Optimized efficient attention-based network for facial expressions analysis in neurological health care.

Facial Expression Analysis (FEA) plays a vital role in diagnosing and treating early-stage neurological disorders (NDs) like Alzheimer's and Parkinson's. Manual FEA is hindered by expertise, time, and training requirements, while automatic methods confront difficulties with real patient data unavailability, high computations, and irrelevant feature extraction. To address these challenges, this paper proposes a novel approach: an efficient, lightweight convolutional block attention module (CBAM) based deep learning network (DLN) to aid doctors in diagnosing ND patients. The method comprises two stages: data collection of real ND patients, and pre-processing, involving face detection and an attention-enhanced DLN for feature extraction and refinement. Extensive experiments with validation on real patient data showcase compelling performance, achieving an accuracy of up to 73.2%. Despite its efficacy, the proposed model is lightweight, occupying only 3MB, making it suitable for deployment on resource-constrained mobile healthcare devices. Moreover, the method exhibits significant advancements over existing FEA approaches, holding tremendous promise in effectively diagnosing and treating ND patients. By accurately recognizing emotions and extracting relevant features, this approach empowers medical professionals in early ND detection and management, overcoming the challenges of manual analysis and heavy models. In conclusion, this research presents a significant leap in FEA, promising to enhance ND diagnosis and care.The code and data used in this work are available at: https://github.com/munsif200/Neurological-Health-Care.

Objective sleep enhancement in Parkinson's disease: A sham-controlled trial of low-frequency repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex.

INTRODUCTION: Parkinson's disease (PD) is often accompanied by sleep disturbances, impacting patients' quality of life. While repetitive transcranial magnetic stimulation (rTMS) shows promise in improving self-reported sleep quality, its effects on objective sleep architecture in PD remain understudied. Sleep disturbances, including rapid eye movement (REM) and slow-wave sleep disturbances, correlate with cognitive decline and motor symptoms. This study investigated the effect of low-frequency rTMS targeting the right dorsolateral prefrontal cortex (DLPFC) modifying objective sleep architecture and explored symptom improvement mechanisms in PD patients. METHODS: In this randomized, double-blind, sham-controlled trial, 67 PD patients received 10 consecutive days of 1-Hz rTMS over the right DLPFC. Polysomnography assessed sleep microstructure, while electroencephalogram recordings evaluated power spectral density and sleep spindle activity. Clinical scales measured sleep quality, motor symptoms, and cognition at baseline, post-treatment, and 3 months post-rTMS. RESULTS: The rTMS group exhibited improvements in sleep quality, motor symptoms, and cognition post-treatment, persisting at the 3-month follow-up. There was a notable increase in the REM sleep proportion post-rTMS. The rTMS group exhibited elevated low-frequency (0.5-2 Hz) slow-wave electroencephalogram spectral density during non-REM sleep. Cognitive enhancement correlated with increased lower delta power, while motor symptom progression correlated with spindle frequency and slow-wave sleep percentage changes. CONCLUSION: Low-frequency rTMS targeting the right DLPFC holds promise for improving clinical symptoms and modulating sleep architecture in PD. These findings suggest a link between symptom improvement and sleep structure enhancement, highlighting the need for further investigation into the therapeutic potential of rTMS in PD management.

Sleep disturbances and associated factors in patients with Parkinson's disease.

AIMS: This study aimed to describe clinical characteristics and sleep quality of Parkinson's Diseases (PD) patients and identify associated factors with sleep quality. METHODS: A cross-sectional study was conducted at the National Geriatric Hospital, Hanoi, Vietnam, from December 2022 to April 2023. A total of 130 Parkinson's disease patients undergoing treatment at the hospital were invited. Demographic and clinical characteristics were obtained. The diagnosis of sleep disorders was based on the standards outlined in the DSM-V. A multivariate logistic regression model was employed. RESULTS: 90.9 % experienced sleep disorder, with the significant types including insomnia (76.2 %) and restless legs syndrome (56.2 %). The majority of patients suffered two (33.1 %) and one kind of sleep disorder (32.3 %). Most patients experienced sleep disorders after diagnosis of PD (80.0 %). Only having shoulder and neck pain was positively associated with a likelihood of having sleep disturbances (OR=4.87, 95 %CI=1.18-20.15). CONCLUSION: This study found a high rate of sleep disorders among PD patients in our sample. Shoulder and neck pain was found to be associated with a risk of sleep disorders. Pain management should be performed to improve the sleep quality of PD patients.

