Search Results (120)

Extracellular vesicles (EVs) are naturally occurring cell-derived vesicles that contain the same nucleic acids, proteins, and lipids as their source cells. These nano-sized systems, which are derived from a wide range of cell types within an organism and are present in all body fluids. EVs play a crucial role both in health and disease, particularly in cancer and neurodegenerative disorders. Due to their particular structure, they can function as natural carriers for therapeutic agents and drugs, akin to synthetic liposomes. EVs exhibit numerous advantages over conventional synthetic nanocarriers and other lipid-based delivery systems, including their favorable biocompatibility, natural blood–brain barrier penetration, and capacity for gene delivery. However, EVs’ complex characterization and standardization, as well as being more expensive than other vesicular systems, are major drawbacks that need to be addressed before drug loading. The present review introduces the classification of EVs and their physiological roles, currently popular methods for isolating and purifying EVs, the main therapeutic approaches of EV-mediated drug delivery, and the functionalization of EVs as carriers. Consequently, it establishes novel pathways for advancing EV-based therapeutic methodologies across diverse medical disciplines. The study concludes with a discussion of the new challenges and future perspectives related to the clinical application of EVs. Full article

p17, the human immunodeficiency virus type 1 (HIV-1) matrix protein traditionally associated with viral assembly, has been recently investigated for its extracellular functions linked to vascular damage. This review examines the molecular and pathogenic signatures by which p17 and its variants (vp17s) contribute to endothelial activation, aberrant angiogenesis, and vascular inflammation, highlighting their relevance even under effective antiretroviral therapy (ART). Specifically, p17 exerts chemokine-like activities by binding to chemokine (C-X-C motif) receptor-1 and 2 (CXCR-1/2) on endothelial cells (ECs). This interaction triggers key signaling cascades, including the protein kinase B (Akt)-dependent extracellular signal-regulated kinase (ERK) pathway and endothelin-1/endothelin receptor B axis, driving EC motility, capillary formation, and lymphangiogenesis. Variants such as S75X demonstrate enhanced lymphangiogenic potency, associating them with tumorigenic processes involved in non-Hodgkin lymphoma (NHL) pathogenesis. Importantly, p17 promotes endothelial von Willebrand factor (vWF) storage and secretion, implicating a pro-coagulant state that may trigger the increased thromboembolic risks observed in HIV-positive patients. Furthermore, p17 crosses the blood–brain barrier (BBB) via CXCR-2-mediated pathways, contributing to neuroinflammation by activating microglia and astrocytes and amplifying monocyte chemoattractant protein-1 (MCP-1) levels, therefore playing a critical role in the development of HIV-associated neurocognitive disorders. Hence, the elaboration of potential therapeutic strategies finalized at inhibiting p17/vp17s’ interaction with their receptors could complement ART by addressing HIV-related neurovascular morbidity. Full article

X-linked adrenoleukodystrophy (X-ALD) is a monogenic progressive neurodegenerative disorder, being simultaneously a systemic metabolic disease and demonstrating severe neurological manifestations with effects to the brain and spinal cord. The objective of the current review is to provide a detailed approach to adeno-associated virus (AAV)-based gene therapy for neurological manifestations of X-ALD. The development of a successful AAV-mediated gene therapy hinges on its ability to deliver ABCD1 cDNA effectively to the relevant organs and cell types, induce therapeutic levels of protein expression, and ultimately, restore normal very-long chain fatty acids (VLCFA) metabolic function. Thus, several key considerations should be addressed when designing AAV-based gene therapy for X-ALD, including the genetic background of the disease and requisite transgene expression levels, the biochemical function of the adrenoleukodystrophy protein (ALDP), the identification of target cells and their role in pathogenesis, the regulation of expression within the genetic construct, the route of administration, the selection of an AAV serotype with high tropism for the central and peripheral nervous systems, and the development of robust in vitro and in vivo models. Full article

