Complex Neurological Conditions Research Articles

Mechanism of Alzheimer type II astrocyte development in hepatic encephalopathy

Type C hepatic encephalopathy (Type C HE) is a major and complex neurological condition that occurs following chronic liver failure. The molecular basis of Type C HE remains elusive. Type C HE is characterized by mental confusion, cognitive and motor disturbances. The presence of Alzheimer type II astrocytes (AT2A) is the key histopathological finding observed in Type C HE. However, nothing is currently known regarding AT2A development and its involvement in cognitive, and motor deficits in Type C HE. We, therefore, examined in rats the mechanisms by which liver failure contributes to the progression of AT2A, and its role in the development of cognitive and motor deficits in thioacetamide (TAA) model of Type C HE. We and others earlier reported increased oxidative/nitrosative stress (ONS), JNK1/2, and cMyc activation in ammonia-treated astrocyte cultures, as well as in brains from chronic liver failure. We now found increased levels of astrocytic glia maturation factor (GMF, a factor strongly implicated in neuroinflammation), as well as various inflammatory factors (IL-1β, TNF-α, IL-6, MMP-3, COX2, CXCL1, and PGE2), and reduced levels of GFAP and increased levels of aggregated nuclear protein Lamin A/C in rat brain cortex post-chronic liver failure. We also found increased levels of GMF and inflammatory factors (MMP-3, COX2, CXCL1, and PGE2) in astrocytes post-ammonia treatment in vitro. Additionally, pharmacological inhibition of upstream signaling of GMF (ONS, JNK1/2, and cMyc) or GMF inhibitors W-7 and trifluoperazine significantly reduced the levels of inflammatory factors, the number of AT2A cells, as well as the cognitive and motor deficits in TAA-treated rats. Increased levels of GMF were also identified in human post-mortem brain sections. These findings strongly suggest that increased levels of astrocytic GMF due to elevated levels of ONS, JNK1/2, and cMyc and the subsequent inflammation contribute to the development of AT2A and the consequent cognitive, and motor deficits in chronic liver failure.

Enhancements in Parkinson's Disease Management: Leveraging Levodopa Optimization and Surgical Breakthroughs.

Parkinson's disease (PD) is a complex neurological condition caused due to inheritance, environment, and behavior among various other parameters. The onset, diagnosis, course of therapy, and future of PD are thoroughly examined in this comprehensive review. This review also insights into pathogenic mechanisms of reactive microgliosis, Lewy bodies, and their functions in the evolution of PD. It addresses interaction complexity with genetic mutations, especially in genes such as UCH-L1, parkin, and α-synuclein, which illuminates changes in the manner dopaminergic cells handle proteins and use proteases. One of the emerging therapeutic routes that are being investigated is neuroprotective medicines that aim to prevent the aggregation of α-synuclein and interventions that modify the progression of diseases. The review concludes by stressing the dynamic nature of PD research and the potential game-changing impact of precision medicines on current approaches to therapy. This raises the improved outcomes and life quality for those with PD. Potential treatments for severe PD include new surgical methods like Deep Brain Stimulation (DBS). Further, exploration of non-motor manifestations, such as cognitive impairment, autonomic dysfunction, and others, is covered in this review article. These symptoms have a significant impact on patients' quality of life. One of the emerging therapeutic routes that are being investigated is neuroprotective medicines that aim to prevent the aggregation of α-synuclein and interventions that modify the progression of diseases. The review concludes by stressing the dynamic nature of PD research and the potential game-changing impact of precision medicines on current approaches to therapy.

Immune signature of gene expression pattern shared by autism spectrum disorder and Huntington's disease

Autism spectrum disorder (ASD) and Huntington's disease (HD) are complex neurological conditions with unclear causes and limited treatments, affecting individuals, families, and society. Despite ASD and HD representing two opposing stages of neuronal development and degeneration, they share similar clinical-pathological features in motor function. In this study, we leveraged transcriptomic data from the prefrontal cortex available in public databases to identify shared transcriptional characteristics of ASD and HD. Differential expression analysis revealed that the majority of differentially expressed genes (DEGs) were up-regulated in ASD carriers, whereas most DEGs were down-regulated in HD carriers. Among the DEGs shared between both diseases, three out of seven protein-coding genes were related to the immune system. Furthermore, we identified two enriched pathways shared between ASD and HD DEGs. The gene interaction network analysis unveiled four hub genes shared by both diseases, all of which are associated with immune functions. The findings suggest a shared gene expression pattern in the prefrontal cortex of people with ASD and HD, closely linked to the immune system. These findings will contribute to exploring the biological mechanisms underlying the shared phenotypes of these two diseases from an immunological perspective.