A new strategy for the treatment of Parkinson's disease: Discovery and bio-evaluation of the first central-targeting tyrosinase inhibitor.

The high level of tyrosinase leads to the generation of neuromelanin, further causing the abnormality of redox-related protein level and mediating the occurrence and development of Parkinson's disease (PD). However, the existing tyrosinase inhibitors are mostly natural product extracts or polyphenolic derivatives, which hindered them from penetrating the blood-brain barrier (BBB). Herein, we obtained a novel tyrosinase inhibitor, 2-06 (tyrosinase: monophenolase IC50 = 70.44 ± 22.69 µM, diphenolase IC50 = 1.89 ± 0.64 µM), through the structure-based screening method. The compound 2-06 presented good in vitro and in vivo safety, and can inhibit the tyrosinase and melanogenesis in B16F10. Moreover, this compound showed neuroprotective effects and Parkinsonism behavior improving function. 2-06 was proved to penetrate the BBB and enter the central nervous system (CNS). The exploration of the binding mode between 2-06 and tyrosinase provided the foundation for the subsequent structural optimization. This is the first research to develop a central-targeting tyrosinase inhibitor, which is crucial for in-depth study on the new strategy for utilizing tyrosinase inhibitors to treat PD.

Single-trial movement intention detection estimation in patients with Parkinson's disease: a movement-related cortical potential study.

OBJECTIVES: Parkinson patients often suffer from motor impairments such as tremor and freezing of movement that can be difficult to treat. To unfreeze movement, it has been suggested to provide sensory stimuli. To avoid constant stimulation, episodes with freezing of movement needs to be detected which is a challenge. This can potentially be obtained using a brain-computer interface (BCI) based on movement-related cortical potentials (MRCPs) that are observed in association with the intention to move. The objective in this study was to detect MRCPs from single-trial EEG. Approach: Nine Parkinson patients executed 100 wrist movements and 100 ankle movements while continuous EEG and EMG were recorded. The experiment was repeated in two sessions on separate days. Using temporal, spectral and template matching features, a random forest, linear discriminant analysis, and k-nearest neighbours classifier were constructed in offline analysis to discriminate between epochs containing movement-related or idle brain activity to provide an estimation of the performance of a BCI. Three classification scenarios were tested: 1) within-session (using training and testing data from the same session and participant), between-session (using data from the same participant from session one for training and session two for testing), and across-participant (using data from all participants except one for training and testing on the remaining participant). Main results: The within-session classification scenario was associated with the highest classification accuracies which were in the range of 88-89% with a similar performance across sessions. The performance dropped to 69-75% and 70-75% for the between-session and across-participant classification scenario, respectively. The highest classification accuracies were obtained for the random forest and k-nearest neighbours classifiers. Significance: The results indicate that it is possible to detect movement intentions in individuals with Parkinson's disease such that they can operate a BCI which may control the delivery of sensory stimuli to unfreeze movement. .

Detecting rhythmic spiking through the power spectra of point process model residuals.

Objective.Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ("RP", the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established "shuffling" procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.Approach.In a novel "residuals" method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the preceding nrmilliseconds. Finally, we compute the PSD of the model's residuals.Main results.We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey -- in which alpha-beta oscillations (8-30 Hz) were anticipated -- the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.Significance.These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

How to accurately quantify brain magnetic susceptibility in the context of Parkinson's disease: Validation on phantoms and healthy volunteers at 1.5 and 3 T.

