Parkinson\'s disease (PD) is a progressive neurodegenerative disorder primarily associated with motor dysfunctions. By the time of definitive diagnosis, about 60% of dopaminergic neurons have already been lost; moreover, even if dopaminergic drugs are highly effective in symptoms control, they only help maintaining a near-healthy condition when started as soon as possible. Therefore, interest in identifying early biomarkers of PD has grown in recent years, especially using neurophysiological techniques such as electroencephalography (EEG). This study aims to investigate brain complexity differences in PD patients compared to healthy controls, focusing on the beta band using approximate entropy (ApEn) analysis of resting-state EEG recordings. Sixty participants were recruited, including 25 PD patients and 35 healthy elderly subjects, matched for age and gender. EEG were recorded for each participant and ApEn values were computed in the beta 1 (13-20 Hz) and beta 2 (20-30 Hz) frequency bands for each EEG-channel and for ROIs. PD patients showed statistically lower ApEn values compared to controls in both beta 1 and beta 2 bands. Regarding electrodes analysis, beta 1 band alterations were found in frontocentral areas, while beta 2 band alterations were observed in centroparietal and frontocentral areas. Considering ROIs, statistically lower ApEn values for PD patients has been reported in central and parietal ROIs in the beta 2 band. Complexity reduction in these areas may underlie beta oscillatory activity dysfunction, reflecting impaired cortical mechanisms associated with motor dysfunction in PD. The results suggest that ApEn analysis of resting EEG activity may serve as a potential tool for early PD detection. Further studies are necessary to validate this approach in PD diagnosis and rehabilitation planning.

BACKGROUND: Patients with pre-existing neurologic disorders present a unique set of challenges for shoulder arthroplasty (SA) surgeons due to the presence of concomitant contractures, muscle weakness, and spasticity, which may affect outcomes and complication rates after shoulder arthroplasty. The goal of this systematic review was to evaluate the clinical and functional outcomes after SA in patients pre-existing with neurologic disorders, focusing on complication and reoperation rates.
METHODS: This systematic review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines outlined by Cochrane Collaboration. A search of PubMed, the Medline Library, and EMBASE from inception until September 2023 was conducted to obtain studies reporting on outcomes after SA in patients with neurological disorders. Study demographics and information on outcomes including patient-reported outcomes and complication rates were collected. The methodological quality of included primary studies was appraised using the MINORS scoring system.
RESULTS: Twenty articles published between 1997 and 2023 met inclusion criteria. In total, 13,126 patients with neurological conditions with 7 different neurological disorders (Parkinson\'s disease (PD), epilepsy and seizures, cerebral palsy (CP), poliomyelitis, Charcot neuropathy (CN), cerebrovascular disease (CVD) and multiple sclerosis (MS)) were included. The mean patient age was 64.3 years (range, 33.0 - 75.8 years), 51.4% of patients were male, and the mean postoperative follow-up time was 5.1 years (range, 1.4 - 9.9 years). PD was the most reported neurological disorder (9 studies, 8,033 patients), followed by epilepsy (4 studies, 3,783 patients), and MS (1 study, 1,077 patients). While these patients did experience improvements in outcomes following SA, high complication and revision rates were noted.
CONCLUSIONS: Patients with neurologic disorders demonstrate improvements in pain and function after SA but have higher reported complication and revision rates when compared with patients without neurologic conditions. This systematic review offers valuable data for both the surgeon and patient regarding anticipated clinical results and possible complications from SA in patients with neurologic disorders that may aid in shared decision-making when considering SA.

OBJECTIVE: 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. .

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.

BACKGROUND: Long-term exposure to ambient air pollution has been linked with all-cause mortality and cardiovascular and respiratory diseases. Suggestive associations between ambient air pollutants and neurodegeneration have also been reported, but due to the small effect and relatively rare outcomes evidence is yet inconclusive. Our aim was to investigate the associations between long-term air pollution exposure and mortality from neurodegenerative diseases.
METHODS: A Dutch national cohort of 10.8 million adults aged ≥30 years was followed from 2013 until 2019. Annual average concentrations of air pollutants (ultra-fine particles (UFP), nitrogen dioxide (NO2), fine particles (PM2.5 and PM10) and elemental carbon (EC)) were estimated at the home address at baseline, using land-use regression models. The outcome variables were mortality due to amyotrophic lateral sclerosis (ALS), Parkinson\'s disease, non-vascular dementia, Alzheimer\'s disease, and multiple sclerosis (MS). Hazard ratios (HR) were estimated using Cox models, adjusting for individual and area-level socio-economic status covariates.
RESULTS: We had a follow-up of 71 million person-years. The adjusted HRs for non-vascular dementia were significantly increased for NO2 (1.03; 95% confidence interval (CI) 1.02-1.05) and PM2.5 (1.02; 95%CI 1.01-1.03) per interquartile range (IQR; 6.52 and 1.47 μg/m3, respectively). The association with PM2.5 was also positive for ALS (1.02; 95%CI 0.97-1.07). These associations remained positive in sensitivity analyses and two-pollutant models. UFP was not associated with any outcome. No association with air pollution was found for Parkinson\'s disease and MS. Inverse associations were found for Alzheimer\'s disease.
CONCLUSIONS: Our findings, using a cohort of more than 10 million people, provide further support for associations between long-term exposure to air pollutants (PM2.5 and particularly NO2) and mortality of non-vascular dementia. No associations were found for Parkinson and MS and an inverse association was observed for Alzheimer\'s disease.

