Search Results (7,715)

According to the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder among older adults, surpassed only by Alzheimer’s disease. PD is characterized by a heterogeneous combination of motor and non-motor symptoms, with involuntary movements constituting a central clinical defining feature. The prodromal phase presents substantial diagnostic challenges, as early symptoms are often mild, nonspecific, and commonly misinterpreted because overt motor signs are absent. Significantly, these early alterations can precede formal diagnosis by up to two decades, highlighting the urgent need for effective early detection strategies. In this work, we propose a functional Magnetic Resonance Imaging (fMRI)-based image-processing and machine learning framework for early detection of PD. Statistical features are extracted to train a set of 25 machine learning kernels, from which the most accurate model is selected. We then apply the Minimum Redundancy Maximum Relevance (mRMR) algorithm to identify the most descriptive fMRI frames for each subject. We introduce a hierarchical classification strategy: an initial binary classification to distinguish control subjects from prodromal + PD cases, followed by a second binary classification to discriminate between Prodromal and PD. The experimental results demonstrate a maximum precision of $96.3$% with 16 axial slices and $86.4$% with a single slice, indicating the effectiveness of the preprocessing strategy and its potential as a non-invasive biomarker for early PD detection, even with reduced input data. These findings suggest that high classification performance can be achieved with a limited number of fMRI slices, facilitating data acquisition and reducing subject burden in clinical studies. Full article

Conventional qualitative eye movement examinations may miss subtle abnormalities, complicating early and accurate diagnosis of progressive supranuclear palsy (PSP). Quantitative oculography, represented by video-oculography (VOG), provides an objective digital assessment of eye movements. This review summarizes abnormalities in advanced eye movement tasks in PSP, including prosaccades (ProSs), antisaccades (ASs), memory-guided saccades (MGSs), predictive saccades (PSs), overlap saccades (OSs) and gap saccades (GSs), and considers their underlying pathophysiological mechanisms. Quantitative metrics from these tasks may help distinguish PSP subtypes and PSP from other neurodegenerative diseases, such as Parkinson’s disease (PD), multiple system atrophy (MSA), corticobasal degeneration (CBD) and Alzheimer’s disease (AD). Advanced eye movement measures are therefore promising candidate biomarkers for PSP diagnosis and longitudinal disease monitoring. Full article

Introduction: Voice-based digital biomarkers have emerged as a promising, non-invasive approach for the early detection and monitoring of neurodegenerative disorders, particularly Parkinson’s disease (PD). Although voice recordings can be acquired easily using mobile health technologies, their integration into routine clinical practice remains limited due to challenges related to model interpretability and clinical validation. This study aimed to investigate the diagnostic potential of voice recordings acquired through the TALIA smartphone and web-based platform and to improve model transparency using explainable artificial intelligence (XAI) techniques. Methods: Voice recordings from participants with PD and control group (CG) were acquired over a six-month period using the TALIA digital-health platform at Vito Fazzi Hospital in Lecce, Italy. The data were evaluated cross-sectionally at the recording level. Sustained vowel (/a/) phonations were preprocessed and transformed into spectrogram images. A transfer-learning framework based on the pre-trained VGGish convolutional neural network (VGGish-CNN) was developed to classify PD and CG voice recordings. To enhance interpretability, explainable artificial intelligence (XAI) methods, including Local Interpretable Model-Agnostic Explanations (LIME) and Occlusion Sensitivity, were integrated to identify the spectro-temporal regions contributing most strongly to model predictions. Results: The proposed VGGish-CNN framework demonstrated excellent classification performance in distinguishing PD from CG. The model achieved an accuracy of 0.93, precision of 0.91, recall of 0.95, F1-score of 0.93, loss of 0.16, and an area under the receiver operating characteristic curve (AUC) of 0.987. XAI analyses provided qualitative, sample-specific visualizations of the spectro-temporal regions contributing to individual model predictions, thereby improving the transparency and interpretability of the deep-learning model. Conclusions: The findings demonstrate that a transfer-learning approach based on VGGish-CNN could achieve promising recording-level classification performance in distinguishing voice recordings from participants with PD and CG within this pilot dataset. Furthermore, XAI techniques provide qualitative insight into the model’s decision-making process. These preliminary findings support further investigation of voice-based approaches for PD screening in larger cohorts using participant-level and external validation. Full article

