Parkinson's Disease (PD) is a complex neurological illness that causes severe motor and non-motor symptoms due to a gradual loss of dopaminergic neurons in the substantia nigra. The aetiology of PD is influenced by a variety of genetic, environmental, and cellular variables. One important aspect of this pathophysiology is autophagy, a crucial cellular homeostasis process that breaks down and recycles cytoplasmic components. Recent advances in genomic technologies have unravelled a significant impact of ncRNAs on the regulation of autophagy pathways, thereby implicating their roles in PD onset and progression. They are members of a family of RNAs that include miRNAs, circRNA and lncRNAs that have been shown to play novel pleiotropic functions in the pathogenesis of PD by modulating the expression of genes linked to autophagic activities and dopaminergic neuron survival. This review aims to integrate the current genetic paradigms with the therapeutic prospect of autophagy-associated ncRNAs in PD. By synthesizing the findings of recent genetic studies, we underscore the importance of ncRNAs in the regulation of autophagy, how they are dysregulated in PD, and how they represent novel dimensions for therapeutic intervention. The therapeutic promise of targeting ncRNAs in PD is discussed, including the barriers that need to be overcome and future directions that must be embraced to funnel these ncRNA molecules for the treatment and management of PD. 

ncRNAs and Their Impact on Dopaminergic Neurons: Autophagy Pathways in Parkinson's Disease

Abstract Background Parkinson's disease (PD) is a degenerative neurological condition marked by the gradual loss of dopaminergic neurons in the substantia nigra pars compacta. The precise etiology of PD remains unclear, but emerging evidence suggests a significant role for disrupted autophagy—a crucial cellular process for maintaining protein and organelle integrity. Methods This review focuses on the role of non‐coding RNAs (ncRNAs) in modulating autophagy in PD. We conducted a comprehensive review of recent studies to explore how ncRNAs influence autophagy and contribute to PD pathophysiology. Special attention was given to the examination of ncRNAs' regulatory impacts in various PD models and patient samples. Results Findings reveal that ncRNAs are pivotal in regulating key processes associated with PD progression, including autophagy, α‐synuclein aggregation, mitochondrial dysfunction, and neuroinflammation. Dysregulation of specific ncRNAs appears to be closely linked to these pathogenic processes. Conclusion ncRNAs hold significant therapeutic potential for addressing autophagy‐related mechanisms in PD. The review highlights innovative therapeutic strategies targeting autophagy‐related ncRNAs and discusses the challenges and prospective directions for developing ncRNA‐based therapies in clinical practice. The insights from this study underline the importance of ncRNAs in the molecular landscape of PD and their potential in novel treatment approaches.

Autophagy‐associated non‐coding RNAs: Unraveling their impact on Parkinson's disease pathogenesis

Modular dynamic graph theory metrics effectively capture the patterns of dynamic information interaction during human brain development. While existing research has employed modular algorithms to examine the overall impact of dynamic changes in community structure throughout development, there is a notable gap in understanding the cross-community dynamic changes within different functional networks during early childhood and their potential contributions to the efficiency of brain information transmission. This study seeks to address this gap by tracing the trajectories of cross-community structural changes within early childhood functional networks and modeling their contributions to information transmission efficiency. We analyzed 194 functional imaging scans from 83 children aged 2 to 8 years, who participated in passive viewing functional magnetic resonance imaging sessions. Utilizing sliding windows and modular algorithms, we evaluated three spatiotemporal metrics-temporal flexibility, spatiotemporal diversity, and within-community spatiotemporal diversity-and four centrality metrics: within-community degree centrality, eigenvector centrality, between-community degree centrality, and between-community eigenvector centrality. Mixed-effects linear models revealed significant age-related increases in the temporal flexibility of the default mode network (DMN), executive control network (ECN), and salience network (SN), indicating frequent adjustments in community structure within these networks during early childhood. Additionally, the spatiotemporal diversity of the SN also displayed significant age-related increases, highlighting its broad pattern of cross-community dynamic interactions. Conversely, within-community spatiotemporal diversity in the language network exhibited significant age-related decreases, reflecting the network's gradual functional specialization. Furthermore, our findings indicated significant age-related increases in between-community degree centrality across the DMN, ECN, SN, language network, and dorsal attention network, while between-community eigenvector centrality also increased significantly for the DMN, ECN, and SN. However, within-community eigenvector centrality remained stable across all functional networks during early childhood. These results suggest that while centrality of cross-community interactions in early childhood functional networks increases, centrality within communities remains stable. Finally, mediation analysis was conducted to explore the relationships between age, brain dynamic graph metrics, and both global and local efficiency based on community structure. The results indicated that the dynamic graph metrics of the SN primarily mediated the relationship between age and the decrease in global efficiency, while those of the DMN, language network, ECN, dorsal attention network, and SN primarily mediated the relationship between age and the increase in local efficiency. This pattern suggests a developmental trajectory in early childhood from global information integration to local information segregation, with the SN playing a pivotal role in this transformation. This study provides novel insights into the mechanisms by which early childhood brain functional development impacts information transmission efficiency through cross-community adjustments in functional networks. 