BACKGROUND: Walking with a concurrent cognitive task (dual-task walking) can pose a challenge to some populations due to aging or neurodegenerative disease. These tasks require cognitive resources involving the prefrontal cortex and can be studied using functional near-infrared spectroscopy (fNIRS). An important step in understanding fNIRS measures during such walking tasks is validating that measures reflect the demands of the tasks and not confounding sources or movement artifacts.
OBJECTIVE: This study aimed to investigate the validity of fNIRS measures of prefrontal cortex activity as an indicator of executive demand during usual walking (single-task) and dual-task walking against clinical and objective measures of motor behavior in young adults, older adults, and people with Parkinson\'s disease (PD), by evaluating several validation hypotheses.
METHODS: In total, 133 participants were recruited from younger adults (18-50 years, n = 42), older adults (≥60 years, n = 49) and people with PD (≥60 years, n = 42). Activity in the prefrontal cortex during walking with and without an auditory Stroop task was measured with fNIRS. A combined hemoglobin measure (correlation-based signal improvement, CBSI) was calculated for use in a region of interest analysis in the dorsolateral prefrontal cortex (dlPFC). Pre-registered hypotheses regarding convergent validity, discriminant validity and known group validity were tested. An exploratory analysis of different hemoglobin measures was also performed.
RESULTS: Increases in dlPFC activity were found from single- to dual-task walking in the younger adults group and from rest to single-task walking in the older adults and PD groups. In line with hypotheses, a positive relationship was found between between dlPFC activity during dual-task walking and dual-task cost in the younger adults group, as well as a positive relationship to step time variability during single-task walking and a negative relationship to walking speed during single-task walking in the PD group. However, several clinical and gait measures lacked a relationship with dlPFC activity.
CONCLUSIONS: The fNIRS results point towards the CBSI measure of dlPFC activity being a valid measure of executive demand during both single and dual-task walking. Some relationships between clinical and gait measures and brain activity during walking need further investigation.

The 14-3-3 family of proteins are highly conserved acidic eukaryotic proteins (25-32 kDa) abundantly present in the body. Through numerous binding partners, the 14-3-3 is responsible for many essential cellular pathways, such as cell cycle regulation and gene transcription control. Hence, its dysregulation has been linked to the onset of critical illnesses such as cancers, neurodegenerative diseases and viral infections. Interestingly, explorative studies have revealed an inverse correlation of 14-3-3 protein in cancer and neurodegenerative diseases, and the direct manipulation of 14-3-3 by virus to enhance infection capacity has dramatically extended its significance. Of these, COVID-19 has been linked to the 14-3-3 proteins by the interference of the SARS-CoV-2 nucleocapsid (N) protein during virion assembly. Given its predisposition towards multiple essential host signalling pathways, it is vital to understand the holistic interactions between the 14-3-3 protein to unravel its potential therapeutic unit in the future. As such, the general structure and properties of the 14-3-3 family of proteins, as well as their known biological functions and implications in cancer, neurodegeneration, and viruses, were covered in this review. Furthermore, the potential therapeutic target of 14-3-3 proteins in the associated diseases was discussed.

