shown groundbreaking achievements related developing classification automatic predictors. With this, deep models, particular, proven effective solving complex problems spanning computer vision data analytics. Consequently, integration healthcare become vital, especially countries where limited medical resources lack awareness prevail, urgent need forecast categorize migraines using artificial intelligence (AI) becomes even more crucial. By training these models publicly available dataset, without augmentation. This study focuses leveraging state-of-the-art algorithms, including support vector (SVM), K-nearest neighbors (KNN), random forest (RF), decision tree (DST), neural networks (DNN), predict classify various types migraines. The proposed augmentations were trained seven migraine. revealed results show DNN, SVM, KNN, DST, RF achieved an accuracy 99.66%, 94.60%, 97.10%, 88.20%, 98.50% respectively augmentation highlighting transformative potential AI enhancing migraine

Language: Английский

Citations

4
Characteristics of Voice Onset Time among Speakers of Jordanian Arabic with Parkinson’s Disease DOI Creative Commons
Firas Alfwaress, Muhammad A. Badarneh,

Rahaf A. Mousa

et al.

Forum for Linguistic Studies, Journal Year: 2025, Volume and Issue: 7(1)

Published: Jan. 1, 2025

Background: The voice onset time (VOT) is an acoustic measure to assess speech neuroregulatory mechanisms. However, the VOT was not measured in individuals of Jordanian Arabic with Parkinson's Disease (PD). Therefore, this research aimed using a cross-sectional design. Sixteen PD and 16 healthy controls had their assessed under two treatment conditions (Off On-medication). several phonetic contexts. results revealed higher effect among voiceless consonants for both experimental than controls. Whereas no effects were observed voiced between groups. In comparison, differences group Off-medication condition. administration levodopa affected measure; significant decrease Off On-medication conditions. Additionally, impacts on found when comparing front back consonants, rounded unrounded vowels, high low words versus sentence. may vary according characteristics medication status patients PD. still considered sensitive investigate production's mechanisms levodopa's Arabic. Notably, these acoustical markers only represent first step objective biological screening from signals.

Language: Английский

Citations

0
Evaluating Heart Rate Variability as a Biomarker for Autonomic Function in Parkinson’s Disease Rehabilitation: A Clustering-Based Analysis of Exercise-Induced Changes DOI Creative Commons
Ahmed M. Basri, Ahmad F. Turki

Medicina, Journal Year: 2025, Volume and Issue: 61(3), P. 527 - 527

Published: March 17, 2025

Background: Heart rate variability (HRV) is a key biomarker reflecting autonomic nervous system (ANS) function and neurocardiac regulation. Reduced HRV has been associated with cardiovascular risk, neurodegenerative disorders, dysfunction. In Parkinson’s disease (PD), impairments indicate altered balance, which may be modifiable through structured exercise interventions. This study investigates the effects of aerobic on in patients PD evaluates adaptations to rehabilitation. Methods: A total 110 (55 male, 55 female) participated supervised three-month program. was assessed pre- post-intervention using electrocardiogram (ECG) recordings. Time-domain frequency-domain metrics, including standard deviation RR intervals (SDRR), very-low-frequency (VLF), low-frequency (LF), high-frequency (HF) power, LF/HF ratio, were analyzed. Principal Component Analysis (PCA) clustering techniques applied identify subgroups responders based adaptation. Results: Significant improvements observed post-intervention, reduction ratio (p < 0.05), indicating improved balance. Cluster analysis identified four distinct response subgroups: Strong Responders, Moderate Mixed/Irregular Low Responders. These findings highlight individual exercise. PCA revealed that parameters contribute differently regulation, emphasizing complexity changes Conclusions: demonstrates induces beneficial patients, as reflected by changes. The identification suggests need for personalized rehabilitation strategies optimize function. Further research warranted explore long-term impact HRV-guided interventions management.

Language: Английский

Citations

0
Global, regional and national burden of Parkinson’s disease in people over 55 years of age: a systematic analysis of the global burden of disease study, 1991–2021 DOI Creative Commons
Siyang Peng, Peng Liu, Xiaowen Wang

et al.

BMC Neurology, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 23, 2025

Parkinson's disease (PD) has emerged as a major global public health challenge. However, there is currently lack of systematic analysis regarding the burden PD and its long-term trends among people over 55 years age. This study utilizes data from Global Burden Disease 2021 database to analyze prevalence, incidence, disability-adjusted life (DALYs), mortality rates in individuals aged older 1990 2021. The annual percentage change was calculated assess temporal burden. Point estimates their corresponding ranges were reported with 95% uncertainty intervals. Globally, DALYs, above significantly increased 2021, all indicators being higher males than females. trend evident across five Socio-Demographic Index (SDI) groups 21 regions worldwide. number prevalent cases, incident deaths showed significant increases positively correlated SDI (R = 0.645, P < 0.001). Among 185 countries, incidence rate increased, DALY rising 74 countries 65 countries. Notably, population 95 older, prevalence particularly remarkable increases, at 735% 505%, respectively. Furthermore, greatest increase observed 55-59 age group, especially Middle High-middle regions. indicates that past three decades. reflects profound impact aging socioeconomic development levels on PD, underscoring urgency addressing

Language: Английский

Citations

0