Search Results (2,423)

Microtubules play a key role in cell division and cell migration. Thus, microtubule-targeting agents (MTAs) are pivotal in cancer therapy due to their ability to disrupt cell division microtubule dynamics. Traditionally divided into stabilizers and destabilizers, MTAs are increasingly being repurposed for central nervous system (CNS) applications, including brain malignancies such as gliomas and neurodegenerative diseases like Alzheimer’s and Parkinson’s. Microtubule-stabilizing agents, such as taxanes and epothilones, promote microtubule assembly and have shown efficacy in both tumour suppression and neuronal repair, though their CNS use is hindered by blood–brain barrier (BBB) permeability and neurotoxicity. Destabilizing agents, including colchicine-site and vinca domain binders, offer potent anticancer effects but pose greater risks for neuronal toxicity. This review highlights the mapping of nine distinct tubulin binding pockets—including classical (taxane, vinca, colchicine) and emerging (tumabulin, pironetin) sites—that offer new pharmacological entry points. We summarize the recent advances in structural biology and drug design, enabling MTAs to move beyond anti-mitotic roles, unlocking applications in both cancer and neurodegeneration for next-generation MTAs with enhanced specificity and BBB penetration. We further discuss the therapeutic potential of combination strategies, including MTAs with radiation, histone deacetylase (HDAC) inhibitors, or antibody–drug conjugates, that show synergistic effects in glioblastoma models. Furthermore, innovative delivery systems like nanoparticles and liposomes are enhancing CNS drug delivery. Overall, MTAs continue to evolve as multifunctional tools with expanding applications across oncology and neurology, with future therapies focusing on optimizing efficacy, reducing toxicity, and overcoming therapeutic resistance in brain-related diseases. Full article

Multiple sclerosis (MS) is a chronic, immune-mediated disorder of the central nervous system (CNS) characterized by inflammation, demyelination, axonal degeneration, and gliosis. Its pathophysiology involves a complex interplay of genetic susceptibility, environmental triggers, and immune dysregulation, ultimately leading to progressive neurodegeneration and functional decline. Although significant advances have been made in disease-modifying therapies (DMTs), many patients continue to experience disease progression and unmet therapeutic needs. Drug repurposing—the identification of new indications for existing drugs—has emerged as a promising strategy in MS research, offering a cost-effective and time-efficient alternative to traditional drug development. Several compounds originally developed for other diseases, including immunomodulatory, anti-inflammatory, and neuroprotective agents, are currently under investigation for their efficacy in MS. Repurposed agents, such as selective sphingosine-1-phosphate (S1P) receptor modulators, kinase inhibitors, and metabolic regulators, have demonstrated potential in promoting neuroprotection, modulating immune responses, and supporting remyelination in both preclinical and clinical settings. Simultaneously, artificial intelligence (AI) is transforming drug discovery and precision medicine in MS. Machine learning and deep learning models are being employed to analyze high-dimensional biomedical data, predict drug–target interactions, streamline drug repurposing workflows, and enhance therapeutic candidate selection. By integrating multiomics and neuroimaging data, AI tools facilitate the identification of novel targets and support patient stratification for individualized treatment. This review highlights recent advances in drug repurposing and discovery for MS, with a particular emphasis on the emerging role of AI in accelerating therapeutic innovation and optimizing treatment strategies. Full article

Accurate detection of Alzheimer’s disease (AD) is critical yet challenging for early medical intervention. Deep learning methods, especially convolutional neural networks (CNNs), have shown promising potential for improving diagnostic accuracy using magnetic resonance imaging (MRI). This study aims to identify the most informative combination of MRI slice orientation and anatomical location for AD classification. We propose an automated framework that first selects the most relevant slices using a feature entropy-based method applied to activation maps from a pretrained CNN model. For classification, we employ a lightweight CNN architecture based on depthwise separable convolutions to efficiently analyze the selected 2D MRI slices extracted from preprocessed 3D brain scans. To further interpret model behavior, an attention mechanism is integrated to analyze which feature level contributes the most to the classification process. The model is evaluated on three binary tasks: AD vs. mild cognitive impairment (MCI), AD vs. cognitively normal (CN), and MCI vs. CN. The experimental results show the highest accuracy (97.4%) in distinguishing AD from CN when utilizing the selected slices from the ninth axial segment, followed by the tenth segment of coronal and sagittal orientations. These findings demonstrate the significance of slice location and orientation in MRI-based AD diagnosis and highlight the potential of lightweight CNNs for clinical use. Full article

