Search Results (468)

Piper nigrum L. (PN), which contains various bioactive compounds, is a plant with homologous medicine and food. Sleep deprivation (SD) profoundly impacts cognitive function and emotional health. However, the mechanisms by which PN improves cognitive function and depressive mood induced by SD remain unclear. In our study, network pharmacology and molecular docking techniques were used to predict the potential mechanisms by which PN regulates SD. In this study, 220 compounds were identified in PN, and 10 core targets were screened through network pharmacology. Animal experiments showed that PN ameliorated depressive mood and cognitive deficits in sleep-deprived mice, upregulated the serum activities of superoxide dismutase (SOD), glutathione (GSH), and catalase (CAT), and downregulated malondialdehyde (MDA) levels. The ELISA assay showed that PN significantly decreased the tumour necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1β) levels. Histopathological staining of brain tissue demonstrated that PN mitigates SD-induced hippocampal damage, enables the hippocampus to produce more neurotransmitters, including 5-hydroxytryptamine (5-HT), gamma-aminobutyric acid (GABA), and dopamine (DA), and reduces glutamate (Glu) levels. RT-qPCR and WB analyses further indicated that PN could exert anti-SD effects by inhibiting the over-activation of the JAK1/STAT3 signalling pathway. In the PC12 cell model, PN could reduce inflammation and prevent apoptosis, exerting neuroprotective effects. In summary, PN has positive effects on alleviating depressive symptoms and cognitive dysfunction induced by SD. Full article

Cranioplasty enables the restoration of cranial defects caused by traumatic injuries, brain tumour excisions, or decompressive craniectomies. Conventional methods rely on Computer-Aided Design (CAD) for implant design, which requires significant resources and expertise. Recent advancements in Artificial Intelligence (AI) have improved Computer-Aided Diagnostic systems for accurate and faster cranial reconstruction and implant generation procedures. However, these face inherent limitations, including the limited availability of diverse datasets covering different defect shapes spanning various locations, absence of a comprehensive pipeline integrating the preprocessing of medical images, cranial reconstruction, and implant generation, along with mechanical testing and validation. The proposed framework incorporates a robust preprocessing pipeline for easier processing of Computed Tomography (CT) images through data conversion, denoising, Connected Component Analysis (CCA), and image alignment. At its core is CRIGNet (Cranial Reconstruction and Implant Generation Network), a novel deep learning model rigorously trained on a diverse dataset of 2160 images, which was prepared by simulating cylindrical, cubical, spherical, and triangular prism-shaped defects across five skull regions, ensuring robustness in diagnosing a wide variety of defect patterns. CRIGNet achieved an exceptional reconstruction accuracy with a Dice Similarity Coefficient (DSC) of 0.99, Jaccard Similarity Coefficient (JSC) of 0.98, and Hausdorff distance (HD) of 4.63 mm. The generated implants showed superior geometric accuracy, load-bearing capacity, and gap-free fitment in the defected skull compared to CAD-generated implants. Also, this framework reduced the implant generation processing time from 40–45 min (CAD) to 25–30 s, suggesting its application for a faster turnaround time, enabling decisive clinical support systems. Full article

Segmentation neural networks are widely used in medical imaging to identify anomalies that may impact patient health. Despite their effectiveness, these networks face significant challenges, including the need for extensive annotated patient data, time-consuming manual segmentation processes and restricted data access due to privacy concerns. In contrast, classification neural networks, similar to segmentation neural networks, capture essential parameters for identifying objects during training. This paper leverages this characteristic, combined with explainable artificial intelligence (XAI) techniques, to address the challenges of segmentation. By adapting classification neural networks for segmentation tasks, the proposed approach reduces dependency on manual segmentation. To demonstrate this concept, the Medical Segmentation Decathlon ‘Brain Tumours’ dataset was utilised. A ResNet classification neural network was trained, and XAI tools were applied to generate segmentation-like outputs. Our findings reveal that GuidedBackprop is among the most efficient and effective methods, producing heatmaps that closely resemble segmentation masks by accurately highlighting the entirety of the target object. Full article