Harmonizing Insights: LR-FFT Feature Extraction for Alzheimer’s and Autism Spectrum Disorder Detection in EEG Signals

Alzheimer’s Disease (AD) and Autism Spectrum Disorder (ASD) represent two distinct but equally impactful challenges in the field of neurology and cognitive health. AD is a degenerative neurological condition characterized by its progressive nature, typically affecting individuals in later stages of life. The hallmark features include cognitive impairment, mem- ory deterioration, and alterations in behavior. In contrast, ASD is a developmental disorder typically diagnosed in childhood, marked by difficulties in social interaction, communication, and repetitive behaviors. This paper explores the potential of the time-frequency feature extraction model known as the Left-Right Fast Fourier Transform (LR-FFT) in the context of these two disorders. While AD and ASD differ significantly in their onset, presentation, and demographic affected, both necessitate early and accurate diagnosis to enable timely intervention and tailored treatment strategies. Our research yields promising results, with classification accuracies reaching 88.26% for AD and 99.86% for ASD, demonstrating the LR-FFT’s potential to enhance diagnostic accuracy. By contributing to improved differentiation between these complex neurological conditions, this work aims to advance our understanding and management of AD and ASD, ultimately benefiting patients, their families, and healthcare practitioners.

A pilot study: Examining cytoskeleton gene expression profiles in Pakistani children with autism spectrum disorder.

Finding effective pharmacological interventions to address the complex array of neurodevelopmental disorders is currently an urgent imperative within the scientific community as these conditions present significant challenges for patients and their families, often impacting cognitive, emotional, and social development. In this study, we aimed to explore non-invasive method to diagnose autism spectrum disorders (ASD) within Pakistan children population and to identify clinical drugs for its treatment. The current report outlines a comprehensive bidirectional investigation showcasing the successful utilization of saliva samples to quantify the expression patterns of profilins (PFN1, 2, and 3); and ERM (ezrin, radixin, and moesin) proteins; and additionally moesin pseudogene 1 and moesin pseudogene 1 antisense (MSNP1AS). Subsequently, these expression profiles were employed to forecast interactions between drugs and genes in children diagnosed with ASD. This study sought to delve into the intricate gene expression profiles using qualitative polymerase chain reaction of profilin isoforms (PFN1, 2, and 3) and ERM genes extracted from saliva samples obtained from children diagnosed with ASD. Through this analysis, we aimed to elucidate potential molecular mechanisms underlying ASD pathogenesis, shedding light on novel biomarkers and therapeutic targets for this complex neurological condition. (n = 22). Subsequently, we implemented a diagnostic model utilizing sparse partial least squares discriminant analysis (sPLS-DA) to predict drugs against our genes of interest. Furthermore, connectivity maps were developed to illustrate the predicted associations of 24 drugs with the genes expression. Our study results showed varied expression profile of cytoskeleton linked genes. Similarly, sPLS-DA model precisely predicted drug to genes response. Sixteen of the examined drugs had significant positive correlations with the expression of the targeted genes whereas eight of the predicted drugs had shown negative correlations. Here we report the role of cytoskeleton linked genes (PFN and ERM) in co-relation to ASD. Furthermore, variable yet significant quantitative expression of these genes successfully predicted drug-gene interactions as shown with the help of connectivity maps that can be used to support the clinical use of these drugs to treat individuals with ASD in future studies.

HÁBITOS ALIMENTARES DURANTE A GESTAÇÃO: UMA INVESTIGAÇÃO SOBRE A POSSÍVEL INFLUÊNCIA NO DESENVOLVIMENTO DO TRANSTORNO DO ESPECTRO AUTISTA (TEA)