S100 proteins, a family of Ca²⁺-binding proteins, play numerous roles in cellular processes such as proliferation, differentiation, and apoptosis. Recent evidence has highlighted their critical involvement in neuroinflammation, a pathological hallmark of various neurodegenerative disorders including Alzheimer’s disease, multiple sclerosis, and Parkinson’s disease. Among these proteins, S100B and S100A8/A9 are particularly implicated in modulating inflammatory responses in the CNS. Acting as DAMPs, they interact with pattern recognition receptors like RAGE and TLRs, triggering pro-inflammatory signaling cascades and glial activation. While low concentrations of S100 proteins may support neuroprotective functions, increased levels are often associated with exacerbated inflammation and neuronal damage. This review explores the dualistic nature of S100 proteins in neuroinflammatory processes, their molecular interactions, and their potential as biomarkers and therapeutic targets in neurodegenerative disease management. Full article

Background: The long-term clinical and laboratory results of a 33-year follow-up of a Greek family with abetalipoproteinemia (ABL) are described. Case Report: The patients (two brothers and their sister, aged 57, 49, and 62 years, respectively) are still alive, being under close surveillance. In two of the three patients, diarrhea appeared in early infancy, while in the third, it appeared during adolescence. CNS symptomatology worsened after the second decade of life. At the same time, night blindness appeared in the advanced stages of the disease, resulting in almost complete loss of vision in one of the male patients and severe impairment in the other. The diagnosis was based on the clinical picture, ophthalmological findings, serum lipid estimations, and presence of peripheral acanthocytosis. All patients exhibited typical serum lipidemic profile, ophthalmological findings, and acanthocytes in the peripheral blood. During the follow-up period, strict dietary modifications were applied, including the substitution of fat with medium-chain triglycerides (MCT oil). After 33 years since the initial diagnosis, all patients are alive without any sign of liver dysfunction despite continuous use of MCT oil. However, symptoms from the central nervous system and vision impairment worsened. Conclusion: The course of these patients suggests that the application of a modified diet, including MCT oil, along with close surveillance, could prolong the survival of patients without significant side effects from the liver. Full article

Powdery mildew (PM), caused by Sphaerotheca phaseoli, severely threatens mungbean (Vigna radiata) productivity and quality, yet the molecular basis of resistance remains poorly defined. This study employed transcriptome profiling to compare defense responses in a resistant genotype, SUPER5, and a susceptible variety, CN84-1, following pathogen infection. A total of 1755 differentially expressed genes (DEGs) were identified, with SUPER5 exhibiting strong upregulation of genes encoding pathogenesis-related (PR) proteins, disease resistance proteins, and key transcription factors. Notably, genes involved in phenylpropanoid and flavonoid biosynthesis, pathways associated with antimicrobial compound and lignin production, were markedly induced in SUPER5. In contrast, CN84-1 showed limited activation of defense genes and downregulation of essential regulators such as MYB14. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighted the involvement of plant–pathogen interaction pathways, MAPK signaling, and reactive oxygen species (ROS) detoxification in the resistant response. Quantitative real-time PCR validated 11 candidate genes, including PAL3, PR2, GSO1, MLO12, and P21, which function in pathogen recognition, signaling, the biosynthesis of antimicrobial metabolites, the production of defense proteins, defense regulation, and the reinforcement of the cell wall. Co-expression network analysis revealed three major gene modules linked to flavonoid metabolism, chitinase activity, and responses to both abiotic and biotic stresses. These findings offer valuable molecular insights for breeding PM-resistant mungbean varieties. Full article

