Subependymal giant cell astrocytomas (SEGAs) are benign, slow-growing, noninvasive tumors frequently associated with the tuberous sclerosis complex (TSC). The tumor\'s location and the patient\'s age should be considered carefully before diagnosis. Considering SEGA as a differential diagnosis, even in adult patients without TSC, is essential. In the present case, a 22-year-old male presented with a progressive headache, dizziness, and blurring of vision. Radiological investigations confirmed the site of the tumor, and a positive expression of thyroid transcription factor 1 in the ganglion cell component, along with the absence of germline mutation in TSC1 and TSC2, led to the final diagnosis of SEGA without TSC.

Glioblastoma (GBM) is a severe form of brain tumor that has a high fatality rate. It grows aggressively and most of the time results in resistance to traditional treatments like chemo- and radiotherapy and surgery. Biodiversity, beyond representing a big resource for human well-being, provides several natural compounds that have shown great potential as anticancer drugs. Many of them are being extensively researched and significantly slow GBM progression by reducing the proliferation rate, migration, and inflammation and also by modulating oxidative stress. Here, the use of some natural compounds, such as Allium lusitanicum, Succisa pratensis, and Dianthus superbus, was explored to tackle GBM; they showed their impact on cell number reduction, which was partially given by cell cycle quiescence. Furthermore, a reduced cell migration ability was reported, accomplished by morphological cytoskeleton changes, which even highlighted a mesenchymal-epithelial transition. Furthermore, metabolic studies showed an induced cell oxidative stress modulation and a massive metabolic rearrangement. Therefore, a new therapeutic option was suggested to overcome the limitations of conventional treatments and thereby improve patient outcomes.

UNASSIGNED: Patients undergoing surgical resection of brain tumors frequently exhibit a spectrum of hemodynamic fluctuations necessitating careful fluid management. This study aimed to evaluate the feasibility of dynamic predictors of fluid responsiveness, such as delta down (DD), aortic velocity time integral variability (VTIAoV), and superior vena cava collapsibility index (SVCCI), in patients undergoing neurosurgery for brain tumors.
UNASSIGNED: In this prospective study, 30 patients scheduled to undergo elective neurosurgery for brain tumor resection were enrolled. Baseline measurements of vitals, anesthetic parameters, and study variables were recorded post-induction. Subsequently, patients received a fluid bolus of 10 mL/kg of colloid over 20 min, and measurements were repeated post-loading. Data were presented as mean ± standard deviation. The normally distributed continuous variables were compared using Student\'s t-test, with P < 0.05 considered statistically significant. The predictive capability of variables for fluid responsiveness was assessed using Pearson\'s coefficient analysis (r).
UNASSIGNED: Of the 30 patients, 22 were identified as volume responders (R), while eight were non-responders (NR). DD >5 mmHg effectively distinguished between R and NR (P < 0.001), with a good predictive ability (r = 0.759). SVCCI >38% differentiated R from NR (P < 0.001), with excellent predictability (r = 0.994). Similarly, VTIAoV >20% was also a good predictor (P < 0.05; r = 0.746).
UNASSIGNED: Our study revealed that most patients undergoing surgical resection of brain tumors exhibited fluid responsiveness. Among the variables assessed, SVCCI >38% emerged as an excellent predictor, followed by VTIAoV >20% and DD >5 mm Hg, for evaluating fluid status in this population.

The precise assessment of vascular heterogeneity in brain tumors is vital for diagnosing, grading, predicting progression, and guiding treatment decisions. However, currently, there is a significant shortage of high-resolution imaging approaches. Herein, we propose a contrast-enhanced susceptibility-weighted imaging (CE-SWI) utilizing the minimalist dextran-modified Fe3O4 nanoparticles (Dextran@Fe3O4 NPs) for ultrahigh-resolution mapping of vasculature in brain tumors. The Dextran@Fe3O4 NPs are prepared via a facile coprecipitation method under room temperature, and exhibit small hydrodynamic size (28 nm), good solubility, excellent biocompatibility, and high transverse relaxivity (r2*, 159.7 mM-1 s-1) under 9.4 T magnetic field. The Dextran@Fe3O4 NPs-enhanced SWI can increase the contrast-to-noise ratio (CNR) of cerebral vessels to 2.5 times that before injection and achieves ultrahigh-spatial-resolution visualization of microvessels as small as 0.1 mm in diameter. This advanced imaging capability not only allows for the detailed mapping of both enlarged peritumoral drainage vessels and the intratumoral microvessels, but also facilitates the sensitive imaging detection of vascular permeability deterioration in a C6 cells-bearing rat glioblastoma model. Our proposed Dextran@Fe3O4 NPs-enhanced SWI provides a powerful imaging technique with great clinical translation potential for the precise theranostics of brain tumors.

The blood-brain barrier (BBB) is a selectively semi-permeable layer, crucial in shielding the brain from external pathogens and toxic substances while maintaining ionic homeostasis and sufficient nutrient supply. However, it poses a significant challenge for drugs to penetrate the BBB in order to effectively target brain tumors. Magnetic resonance-guided laser interstitial thermal therapy (MRg-LITT) is a minimally invasive technique that employs thermal energy to cauterize intracranial lesions with the potential to temporarily disrupt the BBB. This further opens a possible therapeutic window to enhance patient outcomes. Here, we review the impact of MRg-LITT on BBB and blood tumor barrier (BTB) and the duration of the BBB disruption. Studies have shown that MRg-LITT is effective due to its minimally invasive nature, precise tumor targeting, and low complication rates. Although the disruption duration varies across studies, the average peak disruption is within the initial two weeks post-ablation period and subsequently exhibits a gradual decline. However, further research involving larger groups with extended follow-up periods is required to determine disruption duration more accurately. In addition, evaluating toxicity and glymphatic system disruption is crucial to circumvent potential risks associated with this procedure.

