Parkinson's Disease Severity Research Articles

Multi-Shared-Task Self-Supervised CNN-LSTM for Monitoring Free-Body Movement UPDRS-III Using Wearable Sensors.

The Unified Parkinson's Disease Rating Scale (UPDRS) is used to recognize patients with Parkinson's disease (PD) and rate its severity. The rating is crucial for disease progression monitoring and treatment adjustment. This study aims to advance the capabilities of PD management by developing an innovative framework that integrates deep learning with wearable sensor technology to enhance the precision of UPDRS assessments. We introduce a series of deep learning models to estimate UPDRS Part III scores, utilizing motion data from wearable sensors. Our approach leverages a novel Multi-shared-task Self-supervised Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework that processes raw gyroscope signals and their spectrogram representations. This technique aims to refine the estimation accuracy of PD severity during naturalistic human activities. Utilizing 526 min of data from 24 PD patients engaged in everyday activities, our methodology demonstrates a strong correlation of 0.89 between estimated and clinically assessed UPDRS-III scores. This model outperforms the benchmark set by single and multichannel CNN, LSTM, and CNN-LSTM models and establishes a new standard in UPDRS-III score estimation for free-body movements compared to recent state-of-the-art methods. These results signify a substantial step forward in bioengineering applications for PD monitoring, providing a robust framework for reliable and continuous assessment of PD symptoms in daily living settings.

Anxiety Symptoms and Disease Severity in Parkinson Disease.

BACKGROUND: Anxiety is prevalent in Parkinson disease (PD), negatively affecting quality of life for patients and their families. Targeted anxiety interventions are needed that account for variables such as disease severity; however, there is insufficient evidence regarding the trajectory of anxiety along the disease course. OBJECTIVE: The aim of this study was to investigate the association between disease severity and anxiety symptoms in a PD sample. METHODS: This descriptive study used secondary data analyses of data from a web-based survey study of individuals with PD in the United States. Participants were 21 years or older, had access to the Internet, and were given a diagnosis of PD (N = 72). We performed multiple regression analyses to assess the relationship between patient-reported disease severity and anxiety symptoms. RESULTS: There was a statistically significant association between disease severity and anxiety symptoms in people with PD, after controlling for all 5 explanatory variables (sex, age, wearing off, disease severity, and disease duration) ( P < .001). Age and wearing off PD medication also had statistically significant, although smaller, effects on anxiety symptoms ( P < .05). CONCLUSION: Disease severity was related to increased anxiety symptoms among individuals with PD. Anxiety intervention research is needed, and future studies should account for variations in disease severity and medication effects in both intervention and study design.

Prevalence, Impact, and Screening Methods of Sarcopenia in Japanese Patients With Parkinson's Disease: A Prospective Cross-Sectional Study.

Sarcopenia is a skeletal muscle disease manifesting as low muscle mass and impaired muscle function. It has been reported that sarcopenia correlates with a low quality of life (QOL) and an increased risk of falls in patients with Parkinson's disease (PD). Nevertheless, few studies have investigated the prevalence, impact, and screening methods of sarcopenia in Japanese patients with PD. Sarcopenia was diagnosed based on the Asian Working Group for Sarcopenia 2019 consensus. We compared demographic characteristics, severity of PD, levodopa equivalent daily dose, QOL, fatigue, impulsive and compulsive behaviors, body mass index (BMI), calf circumference, skeletal muscle mass index (SMI), handgrip strength, a 4-meter gait speed, a five-time sit-to-stand test (FTSST), short physical performance battery, and SARC-F questionnaire scores between sarcopenia and non-sarcopenia groups. Furthermore, to investigate the best tool for screening sarcopenia in PD, the sensitivity and specificity of calf circumference, handgrip strength, FTSST, and SARC-F questionnaire were compared. The prevalence of sarcopenia in PD was 31.9% (15/47). The sarcopenia group showed significantly higher age (77.3 ± 5.12 versus 70.3 ± 8.17, p = 0.0042), lower BMI (19.3 ± 2.99 versus 23.3 ± 3.18, p = 0.0002), higher rate of decreased calf circumference (86.6% versus 34.3%, p = 0.0013) and SMI (100% versus 6.25%, p < 0.0001), and worse FTSST (15.5 ± 5.57 versus 12.0 ± 4.12, p = 0.0219). The other parameters were not significantly different. Among screening tools, calf circumference had the highest sensitivity (86%) and specificity (65%). All screening tools had higher sensitivity and specificity in men than in women. The SARC-F questionnaire was not useful in distinguishing sarcopenia but was significantly correlated with the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Part 3 (r = 0.41, p = 0.0037) and the 39-item Parkinson's Disease QOL Scale (r = 0.71, p < 0.0001). This study investigated the characteristics of PD patients with sarcopenia in Japan. Calf circumference was found to be the most useful tool for screening sarcopenia in PD. Handgrip strength and FTSST also showed high sensitivities, particularly in men. Conversely, the SARC-F questionnaire is not suitable for diagnosing sarcopenia in PD.