Autism Spectrum Disorder (ASD) is a complex neurological condition that impacts social, communicative, and behavioral development. This study investigates the relationship between the dietary habits of pregnant women and the development of ASD in their children, focusing on folic acid (vitamin B9) supplementation. Previous studies suggest that folic acid is essential for neural tube closure during embryonic development, but its excess may be related to an increased risk of autism. The study uses a qualitative methodology and a comprehensive literature review, analyzing articles published between 2017 and 2024 in databases such as SciELO, PubMed, Google Scholar, and Web of Science. The literature review highlights the importance of epigenetic regulation in the neurological development of ASD, influenced by adequate levels of folic acid during pregnancy. However, there is a significant gap in the complete understanding of this relationship, especially regarding the interaction of several nutrients and their impacts on neurodevelopment. In conclusion, although folic acid supplementation is an essential public health measure to prevent neural tube defects, careful monitoring is crucial to avoid potential risks of autism. The research highlights the need for further studies to elucidate the exact mechanisms and identify reliable biomarkers that can aid in early diagnosis and preventive interventions to improve health outcomes in children at risk of developing ASD.

Diagnostic evaluation of autoimmune encephalitis

Autoimmune encephalitis (AIE) is a complex neurological condition characterized by brain inflammation caused by autoantibodies targeting neuronal surface antigens or synaptic receptors resulting in direct antibody-mediated neuronal dysfunction. The aetiology of AIE includes malignancies and viral infections. However, significant proportion of these patients have no identifiable trigger.The clinical presentation of AIE is varied, ranging from memory deficits and psychiatric symptoms to seizures and movement disorders. The diagnosis is typically based on a combination of supportive clinical features and diagnostic tools such as EEG, MRI, and CSF findings. The detection of antibodies confirms diagnosis of specific autoimmune encephalitis syndromes.Early recognition and prompt treatment of AIE are crucial, as delayed intervention can result in permanent neurological damage. The primary treatment approach is immunotherapy, along with screening for underlying malignancies. With the evolving knowledge on different antibodies and their associated syndromes, it is important for clinicians to have a high degree of suspicion and rule out other differentials to ensure timely and appropriate diagnosis. Furthermore, the use of appropriate diagnostic criteria can help minimize delays in starting treatment.This review provides an overview of the current understanding of AIE, with a focus on pathophysiology, clinical presentation, diagnostics, and treatment modalities, specifically for the most commonly encountered types of AIE associated with cell surface and synaptic antibodies.

Total brain volume is associated with severity of transverse sinus stenosis in idiopathic intracranial hypertension

BackgroundIdiopathic intracranial hypertension (IIH) is a complex neurological condition characterized by symptoms of increased intracranial pressure of unclear etiology. While transverse sinus stenosis (TSS) is often present in patients with...

TRNA Modifications and Dysregulation: Implications for Brain Diseases.

Transfer RNAs (tRNAs) are well-known for their essential function in protein synthesis. Recent research has revealed a diverse range of chemical modifications that tRNAs undergo, which are crucial for various cellular processes. These modifications are necessary for the precise and efficient translation of proteins and also play important roles in gene expression regulation and cellular stress response. This review examines the role of tRNA modifications and dysregulation in the pathophysiology of various brain diseases, including epilepsy, stroke, neurodevelopmental disorders, brain tumors, Alzheimer's disease, and Parkinson's disease. Through a comprehensive analysis of existing research, our study aims to elucidate the intricate relationship between tRNA dysregulation and brain diseases. This underscores the critical need for ongoing exploration in this field and provides valuable insights that could facilitate the development of innovative diagnostic tools and therapeutic approaches, ultimately improving outcomes for individuals grappling with complex neurological conditions.

Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine

Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.

Telemedicine applied to neurology, a syndromic approach

Introduction: Telemedicine has proven invaluable, especially in cases like stroke, where it expedites accurate diagnosis and thrombolytic treatment initiation, thereby reducing mortality rates. Objectives: Evaluate the efficacy of telemedicine in diagnosing neurological syndromes among patients receiving outpatient care through teleneurology. Methodology:A systematic literature review was conducted using a qualitative and descriptive approach, guided by the "PICO" search and analysis strategy. The study population comprised patients seeking outpatient neurological care, with the primary interest being the assessment of telemedicine's efficiency in diagnosing neurological syndromes. Data were collected from PubMed, Scopus, and BVS databases using predefined inclusion and exclusion criteria. Results: Several studies demonstrated the successful application of telemedicine in neurological care. For instance, teleconsultations with patients diagnosed with cognitive impairment yielded positive outcomes, reducing demands while delaying symptom progression. However, the feasibility of telemedicine varied across different regions and patient demographics, highlighting socio-economic factors as determinants of accessibility and acceptance. Additionally, telemedicine showed promise in managing complex neurological conditions such as cerebellar ataxia, Parkinson's disease, and myasthenia gravis, albeit with certain limitations in physical examination capabilities. Conclusion: In conclusion, telemedicine has emerged as a crucial tool in neurology, overcoming geographical barriers and enhancing access to specialized care. Despite its widespread adoption, challenges persist, particularly in ensuring equitable access across diverse populations. Moving forward, addressing these challenges and advancing telemedicine infrastructure will be paramount in optimizing neurological care delivery and improving patient outcomes.