Objective: To evaluate the sustained real-world effectiveness and safety of catechol-O-methyltransferase (COMT) inhibitors added to levodopa in patients with Parkinson’s disease (PD) presenting early motor fluctuations. Methods: REONPARK is an ongoing, multicenter, prospective observational study conducted in Spain. Adult patients with PD and end-of-dose motor fluctuations for <2 years initiating a COMT inhibitor were included. Outcomes assessed at 3, 6, and 12 months included Clinician and Patient Global Impression of Change (CGI-C, PGI-C), Movement Disorder Society–Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Wearing-off Questionnaire (WOQ-19), Non-Motor Symptoms Scale (NMSS), Parkinson’s Disease Questionnaire-8 (PDQ-8), and safety. This article presents the 3-, 6-, and 12-month planned interim analysis of the study. Results: A total of 143 patients were included (99.3% treated with opicapone), of whom 138, 131, and 89 patients completed the 3, 6, and 12 months of follow-up, respectively. Levodopa doses remained stable in most patients (73% at 12 months). Significant and sustained improvements were observed in MDS-UPDRS Parts III and IV scores, as well as the total MDS-UPDRS score over 12 months, with greater likelihood of Part IV improvement in patients receiving <4.5 mg/kg/day of levodopa. OFF time decreased by 1.6–2.0 h from baseline. ON-time quality was maintained over time with 97.7% of patients reporting no or minimal functional impact from dyskinesia, while 47.7% of patients had no impact from motor fluctuations and 36.4% of patients no longer experienced OFF periods at 12 months. PDQ-8 scores remained stable and no overall benefit on total non-motor symptoms burden was demonstrated, despite improvements in selected domains among patients with a higher baseline non-motor symptoms burden. WOQ-19 scores improved significantly. Conclusions: In PD patients with early motor fluctuations, opicapone initiation was associated with sustained improvements in motor outcomes and reduced OFF time, and maintained the ON-time quality over 12 months, with stable levodopa dosing. Full article

Parkinson’s disease (PD) is a clinically and biologically heterogeneous neurodegenerative disorder in which variable symptom profiles, progression rates, and treatment responses likely reflect distinct but partially convergent pathogenic mechanisms. Among these, mitochondrial dysfunction recurs across both familial and sporadic PD; however, this broad concept alone cannot explain disease heterogeneity. To preserve mitochondrial homeostasis, cells rely on a complex mitochondrial quality control (MQC) system that encompasses protein import and proteostasis, redox surveillance, organellar dynamics and positioning, biogenesis, and selective elimination of damaged mitochondria. MQC also depends on coordination with other organelles, particularly the endoplasmic reticulum and lysosomes. In this review, we discuss how different layers of MQC maintain mitochondrial integrity and how these pathways are functionally coupled. We further consider how an MQC-based framework may help explain the clinical heterogeneity of PD, including selective neuronal vulnerability, subtype formation, and divergent disease progression, and how it can frame recent therapeutic advances aimed at biologically stratified intervention. Full article

Parkinson’s disease (PD) is characterized by oxidative stress, mitochondrial dysfunction, and dopaminergic neuron loss, for which effective treatments remain unavailable. Here, we report CL0179, a fungal-derived decahydrofluorene alkaloid with antioxidant-associated neuroprotective properties, and evaluate its effects across cellular and animal PD models. CL0179 exhibited a favorable safety profile and protected SHSY5Y against 6-hydroxydopamine- (6-OHDA), rotenone-, and 1-Methyl-4-phenylpyridinium-iodide (MPP⁺)-induced neurotoxicity by preserving mitochondrial membrane potential and network integrity. Transcriptomic analyses revealed selective restoration of gene-expression programs associated with oxidative phosphorylation, mitochondrial bioenergetics, and stress adaptation disrupted by MPP⁺. CL0179 also enhanced SIRT1 activity under MPP⁺ stress, whereas pharmacological SIRT1 inhibition partially attenuated protection of mitochondrial membrane potential and cell viability. In LRRK2-G2019S astrocytes, CL0179 reduced ROS and α-synuclein accumulation and restored mitochondrial organization, while in human dopaminergic neurons, it attenuated toxin-induced mitochondrial depolarization and preserved neuronal architecture. To overcome the low production of CL0179, we generated the structurally related analogue CL0670. Both compounds crossed the blood–brain barrier and protected mouse primary cortical neurons, while CL0670 improved motor deficits in a 6-OHDA mouse model. Collectively, these compounds promote mitochondrial resilience and stress-adaptive neuroprotection, supporting their potential for PD and related neurodegenerative disorders. Full article