Chromosomal microarray analysis (CMA) was performed for 40 patients with B-ALL undergoing treatment according to the ALL-2016 protocol to investigate the copy number alterations (CNAs) and copy neutral loss of heterozygosity (cnLOH) associated with minimal residual disease (MRD)-positive remission. Aberrations involving over 20,000 genes were identified, and a random forest approach was applied to isolate a subset of genes whose CNAs and cnLOH are significantly associated with poor therapeutic response. We have assembled the triple matched healthy population data and used that data as a reference, but not as a matched control. We identified a recurrent cluster of cnLOH in the 19q13.2–19q13.31 region, significantly enriched in MRD-positive patients (70% vs. 47% in the reference group vs. 16% in MRD-negative patients). This region includes the pregnancy-specific glycoprotein (PSG) gene family and the oncogene ERF, suggesting a potential role in leukemic persistence and treatment resistance. Additionally, we observed significant deletions involving 7p22.3 and 16q13, often as part of large-scale losses affecting almost the entire chromosomes 7 and 16, indicative of global chromosomal instability. These findings highlight specific genomic regions potentially involved in therapy resistance and may contribute to improved risk stratification in B-ALL. Our findings emphasize the value of high-resolution CMA in diagnostics and risk stratification and suggest that PSG genes and other candidate genes could serve as biomarkers for predicting treatment outcomes. Full article

Central nervous system (CNS) disorders present significant therapeutic challenges due to the limited regenerative capacity of neural tissues, resulting in long-term disability for many patients. Consequently, the development of novel therapeutic strategies is urgently warranted. Stem cell therapies show considerable potential for mitigating brain damage and restoring neural connectivity, owing to their multifaceted properties, including anti-apoptotic, anti-inflammatory, neurogenic, and vasculogenic effects. Recent research has also identified exosomes—small vesicles enclosed by a lipid bilayer, secreted by stem cells—as a key mechanism underlying the therapeutic effects of stem cell therapies, and given their enhanced stability and superior blood–brain barrier permeability compared to the stem cells themselves, exosomes have emerged as a promising alternative treatment for CNS disorders. A key challenge in the application of both stem cell and exosome-based therapies for CNS diseases is the method of delivery. Currently, several routes are being investigated, including intracerebral, intrathecal, intravenous, intranasal, and intra-arterial administration. Intracerebral injection can deliver a substantial quantity of stem cells directly to the brain, but it carries the potential risk of inducing additional brain injury. Conversely, intravenous transplantation is minimally invasive but results in limited delivery of cells and exosomes to the brain, which may compromise the therapeutic efficacy. With advancements in catheter technology, intra-arterial administration of stem cells and exosomes has garnered increasing attention as a promising delivery strategy. This approach offers the advantage of delivering a significant number of stem cells and exosomes to the brain while minimizing the risk of additional brain damage. However, the investigation into the therapeutic potential of intra-arterial transplantation for CNS injury is still in its early stages. In this comprehensive review, we aim to summarize both basic and clinical research exploring the intra-arterial administration of stem cells and exosomes for the treatment of CNS diseases. Additionally, we will elucidate the underlying therapeutic mechanisms and provide insights into the future potential of this approach. Full article

Neuroinflammation is a key feature of Alzheimer’s disease (AD), and stem cell therapies have emerged as promising candidates due to their immunomodulatory properties. Neuro-Cells (NC), a combination of unmodified mesenchymal stem cells (MSCs) and hematopoietic stem cells (HSCs), have demonstrated therapeutic potential in models of central nervous system (CNS) injury and neurodegeneration. Here, we studied the effects of NC in APPswe/PS1dE9 mice, an AD mouse model. Twelve-month-old APPswe/PS1dE9 mice or their wild-type littermates were injected with NC or vehicle into the cisterna magna. Five to six weeks post-injection, cognitive, locomotor, and emotional behaviors were assessed. The brain was stained for amyloid plaque density using Congo red, and for astrogliosis using DAPI and GFAP staining. Gene expression of immune activation markers (Il-1β, Il-6, Cd45, Tnf) and plasticity markers (Tubβ3, Bace1, Trem2, Stat3) was examined in the prefrontal cortex. IL-6 secretion was measured in cultured human monocytes following endotoxin challenge and NC treatment. Untreated APPswe/PS1dE9 mice displayed impaired learning in the conditioned taste aversion test, reduced object exploration, and anxiety-like behavior, which were improved in the NC-treated mutants. NC treatment normalized the expression of several immune and plasticity markers and reduced the density of GFAP-positive cells in the hippocampus and thalamus. NC treatment decreased amyloid plaque density in the hippocampus and thalamus, targeting plaques of <100 μm². Additionally, NC treatment suppressed IL-6 secretion by human monocytes. Thus, NC treatment alleviated behavioral deficits and reduced amyloid plaque formation in APPswe/PS1dE9 mice, likely via anti-inflammatory mechanisms. The reduction in IL-6 production in human monocytes further supports the potential of NC therapy for the treatment of AD. Full article