Developing robust methods to differentiate pluripotent stem cells (PSCs) into specific neuronal subtypes is crucial for advancing neuroscience research, including disease modelling and regenerative medicine. Research in this area has primarily focused on generating and studying excitatory neurons, often in co-culture with primary astrocytes to support maturation. Due to the shared ectodermal lineage of these cell types, any mesoderm derived cells, such as microglia, are absent using traditional methods of culture. To more accurately model the intricate complexity of the brain and its normal neuronal physiology, it is important to incorporate other critical neural subtypes, such as inhibitory interneurons and various glial cells. This review highlights recent progress in using transcription factor-based in vitro differentiation strategies to generate these diverse neural populations. A major advantage of this approach is the ability to rapidly produce highly specific cell types in a controlled manner, allowing for the precise seeding of cells at defined anatomical and physiological ratios. This controlled methodology enables the creation of more accurate and reproducible in vitro models, including two-dimensional (2D) and three-dimensional (3D) cultures and organoids, thereby moving beyond the limitations of random differentiation from neuronal progenitor cells. Despite these advances, key challenges remain, including reproducibility between pluripotent stem cell lines, off-target transcriptional effects of exogenous factors, and incomplete phenotypic maturation of derived cells. Addressing these constraints is essential for translating transcription factor-based approaches into robust and clinically relevant neural models. Full article

Despite aggressive current therapies against glioblastoma (GB), residual tumor cells may remain at the edge of the surgical cavity after resection. These cells can rapidly proliferate, giving rise to tumor recurrence in more aggressive and drug-resistant forms. As photodynamic therapy (PDT) has advanced, it has emerged as an option to treat this brain tumor. The oncological basis of PDT involves the selective accumulation of a photosensitizer (PS) in the tumor, followed by its activation with electromagnetic radiation to generate reactive oxygen species (ROS), which induce tumor cell death. Given that first- and second-generation PSs present significant limitations, including poor tumor selectivity, suboptimal biodistribution, limited absorption within the therapeutic window, and slow systemic clearance, research has progressed toward the development of third-generation PSs based on nanotechnology to optimize their therapeutic properties. This review addresses the types of tumor cell death induced by PDT, as well as the advancements of PS design, focusing on titanium dioxide (TiO₂) and zinc oxide (ZnO) nanoparticles. These nanomaterials can be designed as carriers, encapsulating or conjugating conventional PSs, or act as PSs themselves, due to their favorable biocompatibility and intrinsic photoreactivity. Additionally, they can be functionalized with targeting ligands to achieve tumor-specific delivery, enhancing therapeutic selectivity while minimizing toxicity to healthy tissue. Overall, these nanotechnology-based PSs represent a versatile and promising therapeutic paradigm that warrants further investigation through basic research, supporting the development and potential clinical translation of a more precise and effective PDT-based intervention for glioblastoma, initially aimed at eliminating intra-surgical post-resection residual tumor cells. Full article

Although the calcium-dependent proteases, calpains, were discovered more than 60 years ago, we still know very little regarding their functions, mostly because very few studies are addressing questions related to specific members of this relatively large family of cysteine proteases. The “classical calpains”, calpain-1 and calpain-2, are ubiquitous and have received more attention because of the special roles they play in the brain. The authors have been studying the properties and functions of these two calpain isoforms in the brain for over 45 years, and this review will focus on what has been learned over this period of time. In particular, we will discuss the numerous studies that have led to the notion that calpain-1 and calpain-2 play opposite functions in the brain on processes ranging from neuronal survival or death, synaptic plasticity, and learning and memory to neurogenesis. Mechanisms underlying these opposite functions are starting to be understood and the findings support the notion that such opposite functions might be a general feature of these two isoforms in any type of cell. This review concludes with a discussion of the potential benefits of selective calpain-2 inhibitors for the treatment of a variety of neurological disorders. Full article

A wide range of strategies have been developed to modulate dysfunctional brain activities. This narrative review provides a comparative analysis of biophysical, genetic, and biological neuromodulation approaches with an emphasis on their known or unknown molecular targets and translational potential. The review incorporates data from both preclinical and clinical studies covering deep brain stimulation, transcranial electrical and magnetic stimulation, focused ultrasound, chemogenetics, optogenetics, magnetogenetics, and toxin-based neuromodulation. Each method was assessed based on specificity, safety, reversibility, and mechanistic clarity. Biophysical methods are widely used in clinical practice but often rely on empirical outcomes due to undefined molecular targets. Genetic tools offer cell-type precision in experimental systems but face translational barriers related to delivery and safety. Biological agents, such as botulinum neurotoxins, provide long-lasting yet reversible inhibition via well-characterized molecular pathways. However, they require stereotaxic injections and remain invasive. To overcome individual limitations and improve targeting, delivery, and efficacy, there is a growing interest in the synthesis of multiple approaches. This review highlights a critical gap in the mechanistic understanding of commonly used methods. Addressing this gap by identifying molecular targets may help to improve therapeutic precision. This concise review could be valuable for researchers looking to enter the evolving field of the neuromodulation of brain function. Full article