Background/Objectives: Glioblastoma multiforme (GBM), an aggressive and deadly brain tumour, presents significant challenges in achieving effective treatment due to its resistance to current therapies and poor prognosis. This study aimed to synthesise and evaluate 23 novel analogues of 3,4-dihydroquinolin-2(1H)-one, designed to enhance druggability and solubility, and to investigate their potential as VEGFR2 inhibitors for GBM treatment. Methods: The synthesised compounds were analysed using in silico methods, including molecular docking and dynamics studies, to assess their interactions with key residues within the VEGFR2 binding pocket. In vitro evaluations were performed on U87-MG and U138-MG GBM cell lines using MTT assays to determine the IC50 values of the compounds. Results: Among the tested compounds, 4u (IC50 = 7.96 μM), 4t (IC50 = 10.48 μM), 4m (IC50 = 4.20 μM), and 4q (IC50 = 8.00 μM) demonstrated significant antiproliferative effects against both the U87-MG and U138-MG cell lines. These compounds exhibited markedly higher efficacy compared to temozolomide (TMZ), which showed IC50 values of 92.90 μM and 93.09 μM for U87-MG and U138-MG, respectively. Molecular docking and dynamics studies confirmed strong interactions between the compounds and VEGFR2 kinase, supporting their substantial anti-cancer activity. Conclusions: This study highlights the promising potential of 3,4-dihydroquinolin-2(1H)-one analogues, particularly 4m, 4q, 4t, and 4u, as VEGFR2-targeting therapeutic agents for GBM treatment. Further detailed research is warranted to validate and expand upon these findings. Full article

(1) Background/Objectives: Primary and secondary brain tumours often hold devastating prognoses and low survival rates despite the application of maximal neurosurgical resection, and state-of-the-art radiotherapy and chemotherapy. One limiting factor in their management is that several antineoplastic agents are unable to cross the blood–brain barrier (BBB) to reach the tumour microenvironment. Nanomedicine could hold the potential to become an effective means of drug delivery to overcome previous hurdles towards effective neuro-oncological treatments. (2) Methods: A scoping review following the PRISMA-ScR guidelines and checklist was conducted using key terms input into PubMed to find articles that reflect emerging trends in the utilisation of nanomedicine in drug delivery for primary and secondary brain tumours. (3) Results: The review highlights various strategies by which different nanoparticles can be exploited to bypass the BBB; we provide a synthesis of the literature on the ongoing contributions to therapeutic protocols based on chemotherapy, immunotherapy, focused ultrasound, radiotherapy/radiosurgery, and radio-immunotherapy. (4) Conclusions: The emerging trends summarised in this scoping review indicate encouraging advantageous properties of nanoparticles as potential effective drug delivery mechanisms; however, there are still nanotoxicity issues that largely remain to be addressed before the translation of these innovations from laboratory to clinical practice. Full article

Glioblastoma (GB) is a highly malignant brain tumor with a poor prognosis, with a median survival of only 14.6 months despite aggressive treatments. Resistance to chemotherapy, particularly temozolomide (TMZ), is a significant challenge. The DNA repair enzyme MGMT and glioblastoma stem cells (GSCs) often mediate this resistance. Recent studies highlight the therapeutic potential of natural compounds, particularly delphinidins, found in deep purple berries. Delphinidins are known for their ability to inhibit NF-κB signaling, a critical pathway for GB progression, chemoresistance, and MGMT expression. Our research demonstrates that glycosylated delphinidins have potential adjuvant use in the treatment of GB, offering a promising natural strategy to combat TMZ resistance. Specifically, we observed that delphinidin 3,5 di-glucoside has potent anticancer effects when used alone. Meanwhile, delphinidin 3 glucoside acted in synergy with temozolomide to decrease cell viability, highlighting its potential as an adjuvant. It also exerted a faster and more sustained inhibition of NF-κB, highlighting its potential for long-lasting therapeutic effects. These findings open new avenues for targeted therapies against glioblastoma, particularly to overcome treatment resistance. Full article