The Role of Alpha-Synuclein and Tubulin-Associated Unit (Tau) Proteins in the Diagnosis, Prognosis, and Treatment of Parkinson's Disease: A Systematic Review.

Parkinson's disease (PD) is a degenerative neurological disorder resulting from the death of dopaminergic neurons, which, in turn, results in impaired motor and cognitive functions. Early diagnosis is important in achieving a good prognosis for PD. Currently, the only approved way to diagnose PD is through medical history, current symptoms, and neurological examination. This, however, can only happen after PD progresses far enough in patients. Biomarkers in cerebrospinal fluid (CSF) and blood plasma, however, may provide insight into the early progress of PD and potentially concurrent dementia, which can also aid in the development of novel treatments. Specifically, this systematic review explores alpha-synuclein (α-syn) and tubulin-associated unit (Tau) proteins and analyzes their potential roles as biomarkers while also touching on nilotinib and immunotherapy as potential treatment options. PubMed, PubMed Central (PMC), Medline, and Cochrane Library serve as the databases for relevant literature, upon which eligibility criteria and quality checks - Assessment of Multiple Systematic Review (AMSTAR) tool, Newcastle-Ottawa Quality Assessment Scale, Cochrane risk-of-bias assessment 2 (RoB2), and Scale for the Assessment of Narrative Review (SANRA) - were applied. The remaining literature examines the various aspects of PD and Parkinson's disease dementia (PDD) and associated biomarkers. From 10 studies, 2,361 participants, both PD patients and healthy controls (HCs), were assessed and compared. Various assessment scales, such as the Unified Parkinson's Disease Rating Scale part III (UPDRS III), were used to ascertain the severity or progression of PD in patients while also seeking a noticeable correlation with α-syn and total Tau (t-Tau). The lack of standardized clinical testing has led to conflicting reports. Thus, while the articles generally agree on the potential efficacy of α-syn and Tau protein analysis in the diagnosis, prognosis, and treatment of PD and PDD, they also argue for further testing and trials.

Exploring brain asymmetry in early-stage Parkinson's disease through functional and structural MRI.

This study explores the correlation between asymmetrical brain functional activity, gray matter asymmetry, and the severity of early-stage Parkinson's disease (PD). Ninety-three early-stage PD patients (ePD, H-Y stages 1-2.5) were recruited, divided into 47 mild (ePD-mild, H-Y stages 1-1.5) and 46 moderate (ePD-moderate, H-Y stages 2-2.5) cases, alongside 43 matched healthy controls (HCs). The study employed the Hoehn and Yahr (H-Y) staging system for disease severity assessment and utilized voxel-mirrored homotopic connectivity (VMHC) for analyzing brain functional activity asymmetry. Asymmetry voxel-based morphometry analysis (VBM) was applied to evaluate gray matter asymmetry. The study found that, relative to HCs, both PD subgroups demonstrated reduced VMHC values in regions including the amygdala, putamen, inferior and middle temporal gyrus, and cerebellum Crus I. The ePD-moderate group also showed decreased VMHC in additional regions such as the postcentral gyrus, lingual gyrus, and superior frontal gyrus, with notably lower VMHC in the superior frontal gyrus compared to the ePD-mild group. A negative correlation was observed between the mean VMHC values in the superior frontal gyrus and H-Y stages, UPDRS, and UPDRS-III scores. No significant asymmetry in gray matter was detected. Asymmetrical brain functional activity is a significant characteristic of PD, which exacerbates as the disease severity increases, resembling the dissemination of Lewy bodies across the PD neurological framework. VMHC emerges as a potent tool for characterizing disease severity in early-stage PD.