Type 10 17β-hydroxysteroid dehydrogenase (17β-HSD10) is the HSD17B10 gene product. It plays an appreciable part in the carcinogenesis and pathogenesis of neurodegeneration, such as Alzheimer’s disease and infantile neurodegeneration. This mitochondrial, homo-tetrameric protein is a central hub in various metabolic pathways, e.g., branched-chain amino acid degradation and neurosteroid metabolism. It can bind to other proteins carrying out diverse physiological functions, e.g., tRNA maturation. It has also previously been proposed to be an Aβ-binding alcohol dehydrogenase (ABAD) or endoplasmic reticulum-associated Aβ-binding protein (ERAB), although those reports are controversial due to data analyses. For example, the reported k_m value of some substrate of ABAD/ERAB was five times higher than its natural solubility in the assay employed to measure k_m. Regarding any reported “one-site competitive inhibition” of ABAD/ERAB by Aβ, the k_i value estimations were likely impacted by non-physiological concentrations of 2-octanol at high concentrations of vehicle DMSO and, therefore, are likely artefactual. Certain data associated with ABAD/ERAB were found not reproducible, and multiple experimental approaches were undertaken under non-physiological conditions. In contrast, 17β-HSD10 studies prompted a conclusion that Aβ inhibited 17β-HSD10 activity, thus harming brain cells, replacing a prior supposition that “ABAD” mediates Aβ neurotoxicity. Furthermore, it is critical to find answers to the question as to why elevated levels of 17β-HSD10, in addition to Aβ and phosphorylated Tau, are present in the brains of AD patients and mouse AD models. Addressing this question will likely prompt better approaches to develop treatments for Alzheimer’s disease. Full article

Due to their clinical heterogeneity, nonspecific symptoms, and the limitations of existing biomarkers and imaging modalities, metabolic brain diseases (MBDs), such as mitochondrial encephalopathies, lysosomal storage disorders, and glucose metabolism syndromes, pose significant diagnostic challenges. This review examines the growing potential of cell-free DNA (cfDNA) derived from cerebrospinal fluid (CSF) epigenetic profiling as a dynamic, cell-type-specific, minimally invasive biomarker approach for MBD diagnosis and monitoring. We review important technological platforms and their use in identifying CNS-specific DNA methylation patterns indicative of neuronal injury, neuroinflammation, and metabolic reprogramming, including cfMeDIP-seq, enzymatic methyl sequencing (EM-seq), and targeted bisulfite sequencing. By synthesizing current findings across disorders such as MELAS, Niemann–Pick disease, Gaucher disease, GLUT1 deficiency syndrome, and diabetes-associated cognitive decline, we highlight the superior diagnostic and prognostic resolution offered by CSF cfDNA methylation signatures relative to conventional CSF markers or neuroimaging. We also address technical limitations, interpretive challenges, and translational barriers to clinical implementation. Ultimately, this review explores CSF cfDNA epigenetic analysis as a liquid biopsy modality. The central objective is to assess whether epigenetic profiling of CSF-derived cfDNA can serve as a reliable and clinically actionable biomarker for improving the diagnosis and longitudinal monitoring of metabolic brain diseases. Full article

Background/Objectives: Current developments in computer-aided systems rely heavily on complex and computationally intensive algorithms. However, even a simple approach can offer a promising solution to reduce the burden on clinicians. Addressing this, we aim to employ unsupervised cluster analysis to identify prognostic subgroups of non-small-cell lung cancer (NSCLC) patients with brain metastasis (BM). Simple-yet-effective algorithms designed to identify similar group characteristics will assist clinicians in categorizing patients effectively. Methods: We retrospectively collected data from 95 NSCLC patients with BM treated at two oncology centers. To identify clinically distinct subgroups, two types of unsupervised clustering methods—two-step clustering (TSC) and hierarchical cluster analysis (HCA)—were applied to the baseline clinical data. Patients were categorized into prognostic classes according to the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA). Survival curves for the clusters and DS-GPA classes were generated using Kaplan–Meier analysis, and the differences were assessed with the log-rank test. The discriminative ability of three categorical variables on survival was compared using the concordance index (C-index). Results: The mean age of the patients was 61.8 ± 0.9 years, and the majority (77.9%) were men. Extracranial metastasis was present in 71.6% of the patients, with most (63.2%) having a single BM. The DS-GPA classification significantly divided the patients into prognostic classes (p < 0.001). Furthermore, statistical significance was observed between clusters created by TSC (p < 0.001) and HCA (p < 0.001). HCA showed the highest discriminatory power (C-index = 0.721), followed by the DS-GPA (C-index = 0.709) and TSC (C-index = 0.650). Conclusions: Our findings demonstrated that the TSC and HCA models were comparable in prognostic performance to the DS-GPA index in NSCLC patients with BM. These results suggest that unsupervised clustering may offer a data-driven perspective on patient stratification, though further validation is needed to clarify its role in prognostic modeling. Full article

