Search Results (1,008)

The popularity of bioactive compounds extracted from sea cucumbers is growing due to their wide application in the pharmaceutical industry, particularly in the development of drugs for neurological disorders. Different types of compounds, such as saponins, phenolic compounds, cerebrosides, and glucocerebrosides, are being studied intensively for their efficacy in assessing the treatment of neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and brain tumors, among others. Positive results have been observed in the upregulation in the content of p-CREB, p-PL3K, BDNF, SOD, and MDA. Furthermore, the neuroprotective mechanism of the compounds against Alzheimer’s disease revealed that suppressing the phosphorylation of tau protein by the PI3K/Akt/GSK3β pathway leads to improved synaptic plasticity and reduced nerve fiber tangles. This comprehensive review explores recent findings on the therapeutic potential of sea cucumber bioactives in the treatment of brain-related disorders. Full article

Background/Objectives: Traumatic brain injury is one of the leading causes of death and disability. When traumatic brain injury is repeated over time, it can lead to the development of Chronic Traumatic Encephalopathy, a chronic neurodegenerative disease commonly observed in individuals who engage in contact sports or military personnel involved in activities with a high risk of repeated head trauma. At autopsy, the examination of the brain reveals regional atrophy, corresponding to high concentrations of glutamate receptors. Microscopically, the primary findings are the deposition of neurofibrillary tangles and neuropil threads. The aim of this study is to highlight the clinical and histopathological characteristics of Chronic Traumatic Encephalopathy, providing diagnostic support to forensic pathologists. Additionally, it seeks to aid in the differential diagnosis of similar conditions. Methods: A review of literature was conducted following the PRISMA criteria. Of 274 articles, 7 were selected. Results: According to these papers, most patients were male and exhibited neurological symptoms and neuropsychiatric impairments, and a proportion of them committed suicide or had aggressive behavior. Conclusions: Chronic Traumatic Encephalopathy remains largely underdiagnosed during life. The definitive diagnosis of Chronic Traumatic Encephalopathy is established post-mortem through the identification of pathognomonic tauopathy lesions. Early and accurate antemortem recognition, particularly in at-risk individuals, is highly valuable for its differentiation from other neurodegenerative conditions, thereby enabling appropriate clinical management and potential interventions. Full article

Recent findings highlight that Reelin, a glycoprotein involved in neural development, synaptic plasticity, and neuroinflammation, plays some specific roles in neurodegenerative disorders associated with aging, such as age-related macular degeneration (AMD) and Alzheimer’s disease (AD). Reelin modulates synaptic function and guarantees homeostasis in neuronal-associated organs/tissues (brain and retina). The expression of Reelin is dysregulated in these neurological disorders, showing common pathways depending on chronic neurogenic inflammation and/or dysregulation of the extracellular matrix in which Reelin plays outstanding roles. Recently, the relationship between AMD and AD has gained increasing attention as they share many common risk factors (aging, genetic/epigenetic background, smoking, and malnutrition) and histopathological lesions, supporting certain pathophysiological crosstalk between these two diseases, especially regarding neuroinflammation, oxidative stress, and vascular complications. Outside the nervous system, Reelin is largely produced at the gastrointestinal epithelial level, in close association with innervated regions. The expression of Reelin receptors inside the gut suggests interesting aspects in the field of the gut–brain–eye axis, as dysregulation of the intestinal microbiota has been frequently described in neurodegenerative and behavioral disorders (AD, autism, and anxiety and/or depression), most probably linked to inflammatory, neurogenic mediators, including Reelin. Herein we examined previous and recent findings on Reelin and neurodegenerative disorders, offering findings on Reelin’s potential relation with the gut–brain and gut–brain–eye axes and providing novel attractive hypotheses on the gut–brain–eye link through neuromodulator and microbiota interplay. Neurodegenerative disorders will represent the ground for a future starting point for linking the common neurodegenerative biomarkers (β-amyloid and tau) and the new proteins probably engaged in counteracting neurodegeneration and synaptic loss. Full article

About one billion people worldwide are affected by neurologic disorders. Among the various neurologic disorders, one of the most common is Alzheimer’s disease (AD). AD is a neurodegenerative disorder that progressively affects cognitive functions, disrupting the daily lives of millions of individuals. Mild cognitive impairment (MCI) is often considered a prodromal stage of Alzheimer’s disease. In this article, we retrieved data from the online available dataset GSE63060, which includes transcriptomic data of 329 blood samples, of which there are 104 cognitively normal controls, 80 MCI patients, and 145 AD patients. We used transcriptomic data related to all three groups to perform an over-representation analysis of the gene ontologies followed by a network analysis. The aim of our study is to pinpoint alterations, detectable through a non-invasive method, in biological processes affected in MCI that persist during AD. Our goal is to uncover transcriptomic changes that could support earlier diagnosis and the development of more effective therapeutic strategies, starting from the early stages of the disease, to slow down or mitigate its progression. Our work provides a consistent picture of the transcriptomic unbalance of many genes strongly involved in ribosomal formation and biogenesis and splicing processes both in patients with MCI and with AD. Full article