Currently, brain iron content represents a new neuromarker for understanding the physiopathological mechanisms leading to Parkinson's disease (PD). In vivo quantification of biological iron is possible by reconstructing magnetic susceptibility maps obtained using quantitative susceptibility mapping (QSM). Applying QSM is challenging, as up to now, no standardization of acquisition protocols and phase image processing has emerged from referenced studies. Our objectives were to compare the accuracy and the sensitivity of 10 QSM pipelines built from algorithms from the literature, applied on phantoms data and on brain data. Two phantoms, with known magnetic susceptibility ranges, were created from several solutions of gadolinium chelate. Twenty healthy volunteers from two age groups were included. Phantoms and brain data were acquired at 1.5 and 3 T, respectively. Susceptibility-weighted images were obtained using a 3D multigradient-recalled-echo sequence. For brain data, 3D anatomical T1- and T2-weighted images were also acquired to segment the deep gray nuclei of interest. Concerning in vitro data, the linear dependence of magnetic susceptibility versus gadolinium concentration and deviations from the theoretically expected values were calculated. For brain data, the accuracy and sensitivity of the QSM pipelines were evaluated in comparison with results from the literature and regarding the expected magnetic susceptibility increase with age, respectively. A nonparametric Mann-Whitney U-test was used to compare the magnetic susceptibility quantification in deep gray nuclei between the two age groups. Our methodology enabled quantifying magnetic susceptibility in human brain and the results were consistent with those from the literature. Statistically significant differences were obtained between the two age groups in all cerebral regions of interest. Our results show the importance of optimizing QSM pipelines according to the application and the targeted magnetic susceptibility range, to achieve accurate quantification. We were able to define the optimal QSM pipeline for future applications on patients with PD.

Nuclear alpha-synuclein accelerates cell senescence and neurodegeneration.

BACKGROUND: The progression of Parkinson's disease (PD) is related to ageing. The accumulation of nuclear alpha-synuclein (α-syn) may accelerate the occurrence of neurodegenerative diseases, but its role in PD remains poorly understood. METHODS: In the present study, α-syn expression was specifically targeted to the nucleus by constructing an adeno-associated virus (AAV) vector in which a nuclear localization sequence (NLS) was added to the α-syn coding sequence. Virus-mediated gene transfer, behavioural tests, RNA-Seq, immunohistochemistry, western blotting, and quantitative real-time PCR were then performed. RESULTS: In vivo experiments using a mouse model showed that nuclear α-syn increased the severity of the PD-like phenotype, including the loss of dopaminergic neurons concomitant with motor impairment and the formation of α-syn inclusions. These nuclear inclusions contained α-syn species of high molecular weights and induced strong transcriptional dysregulation, especially induced high expression of p21 and senescence-associated secretory phenotype (SASP)-related genes. In addition, the transcriptional alterations induced by nuclear α-syn were associated with gliosis, inflammation, oxidative and DNA damage, and lysosomal dysfunction, and they eventually accelerated neuronal loss and neurodegeneration. CONCLUSIONS: Our results suggest that nuclear α-syn plays a crucial role in PD pathogenesis.

Serum Oligomeric α-Synuclein and p-tau181 in Progressive Supranuclear Palsy and Parkinson's Disease.

Clinical differentiation of progressive supranuclear palsy (PSP) from Parkinson's disease (PD) is challenging due to overlapping phenotypes and the late onset of specific atypical signs. Therefore, easily assessable diagnostic biomarkers are highly needed. Since PD is a synucleopathy while PSP is a tauopathy, here, we investigated the clinical usefulness of serum oligomeric-α-synuclein (o-α-synuclein) and 181Thr-phosphorylated tau (p-tau181), which are considered as the most important pathological protein forms in distinguishing between these two parkinsonisms. We assessed serum o-α-synuclein and p-tau181 by ELISA and SIMOA, respectively, in 27 PSP patients, 43 PD patients, and 39 healthy controls (HC). Moreover, we evaluated the correlation between serum biomarkers and biological and clinical features of these subjects. We did not find any difference in serum concentrations of p-tau181 and o-α-synuclein nor in the o-α-synuclein/p-tau181 ratio between groups. However, we observed that serum p-tau181 positively correlated with age in HC and PD, while serum o-α-synuclein correlated positively with disease severity in PD and negatively with age in PSP. Finally, the o-α-synuclein/p-tau181 ratio showed a negative correlation with age in PD.

