Sinapic acid (SA) is a phenylpropanoid derivative found in various natural sources that exhibits remarkable versatile properties, including antioxidant, anti-inflammatory, and metal-chelating capabilities, establishing itself as a promising candidate for the prevention and treatment of conditions affecting the central nervous system, such as Alzheimer\'s disease (AD), Parkinson\'s disease (PD), ischemic stroke, and other neurological disorders. These effects also include neuroprotection in epilepsy models, as evidenced by a reduction in seizure-like behavior, cell death in specific hippocampal regions, and lowered neuroinflammatory markers. In AD, SA treatment enhances memory, reverses cognitive deficits, and attenuates astrocyte activation. SA also has positive effects on cognition by improving memory and lowering oxidative stress. This is shown by lower levels of oxidative stress markers, higher levels of antioxidant enzyme activity, and better memory retention. Additionally, in ischemic stroke and PD models, SA provides microglial protection and exerts anti-inflammatory effects. This review emphasizes SA\'s multifaceted neuroprotective properties and its potential role in the prevention and treatment of various brain disorders. Despite the need for further research to fully understand its mechanisms of action and clinical applicability, SA stands out as a valuable bioactive compound in the ongoing quest to combat neurodegenerative diseases and enhance the quality of life for affected individuals.

OBJECTIVE: Cerebral palsy (CP) is the term for a set of neurological disorders resulting from brain damage that impairs motor function. The aim of the present study was to perform a systematic review of the literature to determine whether individuals with CP are at a greater risk of negative periodontal health outcomes compared to those without CP.
METHODS: This study followed the recommendations of the MOOSE guidelines. Electronic searches were conducted in the PubMed, Web of Science, Scopus, Ovid, Embase, and PsycInfo databases. Observational studies assessing periodontal outcomes in individuals with CP were included. Risk of bias was appraised using the Newcastle-Ottawa scale. Meta-analyses were conducted and the results were presented using standardized mean differences (SMD), odds ratios (OR), and 95% confidence intervals (CI). The strength of the evidence was also assessed.
RESULTS: A total of 316 records were retrieved from the electronic databases, 17 of which were included in the qualitative synthesis. Meta-analyses revealed significantly higher scores in individuals with CP compared to those without CP for the oral hygiene index (SMD = 0.47 [95% CI: 0.17-0.78, I2 = 80%), gingival index (SMD = 0.75 [95% CI: 0.39-1.11], I2 = 79%), plaque index (SMD = 0.70 [95% CI: 0.07-1.33], I2 = 93%), and calculus index (SMD = 0.98 [95% CI: 0.76-1.20], I2 = 0%). However, no significant difference was found between groups for the prevalence of gingivitis (OR = 1.27 [95% CI: 0.28-5.66], I2 = 93%). The risk of bias for the outcome assessment and statistical tests was low. The strength of the evidence was deemed very low.
CONCLUSIONS: Individuals with CP may experience more significant negative periodontal health outcomes compared to those without CP.

A herb, Panax ginseng C.A. Meyer has been used traditionally for the treatment of various diseases. In this work, its chemical components have been explored by computational methods for the possibility of therapeutic potential against early Huntington\'s disease. The molecular docking calculations against dopamine receptor D1 (PDB ID: 7X2F) involved in pathogenesis of early Huntington\'s disease gave the binding affinities (kcal/mol) of schizandrin (-10.530), ergosterol (-10.124), protopanaxadiol (-9.650), panaxydol (-9.399), diphenhydramine (-9.358), and panasenoside (-9.358). The values for native ligand (-7.748) and some selected drugs, Nefazodone (-9.880), Risperidone (-9.752), and Haloperidol (-9.712) were higher revealing weaker interactions. The stability assessment of top protein-ligand adducts in terms of various geometrical and thermodynamical parameters extracted from 200 ns molecular dynamics simulations pointed to schizandrin, protopanaxadiol, and panasenoside as hit molecules. The minimal translational and rotational motion of the docked ligands at orthosteric pocket of the receptor at near physiological conditions hinted at the probability of it restricting or inhibiting over-activation of DRD1. The sustained thermodynamic spontaneity of complex formation reaction augmented the inferences derived from spatial results. The phytochemicals from Panax ginseng could be used in the prophylactics of early Huntington\'s disease and recommendation is made for further evaluation by experimental work.

Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though MS lesion detection has been studied, limited attention has been paid to clinical analysis and computational risk factor prediction. Artificial intelligence (AI) techniques and Machine Learning (ML) methods offer accurate and effective alternatives to mapping MS progression. However, there are challenges in accessing clinical data and interdisciplinary collaboration. By analyzing 103 papers, we recognize the trends, strengths and weaknesses of AI, ML, and statistical methods applied to MS diagnosis. AI/ML-based approaches are suggested to identify MS risk factors, select significant MS features, and improve the diagnostic accuracy, such as Rule-based Fuzzy Logic (RBFL), Adaptive Fuzzy Inference System (ANFIS), Artificial Neural Network methods (ANN), Support Vector Machine (SVM), and Bayesian Networks (BNs). Meanwhile, applications of the Expanded Disability Status Scale (EDSS) and Magnetic Resonance Imaging (MRI) can enhance MS diagnostic accuracy. By examining established risk factors like obesity, smoking, and education, some research tackled the issue of disease progression. The performance metrics varied across different aspects of MS studies: Diagnosis: Sensitivity ranged from 60 % to 98 %, specificity from 60 % to 98 %, and accuracy from 61 % to 97 %. Prediction: Sensitivity ranged from 76 % to 98 %, specificity from 65 % to 98 %, and accuracy from 62 % to 99 %. Segmentation: Accuracy ranged up to 96.7 %. Classification: Sensitivity ranged from 78 % to 97.34 %, specificity from 65 % to 99.32 %, and accuracy from 71 % to 97.94 %. Furthermore, the literature shows that combining techniques can improve efficiency, exploiting their strengths for better overall performance.

BACKGROUND: Following the standardized nomenclature proposed by the American Clinical Neurophysiology Society (ACNS), rhythmic high-amplitude delta activity with superimposed spikes (RHADS) can be reported as an extreme delta brush (EDB). The clinical implications of similar electrographic patterns being reported as RHADS versus EDB are important to highlight. We aim to review the electrographic characteristics of RHADS, evaluate whether RHADS is seen in other neurological disorders, and identify the similar and unique characteristics between RHADS and EDB to ultimately determine the most accurate way to differentiate and report these patterns. We believe that the differentiation of RHADS and EDB is important as there is a vast difference in the diagnostic approach and the medical management of associated underlying etiologies.
METHODS: We conducted an extensive search on MEDLINE and Pubmed utilizing various combinations of keywords. Searching for \"gamma polymerase and EEG\", or \"RHADS\" or \"Alpers syndrome and EEG\" or \"EEG\" AND \"Alpers-Huttenlocher syndrome\".
RESULTS: Three articles were found to be focused on the description of \"RHADS\" pattern in Alpers Syndrome. No publication to date were found when searching for the terms \"EDB\" AND \"children\", AND \"infant\" AND \"adolescent\" excluding \"encephalitis\" and \"neonate\". Although RHADS and EDB appear as similar EEG patterns, meticulous analysis can differentiate them. RHADS is not exclusive to patients with Alpers-Huttenlocher syndrome and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia can be two other elements that help in the differentiation of these patterns.
CONCLUSIONS: RHADS is not exclusive to patients with AHS and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia are features that help in the differentiation of these patterns.

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.