Moderate intensity aerobic exercise alleviates motor deficits in 6-OHDA lesioned rats and reduces serum levels of biomarkers of Parkinson's disease severity without recovery of striatal dopamine or tyrosine hydroxylase

Alleviation of motor impairment by aerobic exercise (AE) in Parkinson's disease (PD) patients points to activation of neurobiological mechanisms that may be targetable by therapeutic approaches. However, evidence for AE-related recovery of striatal dopamine (DA) signaling or tyrosine hydroxylase (TH) loss has been inconsistent in rodent studies. This ambiguity may be related to the timing of AE intervention in relation to the status of nigrostriatal neuron loss. Here, we replicated human PD at diagnosis by establishing motor impairment with >80% striatal DA and TH loss prior to initiating AE, and assessed its potential to alleviate motor decline and restore DA and TH loss. We also evaluated if serum levels of neurofilament light (NfL) and glial fibrillary acidic protein (GFAP), biomarkers of human PD severity, changed in response to AE. 6-hydroxydopamine (6-OHDA) was infused unilaterally into rat medial forebrain bundle to induce progressive nigrostriatal neuron loss over 28 days. Moderate intensity AE (3× per week, 40 min/session), began 8–10 days post-lesion following establishment of impaired forelimb use. Striatal tissue DA, TH protein and mRNA, and serum levels of NfL/GFAP were determined 3-wks after AE began. Despite severe striatal DA depletion at AE initiation, forelimb use deficits and hypokinesia onset were alleviated by AE, without recovery of striatal DA or TH protein loss, but reduced NfL and GFAP serum levels. This proof-of-concept study shows AE alleviates motor impairment when initiated with >80% striatal DA loss without obligate recovery of striatal DA or TH protein. Moreover, the AE-related reduction of NfL and GFAP serum levels may serve as objective blood-based biomarkers of AE efficacy.

Interpretable video-based tracking and quantification of parkinsonism clinical motor states

Quantification of motor symptom progression in Parkinson’s disease (PD) patients is crucial for assessing disease progression and for optimizing therapeutic interventions, such as dopaminergic medications and deep brain stimulation. Cumulative and heuristic clinical experience has identified various clinical signs associated with PD severity, but these are neither objectively quantifiable nor robustly validated. Video-based objective symptom quantification enabled by machine learning (ML) introduces a potential solution. However, video-based diagnostic tools often have implementation challenges due to expensive and inaccessible technology, and typical “black-box” ML implementations are not tailored to be clinically interpretable. Here, we address these needs by releasing a comprehensive kinematic dataset and developing an interpretable video-based framework that predicts high versus low PD motor symptom severity according to MDS-UPDRS Part III metrics. This data driven approach validated and robustly quantified canonical movement features and identified new clinical insights, not previously appreciated as related to clinical severity, including pinkie finger movements and lower limb and axial features of gait. Our framework is enabled by retrospective, single-view, seconds-long videos recorded on consumer-grade devices such as smartphones, tablets, and digital cameras, thereby eliminating the requirement for specialized equipment. Following interpretable ML principles, our framework enforces robustness and interpretability by integrating (1) automatic, data-driven kinematic metric evaluation guided by pre-defined digital features of movement, (2) combination of bi-domain (body and hand) kinematic features, and (3) sparsity-inducing and stability-driven ML analysis with simple-to-interpret models. These elements ensure that the proposed framework quantifies clinically meaningful motor features useful for both ML predictions and clinical analysis.

Exploring the role of anticipatory postural adjustment duration within APA2 subphase as a potential mediator between clinical disease severity and fall risk in Parkinson's disease.