Choosing the optimal first-line treatment for patients with advanced non-small cell lung cancer (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangements can be challenging in daily practice. Although clinical trials with next-generation ALK-tyrosine kinase inhibitors (TKIs) have played a key role in evaluating their efficacy and safety, which patients benefit from a specific ALK-TKI may still be questioned. The methodological inconsistencies in these trials, which led to the inclusion of different patient populations, appear to have been inadequately addressed. ALK-rearranged NSCLC is a heterogeneous disease, and co-existing molecular alterations may affect the outcome. The questions explored in these trials appear insufficient to support a personalized approach to the first-line treatment, while defining long-term responders and early progressors would be clinically useful. This narrative review presents several considerations from oncologists’ and pathologists’ perspectives. We propose defining favorable and unfavorable features, such as histology, type of ALK fusion, co-existing molecular alterations, plasma circulating tumor DNA (ctDNA, performance status, and brain metastases, to help identify patients with lower and higher risk of progression. Consequently, the most potent ALK-TKI to date, Lorlatinib, may be considered as the first-line treatment for high-risk patients with unfavorable features, while sequencing of ALK-TKIs may be appropriate for low-risk patients with favorable features. Although ALK signal inhibition is critical in this disease, it may not be sufficient for clinical control due to de novo co-alterations. A more personalized approach to first-line therapy requires consideration of risk factors for each patient. Full article

Obesity is characterized by excessive fat accumulation that triggers chronic low-grade inflammation and systemic immune dysregulation, significantly increasing the risk of metabolic disorders including insulin resistance, type 2 diabetes, and cardiovascular disease. This review examines the bidirectional relationship between obesity and immune dysfunction, focusing on how immune cell infiltration in adipose tissue drives inflammatory processes. We highlight the phenotypic shifts in key immune populations—macrophages polarized toward proinflammatory M1 phenotypes, T cell exhaustion occurrs, and alterations appear in B cells, natural killer (NK) cells, and dendritic cells—that collectively contribute to metabolic deterioration. The gut microbiome emerged as a critical mediator in this relationship, influencing both immune responses and metabolic regulation through gut–liver and gut–brain axes. We explore emerging immunomodulatory therapeutic strategies, including anti-inflammatory agents, microbiota interventions, and targeted immune therapies such as innovative nanomedicine approaches. The review also addresses the challenges of immunotherapy in obesity, particularly the paradoxical effects observed in cancer immunotherapy outcomes and the need for personalized treatment approaches. Artificial intelligence is highlighted as a potential tool to enhance patient stratification and treatment optimization in future immunomodulatory interventions. Understanding these immunometabolic interactions provides a foundation for developing more effective therapeutic strategies that could transform obesity management and reduce the burden of obesity-related metabolic diseases. Full article