Anesthetic Management in a Pediatric Patient with Cyanotic Congenital Heart Disease and Cerebral Abscess: A Case Report

Brain abscesses, often linked to congenital heart disease, present a significant challenge in developing countries, where they constitute around 8% of intracranial mass cases. These abscesses lead to increased intracranial pressure and higher morbidity and mortality rates. Anesthetic management in patients with cyanotic congenital heart disease, such as those with ventricular septal defects (VSD) and pulmonary hypertension, is particularly complex due to the need to anticipate shunting at various stages. This case report details the anesthetic management of a 7-year-old boy with a suspected cerebral abscess, VSD, and pulmonary hypertension. The patient, presenting with intermittent headaches and cyanosis, underwent abscess drainage. Preoperative and intraoperative care focused on maintaining hemodynamic stability and preventing alterations in systemic and pulmonary vascular resistance. Sevoflurane was chosen for maintenance anesthesia due to its minimal impact on vascular resistance. Postoperative management included intensive monitoring and pain control to prevent complications such as hypoxia and cardiac decompensation. This case underscores the importance of tailored anesthetic strategies in managing patients with complex cardiac and neurological conditions undergoing surgery.

Anesthetic Management in a Pediatric Patient with Cyanotic Congenital Heart Disease and Cerebral Abscess: A Case Report

Brain abscesses, often linked to congenital heart disease, present a significant challenge in developing countries, where they constitute around 8% of intracranial mass cases. These abscesses lead to increased intracranial pressure and higher morbidity and mortality rates. Anesthetic management in patients with cyanotic congenital heart disease, such as those with ventricular septal defects (VSD) and pulmonary hypertension, is particularly complex due to the need to anticipate shunting at various stages. This case report details the anesthetic management of a 7-year-old boy with a suspected cerebral abscess, VSD, and pulmonary hypertension. The patient, presenting with intermittent headaches and cyanosis, underwent abscess drainage. Preoperative and intraoperative care focused on maintaining hemodynamic stability and preventing alterations in systemic and pulmonary vascular resistance. Sevoflurane was chosen for maintenance anesthesia due to its minimal impact on vascular resistance. Postoperative management included intensive monitoring and pain control to prevent complications such as hypoxia and cardiac decompensation. This case underscores the importance of tailored anesthetic strategies in managing patients with complex cardiac and neurological conditions undergoing surgery.

Can Stem Cell Therapy be an Effective Therapeutic Option for Complex and Neurological Conditions?

This article explores the feasibility and potential benefits of stem cell therapy as a promising therapeutic intervention for individuals facing severe behavioral and cognitive impairments, targeting underlying neurological mechanisms to offer potential symptom improvement and function restoration, thereby enhancing the quality of life for patients and potentially alleviating stress and burnout among caregivers. The aims of the study include investigating the efficacy of stem cell therapy in addressing these impairments and evaluating its potential to alleviate caregiver burden. Through a comprehensive review of existing literature, clinical trials, and studies, this research synthesizes the mechanisms of stem cell therapy, potential applications, clinical trial outcomes, caregiver experiences, and economic implications. The methods employed involve analyzing diverse data sources to provide a holistic understanding of the possibilities and challenges associated with stem cell therapy. Key outcomes of the study include highlighting promising results from clinical trials targeting conditions such as autism spectrum disorder, Parkinson's disease, and Crohn's disease, which underscore the transformative potential of stem cell therapy in patient care. Additionally, economic implications suggest potential reductions in healthcare costs and alleviation of financial strain on individuals, families, and healthcare providers. Stem cell therapy represents a paradigm shift in healthcare, promising to redefine treatment approaches and alleviate broader societal burdens associated with complex neurological conditions. The relevance of the study lies in emphasizing the need for continued research, ethical considerations, and multidisciplinary collaboration to ensure the safe and effective integration of stem cell therapy into clinical practice, ultimately offering new hope and improved care for patients, caregivers, and healthcare systems worldwide.