Repurposing ezetimibe as a neuroprotective agent in a rotenone-induced Parkinson's disease model in rats: Role of AMPK/SIRT-1/PGC-1α signaling and autophagy.

As a severe neurological disorder, Parkinson's disease (PD) is distinguished by dopaminergic neuronal degeneration in the substantia nigra (SN), culminating in motor impairments. Several studies have shown that activation of the AMPK/SIRT1/PGC1α pathway contributes to an increase in mitochondrial biogenesis and is a promising candidate for the management of PD. Furthermore, turning on the AMPK/SIRT1/PGC1α pathway causes autophagy activation, which is fundamental for maintaining neuronal homeostasis. Interestingly, ezetimibe is an antihyperlipidemic agent that was recently reported to possess pleiotropic properties in neurology by triggering the phosphorylation and activation of AMPK. Thus, our study aimed to investigate the neuroprotective potential of ezetimibe in rats with rotenone-induced PD by activating AMPK. Adult male Wistar rats received rotenone (1.5 mg/kg, s.c.) every other day for 21 days to induce experimental PD. Rats were treated with ezetimibe (5 mg/kg/day, i.p.) 1 h before rotenone. Ezetimibe ameliorated the motor impairments in open field, rotarod and grip strength tests, restored striatal dopamine and tyrosine hydroxylase in the SN, up-regulated p-AMPK, SIRT1, and PGC1α striatal expression, upsurged the expression of ULK1, beclin1, and LC3II/I, reduced Bax/Bcl2 ratio, and alleviated rotenone-induced histopathological changes in striatum and SN. Our findings also verified the contribution of AMPK activation to the neuroprotective effect of ezetimibe by using the AMPK inhibitor dorsomorphin. Together, this work revealed that ezetimibe exerts a neuroprotective impact in rotenone-induced PD by activating AMPK/SIRT-1/PGC-1α signaling, enhancing autophagy, and attenuating apoptosis. Thus, ezetimibe's activation of AMPK could hold significant therapeutic promise for PD management.

A causal counterfactual graph neural network for arising-from-chair abnormality detection in parkinsonians.

The arising-from-chair task assessment is a key aspect of the evaluation of movement disorders in Parkinson's disease (PD). However, common scale-based clinical assessment methods are highly subjective and dependent on the neurologist's expertise. Alternate automated methods for arising-from-chair assessment can be established based on quantitative susceptibility mapping (QSM) images with multiple-instance learning. However, performance stability for such methods can be typically undermined by the presence of irrelevant or spuriously-relevant features that mask the intrinsic causal features. Therefore, we propose a QSM-based arising-from-chair assessment method using a causal graph-neural-network framework, where counterfactual and debiasing strategies are developed and integrated into this framework for capturing causal features. Specifically, the counterfactual strategy is proposed to suppress irrelevant features caused by background noise, by producing incorrect predictions when dropping causal parts. The debiasing strategy is proposed to suppress spuriously relevant features caused by the sampling bias and it comprises a resampling guidance scheme for selecting stable instances and a causal invariance constraint for improving stability under various interferences. The results of extensive experiments demonstrated the superiority of the proposed method in detecting arising-from-chair abnormalities. Its clinical feasibility was further confirmed by the coincidence between the selected causal features and those reported in earlier medical studies. Additionally, the proposed method was extensible for another motion task of leg agility. Overall, this study provides a potential tool for automated arising-from-chair assessment in PD patients, and also introduces causal counterfactual thinking in medical image analysis. Our source code is publicly available at https://github.com/SJTUBME-QianLab/CFGNN-PDarising.

Pterostilbene alleviates MPTP-induced neurotoxicity by targeting neuroinflammation and oxidative stress.