In this study, we delved into the hippocampal region to understand the effects of adipose stem cells (ADSCs) and rosemary extract (RE). Our main objective was to explore how these substances influence spatial memory, neurotrophins, and changes in antioxidant enzymes. Moreover, we meticulously investigated the impact of dopamine deficiency, a notable characteristic linked with Parkinson\'s disease (PD), on memory impairment. This study comprised five groups of Wistar rats - all male, all selected randomly. We labeled two of these gatherings \"lesion\" (L) and \"sham\" (SH). Each got injections in the bilateral form with 6 μg - one group getting saline, while another got 6-OHDA. From couple weeks before the neurotoxin injection to 8 weeks later on, our lesion cohort was treated with rosemary at a dosage rate of 50 mg/kg body weight - let\'s call it RE for simplicity sake. Moreover, there is also this other lot, designated as cell-transplanted lesion group or catchy exercise (CE) as we prefer to interpret them; they had cell transplants conducted exactly 7 days after receiving their respective injections. Bringing up the rear, we got a group treated with both cell transplant and rosemary (CE+R). We performed spatial memory tests at 4 weeks, then again at 8. At the end of eighth week, the brains were extracted for q-PCR, enzymatic and immunohistochemical studies. Turning our gaze toward a comparison between the CE+R and CE groups versus the L group, we spot an intriguing drop in escape latency time. There is also more time spent in quadrants. Digging deeper into this matter, the CE+R bunch unveiled a clear surge when it comes to the expression of four genes, namely NGF, BDNF, NT3, and NT4! This was notable especially while comparing with both R and even other fellows from its very own broader group - CE. In a bit complex bit related to enzyme activity now, there is some good news as well for those in favor of potent antioxidants such as GPx or SOD. CE + R group, showed a significant increase of GPX and SOD enzymes, compared to the SH and L groups, and a significant decrease of MDA activity as compared to other treated groups. A significant decrease of escape latency and increase of time in quadrant were observed in the CE+R and CE groups compared to L group. What\'s more, the levels of MDA in the CE+R group plummeted significantly when set up against the SH group. Wrapping things up, a definite downscale was observed in the density of GFAP-positive cells throughout different regions located within the hippocampus; this decline presented itself not solely in treatment groups but gripped onto those falling under SH as well, especially when compared to its comrade - the L group. Using ADSCs and taking RE orally have shown promising results in improving memory issues linked with PD.

BACKGROUND: Dementia is caused by neurodegenerative conditions and characterized by cognitive decline. Diagnostic accuracy for dementia subtypes, such as Alzheimer\'s Disease (AD), Dementia with Lewy Bodies (DLB) and Parkinson\'s Disease with dementia (PDD), remains challenging.
METHODS: Here, different methods of quantitative electroencephalography (qEEG) analyses were employed to assess their effectiveness in distinguishing dementia subtypes from healthy controls under eyes closed (EC) and eyes open (EO) conditions.
RESULTS: Classic Fast-Fourier Transform (FFT) and autoregressive (AR) power analyses differentiated between all conditions for the 4-8 Hz theta range. Only individuals with dementia with Lewy Bodies (DLB) differed from healthy subjects for the wider 4-15 Hz frequency range, encompassing the actual dominant frequency of all individuals. FFT results for this range yielded wider significant discriminators vs AR, also detecting differences between AD and DLB. Analyses of the inclusive dominant / peak frequency range (4-15 Hz) indicated slowing and reduced variability, also discriminating between synucleinopathies vs controls and AD. Dissociation of periodic oscillations and aperiodic components of AR spectra using Fitting-Oscillations-&-One-Over-F (FOOOF) modelling delivered a reliable and subtype-specific slowing of brain oscillatory peaks during EC and EO for all groups. Distinct and robust differences were particularly strong for aperiodic parameters, suggesting their potential diagnostic power in detecting specific changes resulting from age and cognitive status.
CONCLUSIONS: Our findings indicate that qEEG methods can reliably detect dementia subtypes. Spectral analyses comprising an integrated, multi-parameter EEG approach discriminating between periodic and aperiodic components under EC and EO conditions may enhance diagnostic accuracy in the future.

UNASSIGNED: Researchers using herbs and natural products to find new drugs often prefer flavonoids because of their potential as antioxidants and anti-inflammatories. The planned review addressed baicalein research findings in detail. This manuscript provides a complete review of baicalein\'s potential pharmacological effects along with several molecular targets for better understanding of its therapeutic activities.
UNASSIGNED: We targeted the review on in vitro and in vivo studies reported on baicalein. For this, the literature is gathered from the database available on search engines like PubMed, ScienceDirect, Scopus, and Google Scholar up to 21 December 2023. The keywords \"Scutellaria baicalensis\", \"Oroxylum indicum\", \"Neuroprotective\", \"Cardioprotective\", \"Toxicity studies\", and \"Baicalein\" were used to fetch the content.
UNASSIGNED: Baicalein\'s molecular receptor binding approach has shown anticancer, antidiabetic, antimicrobial, antiaging, neuroprotective, cardioprotective, respiratory protective, gastroprotective, hepatic protective, and renal protective effects. The synergistic effects of this drug with other selective herbs are also contributed towards significant therapeutic potential.
UNASSIGNED: This systematic review article from a contemporary and scientific perspective offers fresh insight into S. baicalensis, O. indicum, and its bioactive component baicalein as a potential complementary medicine. Baicalein may be transformed into more efficacious and acceptable evidence-based medicine. However, we recommend more clinical and mechanistic approaches to confirm safety and efficacy of baicalein.