Oligodendrocyte precursor cells (OPCs) are a distinct and dynamic glial population that retain proliferative and migratory capacities throughout life. While traditionally recognized for differentiating into oligodendrocytes (OLs) and generating myelin to support rapid nerve conduction, OPCs are now increasingly appreciated for their diverse and non-canonical roles in the central nervous system (CNS), including direct interactions with neurons. A notable feature of OPCs is their expression of diverse ion channels that orchestrate essential cellular functions, including proliferation, migration, and differentiation. Given their widespread distribution across the CNS, OPCs are increasingly recognized as active contributors to the development and progression of various neurological disorders. This review aims to present a detailed summary of the physiological and pathological functions of ion channels in OPCs, emphasizing their contribution to CNS dysfunction. We further highlight recent advances suggesting that ion channels in OPCs may serve as promising therapeutic targets across a broad range of disorders, including, but not limited to, multiple sclerosis (MS), spinal cord injury, amyotrophic lateral sclerosis (ALS), psychiatric disorders, Alzheimer’s disease (AD), and neuropathic pain (NP). Finally, we discuss emerging therapeutic strategies targeting OPC ion channel function, offering insights into potential future directions in the treatment of CNS diseases. Full article

A variety of epigenetic mechanisms—such as DNA methylation, histone alterations, RNA chemical modifications, and regulatory non-coding RNAs—collectively influence gene regulation and cellular processes. Among these, N6-methyladenosine (m⁶A) represents the most widespread internal modification in eukaryotic mRNA, exerting significant influence on RNA metabolic pathways and modulating mRNA function at multiple levels. Studies have shown that m⁶A modification is highly enriched in the brain and regulates central nervous system development and various physiological functions. Recent studies have demonstrated that m⁶A interacts with other epigenetic regulators and triggers epigenetic remodeling, which further affects the development and occurrence of central nervous system diseases. In this review, we provide an up-to-date overview of this emerging research hotspot in biology, with a focus on the interplay between m⁶A and other epigenetic regulators. We highlight their potential roles and regulatory mechanisms in epigenetic reprogramming during central nervous system development and disease, offering insights into potential novel targets and therapeutic strategies for CNS disorders. Full article

The agents of prion diseases have the capacity to efficiently infect susceptible hosts by peripheral routes and to project to clinical target areas of the central nervous system (CNS) via peripheral nerves. Understanding the process of prion spread from the site of infection to the CNS may allow us to identify novel therapeutic strategies. To investigate the mechanism involved in the intranerval transit of 263K scrapie prions in golden Syrian hamsters (GSHs), we transected the sciatic nerve at increasing times post-footpad injection and recorded the incubation periods as estimates of the efficiency of infection. We calculated that intranerval transit of this strain of scrapie is at least 10 times faster than previously reported and may reach 50 mm/day, similar to other neurotropic viruses. By in vivo exposure/injection of sciatic nerves to 263K infectivity, we have also shown that prion entry likely occurs via nerve terminals rather than by direct contact with the sciatic nerve. Application of this experimental approach in other forms of prion diseases could allow verification of the timing of neuroinvasion, a relevant parameter for the definition of therapeutic interventions. Full article

Neurodegenerative diseases (NDDs) such as Alzheimer’s, Parkinson’s, ALS, and Huntington’s pose a growing global challenge due to their complex pathobiology and aging demographics. Once considered as cellular debris, small extracellular vesicles (sEVs) are now recognized as active mediators of intercellular signaling in NDD progression. These nanovesicles (~30–150 nm), capable of crossing the blood–brain barrier, carry pathological proteins, RNAs, and lipids, facilitating the spread of toxic species like Aβ, tau, TDP-43, and α-synuclein. sEVs are increasingly recognized as valuable diagnostic tools, outperforming traditional CSF biomarkers in early detection and disease monitoring. On the therapeutic front, engineered sEVs offer a promising platform for CNS-targeted delivery of siRNAs, CRISPR tools, and neuroprotective agents, demonstrating efficacy in preclinical models. However, translational hurdles persist, including standardization, scalability, and regulatory alignment. Promising solutions are emerging, such as CRISPR-based barcoding, which enables high-resolution tracking of vesicle biodistribution; AI-guided analytics to enhance quality control; and coordinated regulatory efforts by the FDA, EMA, and ISEV aimed at unifying identity and purity criteria under forthcoming Minimal Information for Studies of Extracellular Vesicles (MISEV) guidelines. This review critically examines the mechanistic roles, diagnostic potential, and therapeutic applications of sEVs in NDDs, and outlines key strategies for clinical translation. Full article