Neurodegenerative diseases share features of neuronal loss, neuroinflammation, and protein aggregation. The cGAS-STING pathway, a key DNA sensor, mediates neuroinflammation via TBK1-IRF3 and IKK-NF-κB axes, inducing type I interferons and pro-inflammatory cytokines. This pathway upregulates ZBP1, promotes PANoptosome assembly, and triggers PANoptosis, releasing DAMPs and creating a self-amplifying “inflammation–death” cycle. In Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis, pathological proteins (Aβ, Tau, α-synuclein, TDP-43) or genetic defects (e.g., C9orf72 repeats) cause mitochondrial DNA leakage or genomic instability, activating this axis. This review highlights the cGAS-STING-PANoptotic cascade as a shared pathogenic mechanism and discusses the current evidence and remaining challenges in confirming this hypothesis. Full article

Failure of axonal maintenance is proposed as a mechanism shared by Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). We reanalysed three public post-mortem resources under one rule set: bulk RNA-seq of 1242 samples from 319 donors (GSE153960) and midbrain single-nucleus RNA-seq (GSE157783, GSE178265). As a contributing project, a second batch variable tracked diagnosis in both cord segments and was completely separated from it in three cortical regions, which we removed. Adjusting for this removed a third of the naive differential expression. In ALS cord, the dominant depleted program was microtubule-based axonal transport (normalised enrichment score −2.40, FDR < 0.001); a regeneration-associated panel reached significance in none of ten fits. An ALS cord signature carried into the PD midbrain and scored highest on microglia in all 11 donors (+3.55 versus +0.73 next). Of 86 gene sets significant in both diseases, a translation block contained the GCN2 amino-acid-deficiency response. Both axes are compartment-level: within PD microglia, the complement panel is null (+0.21, p = 0.57). No GCN2 activity was measured, and the ALS cord is compared against PD midbrain. The axes that survive this control are glial and translational; the axonal question is not adjudicable in PD, where the panel score tracks dopaminergic content. Full article

Background: Progressive supranuclear palsy (PSP) and Parkinson’s disease (PD) frequently present with overlapping clinical features, creating diagnostic challenges, particularly during the early stages of disease. Structural MRI and peripheral inflammatory biomarkers may provide complementary information for differential diagnosis. Objective: To evaluate the diagnostic performance of automated pallidal volumetry and the neutrophil-to-lymphocyte ratio (NLR), individually and in combination, for distinguishing PSP from PD. Methods: This retrospective case–control study included 12 patients with PSP and 12 patients with PD. Automated brain volumetry was performed using the volBrain 2.0 platform. Total pallidal volume was selected as the primary imaging biomarker based on its established involvement in PSP pathology. NLR was calculated from routine blood counts. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. A combined MRI–blood model was constructed using binary logistic regression. Results: Patients with PSP demonstrated lower normalized pallidal volumes than patients with PD. Pallidal volume showed high diagnostic performance for differentiating PSP from PD (AUC = 0.885), whereas NLR demonstrated only modest discriminatory ability (AUC = 0.715). The combined pallidal volume–NLR model achieved an AUC of 0.903 compared with 0.885 for pallidal volumetry alone, but this difference was not statistically significant (DeLong p = 0.732), and sensitivity, specificity and overall accuracy remained unchanged. Conclusions: Automated pallidal volumetry provided substantially better discrimination between PSP and PD than NLR alone. Although the combined model showed a small numerical increase in AUC, this improvement was not statistically significant and did not alter sensitivity, specificity or overall accuracy. These findings do not demonstrate incremental diagnostic value of NLR beyond pallidal volumetry in this cohort. Larger prospective studies are needed to determine the clinical utility of combined MRI–blood biomarker approaches in PSP. Full article

Emergency department providers may be challenged by the presentation of patients who exhibit movement abnormalities that could indicate conditions requiring interventions to reduce the risk of potential morbidity and mortality. Crucially, interventions for potential neurological diseases that require immediate intervention (e.g., stroke) are contraindicated in patients exhibiting movements that may be voluntary (e.g., emotional expressions and fabricated symptoms) or functional (e.g., functional movement disorders such as functional tremors or psychogenic nonepileptic seizures (PNES)). Current motor assessment relies on subjective visual observation by human examiners, which limits the speed and accuracy of this differentiation. We hypothesize that technology measuring the temporal and spatial characteristics of movement can provide quantifiable signatures to differentiate movement subtypes and reflect the distinct neural pathways underlying voluntary and involuntary movement. To assess clinical and commercial interest in such technology, we conducted exploratory interviews with 17 of 56 invited potential customers (neurologists, biomedical engineers, and other clinicians) through a National Science Foundation I-Corps program where interviewees confirmed motor assessments are often performed without instrumentation and expressed willingness to adopt inexpensive, validated technology. The findings support interest in our proposed approach; however, this evidence is still preliminary as the interview sample was a non-random convenience sample and no comparison of respondents and non-respondents was performed. The sensor-based technology also remains conceptual with no current prototype, indicating the need for further studies utilizing more rigorous sampling and prototype development before clinical application. Full article

Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible neurological disorder characterized by gait impairment, cognitive decline, and urinary dysfunction. Despite improvements in diagnostic criteria and neuroimaging techniques, accurate diagnosis remains challenging due to clinical overlap with neurodegenerative diseases, particularly Alzheimer’s disease (AD) and synucleinopathies. Biomarkers capable of improving differential diagnosis, patient selection for shunt surgery, and prognostic assessment are therefore of considerable clinical interest, as has been in AD biomarkers. This review summarizes current evidence regarding the role of α-synuclein as a potential additional marker in iNPH, focusing on its association with concomitant neurodegenerative pathology, clinical manifestations, and treatment outcomes. Available studies indicate that α-synuclein pathology may coexist with iNPH in a substantial proportion of patients, with reported positivity rates ranging from approximately 14% to 33%, depending on the detection method used. Patients with concomitant α-synuclein pathology may exhibit clinical features atypical for pure iNPH, including upper limb rigidity, olfactory dysfunction, hallucinations, autonomic dysfunction, sleep disturbances, and fluctuating cognitive impairment. However, current evidence does not support α-synuclein positivity as an independent predictor of poor response to cerebrospinal fluid (CSF) drainage or shunt surgery. On the contrary, α-synuclein presence may provide additional information regarding mixed neurodegenerative pathology and contribute to personalized clinical management. Future studies should focus on standardized detection techniques, larger multicenter cohorts, longitudinal follow-up, and integration of α-synuclein assessment with established AD biomarkers, neuroimaging findings, and clinical evaluation. Overall, α-synuclein represents a promising complementary marker in iNPH, with potential value in being taken into consideration during clinical evaluation and understanding disease heterogeneity. Full article

Selenium-dependent antioxidant systems are critical for neuronal redox balance, but whether Parkinson’s disease (PD) involves systemic selenium deficiency or selective utilization impairment remains unclear. Using Parkinson’s Progression Markers Initiative (PPMI) proteomic data, we identified specific downregulation of glutathione peroxidase 3 (GPX3) in cerebrospinal fluid in PD, suggesting a compartment-specific alteration in GPX3-related antioxidant defense rather than a uniform systemic selenium deficit. Inorganic selenium sources suffer from low bioavailability and narrow therapeutic windows. We therefore developed a selenium-enriched peptide fraction (IPP-Se-F12) via controlled selenization of Idesia polycarpa Maxim. cake meal peptides, and characterized its selenium content, size distribution, and radical-scavenging activity. In SH-SY5Y and nematode models, IPP-Se-F12 attenuated 6-hydroxydopamine (6-OHDA)-induced cell death and rescued locomotor and dopamine-dependent behaviors more effectively than sodium selenite treatment. RNAseq further showed that IPP-Se-F12 treatment was associated with transcriptional changes in dephosphorylation, axon-guidance, and GPX3-centered antioxidant networks, including increased expression of gpx-3 and gpx-5. This study supports IPP-Se-F12 as a plant-derived selenium-associated peptide fraction with protective activity in cellular and nematode models and identifies GPX-related antioxidant regulation as a candidate mechanism for further investigation. Full article

3,4-dihydroxyphenethylamine, commonly known as dopamine (DA), is a neuromodulator that fine-tunes neuronal excitability, neurotransmitter release, and the effects of other neurotransmitters on postsynaptic neurons. DA, acting on D1 and D2 receptor families, is involved in myriad functions. In the striatum, it is mainly implicated in motor control, motivation, and reward mechanisms. In the cerebral cortex it participates in attention processes, working memory, long-term memory, etc. DA overproduction or deficits lead to neuronal circuit imbalance that underlies a number of neurological and psychiatric diseases, including Parkinson’s disease (PD), schizophrenia, Huntington’s disease (HD), and substance use disorders (SUDs), to name a few. DA regulates neuronal excitability by modulating ion channels, the release of excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters, and postsynaptic interactions with glutamate and GABA receptors. Together, these pre- and postsynaptic actions of DA underlie a number of synergistic or antagonistic actions that have important implications for setting membrane potentials, improving the signal-to-noise ratio, and directing the sign of synaptic plasticity. In this review, I will first provide a historical overview of the many studies exploring DA actions in the brain, with particular focus on the striatum. Then, I will emphasize some of the contributions of our laboratory to the understanding of DA modulatory effects from an electrophysiological perspective. Finally, I will discuss the mechanistic and therapeutic implications of DA function and dysfunction. Full article

Neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) are characterized by the progressive loss of specific neuronal cell populations and are associated with protein aggregates. Current therapeutic approaches are still limited due to the complexity and heterogeneity of these diseases, which points toward an urgent need to discover and develop new therapeutic agents. Natural compounds are a promising source of novel bioactive agents targeting multiple mechanisms of action implicated in neurodegeneration. Andrographolide (ANDRO) is a natural compound extracted from Andrographis paniculata, a traditional Chinese herb known for its anti-inflammatory and antioxidant properties, which has emerged as a potential neuroprotective agent due to its ability to cross the blood–brain barrier (BBB). ANDRO can exert neuroprotective effects by modulating numerous transcription factors and signaling pathways across different cell types in the central nervous system (CNS). It has been described that ANDRO reverses cognitive and/or motor impairments in AD and PD study models. However, the cellular and molecular mechanisms behind these protective effects are still being elucidated. In this review, we analyze the most recent findings on ANDRO, a neuroprotective agent with multiple biological targets that could reduce the progression of the most prevalent neurodegenerative diseases, AD and PD. Full article

Neurological disorders are a major cause of disability and mortality worldwide, and accessible methods for detecting tremor-related trajectory deviations remain an important research challenge. We present an augmented reality (AR)-based approach for evaluating trajectory deviations associated with tremor-related hand movements in Parkinson’s disease (PD) and neurological sequelae of traumatic brain injury (TBI). Unlike conventional surface-based drawing tests, the proposed approach removes the physical support point that may facilitate compensatory stabilization of hand movements during task performance. The method implementing this concept was preliminarily evaluated in a pilot cohort of 131 participants, including 50 healthy controls, 6 patients with PD, and 75 combat veterans with TBI, and was compared with a standard geometric figure drawing test. In the PD subgroup, the AR protocol flagged algorithmically detected trajectory deviations in all six participants. Given the small PD sample and the limited number of additional findings in the TBI group, these observations should be interpreted as preliminary and hypothesis-generating rather than as evidence of proof-of-concept accuracy or sensitivity. The results suggest that the anchor-free AR-based trajectory-assessment method may warrant further investigation as a potential approach for tremor-related movement analysis. Larger clinically validated studies with independent confirmation and standard concept metrics will be required to determine the clinical utility of the proposed method. Full article