BACKGROUND: Radionecrosis is a common complication in radiation oncology, while mechanisms and risk factors have yet to be fully explored. We therefore conducted a systematic review to understand the pathogenesis and identify factors that significantly affect the development.
METHODS: We performed a systematic literature search based on the PRISMA guidelines using PubMed, Ovid, and Web of Science databases. The complete search strategy can be found as a preregistered protocol on PROSPERO (CRD42023361662).
RESULTS: We included 83 studies, most involving healthy animals (n = 72, 86.75 %). High doses of hemispherical irradiation of 30 Gy in rats and 50 Gy in mice led repeatedly to radionecrosis among different studies and set-ups. Higher dose and larger irradiated volume were associated with earlier onset. Fractionated schedules proved limited effectiveness in the prevention of radionecrosis. Distinct anatomical brain structures respond to irradiation in various ways. White matter appears to be more vulnerable than gray matter. Younger age, more evolved animal species, and genetic background were also significant factors, whereas sex was irrelevant. Only 13.25 % of the studies were performed on primary brain tumor bearing animals, no studies on brain metastases are currently available.
CONCLUSIONS: This systematic review identified various factors that significantly affect the induction of radionecrosis. The current state of research neglects the utilization of animal models of brain tumors, even though patients with brain malignancies constitute the largest group receiving brain irradiation. This latter aspect should be primarily addressed when developing an experimental radionecrosis model for translational implementation.

Conventional chemotherapeutic approaches currently used for brain tumor treatment have low efficiency in targeted drug delivery and often have non-target toxicity. Development of stable and effective drug delivery vehicles for the most incurable diseases is one of the urgent biomedical challenges. We have developed polymer nanoparticles (NPs) with improved temozolomide (TMZ) delivery for promising brain tumor therapy, performing a rational design of polyelectrolyte complexes of oppositely charged polysaccharides of cationic chitosan and anionic pectin. The NPs\' diameter (30 to 330 nm) and zeta-potential (-29 to 73 mV) varied according to the initial mass ratios of the biopolymers. The evaluation of nanomechanical parameters of native NPs demonstrated changes in Young\'s modulus from 58 to 234 kPa and adhesion from -0.3 to -3.57 pN. Possible mechanisms of NPs\' formation preliminary based on ionic interactions between ionogenic functional groups were proposed by IR spectroscopy and dynamic rheology. The study of the parameters and kinetics of TMZ sorption made it possible to identify compounds that most effectively immobilize and release the active substance in model liquids that simulate the internal environment of the body. A polyelectrolyte carrier based on an equal ratio of pectin-chitosan (0.1% by weight) was selected as the most effective for the delivery of TMZ among a series of obtained NPs, which indicates a promising approach to the treatment of brain tumors.

The application of magnetic resonance imaging (MRI) in the classification of brain tumors is constrained by the complex and time-consuming characteristics of traditional diagnostics procedures, mainly because of the need for a thorough assessment across several regions. Nevertheless, advancements in deep learning (DL) have facilitated the development of an automated system that improves the identification and assessment of medical images, effectively addressing these difficulties. Convolutional neural networks (CNNs) have emerged as steadfast tools for image classification and visual perception. This study introduces an innovative approach that combines CNNs with a hybrid attention mechanism to classify primary brain tumors, including glioma, meningioma, pituitary, and no-tumor cases. The proposed algorithm was rigorously tested with benchmark data from well-documented sources in the literature. It was evaluated alongside established pre-trained models such as Xception, ResNet50V2, Densenet201, ResNet101V2, and DenseNet169. The performance metrics of the proposed method were remarkable, demonstrating classification accuracy of 98.33%, precision and recall of 98.30%, and F1-score of 98.20%. The experimental finding highlights the superior performance of the new approach in identifying the most frequent types of brain tumors. Furthermore, the method shows excellent generalization capabilities, making it an invaluable tool for healthcare in diagnosing brain conditions accurately and efficiently.

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.

Brain tumors such as glioblastomas are resistant to immune checkpoint blockade therapy, largely due to limited T cell infiltration in the tumors. Here, we show that mice bearing intracranial tumors exhibit systemic immunosuppression and T cell sequestration in bone marrow, leading to reduced T cell infiltration in brain tumors. Elevated plasma corticosterone drives the T cell sequestration via glucocorticoid receptors in tumor-bearing mice. Immunosuppression mediated by glucocorticoid-induced T cell dynamics and the subsequent tumor growth promotion can be abrogated by adrenalectomy, the administration of glucocorticoid activation inhibitors or glucocorticoid receptor antagonists, and in mice with T cell-specific deletion of glucocorticoid receptor. CCR8 expression in T cells is increased in tumor-bearing mice in a glucocorticoid receptor-dependent manner. Additionally, chemokines CCL1 and CCL8, the ligands for CCR8, are highly expressed in bone marrow immune cells in tumor-bearing mice to recruit T cells. These findings suggested that brain tumor-induced glucocorticoid surge and CCR8 upregulation in T cells lead to T cell sequestration in bone marrow, impairing the anti-tumor immune response. Targeting the glucocorticoid receptor-CCR8 axis may offer a promising immunotherapeutic approach for the treatment of intracranial tumors.