Vitamin D binding protein (VDBP) serves as a key transporter protein responsible for binding and delivering vitamin D and its metabolites to target organs. VDBP plays a crucial part in the inflammatory reaction following tissue damage and is engaged in actin degradation. Recent research has shed light on its potential role in various diseases, leading to a growing interest in understanding the implications of VDBP in psychiatric and neurological disorders. The purpose of this review was to provide a summary of the existing understanding regarding the involvement of VDBP in neurological and psychiatric disorders. By examining the intricate interplay between VDBP and these disorders, this review contributes to a deeper understanding of underlying mechanisms and potential therapeutic avenues. Insights gained from the study of VDBP could pave the way for novel strategies in the diagnosis, prognosis, and treatment of psychiatric and neurological disorders.

The development of the central nervous system is highly complex, involving numerous developmental processes that must take place with high spatial and temporal precision. This requires a series of complex and well-coordinated molecular processes that are tighly controlled and regulated by, for example, a variety of proteins and lipids. Deregulations in these processes, including genetic mutations, can lead to the most severe maldevelopments. The present review provides an overview of the protein family Plasticity-related genes (PRG1-5), including their role during neuronal differentiation, their molecular interactions, and their participation in various diseases. As these proteins can modulate the function of bioactive lipids, they are able to influence various cellular processes. Furthermore, they are dynamically regulated during development, thus playing an important role in the development and function of synapses. First studies, conducted not only in mouse experiments but also in humans, revealed that mutations or dysregulations of these proteins lead to changes in lipid metabolism, resulting in severe neurological deficits. In recent years, as more and more studies have shown their involvement in a broad range of diseases, the complexity and broad spectrum of known and as yet unknown interactions between PRGs, lipids, and proteins make them a promising and interesting group of potential novel therapeutic targets.

Adeno-associated virus (AAV)-based gene therapy is a clinical stage therapeutic modality for neurological disorders. A common genetic defect in myriad monogenic neurological disorders is nonsense mutations that account for about 11% of all human pathogenic mutations. Stop codon readthrough by suppressor transfer RNA (sup-tRNA) has long been sought as a potential gene therapy approach to target nonsense mutations, but hindered by inefficient in vivo delivery. The rapid advances in AAV delivery technology have not only powered gene therapy development but also enabled in vivo preclinical assessment of a range of nucleic acid therapeutics, such as sup-tRNA. Compared with conventional AAV gene therapy that delivers a transgene to produce therapeutic proteins, AAV-delivered sup-tRNA has several advantages, such as small gene sizes and operating within the endogenous gene expression regulation, which are important considerations for treating some neurological disorders. This review will first examine sup-tRNA designs and delivery by AAV vectors. We will then analyze how AAV-delivered sup-tRNA can potentially address some neurological disorders that are challenging to conventional gene therapy, followed by discussing available mouse models of neurological diseases for in vivo preclinical testing. Potential challenges for AAV-delivered sup-tRNA to achieve therapeutic efficacy and safety will also be discussed.

Despite the fact that the global COVID-19 pandemic has officially ended, we continue to feel its effects and discover new correlations between SARS-CoV-2 infection and changes in the organism that have occurred in patients. It has been shown that the disease can be associated with a variety of complications, including disorders of the nervous system such as a characteristic loss of smell and taste, as well as less commonly reported incidents such as cranial polyneuropathy or neuromuscular disorders. Nervous system diseases that are suspected to be related to COVID-19 include Guillain-Barré syndrome, which is frequently caused by viruses. During the course of the disease, autoimmunity destroys peripheral nerves, which despite its rare occurrence, can lead to serious consequences, such as symmetrical muscle weakness and deep reflexes, or even their complete abolition. Since the beginning of the pandemic, case reports suggesting a relationship between these two disease entities have been published, and in some countries, the increasing number of Guillain-Barré syndrome cases have also been reported. This suggests that previous contact with SARS-CoV-2 may have had an impact on their occurrence. This article is a review and summary of the literature that raises awareness of the neurological symptoms\' prevalence, including Guillain-Barré syndrome, which may be impacted by the commonly occurring COVID-19 disease or vaccination against it. The aim of this review was to better understand the mechanisms of the virus\'s action on the nervous system, allowing for better detection and the prevention of its complications.