People with Parkinson's Disease (PD) often show reduced anticipatory postural adjustments (APAs) before voluntary steps, impacting their stability. The specific subphase within the APA stage contributing significantly to fall risk remains unclear. We analyzed center of pressure (CoP) trajectory parameters, including duration, length, and velocity, throughout gait initiation. This examination encompassed both the postural phase, referred to as anticipatory postural adjustment (APA) (APA1, APA2a, APA2b), and the subsequent locomotor phases (LOC). Participants were instructed to initiate a step and then stop (initiating a single step). Furthermore, we conducted assessments of clinical disease severity using the Unified Parkinson's Disease Rating Scale (UPDRS) and evaluated fall risk using Tinetti gait and balance scores during off-medication periods. Freezing of gait (FOG) was observed in 18 out of 110 participants during the measurement of CoP trajectories. The Ramer-Douglas-Peucker algorithm successfully identified CoP displacement trajectories in 105 participants (95.5%), while the remaining 5 cases could not be identified due to FOG. Tinetti balance and gait score showed significant associations with levodopa equivalent daily dose, UPDRS total score, disease duration, duration (s) in APA2a (s) and LOC (s), length in APA1 (cm) and APA2b (cm), mediolateral velocity in APA1 (X) (cm/s), APA2a (X) (cm/s), APA2b (X) (cm/s) and LOC (X) (cm/s), and anterior-posterior velocity in APA2a (Z) (cm/s) and APA2b (Z) (cm/s). Multiple linear regression revealed that only duration (s) in APA2a and UPDRS total score was independently associated with Tinetti gait and balance score. Further mediation analysis showed that the duration (s) in APA2a served as a mediator between UPDRS total score and Tinetti balance and gait score (Sobel test, p = 0.047). APA2 subphase duration mediates the link between disease severity and fall risk in PD, suggesting that longer APA2a duration may indicate reduced control during gait initiation, thereby increasing fall risk.

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.

Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier.

Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Motor alterations affect the gait according to the progression of PD and can be used by experts in movement disorders to rate the severity of the disease. However, this rating depends on the expertise of the clinical specialist. Therefore, the diagnosis may be inaccurate, particularly in the early stages of PD where abnormal gait patterns can result from normal aging or other medical conditions. Consequently, several classification systems have been developed to enhance PD diagnosis. In this paper, a PD gait severity classification algorithm was developed using vertical ground reaction force (VGRF) signals. The VGRF records used are from a public database that includes 93 PD patients and 72 healthy controls adults. The work presented here focuses on modeling each foot's gait stance phase signals using a modified convolutional long deep neural network (CLDNN) architecture. Subsequently, the results of each model are combined to predict PD severity. The classifier performance was evaluated using ten-fold cross-validation. The best-weighted accuracies obtained were 99.296(0.128)% and 99.343(0.182)%, with the Hoehn-Yahr and UPDRS scales, respectively, outperforming previous results presented in the literature. The classifier proposed here can effectively differentiate gait patterns of different PD severity levels based on gait signals of the stance phase.

Effectiveness of Continuous Dopaminergic Therapies in Parkinson's Disease: A Review of L-DOPA Pharmacokinetics/Pharmacodynamics.

Parkinson's disease (PD) is characterized by striatal dopamine deficiency. Since dopamine cannot cross the digestive and blood-brain barriers, its precursor, levodopa (L-DOPA), remains the mainstay of treatment. However, the significant pharmacokinetic (Pk) and pharmacodynamic (Pd) limitations of L-DOPA, combined with the severity of PD, may trigger motor and non-motor complications, for which continuous dopaminergic delivery therapies have been developed. The aim of this study was to review the literature on the Pk/Pd limitations of L-DOPA and how current treatments of continuous dopaminergic administration ameliorate these problems, in order to identify the need for new therapeutic avenues. A comprehensive literature search was carried out using PubMed and 75 articles were initially extracted. Following independent screening by two reviewers and consideration of eligibility, 10 articles were chosen for further analysis. Information concerning the Pk/Pd of L-DOPA was classified for each article. Pk/Pd problems notably include: (i) restricted digestive and cerebral absorption; (ii) unnecessary peripheral distribution; (iii) short half-life; (iv) age- and PD-induced decline of central aromatic L-amino acid decarboxylase; (v) misdistribution in many cells; and (vii) pulsatile stimulation of dopaminergic receptors. Current treatments only slightly ameliorate some of these problems. Many Pk/Pd constraints are not resolved by existing continuous dopaminergic delivery therapies. This highlights the significant gap between these treatments and the ideal of continuous dopaminergic stimulation.

Swallowing Characteristics and Water Swallow Capacity in Patients with Parkinsonism.