Parkinson’s disease (PD), a progressive neurodegenerative disorder, imposes growing clinical and socioeconomic burdens worldwide. Despite landmark discoveries in dopamine biology and α-synuclein pathology, translating mechanistic insights into effective, personalized interventions remains elusive. Recent advances in molecular profiling, neuroimaging, and computational modeling have broadened the understanding of PD as a multifactorial systems disorder rather than a purely dopaminergic condition. However, critical gaps persist in diagnostic precision, biomarker standardization, and the translation of bench side findings into clinically meaningful therapies. This review critically examines the current landscape of PD research, identifying conceptual blind spots and methodological shortfalls across pathophysiology, clinical evaluation, trial design, and translational readiness. By synthesizing evidence from molecular neuroscience, data science, and global health, the review proposes strategic directions to recalibrate the research agenda toward precision neurology. Here I highlight the urgent need for interdisciplinary, globally inclusive, and biomarker-driven frameworks to overcome the fragmented progression of PD research. Grounded in the Accelerating Medicines Partnership-Parkinson’s Disease (AMP-PD) and the Parkinson’s Progression Markers Initiative (PPMI), this review maps shared biomarkers, open data, and patient-driven tools to faster personalized treatment. In doing so, it offers actionable insights for researchers, clinicians, and policymakers working at the intersection of biology, technology, and healthcare delivery. As the field pivots from symptomatic relief to disease modification, the road forward must be cohesive, collaborative, and rigorously translational, ensuring that laboratory discoveries systematically progress to clinical application. Full article

Bruton Tyrosine Kinase (BTK) has emerged as a critical mediator in the pathophysiology of neuroinflammation associated with neurodegenerative diseases. BTK, a non-receptor tyrosine kinase predominantly expressed in cells of the hematopoietic lineage, modulates B-cell receptor signaling and innate immune responses, including microglial activation. Recent evidence implicates aberrant BTK signaling in the exacerbation of neuroinflammatory cascades contributing to neuronal damage in disorders such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, ischemic stroke, and Huntington’s disease. Pharmacological inhibition of BTK has shown promise in attenuating microglial-mediated neurotoxicity, reducing pro-inflammatory cytokine release, and promoting neuroprotection in preclinical models. BTK inhibitors, originally developed for hematological malignancies, demonstrate favorable blood–brain barrier penetration and immunomodulatory effects relevant to central nervous system pathology. This therapeutic approach may counteract detrimental neuroimmune interactions without broadly suppressing systemic immunity, thus preserving host defense. Ongoing clinical trials are evaluating the safety and efficacy of BTK inhibitors in patients with neurodegenerative conditions, with preliminary results indicating potential benefits in slowing disease progression and improving neurological outcomes. This review consolidates current knowledge on BTK signaling in neurodegeneration and highlights the rationale for BTK inhibition as a novel, targeted therapeutic strategy to modulate neuroinflammation and mitigate neurodegenerative processes. Full article

Prosaposin (PSAP), a multifunctional protein, plays a central role in various biological processes and diseases. It is the precursor of lysosomal activating protein, which is important for lipid metabolism and glucose metabolism. PSAP is implicated in cell signaling, neuroprotection, immunomodulation, and tumorigenesis. In neurological disorders, PSAP acts as a neurotrophic factor influencing nerve cell survival and synapse growth, and its dysfunction is associated with a variety of diseases. It modulates immune responses and macrophage functions, affecting inflammation and immune cell activities. The role of PSAP in cancers is complex, because it promotes or inhibits tumor growth depending on the context and it serves as a potential biomarker for various malignancies. This review examines current research on the functional and pathological roles of PSAP, emphasizing the importance of PSAP in Gaucher disease, neurodegenerative diseases, cardiovascular diseases, and cancer. In order to develop targeted therapies for various diseases, it is essential to understand the mechanisms of action of PSAP in different biological processes. Full article

Inorganic polyphosphate (polyP) is an evolutionarily conserved polymer that has recently gained relevance in neuronal physiology and pathophysiology. Although its roles, such as mitochondrial bioenergetics, calcium homeostasis, and the oxidative stress response, for example, are increasingly recognized, its specific implications in neurological disorders remain underexplored. This review focuses on synthesizing the current knowledge of polyP in the context of central nervous system (CNS) diseases, highlighting how its involvement in key mitochondrial processes may influence neuronal survival and function. In particular, we examine recent evidence linking polyP to mechanisms relevant to neurodegeneration, such as the modulation of the mitochondrial permeability transition pore (mPTP), regulation of amyloid fibril formation, and oxidative stress responses. In addition, we analyze the emerging roles of polyP in inflammation and related cell signaling in CNS disorders. By organizing the existing data around the potential pathological and protective roles of polyP in the CNS, this review identifies it as a candidate of interest in the context of neurodegenerative disease mechanisms. We aim to clarify its relevance and stimulate future research on its molecular mechanisms and translational potential. Full article