Pterostilbene (PTE), a naturally occurring phenolic compound primarily found in blueberries, demonstrates neuroprotective properties. However, the role of PTE in Parkinson's disease (PD) remains unclear. This study aimed to investigate the neuroprotective role of PTE in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD animal model. Our findings demonstrate that administering PTE effectively reversed the diminished levels of dopamine in the striatum, thereby ameliorating motor impairments in the MPTP model. Moreover, PTE administration mitigated the loss of dopaminergic (DA) neurons and reduced the upregulation of α-synuclein (α-syn) induced by MPTP. Mechanistic analysis revealed that PTE administration inhibited the activation of microglia and astrocytes, as well as pro-inflammatory factors such as TNF-α and IL-1ß in the MPTP model. Additionally, PTE administration decreased MPTP-induced levels of reactive oxygen species (ROS) and malondialdehyde (MDA), while increasing total antioxidant capacity (TAOC) and superoxide dismutase (SOD) activity, thereby attenuating oxidative stress. Collectively, these findings demonstrate that PTE exerts neuroprotective effects in the MPTP mouse model of PD by suppressing neuroinflammation and oxidative stress. Thus, PTE holds promise as a therapeutic agent for PD.

Investigating the therapeutic effects of a Japanese sake yeast supplement on a zebrafish model of Parkinson's disease: Antioxidant and inflammatory responses.

Sake may potentially halt the progression of Parkinson's disease due to its properties, yet no studies have explored its effects. This preliminary study aimed to assess the impact of sake supplementation on Parkinson's disease using a zebrafish model. Sixty fish were divided into six groups: control, rotenone (ROT), and groups administered rotenone along with sake at concentrations of 25, 50, 75, and 100 mg/L (25S, 50S, 75S, and 100S). After 28 days of treatment, behavioral responses and the activities of catalase (CAT), superoxide dismutase (SOD), reduced glutathione (GSH), and glutathione-S-transferase (GST), as well as the expressions of TNF-α, IL-1ß, and COX-2, were evaluated. The results indicated that rotenone administration significantly reduced crossing number (P = 0.001), entries in the top area (P = 0.001), and time spent in the top area (P = 0.001). It also markedly increased levels of TBARS and SH compared to the control group (P = 0.001). Rotenone significantly decreased CAT, SOD, and GSH activities while increasing GST levels. Furthermore, it upregulated the expressions of TNF-α (P = 0.001), IL-1ß (P = 0.001), and COX-2 (P = 0.001). Supplementation with sake, particularly at higher doses, reversed the adverse effects of rotenone on behavioral, oxidative, and inflammatory responses. In conclusion, sake shows promise for preventing Parkinson's disease pending further clinical studies.

GBA1-Associated Parkinson's Disease Is a Distinct Entity.

GBA1-associated Parkinson's disease (GBA1-PD) is increasingly recognized as a distinct entity within the spectrum of parkinsonian disorders. This review explores the unique pathophysiological features, clinical progression, and genetic underpinnings that differentiate GBA1-PD from idiopathic Parkinson's disease (iPD). GBA1-PD typically presents with earlier onset and more rapid progression, with a poor response to standard PD medications. It is marked by pronounced cognitive impairment and a higher burden of non-motor symptoms compared to iPD. Additionally, patients with GBA1-PD often exhibit a broader distribution of Lewy bodies within the brain, accentuating neurodegenerative processes. The pathogenesis of GBA1-PD is closely associated with mutations in the GBA1 gene, which encodes the lysosomal enzyme beta-glucocerebrosidase (GCase). In this review, we discuss two mechanisms by which GBA1 mutations contribute to disease development: 'haploinsufficiency,' where a single functional gene copy fails to produce a sufficient amount of GCase, and 'gain of function,' where the mutated GCase acquires harmful properties that directly impact cellular mechanisms for alpha-synuclein degradation, leading to alpha-synuclein aggregation and neuronal cell damage. Continued research is advancing our understanding of how these mechanisms contribute to the development and progression of GBA1-PD, with the 'gain of function' mechanism appearing to be the most plausible. This review also explores the implications of GBA1 mutations for therapeutic strategies, highlighting the need for early diagnosis and targeted interventions. Currently, small molecular chaperones have shown the most promising clinical results compared to other agents. This synthesis of clinical, pathological, and molecular aspects underscores the assertion that GBA1-PD is a distinct clinical and pathobiological PD phenotype, necessitating specific management and research approaches to better understand and treat this debilitating condition.