The effective suppression of inflammation using disease-modifying therapies is essential in the treatment of multiple sclerosis (MS). Anti-CD20 monoclonal antibodies are commonly used long-term as maintenance therapies, largely due to the lack of reliable biomarkers to guide dosing and evaluate treatment response. However, prolonged use increases the risk of infections and other immune-mediated side effects. The unique ability of brain-derived blood extracellular vesicles (EVs) to cross the blood–brain barrier and reflect the central nervous system (CNS) immune status has sparked interest in their potential as biomarkers. This study aimed to assess whether blood-derived L1CAM⁺ EVs could serve as biomarkers of treatment response to rituximab (RTX) in patients with relapsing-remitting MS (RRMS). Serum samples (n = 25) from the baseline (month 0) and after 6 months were analyzed from the RTX arm of the ongoing randomized clinical trial OVERLORD-MS (comparing anti-CD20 therapies in RRMS patients) and were compared with serum samples from healthy controls (n = 15). Baseline cerebrospinal fluid (CSF) samples from the same study cohort were also included. EVs from both serum and CSF samples were characterized, considering morphology, size, and concentration, using transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). The immunophenotyping of EV surface receptors was performed using flow cytometry with the MACSPlex exosome kit, while label-free quantitative proteomics of EV protein cargo was conducted using a proximity extension assay (PEA). TEM confirmed the presence of EVs with the expected round morphology with a diameter of 50–150 nm. NTA showed significantly higher concentrations of L1CAM⁺ EVs (p < 0.0001) in serum total EVs and EBNA1⁺ EVs (p < 0.01) in serum L1CAM⁺ EVs at baseline (untreated) compared to in healthy controls. After six months of RTX therapy, there was a significant reduction in L1CAM⁺ EV concentration (p < 0.0001) and the downregulation of TNFRSF13B (p = 0.0004; FC = −0.49) in serum total EVs. Additionally, non-significant changes were observed in CD79B and CCL2 levels in serum L1CAM⁺ EVs at baseline compared to in controls and after six months of RTX therapy. In conclusion, L1CAM⁺ EVs in serum showed distinct immunological profiles before and after rituximab treatment, underscoring their potential as dynamic biomarkers for individualized anti-CD20 therapy in MS. Full article

Background: Mild Cognitive Impairment (MCI) represents an intermediate stage between normal cognitive aging and Alzheimer’s Disease (AD). Early and accurate identification of MCI is crucial for implementing interventions that may delay or prevent further cognitive decline. This study aims to develop a machine learning-based model for differentiating between Cognitively Normal (CN) individuals and MCI patients using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: An ensemble classification approach was designed by integrating Extra Trees, Random Forest, and Light Gradient Boosting Machine (LightGBM) algorithms. Feature selection emphasized clinically relevant biomarkers, including Amyloid-β 42, phosphorylated tau, diastolic blood pressure, age, and gender. The dataset was split into training and held-out test sets. A probability thresholding strategy was employed to flag uncertain predictions for potential deferral, enhancing model reliability in borderline cases. Results: The final ensemble model achieved an accuracy of 83.2%, a recall of 80.2%, and a precision of 86.3% on the independent test set. The probability thresholding mechanism flagged 23.3% of cases as uncertain, allowing the system to abstain from low-confidence predictions. This strategy improved clinical interpretability and minimized the risk of misclassification in ambiguous cases. Conclusions: The proposed AI-driven ensemble model demonstrates strong performance in classifying MCI versus CN individuals using multimodal ADNI data. Incorporating a deferral mechanism through uncertainty estimation further enhances the model’s clinical utility. These findings support the integration of machine learning tools into early screening workflows for cognitive impairment. Full article