Gait Data-Driven Analysis of Parkinson’s Disease Using Machine Learning

INTRODUCTION: Parkinson's disease is a progressive and complex neurological condition that mostly affects coordination and motor control. Parkinson's disease is most commonly associated with its motor symptoms, which include tremors, bradykinesia (slowness of movement), rigidity, and postural instability.
 OBJECTIVES: Determine any minor alterations in walking patterns that could be early signs of Parkinson's disease. Track the course of Parkinson's disease over time by using gait data.
 METHODS: In this study, we applied three types of VGRF datasets ("Dual Tasking, RAS, and Treadmill Walking") and developed an ML-based model using six different classifier methods. The datasets were analysed using 16 sensors, of which 8 were applied to each foot and the total pressure of the left and right foot. The aforementioned three distinct gait patterns movement disorders were the sources of the dataset. The gait signals dataset benefited by the participant demographic data. 
 RESULTS: Then, we passed the outcome of applying the model and measuring performance through a cross-validation operator to check the accuracy and decision-making of the five algorithms i) Deep Learning, ii) Neural Networks, iii) Support Vector Machine (SVM), iv) Gradient Boost Tree (GBT), v) Random Forest”. The following findings compare the effectiveness of the various algorithms utilized and the observed PD very well.
 CONCLUSION: The different ML classifier algorithms demonstrated good detection capability with different accuracy. Our proposed ensemble model is superior to compare with the existing models. Because we can observe the proposed ensemble model result and accuracy better than the other classifier model. The other classifier model’s highest accuracy is 92.08% whereas our ensemble model got 92.31%. So, it has proved that our proposed ensemble model is excellent and robust.

MANAGEMENT OF BELL’S PALSY - A CASE REPORT

Bell’s palsy is a disease affecting one side of the facial muscles abruptly due to compression or inflammation of the facial nerve. This case study explores the clinical presentation and Ayurvedic management of a 52-year-old female patient presenting with symptoms consistent with Bell's palsy, termed as Sopha/Kapha Anubanda Arddita in Ayurveda. The patient exhibited sudden onset facial deviation, speech difficulty, and other associated symptoms. The diagnosis was primarily clinical, supported by classical symptoms of Ardita and Bell's palsy. Treatment involved a combination of Kaphahara/Sophahara medications followed by Vatahara medicines, alongside specific therapeutic procedures tailored to address the underlying doshic imbalances. Critical interventions included the administration of Amrutotharam Kashayam, topical applications of Lepana, and Nasya with Ksheerabala Taila 101 Avartti, among others. The patient showed significant improvement in symptoms and motor functions over a 14-day inpatient treatment period, demonstrating the efficacy of Ayurvedic interventions in managing acute onset LMN Facial palsy. This case underscores the importance of individualised treatment approaches and the potential of Ayurveda in addressing complex neurological conditions.

Therapeutic Potential for Metabotropic Glutamate Receptor 7 Modulators in Cognitive Disorders.

Metabotropic glutamate receptor 7 (mGlu7) is the most highly conserved and abundantly expressed mGlu receptor in the human brain. The presynaptic localization of mGlu7, coupled with its low affinity for its endogenous agonist, glutamate, are features that contribute to the receptor's role in modulating neuronal excitation and inhibition patterns, including long-term potentiation, in various brain regions. These characteristics suggest that mGlu7 modulation may serve as a novel therapeutic strategy in disorders of cognitive dysfunction, including neurodevelopmental disorders that cause impairments in learning, memory, and attention. Primary mutations in the GRM7 gene have recently been identified as novel causes of neurodevelopmental disorders, and these patients exhibit profound intellectual and cognitive disability. Pharmacological tools, such as agonists, antagonists, and allosteric modulators, have been the mainstay for targeting mGlu7 in its endogenous homodimeric form to probe effects of its function and modulation in disease models. However, recent research has identified diversity in dimerization, as well as trans-synaptic interacting proteins, that also play a role in mGlu7 signaling and pharmacological properties. These novel findings represent exciting opportunities in the field of mGlu receptor drug discovery and highlight the importance of further understanding the functions of mGlu7 in complex neurologic conditions at both the molecular and physiologic levels. SIGNIFICANCE STATEMENT: Proper expression and function of mGlu7 is essential for learning, attention, and memory formation at the molecular level within neural circuits. The pharmacological targeting of mGlu7 is undergoing a paradigm shift by incorporating an understanding of receptor interaction with other cis- and trans- acting synaptic proteins, as well as various intracellular signaling pathways. Based upon these new findings, mGlu7's potential as a drug target in the treatment of cognitive disorders and learning impairments is primed for exploration.