A Comprehensive Approach to Parkinson's Disease: Addressing Its Molecular, Clinical, and Therapeutic Aspects.

Parkinson's disease (PD) is a gradually worsening neurodegenerative disorder affecting the nervous system, marked by a slow progression and varied symptoms. It is the second most common neurodegenerative disease, affecting over six million people in the world. Its multifactorial etiology includes environmental, genomic, and epigenetic factors. Clinical symptoms consist of non-motor and motor symptoms, with motor symptoms being the classic presentation. Therapeutic approaches encompass pharmacological, non-pharmacological, and surgical interventions. Traditional pharmacological treatment consists of administering drugs (MAOIs, DA, and levodopa), while emerging evidence explores the potential of antidiabetic agents for neuroprotection and gene therapy for attenuating parkinsonian symptoms. Non-pharmacological treatments, such as exercise, a calcium-rich diet, and adequate vitamin D supplementation, aim to slow disease progression and prevent complications. For those patients who have medically induced side effects and/or refractory symptoms, surgery is a therapeutic option. Deep brain stimulation is the primary surgical option, associated with motor symptom improvement. Levodopa/carbidopa intestinal gel infusion through percutaneous endoscopic gastrojejunostomy and a portable infusion pump succeeded in reducing "off" time, where non-motor and motor symptoms occur, and increasing "on" time. This article aims to address the general aspects of PD and to provide a comparative comprehensive review of the conventional and the latest therapeutic advancements and emerging treatments for PD. Nevertheless, further studies are required to optimize treatment and provide suitable alternatives.

The Role of miR-137 in Neurodegenerative Disorders.

Neurodegenerative diseases affect an increasing part of the population of modern societies, burdening healthcare systems and causing immense suffering at the personal level. The pathogenesis of several of these disorders involves dysregulation of gene expression, which depends on several molecular processes ranging from transcription to protein stability. microRNAs (miRNAs) are short non-coding RNA molecules that modulate gene expression by suppressing the translation of partially complementary mRNAs. miR-137 is a conserved, neuronally enriched miRNA that is implicated in neurodegeneration. Here, we review the current body of knowledge about the role that miR-137 plays in five prominent neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and multiple sclerosis. The presented data indicate that, rather than having a general neuroprotective role, miR-137 modulates the pathology of distinct disorders differently.

Grasping the big picture: impact analysis of screening tools for timely referral for device-aided therapies.

Several screening tools are available to assist general neurologists in the timely identification of patients with advanced Parkinson's disease (PD) who may be eligible for referral for a device-aided therapy (DAT). However, it should be noted that not all of these clinical decision rules have been developed and validated in a thorough and consistent manner. Furthermore, only a limited number of head-to-head comparisons have been performed. Available studies suggest that D-DATS has a higher positive predictive value and higher specificity than the 5-2-1 criteria, while the sensitivity of both screening tools is similar. However, unanswered questions remain regarding the validity of the decision rules, such as whether the diagnostic performance measures from validation studies are generalizable to other populations. Ultimately, the question is whether a screening tool will effectively and efficiently improve the quality of life of patients with PD. To address this key question, an impact analysis should be performed. The authors intend to set up a multinational cluster randomised controlled trial to compare the D-DATS and 5-2-1 criteria on the downstream consequences of implementing these screening tools, with a particular focus on the impact on disability and quality of life.

Head and Neck Cancer: A Potential Risk Factor for Parkinson's Disease?