Prevalence and characteristics of dysphagia (including aspiration) in patients with parkinsonism is variable, depending on type of assessment, diagnosis, disease stage and duration. The aim of this study was to further evaluate dysphagia characteristics in patients with different types of parkinsonism with both instrumental (Flexible Endoscopic Evaluation of Swallowing, FEES) and non-instrumental (Timed Water Swallow Test, TWST) assessments. Swallowing characteristics in 74 patients with parkinsonism were prospectively assessed using FEES and TWST. Statistics employed were (a) Spearman rank correlation to measure correlation between dysphagia results and Parkinson subtypes, disease severity and duration and (b) the non-parametric tests Mann Whitney U and Kruskal Wallis to measure difference between groups. Dysphagia was common, with 50 (67.6%) of the patients demonstrating a mild-severe Dysphagia Outcome Severity Scale (DOSS, level 1-5). During FEES, 42% aspirated and 68% of these had silent aspiration. Aspiration was seen more frequently with increased disease severity as per Hoehn and Yahr (H&Y) (r = .459, p = < 0.001) and disease duration (r = .269, p = .021). Thin liquid (IDDSI level 0) was the most common consistency to aspirate, and the frequency of aspiration decreased with thicker liquids. Dysphagia and aspiration are common in all subgroups of parkinsonism and seen in early stages of H&Y and within the first year of disease duration. Hence, it is recommended that these patients are evaluated early for optimal management and to avoid aspiration-related complications.

Relationship of Hearing Loss to Parkinson's Disease, Dementia, and APOE Genotype in Adults.

Background: Hearing loss has been recognized as a risk factor for dementia and non-motor features of Parkinson's disease (PD). The apolipoprotein E (APOE) protein contributes to maintenance and repair of neuronal cell membranes, causing age-related disorders. This study aimed to analyze the impact of hearing loss on cognitive impairment, PD severity, and APOE gene expression in these patients. Methods: A total of 72 out-patients diagnosed with either PD or hearing loss were enrolled in this study. The hearing assessment included pure-tone audiometry, speech reception thresholds, and speech discrimination ability. Dementia was assessed by filling out the Clinical Dementia Rating and Mini-Mental State Examination questionnaires. The severity of PD was assessed using the Modified Hoehn and Yahr scale. Blood samples were tested for the gene expression of APOE. Results: Out of the 72 cases, there were 44 males and 28 females, with an average age of 64.4 ± 9.1 years. A total of 41 out of 72 cases had dementia and had a worse hearing threshold than those without dementia (47.1 ± 24.4 vs. 31.7 ± 22.1 dB, p = 0.006). A total of 58 patients were diagnosed with PD, with 14 of them classified as having severe symptoms (Modified Hoehn and Yahr scale > 2). Patients with severe PD were found to have a worse hearing threshold (49.6 ± 28.3 vs. 30.3 ± 17.8 dB, p = 0.028) and higher prevalence of dementia (12/14 vs. 18/44, p = 0.006). Among 10 individuals with the APOE ε4 gene, the prevalence of dementia was higher than those without the ε4 allele (9/10 vs. 32/62, p = 0.036). Conclusions: Hearing loss is common in severe PD and in dementia patients. Severe PD has a negative impact on the hearing threshold and cognitive dysfunction. Patients with APOE ε4 have a higher prevalence of dementia.

A comprehensive multivariate analysis of the center of pressure during quiet standing in patients with Parkinson's disease

BackgroundWe hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing.Methods127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD.ResultsThe factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated.ConclusionsThe cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

Real-Time Monitoring of Tyrosine Hydroxylase Activity with a Ratiometric Fluorescent Probe.

Parkinson's disease (PD) represents the second most widespread neurodegenerative disease, and early monitoring and diagnosis are urgent at present. Tyrosine hydroxylase (TH) is a key enzyme for producing dopamine, the levels of which can serve as an indicator for assessing the severity and progression of PD. This renders the specific detection and visualization of TH a strategically vital way to meet the above demands. However, a fluorescent probe for TH monitoring is still missing. Herein, three rationally designed wash-free ratiometric fluorescent probes were proposed. Among them, TH-1 exhibited ideal photophysical properties and specific dual-channel bioimaging of TH activity in SH-SY5Y nerve cells. Moreover, the probe allowed for in vivo imaging of TH activity in zebrafish brain and living striatal slices of mice. Overall, the ratiometric fluorescent probe TH-1 could serve as a potential tool for real-time monitoring of PD in complex biosystems.

Are physical activity levels, cardiorespiratory fitness and peak power associated with Parkinson's disease severity?