Unveiling the Intricacies: A Comprehensive Review of Magnetic Resonance Imaging (MRI) Assessment of T2-Weighted Hyperintensities in the Neuroimaging Landscape.

T2-weighted hyperintensities in neuroimaging represent areas of heightened signal intensity on magnetic resonance imaging (MRI) scans, holding crucial importance in neuroimaging. This comprehensive review explores the T2-weighted hyperintensities, providing insights into their definition, characteristics, clinical relevance, and underlying causes. It highlights the significance of these hyperintensities as sensitive markers for neurological disorders, including multiple sclerosis, vascular dementia, and brain tumors. The review also delves into advanced neuroimaging techniques, such as susceptibility-weighted and diffusion tensor imaging, and the application of artificial intelligence and machine learning in hyperintensities analysis. Furthermore, it outlines the challenges and pitfalls associated with their assessment and emphasizes the importance of standardized protocols and a multidisciplinary approach. The review discusses future directions for research and clinical practice, including the development of biomarkers, personalized medicine, and enhanced imaging techniques. Ultimately, the review underscores the profound impact of T2-weighted hyperintensities in shaping the landscape of neurological diagnosis, prognosis, and treatment, contributing to a deeper understanding of complex neurological conditions and guiding more informed and effective patient care.

Unraveling the Genetic Landscape of Neurological Disorders: Insights into Pathogenesis, Techniques for Variant Identification, and Therapeutic Approaches.

Genetic abnormalities play a crucial role in the development of neurodegenerative disorders (NDDs). Genetic exploration has indeed contributed to unraveling the molecular complexities responsible for the etiology and progression of various NDDs. The intricate nature of rare and common variants in NDDs contributes to a limited understanding of the genetic risk factors associated with them. Advancements in next-generation sequencing have made whole-genome sequencing and whole-exome sequencing possible, allowing the identification of rare variants with substantial effects, and improving the understanding of both Mendelian and complex neurological conditions. The resurgence of gene therapy holds the promise of targeting the etiology of diseases and ensuring a sustained correction. This approach is particularly enticing for neurodegenerative diseases, where traditional pharmacological methods have fallen short. In the context of our exploration of the genetic epidemiology of the three most prevalent NDDs-amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease, our primary goal is to underscore the progress made in the development of next-generation sequencing. This progress aims to enhance our understanding of the disease mechanisms and explore gene-based therapies for NDDs. Throughout this review, we focus on genetic variations, methodologies for their identification, the associated pathophysiology, and the promising potential of gene therapy. Ultimately, our objective is to provide a comprehensive and forward-looking perspective on the emerging research arena of NDDs.

A pilot study on determination of dietary intake of geriatric epileptic patients

Epilepsy, a complex neurological condition, stems from multifaceted factors, including genetic predispositions and various triggers. The elderly, a rapidly growing demographic globally, encounter an increased risk of seizures. In India, a significant population lives with epilepsy, notably more prevalent in rural areas. Moreover, malnutrition and epilepsy exhibit a complex relationship, potentially influencing each other's onset and progression. Geriatric individuals with epilepsy often face sedentary lifestyles and potential weight-related concerns due to medication. This pilot study aimed to assess the nutrient profile of geriatric patients with epilepsy. A quantitative research approach was adopted; studying 30 individuals aged 60 to 80 years at a private neurology hospital in Tamil Nadu. Data was collected through interviews and dietary assessments, including the 24-hour recall and food frequency methods. Statistical analysis using SPSS provided insights into nutrient intake among the participants. Results indicated that while certain nutrients met recommended levels, fat and carbohydrate intake exceeded the prescribed amounts. Additionally, dietary patterns varied among different types of seizures. Despite differences, no statistical significance was found. Food frequency analysis revealed varied consumption patterns, notably lower intake of fruits and vegetables among the epilepsy geriatric patients. The study emphasizes the importance of understanding the nutritional needs of individuals with epilepsy, particularly in the geriatric population, to formulate personalized dietary interventions for improved seizure management and overall health.