Head and neck cancers (HNC) are frequently associated with neurodegeneration. However, the association between HNC and Parkinson's disease (PD) remains unclear. This study aimed to clarify the relationship between HNC and subsequent PD. This retrospective study used data from a nationally representative cohort. Patients with HNC were identified based on the presence of corresponding diagnostic codes. Participants without cancer were selected using 4:1 propensity score matching based on sociodemographic factors and year of enrollment; 2296 individuals without HNC and 574 individuals with HNC were included in the study. Hazard ratios (HR) for the incidence of PD in patients with HNC were calculated using 95% confidence intervals (CI). The incidence of PD was 4.17 and 2.18 per 1000 person-years in the HNC and control groups, respectively (adjusted HR = 1.89, 95% CI = 1.08-3.33). The HNC group also showed an increased risk of subsequent PD development. The risk of PD was higher in middle-aged (55-69 years) patients with HNC and oral cavity cancer. Our findings suggest that middle-aged patients with HNC have an increased incidence of PD, specifically those with oral cavity cancer. Therefore, our findings provide new insights into the development of PD in patients with HNC.

Prediction of Freezing of Gait in Parkinson's disease based on multi-channel time-series neural network.

Freezing of Gait (FOG) is a noticeable symptom of Parkinson's disease, like being stuck in place and increasing the risk of falls. The wearable multi-channel sensor system is an efficient method to predict and monitor the FOG, thus warning the wearer to avoid falls and improving the quality of life. However, the existing approaches for the prediction of FOG mainly focus on a single sensor system and cannot handle the interference between multi-channel wearable sensors. Hence, we propose a novel multi-channel time-series neural network (MCT-Net) approach to merge multi-channel gait features into a comprehensive prediction framework, alerting patients to FOG symptoms in advance. Owing to the causal distributed convolution, MCT-Net is a real-time method available to give optimal prediction earlier and implemented in remote devices. Moreover, intra-channel and inter-channel transformers of MCT-Net extract and integrate different sensor position features into a unified deep learning model. Compared with four other state-of-the-art FOG prediction baselines, the proposed MCT-Net obtains 96.21% in accuracy and 80.46% in F1-score on average 2 s before FOG occurrence, demonstrating the superiority of MCT-Net.

Changes in slow-wave sleep characteristics in Parkinson's disease patients with mild-moderate depression.

INTRODUCTION: Depression and sleep disturbances are commonly seen non-motor symptoms in patients with Parkinson's disease (PD). This study used polysomnography to examine the relationship between mild-moderate depression in PD and sleep characteristics, particularly slow wave activities (SWA). METHODS: 59 PD patients were split into two groups: nd-PD (n = 27) (patients with PD without depression) and d-PD (n = 32) (patients with PD with mild-moderate depression). Their clinical features, polysomnography parameters, and demographics were evaluated. Early and late sleep SWA spectrum densities and overnight SWA decline in different brain regions were particularly analyzed. RESULTS: Non-rapid eye movement 3 (N3) sleep duration and percentage were greater in the d-PD group. N3 percentage was linked to depression (p = 0.014). During late sleep, higher SWA (0.5-4Hz) in the frontal and central regions, higher low-SWA (0.5-2Hz) in the whole brain, central and occipital regions, and higher high-SWA (2-4Hz) in the frontal region was observed in the d-PD group. During early sleep, there was also higher low-SWA (0.5-2Hz) in the occipital region. Patients in d-PD group exhibited reduced overnight high-SWA (2-4Hz) decline (Δhigh-SWA) in the whole brain and occipital regions. Δhigh-SWA(2-4Hz) in the occipital region were associated with depression (p = 0.049). CONCLUSION: PD patients with mild-moderate depression have impaired slow wave sleep, exhibiting as increased N3 sleep, SWA, and reduced overnight SWA decline. This implies that synaptic strength reduction during sleep and impaired synaptic homeostasis regulation may be associated with depression in PD. Reduced overnight high-SWA decline in the occipital region may serve as a novel electrophysiological biomarker for indicating depression in PD.