Evolving brain network dynamics in early childhood: Insights from modular graph metrics

BACKGROUND
The oxidative deamination of a wide range of endogenous and exogenous amines is catalyzed by a family of enzymes known as monoamine oxidases (MAOs), which are reliant on flavin-adenine dinucleotides. Numerous neurological conditions, such as Parkinson's disease (PD) and Alzheimer's disease (AD), are significantly correlated with changes in the amounts of biogenic amines in the brain caused by MAO. Hydrogen peroxide, reactive oxygen species, and ammonia, among other toxic consequences of this oxidative breakdown, can harm brain cells' mitochondria and cause oxidative damage.


OBJECTIVE
The prime objective of this review article was to highlight and conclude the recent advancements in structure-activity relationships of synthetic derivatives of coumarins for MAO-B inhibition, published in the last five years' research articles.


METHODS
The literature (between 2019 and 2023) was searched from platforms like Science Direct, Google Scholar, PubMed, etc. After going through the literature, we have found a number of coumarin derivatives being synthesized by researchers for the inhibition of MAO-B for the management of diseases associated with the enzyme such as Alzheimer's Disease and Parkinson's Disease. The effect of these coumarin derivatives on the enzyme depends on the substitutions associated with the structure. The structure-activity relationships of the synthetic coumarin derivatives that are popular nowadays have been described and summarized in the current study.


RESULTS
The results revealed the updated review on SAR studies of synthetic coumarins as MAO-B inhibitors, specifically for Alzheimer's Disease and Parkinson's Disease. The patents reported on coumarin derivatives as MAO-B inhibitors were also highlighted.


CONCLUSION
Recently, coumarins, a large class of chemicals with both natural and synthetic sources, have drawn a lot of attention because of the vast range of biological actions they have that are linked to neurological problems. Numerous studies have demonstrated that chemically produced and naturally occurring coumarin analogs both exhibited strong MAO-B inhibitory action. Coumarins bind to MAO-B reversibly thereby preventing the breakdown of neurotransmitters like dopamine leading to the inhibition of the enzyme A number of MAO-B blockers have been proven to be efficient therapies for treating neurological diseases like Alzheimer's Disease and Parkinson's Disease. To combat these illnesses, there is still an urgent need to find effective treatment compounds.

Recent Advancements and SAR Studies of Synthetic Coumarins as MAO-B Inhibitors: An Updated Review.

Association of long-term blood pressure exposure with DTI-ALPS: A population-based cohort study

The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes, but little was known about the functional network among the cortical areas during this process. To address the question, we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven area. Whole-brain electroencephalography signals were recorded by 32-channel implanted electrodes. Afterward, we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag index. Finally, machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of rats. We found that the functional connectivity level was higher in the preparation phase compared to the walking phase. In addition, the cortex pays more attention to the control of hind limbs with higher requirements for muscle activity. The level of functional connectivity was lower where the terrain ahead can be predicted. Functional connectivity bursts after the rat accidentally made contact with uneven terrain, while in subsequent movement, it was significantly lower than normal walking. In addition, the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during walking. These results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.

Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain

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Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain