Parkinson Disease is a progressive neurodegenerative disorder for which accessible, low-cost screening methods remain limited. Sustained-vowel voice recordings contain measurable acoustic biomarkers associated with disease-related dysphonia that can be acquired without specialized equipment. This protocol describes a four-qubit quantum-classical hybrid convolutional neural network (QI-HCNN) that combines a parameterized quantum circuit with a shallow classical classification layer to classify Parkinson Disease using dimensionally reduced acoustic voice features. The protocol also benchmarks the proposed approach against a dimensionality-matched classical neural network and gradient-boosted tree classifiers trained on both the reduced and full feature sets. Using a publicly available, de-identified dataset comprising 195 voice recordings from 31 individuals, the QI-HCNN achieved an area under the receiver operating characteristic curve of 0.78 using three-fold stratified cross-validation, compared with 0.87 for the matched classical neural network and 0.94-0.95 for the gradient-boosted baselines trained on the reduced and full feature sets, respectively. A controlled ablation analysis demonstrated that one of the two entanglement operations in the circuit could not influence the measured output by design, whereas the remaining entanglement operation reduced, rather than improved, classification performance relative to a non-entangled variant. Patient-grouped cross-validation further showed that performance estimates varied substantially depending on the individuals assigned to the test set, reflecting the limited cohort size. This protocol therefore provides a fully specified and independently reproducible quantum-classical baseline together with a data-supported evaluation of the strengths and limitations of the current circuit design, providing a methodological foundation for future investigations rather than supporting claims of diagnostic readiness.

Parkinson's disease is one of the most common neurodegenerative disorders, and the pesticide rotenone is widely used to model Parkinson's disease in experimental studies. Rotenone-induced mitochondrial dysfunction is associated with oxidative stress and intracellular Ca2+ ([Ca2+]ᵢ) dysregulation in neuronal systems. L-type Ca2+ channels (LTCCs) contribute to Ca² ⁺ influx under oxidative stress conditions, but pharmacological inhibition of LTCCs is limited by cardiovascular side effects. Phospholipase D (PLD) has also been implicated in cellular stress-associated signaling pathways. Ginsenosides are known to influence Ca² ⁺ -related signaling; however, differences among ginsenosides in neuronal and microglial Ca² ⁺ regulation have not been fully characterized. Therefore, this study aimed to investigate the effects of ginsenosides on intracellular Ca² ⁺ homeostasis and oxidative stress of rotenone-exposed SH-SY5Y neuronal cells and BV2 microglial cells. Cell viability, superoxide dismutase (SOD) activity, interleukin-6 (IL-6) levels, intracellular Ca² ⁺ influx, and malondialdehyde (MDA) levels were evaluated. Intracellular Ca² ⁺ was measured using Fura-2 AM ratiometric fluorescence analysis. The effects of ginsenosides Rg1, Rg2, and Rd were examined using pharmacological inhibitors targeting PLD, LTCCs, and protein kinase A (PKA). Rotenone reduced cell viability and SOD activity, while increasing IL-6 levels, [Ca2+]ᵢ influx, and MDA levels in both cell types. Treatment with ginsenosides immediately before rotenone exposure attenuated rotenone-induced increases in [Ca2+]ᵢ and MDA levels. Ca² ⁺ responses in both SH-SY5Y and BV2 cells were sensitive to PLD inhibition. In SH-SY5Y cells, responses were additionally sensitive to LTCC inhibition, whereas BV2 cells showed weaker LTCC-associated pharmacological responses. Rd showed broader pharmacological sensitivity involving PLD-, LTCC-, and PKA-associated components, whereas Rg1 and Rg2 showed predominantly PLD-associated response patterns. These findings suggest that ginsenosides differentially modulate rotenone-associated Ca² ⁺ dysregulation through PLD-associated pharmacological pathways in a cell type-dependent manner. Overall, the present findings demonstrate distinct pharmacological response profiles among structurally different ginsenosides under rotenone-induced oxidative stress conditions.

Gut motility dysfunction is a common symptom of Parkinson's disease (PD), but its central mechanisms remain unclear. Here, we utilize multiple mouse models, which mimic both genetic and sporadic PD, to reproduce PD-related gut motility dysfunction. We find that α-synuclein pathology significantly impairs the excitability of cholinergic neurons in the dorsal motor nucleus of the vagus (DMV). Chemogenetic activation of these neurons effectively restores gut motility in PD models, revealing a causal link between DMV neuronal hypoexcitability and gut motility dysfunction. Notably, electroacupuncture (EA) at ST36, a classic acupoint that activates vagal pathways, robustly increases the excitability of DMV neurons and alleviates gut dysmotility in PD mice, a therapeutic effect mediated by the cholinergic brain-gut axis. Together, our findings demonstrate that DMV neuronal hypoexcitability is a key driver of PD-related gut dysmotility and suggest that EA at ST36 could serve as a promising therapeutic strategy.

Alterations in the gut microbiota have been associated with Parkinson's disease (PD), but longitudinal microbial changes after fecal microbiota transplantation (FMT) and their clinical associations remain poorly understood. This single-center retrospective observational study included 6 patients with PD, stratified into high- and low-severity subgroups based on disease duration (>6 years vs ≤6 years). Thirty-six fecal samples were collected before FMT and monthly for five months afterward. Microbial diversity, community structure, taxonomic composition, and predicted functional profiles were assessed using 16S ribosomal RNA gene sequencing. Analyses included alpha and beta diversity, taxonomic abundance, linear discriminant analysis effect size, Tax4Fun2-based functional prediction, and Spearman rank correlations between microbial features and clinical indicators. Descriptive analyses indicated differences in microbial richness, diversity, community structure, and predicted functions between severity subgroups and across post-FMT time points. At baseline, the low-severity subgroup had greater microbial richness and diversity than the high-severity subgroup, with relatively higher abundances of taxa including Bifidobacterium and Lactobacillus. One month after FMT, richness and diversity increased from baseline in the high-severity subgroup, accompanied by changes in taxonomic composition. Both subgroups showed time-associated variation in microbial diversity and predicted Kyoto Encyclopedia of Genes and Genomes pathway enrichment after FMT. Predicted functions included carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, membrane transport, and signal transduction. Several operational taxonomic units correlated with indicators of motor impairment, constipation, sleep quality, functional status, and neuropsychiatric symptoms. FMT was therefore associated with longitudinal changes in gut microbial diversity, composition, and predicted functions, and specific microbial features were associated with motor and non-motor indicators. Given the small retrospective cohort, these findings are preliminary and warrant confirmation in larger controlled studies. Future studies should determine whether these microbial alterations are reproducible, persist beyond five months, reflect donor engraftment, and correspond to measurable clinical improvement after transplantation in PD.

Respiratory dysfunction is increasingly recognized as a clinically relevant yet underexplored feature of neurodegenerative diseases, particularly Parkinson's disease (PD). Although traditionally defined by motor symptoms resulting from dopaminergic degeneration, PD also affects neural systems involved in autonomic and respiratory control. Clinical and experimental evidence demonstrates that respiratory impairments in PD include alterations in respiratory rhythm generation, chemosensitivity, ventilatory responses to hypoxia and hypercapnia, and sleep-related breathing regulation. Emerging data indicate that these disturbances are not merely secondary consequences of motor dysfunction, but instead reflect selective vulnerability of brainstem respiratory networks. In this review, we discuss current evidence from human studies and experimental models, with emphasis on circuit-level mechanisms underlying respiratory dysfunction in PD. We highlight how oxidative stress, neuroinflammation, and neuromodulatory alterations contribute to degeneration and dysfunction of respiratory-related nuclei. We further examine the complex interactions between chemosensory control, sleep-wake regulation, and respiratory stability, as well as compensatory mechanisms that may partially preserve ventilatory function during disease progression. Finally, we discuss potential treatments for these dysfunctions, as well as major conceptual gaps and controversies in the field, including species-dependent differences, limitations of current experimental models, and challenges in translating mechanistic findings into clinical interventions. We propose that respiratory control networks represent a mechanistically relevant and selectively vulnerable system in PD, with important implications for early diagnosis, biomarker discovery, and the development of targeted therapeutic strategies.

Parkinson's disease (PD) disrupts intrinsic brain networks that support motor and cognitive functions. Using resting-state fMRI from 138 PD patients and 54 controls, we combined independent component analysis (ICA) with nonlinear functional connectivity (FC) based on distance correlation. Compared with conventional Pearson-based measures, nonlinear FC revealed stronger and spatially distinct connectivity patterns, especially in parietal and sensorimotor regions. Group comparisons showed robust differences (p < 1×10⁻⁷), with four ICA networks (Components 4, 10, 19, and 20) displaying consistent alterations. Importantly, hyperconnectivity within a posterior midline network (Component 10), overlapping with regions commonly associated with the default mode network, correlated positively with Hoehn & Yahr stage (r = 0.51, p = 0.022), linking network reorganization to clinical severity. These findings demonstrate that nonlinear FC enhances sensitivity to PD-related network alterations, while spatial features highlight clinically relevant biomarkers. By integrating advanced connectivity metrics with data-driven network analysis, our study contributes to the methodological development of resting-state fMRI and its translational application to PD.

CD4⁺ T cells are central regulators of neuroimmune responses, and their dysregulation is increasingly recognized as a pathogenic driver across multiple neurological disorders, including multiple sclerosis (MS), Alzheimer's disease (AD), Parkinson's disease (PD), ischemic stroke (IS), traumatic brain injury (TBI), central nervous system (CNS) infections, and stress-induced vestibular dysfunction. This review outlines the differentiation and functional specialization of CD4⁺ T cell subsets T helper 1 (Th1), Th17, Th2, Th9, regulatory T cells (Tregs), and T follicular helper (Tfh) cells and evaluates their distinct roles in CNS injury and repair. In MS, autoreactive Th17 cells promote demyelination through C-C chemokine receptor type 6 (CCR6)-C-C motif ligand 20 (CCL20)-mediated CNS trafficking and granulocyte-macrophage colony-stimulating factor (GM-CSF)-dependent microglial activation. In contrast, neurodegenerative conditions involve antigen-specific CD4⁺ T cell responses to disease-associated neoantigens, including amyloid-beta (Aβ) and tau in AD, and α-synuclein in PD, often preceding clinical manifestation. Disease-specific differences in antigen identity, glial crosstalk, and temporal infiltration patterns are described for each condition. Age-related CD4⁺ T cell dysfunction, encompassing thymic involution, imbalance between naïve and memory T cell populations, diminished plasticity, and metabolic alterations in senescent lymphocytes, is discussed as a contributor to chronic neuroinflammation in aging. Current and emerging therapeutic strategies are evaluated, including disease-modifying therapies, immune checkpoint modulation, cytokine blockade, Treg-based adoptive transfer, antigen-specific tolerance via nanoparticle systems, metabolic interventions, and chimeric antigen receptor (CAR)-Treg and gene-based approaches. Collectively, these insights indicate the importance of CD4⁺ T cell dynamics in shaping targeted immunotherapeutic strategies for neurological diseases.

Anti-amyloid immunotherapies (lecanemab, donanemab) produce statistically significant but clinically modest slowing of decline in early Alzheimer's disease (AD), with substantial inter-individual response variability that current covariates-antibody titer, baseline amyloid load, apolipoprotein E ε4 (APOE4) status, or tau burden-leave largely unexplained. We propose that a systematically unmeasured upstream variable contributes to this variability: the structural integrity of the locus coeruleus (LC), the principal source of brain norepinephrine (NE), framed as a candidate determinant of amyloid-β (Aβ) clearance efficiency rather than of overall clinical outcome. This hypothesis paper synthesizes three peer-reviewed lines of evidence and derives a hierarchy of falsifiable predictions; no new data are reported. First, tau pathology initiates in LC neurons before any cortical structure, reducing NE output from the earliest preclinical stage. Second, NE governs two complementary Aβ-clearance pathways: glymphatic flow, via aquaporin-4 dynamics driven by slow LC oscillations during non-REM sleep, and microglial phagocytosis, via β2-adrenergic receptor signaling. Third, in Parkinson's disease, the DTI-ALPS index mediates the relationship between LC integrity on neuromelanin-sensitive MRI and cognition. We term this the Locus Coeruleus Gateway Hypothesis (LCGH). Its mediation chain is testable now in ADNI, which holds research-grade diffusion-tensor imaging; its treatment-response prediction requires immunotherapy cohorts that acquire such imaging, not the existing CLARITY-AD or TRAILBLAZER-ALZ 2 archives, whose safety MRI used diffusion-weighted, not tensor, sequences. We state explicitly that Aβ clearance is only one contributor to clinical benefit, and that the LCGH predicts pharmacodynamic efficiency, not that NE restoration treats AD.

BackgroundBalance impairments in Huntington's Disease (HD) are common but difficult to treat.ObjectivesWe aimed to investigate the potential effects and feasibility of multimodal physiotherapy balance intervention in HD.MethodIn this prospective, double-blind, parallel group randomized clinical trial (phase 1pilot study), we screened 56 persons with genetically confirmed HD; 36 were assigned randomly into three groups: 1) multimodal physiotherapy balance intervention supported by rhythmical auditory stimuli (RAS-supported, n = 12); (2) multimodal physiotherapy balance intervention without rhythmical auditory stimuli (Regular, n = 12); and (3) control intervention (educational program, n = 12). Interventions were delivered for 2-months, at a low dose, 1 session/week. The primary outcome was the Mini-BESTest scored directly after the intervention. All outcomes were assessed at three time-points.ResultsDirectly post-intervention, both the RAS-supported group and the Regular group improved significantly on the Mini-BESTest score compared to the Control group (RAS-supported 4.2 (95% Confidence Interval(CI) 3.1; 5.2), p < 0.001; Regular 2.7 (CI 1.7; 3.6), p < 0.001. These improvements were retained at 6-month follow-up only for the RAS-supported group.ConclusionThese findings motivate future studies to further explore multimodal physiotherapy interventions to improve balance in HD.