Background: Cerebral intra-arterial chemotherapy (CIAC) has been demonstrated to achieve tumoricidal concentrations in cerebral tumour cells that are otherwise unachievable due to the presence of the blood–brain barrier. In this study, we sought to analyze the safety of CIAC in a cohort of patients treated at the Centre intégré universitaire de santé et de services sociaux de l’Estrie—Centre hospitalier universitaire de Sherbrooke (CIUSSS-CHUS). Methods: Treatments consisted of monthly CIAC. A neurological examination and neuroimaging study (MRI) were performed before every treatment. The files of patients enrolled in our CIAC programme were reviewed. Adverse events were analyzed and categorized. Results: Overall, 2991 CIAC procedures were performed in 642 patients. Pathologies were as follows: malignant gliomas (68.7%), cerebral metastasis (17.6%), and cerebral lymphomas (13.7%). Perfusion vessels were as follows: 80% internal carotid artery and 20% vertebral artery. The chemotherapeutic agents used were carboplatin (86.4%), methotrexate (28.5%), melphalan (28.6%), and liposomal doxorubicin (2.8%). Osmotic blood–brain barrier disruption (BBBD) was induced in 30.5% of treatments. Symptomatic vascular adverse events occurred during 27 procedures (0.9%) in 26 patients (4%). Namely, 23 strokes, one carotid artery occlusion (responsible for one of the strokes), and two intratumoral and one subdural hemorrhage. The absolute risk of stroke was 1.3% and 0.5% for CIAC with or without BBBD, respectively. The use of the vertebral artery significantly increased the risk of stroke. Drug infusion-related seizures occurred in 2.5% of patients; 83.8% were associated with methotrexate and 16.2% with carboplatin. Conclusions: CIAC is a safe procedure with a 0.9% overall rate of symptomatic complications (stroke, carotid occlusion, subdural hemorrhage or intratumoral bleeding—n = 27/2991) on a treatment basis, mainly consisting of strokes (85%, n = 23), with a modified NIH Stroke Scale score of 4.1 ± 3.3. Full article

HA (hyaluronan) has been considered in recent years as a naturally occurring modifiable gel-like scaffold that has the capability to absorb and release drugs over an extended period of time making it suitable as a potential chemotherapeutic delivery agent. Considering the limited treatment options available in the treatment of glioblastoma, in this review, we discuss the novel utilisation of ultra-high molecular weight HA—originally identified as a mechanism for maintaining longevity in the naked mole-rat—as both a protective and extracellular matrix-optimizing colloidal scaffold, and a means to deliver therapy in resected brain tumours. The unique properties of this unique form of HA cross-linked gel indicate potential future use in the prevention and treatment of both proliferative-based and inflammation-driven disease. Full article

Changes in epigenetic processes such as histone acetylation are proposed as key events influencing cancer cell function and the initiation and progression of pediatric brain tumors. Valproic acid (VPA) is an antiepileptic drug that acts partially by inhibiting histone deacetylases (HDACs) and could be repurposed as an epigenetic anticancer therapy. Here, we show that VPA reduced medulloblastoma (MB) cell viability and led to cell cycle arrest. These effects were accompanied by enhanced H3K9 histone acetylation (H3K9ac) and decreased expression of the MYC oncogene. VPA impaired the expansion of MB neurospheres enriched in stemness markers and reduced MYC while increasing TP53 expression in these neurospheres. In addition, VPA induced morphological changes consistent with neuronal differentiation and the increased expression of differentiation marker genes TUBB3 and ENO2. The expression of stemness genes SOX2, NES, and PRTG was differentially affected by VPA in MB cells with different TP53 status. VPA increased H3K9 occupancy of the promoter region of TP53. Among the genes regulated by VPA, the stemness regulators MYC and NES showed an association with patient survival in specific MB subgroups. Our results indicate that VPA may exert antitumor effects in MB by influencing histone acetylation, which may result in the modulation of stemness, neuronal differentiation, and the expression of genes associated with patient prognosis in specific molecular subgroups. Importantly, the actions of VPA in MB cells and neurospheres include a reduction in the expression of MYC and an increase in TP53. Full article