On a worldwide scale, neurodegenerative diseases, including multiple sclerosis, Parkinson’s, and Alzheimer’s, face considerable healthcare challenges demanding the development of novel approaches to early detection and efficient treatment. With its ability to provide real-time patient monitoring, customized medical care, and advanced predictive analytics, artificial intelligence (AI) is fundamentally transforming the way healthcare is provided. Through the integration of wearable physiological sensors, motion sensors, and neurological assessment tools, the NeuroPredict platform harnesses AI and smart sensor technologies to enhance the management of specific neurodegenerative diseases. Machine learning algorithms process these data flows to find patterns that point out disease evolution. This paper covers the design and architecture of the NeuroPredict platform, stressing the ethical and regulatory requirements that guide its development. Initial development of AI algorithms for disease monitoring, technical achievements, and constant enhancements driven by early user feedback are addressed in the discussion section. To ascertain the platform’s trustworthiness and data security, it also points towards risk analysis and mitigation approaches. The NeuroPredict platform’s capability for achieving AI-driven smart healthcare solutions is highlighted, even though it is currently in the development stage. Subsequent research is expected to focus on boosting data integration, expanding AI models, and providing regulatory compliance for clinical application. The current results are based on incremental laboratory tests using simulated user roles, with no clinical patient data involved so far. This study reports an experimental technology evaluation of modular components of the NeuroPredict platform, integrating multimodal sensors and machine learning pipelines in a laboratory-based setting, with future co-design and clinical validation foreseen for a later project phase. Full article

Gait analysis is a valuable tool for aiding in the diagnosis of neurological diseases, providing objective measurements of human gait kinematics and kinetics. These data enable the quantitative estimation of movement abnormalities, which helps to diagnose disorders and assess their severity. In this regard, machine learning techniques and explainability methods offer an opportunity to enhance anomaly detection in gait measurements and support a more objective assessment of neurodegenerative disease, providing insights into the most relevant gait parameters used for disease identification. This study employs several classifiers and explainability methods to analyze gait data from a public dataset composed of patients affected by degenerative neurological diseases and healthy controls. The work investigates the relevance of spatial, temporal, and kinematic gait parameters in distinguishing such diseases. The findings are consistent among the classifiers employed and in agreement with known clinical findings about the major gait impairments for each disease. This work promotes the use of data-driven assessments in clinical settings, helping reduce subjectivity in gait evaluation and enabling broader deployment in healthcare environments. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that impairs motor function, including the fine motor control required for handwriting. Traditional diagnostic methods often lack sensitivity and objectivity in the early stages, limiting opportunities for timely intervention. There is a growing need for non-invasive, accessible tools capable of capturing subtle motor changes that precede overt clinical symptoms. Among early PD manifestations, handwriting impairments such as micrographia have shown potential as digital biomarkers. However, conventional handwriting analysis remains subjective and limited in scope. Recent advances in artificial intelligence (AI) and machine learning (ML) enable automated analysis of handwriting dynamics, such as pressure, velocity, and fluency, collected via digital tablets and smartpens. These tools support the detection of early-stage PD, monitoring of disease progression, and assessment of therapeutic response. This paper highlights how AI-enhanced handwriting analysis provides a scalable, non-invasive method to support diagnosis, enable remote symptom tracking, and personalize treatment strategies in PD. This approach integrates clinical neurology with computer science and rehabilitation, offering practical applications in telemedicine, digital health, and personalized medicine. By capturing dynamic features often missed by traditional assessments, AI-based handwriting analysis contributes to a paradigm shift in the early detection and long-term management of PD, with broad relevance across neurology, digital diagnostics, and public health innovation. Full article

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor symptoms, including cognitive decline, mood disturbances, and sensory deficits. While dopaminergic treatments remain the gold standard, they present long-term side effects and limited impact on non-motor symptoms. Transcranial Pulse Stimulation (TPS) has emerged as a promising adjunct therapy in neurological and psychiatric conditions, but its effects in PD remain underexplored. This open-label, single-arm trial protocol involves 14 PD participants and outlines a personalized 12-session treatment approach combined with a homogeneously distributed TPS intervention among patients with PD. The approach addresses the subject’s most prominent symptoms, as identified through validated clinical assessments, encompassing domains related to both motor and non-motor symptoms. Over 2.5 months, besides the intervention sessions, the 14 participants will undergo an MRI brain scan, a baseline assessment, a post-treatment assessment, and a 1-month follow-up assessment. The study aims to determine whether personalized TPS is a feasible and safe intervention and whether it improves PD symptoms across multiple functional domains. This study represents the first structured attempt to evaluate a multimodal, personalized TPS intervention in patients with PD. It addresses gaps in current treatment approaches and may support the development of future strategies for integrated, symptom-targeted neuromodulation. Full article