Gliomas are incurable, heterogeneous brain tumors, with rare forms often constituting diagnostic and treatment challenges. Molecular diagnostics, mainly implemented through the World Health Organization (WHO) 2021 guidelines, have refined the classification, but highlight difficulties in diagnosing rare gliomas remain. This case series analyzes four patients with rare gliomas treated at the University Hospital, Ulm, between 2002 and 2024. Patients were selected based on unique histopathological features and long-term clinical follow-up. Clinical records, imaging, and histological data were reviewed. Molecular diagnostics followed WHO 2021 guidelines. Quality of life was assessed using standardized tools including the EQ-5D-5L, EQ VAS, the Distress Thermometer, and the Montreal Cognitive Assessment (MoCA). In the first case, a 51-year-old male’s diagnosis evolved from pleomorphic xanthoastrocytoma to a high-grade glioma with pleomorphic and pseudopapillary features, later identified as a neuroepithelial tumor with a PATZ1 fusion over 12 years. Despite multiple recurrences, extensive surgical interventions led to excellent outcomes. The second case involved a young female with long-term survival of astroblastoma, demonstrating significant improvements in both longevity and quality of life through personalized care. The third case involved a patient with oligodendroglioma, later transforming into glioblastoma, emphasizing the importance of continuous diagnostic reevaluation and adaptive treatment strategies, contributing to prolonged survival and quality of life improvements. Remarkably, the patient has achieved over 20 years of survival, including 10 years of being both therapy- and progression-free. The fourth case presents a young woman with neurofibromatosis type 1, initially misdiagnosed with glioblastoma based on histopathological findings. Subsequent molecular diagnostics revealed a subependymal giant cell astrocytoma-like astrocytoma, highlighting the critical role of early advanced diagnostic techniques. These cases underscore the importance of precise molecular diagnostics, individualized treatments, and ongoing diagnostic reevaluation to optimize outcomes. They also address the psychological impact of evolving diagnoses, stressing the need for comprehensive patient support. Even in complex cases, extensive surgical interventions can yield favorable results, reinforcing the value of adaptive, multidisciplinary strategies based on evolving tumor characteristics. Full article

Arboviruses, transmitted by blood-sucking arthropods, are responsible for significant human and animal diseases, including fever, hemorrhagic fever, and encephalitis, posing a serious threat to global public health. Nevertheless, research on the mechanisms of arbovirus infection and the development of therapeutic interventions has been impeded. This delay is primarily due to the limitations inherent in current in vitro research models, including cell cultures and animal models. The simplicity of cell types and interspecies differences present significant obstacles to advancing our understanding of arbovirus infection mechanisms and the development of effective drugs. Human brain organoids, derived from human pluripotent stem cells or human embryonic stem cells and cultured in three-dimensional systems, more accurately replicate the extensive neuronal cellular diversity and key characteristics of human neurodevelopment. These organoids serve as an ideal model for investigating the intricate interactions between viruses and human hosts, and providing a novel platform for the development of antiviral drugs. In this review, we summarize how brain organoid models complement classical approaches to accelerate research into the infection mechanisms of arboviruses, with a particular focus on the types of neural cells, key factors, and cellular signaling pathways involved in the arbovirus infection of brain organoids that have been reported. Furthermore, we examine the development of brain organoids, address their current limitations, and propose future directions to enhance the application of brain organoids in the study of arboviral infectious diseases. Full article

Glioblastoma (GBM, isocitrate dehydrogenase wild-type) is the most common primary malignant brain tumor in adults and is associated with a severely low survival rate. Treatments offer mere palliation and are ineffective, due, in part, to a lack of understanding of the intricate mechanisms underlying the disease, including the contribution of the tumor microenvironment (TME). Current GBM models continue to face challenges as they lack the critical components and properties required. To address this limitation, we developed innovative and practical three-dimensional (3D) GBM models with structural and mechanical biomimicry and tunability. These models allowed for more accurate emulation of the extracellular matrix (ECM) and vasculature characteristics of the native GBM TME. Additionally, 3D bioprinting was utilized to integrate these complexities, employing a hydrogel composite to mimic the native environment that is known to contribute to tumor cell growth. First, we examined the changes in physical properties that resulted from adjoining hydrogels at diverse concentrations using Fourier-Transform Infrared Spectroscopy (FTIR), compression testing, scanning electron microscopy (SEM), rheological analysis, and degradation analysis. Subsequently, we refined and optimized the embedded bioprinting processes. The resulting 3D GBM models were structurally reliable and reproducible, featuring integrated inner channels and possessing tunable properties to emulate the characteristics of the GBM ECM. Biocompatibility testing was performed via live/dead and AlamarBlue analyses using GBM cells (both commercial cell lines and patient-derived cell lines) encapsulated in the constructs, along with immunohistochemistry staining to understand how ECM properties altered the functions of GBM cells. The observed behavior of GBM cells indicated greater functionality in softer matrices, while the incorporation of hyaluronic acid (HA) into the gelatin methacryloyl (gelMA) matrix enhanced its biomimicry of the native GBM TME. The findings underscore the critical role of TME components, particularly ECM properties, in influencing GBM survival, proliferation, and molecular expression, laying the groundwork for further mechanistic studies. Additionally, the outcomes validate the potential of leveraging 3D bioprinting for GBM modeling, providing a fully controllable environment to explore specific pathways and therapeutic targets that are challenging to study in conventional model systems. Full article