IntroductionIncreased physical activity (PA) may slow Parkinson's disease (PD) progression. Associations between markers of PA and PD severity could justify further studies evaluating interventions increasing PA levels in PD. The objectives of the present study were to assess associations between PA, cardiorespiratory fitness (VO2-max), and muscle peak power and measures of the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the Parkinson's disease questionnaire-39 (PDQ-39), and the four PD hallmark motor symptoms (rigidity, bradykinesia, postural instability, and tremor). MethodsData from 105 people with PD were used. PA was measured for seven consecutive days using accelerometers. Peak power was measured with a linear encoder during a chair rise test, while VO2-max was directly assessed during a graded bicycle test. Analyses included simple and multiple linear regression and hurdle exponential regression. ResultsPA was weakly to moderately associated with MDS-UPDRS II + III, rigidity, bradykinesia, and postural instability, as well as PDQ-39 mobility and activities of daily living sub-scores. VO2-max and peak power were weakly to moderately associated with MDS-UPDRS III, bradykinesia, and postural instability, while peak power was further weakly associated with the MDS-UPDRS II. Lastly, VO2-max was associated with PDQ-39 mobility and activities of daily living sub-scores. ConclusionPA, VO2-max, and peak power were associated with PD severity, thus highlighting the potential benefits of a physically active lifestyle. Furthermore, PA and VO2-max were associated with PDQ-39 sub-scores. This calls for confirmation of the potential effect of PA on quality of life in PD.

Association Between Serum Uric Acid Level and the Severity of Parkinsons Disease: A cross sectional study

Background: Parkinson’s disease is a chronic, progressive, neurodegenerative disease. Various factors have been attributed to the development and progression of the diseaseover the years. Uric acid is the final oxidation product of purine metabolism with potent antioxidant properties, which could play an important role in reducing the risk of development of Parkinson’s disease (PD) as well as it could have a role in delaying the progression of Parkinson’s disease (PD). Aim: This study aims at evaluating the role of serum uric acid level in clinical progression of Parkinson’s disease. Methods: This cross-sectional study was conducted among 70 patients of Parkinson’s disease attending the outpatient department and meeting the inclusion criteria. All the clinical and biochemical data were collected and analyzed by SPSS. Mean serum uric acid levels were compared between different stages of Parkinson’s disease. A p value of less than 0.05 was considered as significant. Result: Mean age of the patients with Parkinson’s disease was 62.25 ± 8.56 years with a male to female ratio of 1.12:1. Regarding the clinical presentation of the patients, it was observed that 16 (22.9%) patients had combination of tremor, hypokinesia, rigidity and postural imbalance, 18 (25.7%) had tremor, hypokinesia &amp; rigidity and 36 (51.4%) had tremor and rigidity. It was observed that 24.3% of the patients had sensory, sleep and cognitive disorder, 21.4% patients had sleep and cognitive disorder, 2.9% patient had disorder in sleep and anosmia, 8.6% patients had only sleep disturbance, 17.1% had only cognitive disturbance but 25.7% had no non-motor symptoms. Majority (61.4%) patient’s disease duration was 1-5 years. The mean duration of disease was found 6.34±5.53 years. Majority 34 (48.6%) patients were in stage II, 19 (27.1%) were in stage III, 5 (10.0%) were in stage IV and 12 (17.1%) were in stage V. Mean serum uric acid was found to be 3.45±1.26mg/dL (2.0-5.8) in male and 3.36±0.81mg/dL(2.1-5.8) in female patients.Serum uric acid level steadily reduced with the severity of PD which is statistically significant. Advanced stages of parkinson’s disease were associated with significantly lower levels of serum uric acid. The difference between the stages were statistically significant (p=0.007). Conclusion: This study shows a negative association between serum uric acid level and the severity of Parkinson’s disease. The level of serum uric acid decreased with the disease progression. This study added evidence consistent with an association between serum uric acid level and the severity of Parkinson’s disease. This finding pushes us to emphasize on the role of uric acid levels on the Parkinson’s disease. Bangladesh Crit Care J March 2024; 12 (1): 18-24

Sesamol: A Phenolic Compound of Health Benefits and Therapeutic Promise in Neurodegenerative Diseases.