The discovery of effective therapeutics against Alzheimer’s disease (AD) and other neurological disorders remains a significant challenge. Artificial intelligence (AI) tools are of considerable interest in modern drug discovery processes and, by exploiting machine learning (ML) algorithms and deep learning (DL) tools, as well as data analytics, can expedite the identification of new drug targets and potential lead molecules. The current study was aimed at assessing the role of AI-based tools in the discovery of new drug targets against AD and other related neurodegenerative diseases and their efficacy in the discovery of new drugs against these diseases. AD represents a multifactorial neurological disease with limited therapeutics available for management and limited efficacy. The discovery of more effective medications is limited by the complicated pathophysiology of the disease, involving amyloid beta (Aβ), neurofibrillary tangles (NFTs), oxidative stress, and inflammation-induced damage in the brain. The integration of AI tools into the traditional drug discovery process against AD can help to find more effective, safe, highly potent compounds, identify new targets of the disease, and help in the optimization of lead molecules. A detailed literature review was performed to gather evidence regarding the most recent AI tools for drug discovery against AD, Parkinson’s disease (PD), multiple sclerosis (MLS), and epilepsy, focusing on biological markers, early diagnoses, and drug discovery using various databases like PubMed, Web of Science, Google Scholar, Scopus, and ScienceDirect to collect relevant literature. We evaluated the role of AI in analyzing multifaceted biological data and the properties of potential drug candidates and in streamlining the design of clinical trials. By exploring the intersection of AI and neuroscience, this review focused on providing insights into the future of AD treatment and the potential of AI to revolutionize the field of drug discovery. Our findings conclude that AI-based tools are not only cost-effective, but the success rate is extremely high compared to traditional drug discovery methods in identifying new therapeutic targets and in the screening of the majority of molecules for clinical trial purposes. Full article

A properly functioning capillary microcirculation is essential for sufficient oxygen and nutrient delivery to the central nervous system. The physical mechanisms governing the transport of red blood cells (RBCs) inside the narrow and irregularly shaped capillary lumen are complex, but understanding them is essential for identifying the root causes of neurological disorders like cerebral ischemia, Alzheimer’s disease, and other neurodegenerative conditions such as concussion and cognitive dysfunction in systemic inflammatory conditions. In this work, we conducted numerical simulations of three-dimensional capillary models, which were acquired ex vivo from a mouse retina, to characterize RBC transport. We show how the spatiotemporal velocity of the RBCs deviates in realistic capillaries and equivalent cylindrical tubes, as well as how this profile is affected by hematocrit and red cell distribution width (RDW). Our results show a previously unprecedented level of RBC velocity fluctuations in capillaries that depends on the geometric features of different confinement regions and a capillary circularity index $\left(I_{cc}\right)$ that represents luminal irregularity. This velocity fluctuation is aggravated by high hematocrit conditions, without any further effect on RDW. These results can provide a better understanding of the underlying mechanisms of pathologically high capillary transit time heterogeneity that results in microcirculatory dysfunction. Full article

Introduction: There are no validated clinical diagnostic criteria for chronic traumatic encephalopathy or traumatic encephalopathy syndrome (TES). To understand the historical clinical condition, its applicability to modern day athletes, and the pathogenesis of clinical problems, we examined the literature describing boxers from the 20th century, with specific attention paid to neurological findings and characteristics of clinical disease progression. Methods: Data were extracted for 243 boxers included in 45 articles published between 1928 and 1999, including cases from articles originally published in German. The presence or absence of 22 neurological signs and features were extracted. Results: The most common neurological problems were slurring dysarthria (49%), gait disturbances (44%), and memory loss (36%), with several other problems that were less frequent, including hyperreflexia (25%), ataxia (22%), increased tone (19%), and extensor Babinski sign (16%). Frank dementia appeared in some cases (17%). There were significantly fewer neurological deficits reported in boxers who fought in the latter part of the 20th century compared to boxers who fought earlier in the century. For more than half of the cases, there were no comments about whether the neurological problems were progressive (145, 60%). A progressive condition was described in 71 cases (29%) and a stationary or improving condition was described in 27 cases (11%). Canonical neurodegenerative disease-like progression was described in 15 cases (6%). Discussion: Neurological problems associated with boxing-related neurotrauma during the 20th century are the foundation for present-day TES. However, the clinical signs and features in the 20th century differ in most ways from the modern criteria for TES. Full article