Glioblastomas are highly lethal cancers defined by resistance to conventional therapies and rapid recurrence. While new brain tumor cell-specific drugs are continuously becoming available, efficient drug delivery to brain tumors remains a limiting factor. We developed a multicomponent nanoparticle, consisting of an iron oxide core and a mesoporous silica shell that can effectively deliver drugs across the blood-brain barrier into glioma cells. When exposed to alternating low-power radiofrequency (RF) fields, the nanoparticle's mechanical tumbling releases the entrapped drug molecules from the pores of the silica shell. After directing the nanoparticle to target the near-perivascular regions and altered endothelium of the brain tumor via fibronectin-targeting ligands, rapid drug release from the nanoparticles is triggered by RF facilitating wide distribution of drug delivery across the blood-brain tumor interface.
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http://dx.doi.org/10.1039/c9nr02876e | DOI Listing |
Mol Biol Rep
January 2025
Institute of Pathogenic Biology, Guilin Medical University, Guilin, 541199, China.
Cyclin-dependent kinase 5 (CDK5), a unique member of the CDK family, is a proline-directed serine/threonine protein kinase with critical roles in various physiological and pathological processes. Widely expressed in the central nervous system, CDK5 is strongly implicated in neurological diseases. Beyond its neurological roles, CDK5 is involved in metabolic disorders, psychiatric conditions, and tumor progression, contributing to processes such as proliferation, migration, immune evasion, genomic stability, and angiogenesis.
View Article and Find Full Text PDFElectromagn Biol Med
January 2025
Department of Computer Applications, Kalasalingam Academy of Research and Education - Deemed to be University, Krishnankoil, India.
Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues.
View Article and Find Full Text PDFElife
January 2025
Department of Neurology, Weill Institute for Neuroscience, University of California San Francisco, San Francisco, United States.
Mutations in Sonic Hedgehog (SHH) signaling pathway genes, for example, (SUFU), drive granule neuron precursors (GNP) to form medulloblastomas (MB). However, how different molecular lesions in the Shh pathway drive transformation is frequently unclear, and mutations in the cerebellum seem distinct. In this study, we show that fibroblast growth factor 5 (FGF5) signaling is integral for many infantile MB cases and that expression is uniquely upregulated in infantile MB tumors.
View Article and Find Full Text PDFPediatr Blood Cancer
January 2025
The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Introduction: Medulloblastoma (MB) is the most common malignant childhood brain tumor. Molecular subgrouping of MB has become a major determinant of management in high-income countries. Subgrouping is still very limited in low- and middle-income countries (LMICs), and its relevance to management with the incorporation of risk stratification (low risk, standard risk, high risk, and very high risk) has yet to be evaluated in this setting.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective: To develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).
Materials And Methods: A total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] = 194, brain metastases of breast cancer [BMBC] = 108, brain metastases of gastrointestinal tumor [BMGiT] = 48) and test sets (BMLC = 50, BMBC = 27, BMGiT = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE).
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