Sesamol, one of the key bioactive ingredients of sesame seeds (Sesamum indicum L.), is responsible for many of its possible nutritional benefits. Both the Chinese and Indian medical systems have recognized the therapeutic potential of sesame seeds. It has been shown to have significant therapeutic potential against oxidative stress, inflammatory diseases, metabolic syndrome, neurodegeneration, and mental disorders. Sesamol is a benign molecule that inhibits the expression of inflammatory indicators like numerous enzymes responsible for inducing inflammation, protein kinases, cytokines, and redox status. This review summarises the potential beneficial effects of sesamol against neurological diseases including Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Recently, sesamol has been shown to reduce amyloid peptide accumulation and attenuate cognitive deficits in AD models. Sesamol has also been demonstrated to reduce the severity of PD and HD in animal models by decreasing oxidative stress and inflammatory pathways. The mechanism of sesamol's pharmacological activities against neurodegenerative diseases will also be discussed in this review.

Data-driven Gait based Severity Classification for Parkinson's Disease using Duo Spatiotemporal Convoluted Kernel Boosted ResNet model

Parkinson’s disease (PD) is one of the reformed brain syndromes that results in unintended stiffness and difficulty with balance and dexterity. To detect PD in medical scenery, physicians commonly use experimental indicators like motorized and non-motor symptoms and the severity rating depends on the unified PD Rating Scale (UPDRS). However, these medical assessments highly rely on expertized clinicians and lead to inter-variability discrepancies. Nowadays, gait sensor data assists doctors in diagnosing PD and estimates the severity level of gait abnormalities in patients. However, the gait sensor data increases the dimensionality issues and is subjected to high non-linear complexity. Hence, this study suggests an innovative deep learning (DL) technique for accurate PD analysis using gait patterns. Initially, the gait sensor data is preprocessed by performing data cleaning, and decimal scaling normalization (DS- Norm) to enhance the data quality. The Hoehn and Yahr (H&amp;amp;Y) scale is a commonly used rating scale for measuring the progression of Parkinson's disease symptoms. It's typically used to assess motor symptoms like tremors, rigidity, and bradykinesia. The scale ranges from 0 to 5, with higher numbers indicating more severe symptoms and disability. The preprocessed data are then fed into the proposed Duo spatiotemporal convoluted kernel boosted ResNet (DSCK-RNet) model for classifying the PD severity rating by learning the gait spatiotemporal features. The developed method is processed and scrutinized via the Python platform and a publicly available Physio- Net dataset is utilized for the simulation process. Various assessment measures like accuracy, precision, sensitivity, specificity, PPV, FPR, and MCC are examined and compared with traditional studies. In the experimental section, the developed DSCK-RNet model achieved an accuracy of 100%, 99.6%, 99%, and 99.64% for different classes like healthy, severity-2, severity-2.5, and severity-3 respectively. Compared to the conventional techniques, our suggested approach performs better. The experimental findings demonstrate the clinical significance of the suggested approach for the impartial evaluation of gait motor impairment in PD patients.

Evaluation of Substantia Nigra morphology in Parkinson's Disease.

In the elderly population, Parkinson's Disease (PD) is the second most common neurodegenerative disorder and is associated with morphological changes in the basal ganglia, especially the substantia nigra (SN). This study aimed to evaluate the volume and signal intensity (SI) of SN using Magnetic Resonance Imaging (MRI) to detect structural changes and investigate the relationship between the onset side and disease severity of PD. Clinical features and imaging data of 58 patients with PD were retrospectively analyzed from their medical records. Axial T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences of 3 Tesla (T) MRIs were used for the measurements. The right and left SN volumes and SI measurements were calculated in duplicate by 2 blinded and qualified neuroradiologists. The side of disease onset, disease duration, levodopa equivalent daily dose, Movement Disorder Society-sponsored Unified Parkinson Disease Rating Scale (MDS-UPDRS III) motor score, and modified Hoehn and Yahr (H&Y) scale scores were recorded and compared with SN volume and SI measurements. No statistically significant difference was found between the disease onset side and contralateral SN volume or SI measurements (P > .05). Despite high inter- and intra-rater reliability rates, there was no significant difference in the volume and SI of the contralateral SN according to H&Y stages (P > .05). Furthermore, SN volume and SI measurements were not significantly correlated with disease duration and MDS-UPDRS III motor score (P > .05). SN volume and SI values measured using axial FLAIR 3T MRI are not correlated with the side of onset or disease severity in PD. New imaging methods are required to detect preclinical or early-stage PD.