BACKGROUND: Maximal safe resection is the objective of most neuro-oncological operations. Intraoperative magnetic resonance imaging (iMRI) may guide the surgeon to improve the extent of safe resection. There is limited evidence comparing the impact of iMRI on the rates of further resection between tumour types. AIM: To investigate the impact of iMRI on the rate of further resection following visualisation of residual tumour. METHODS: A retrospective cohort study identified all intracranial tumour operations performed in the 1.5 T iMRI machine of a single centre (2007–2023). Patients were identified using SurgiNet and were grouped according to their histopathological diagnosis in accordance with the WHO 2021 classification. The primary outcome was the rate of reoperation due to iMRI visualisation of residual tumours. RESULTS: A total of 574 cases were identified, including 152 low-grade gliomas (LGG), 108 high-grade gliomas (HGG), 194 pituitary neuroendocrine tumours (PitNETs), 15 metastases, and 6 meningiomas. Further resection following iMRI visualisation occurred in 45% of LGG cases, 47% of HGG cases, 29% of PitNET cases, and no meningioma or metastasis cases. Chi-square analysis showed that the rate of further resection after iMRI use across 2018–2023 was significantly higher than that across 2007–2012 (46% versus 33%, p = 0.036). CONCLUSION: Intraoperative MRI for guiding further resection was most useful in cases of LGG and HGG, possibly reflecting the difficulty of differentiating these tumour types from normal brain tissue. In addition, there was increased reliance on iMRI over time, which may represent our surgeons becoming accustomed to its use. Full article

The overall goal of this work was to assess the ability of Natural Killer cells to kill cultures of patient-derived glioblastoma cells. Herein we report impressive levels of NK-92 mediated killing of various patient-derived glioblastoma cultures observed at ET (effector: target) ratios of 5:1 and 1:1. This enabled direct comparison of the degree of glioblastoma cell loss across a broader range of glioblastoma cultures. Importantly, even at high ET ratios of 5:1, there are always subpopulations of glioblastoma cells that prove very challenging to kill that evade the NK-92 cells. Of value in this study has been the application of ECIS (Electric Cell–Substrate Impedance Sensing) biosensor technology to monitor the glioblastoma cells in real-time, enabling temporal assessment of the NK-92 cells. ECIS has been powerful in revealing that at higher ET ratios, the glioblastoma cells are acutely sensitive to the NK-92 cells, and the observed glioblastoma cell death is supported by the high-content imaging data. Moreover, long-term ECIS experiments reveal that the surviving glioblastoma cells were then able to grow and reseed the culture, which was evident 300–500 h after the addition of the NK-92 cells. This was observed for multiple glioblastoma lines. In addition, our imaging provides evidence that some NK-92 cells appear to be compromised early, which would be consistent with potent evasive mechanisms by the glioblastoma tumour cells. This research strongly highlights the potential for NK-92 cells to kill glioblastoma tumour cells and provides a basis to identify the mechanism utilised by the surviving glioblastoma cells that we now need to target to achieve maximal cytolysis of the resistant glioblastoma cells. It is survival of the highly resistant glioblastoma clones that results in tumour relapse. Full article

The early and precise identification of a brain tumour is imperative for enhancing a patient’s life expectancy; this can be facilitated by quick and efficient tumour segmentation in medical imaging. Automatic brain tumour segmentation tools in computer vision have integrated powerful deep learning architectures to enable accurate tumour boundary delineation. Our study aims to demonstrate improved segmentation accuracy and higher statistical stability, using datasets obtained from diverse imaging acquisition parameters. This paper introduces a novel, fully automated model called Enhanced Channel Attention Transformer (E-CATBraTS) for Brain Tumour Semantic Segmentation; this model builds upon 3D CATBraTS, a vision transformer employed in magnetic resonance imaging (MRI) brain tumour segmentation tasks. E-CATBraTS integrates convolutional neural networks and Swin Transformer, incorporating channel shuffling and attention mechanisms to effectively segment brain tumours in multi-modal MRI. The model was evaluated on four datasets containing 3137 brain MRI scans. Through the adoption of E-CATBraTS, the accuracy of the results improved significantly on two datasets, outperforming the current state-of-the-art models by a mean DSC of 2.6% while maintaining a high accuracy that is comparable to the top-performing models on the other datasets. The results demonstrate that E-CATBraTS achieves both high segmentation accuracy and elevated generalisation abilities, ensuring the model is robust to dataset variation. Full article

Background: Elastic image fusion (EIF) using an intraoperative CT (iCT) scan may enhance neuronavigation accuracy and compensate for brain shift. Objective: To evaluate the safety and reliability of the EIF algorithm (Virtual iMRI Cranial 4.5, Brainlab AG, Munich Germany, for the identification of residual tumour in glioblastoma surgery. Moreover, the impact of brain shift on software reliability is assessed. Methods: This ambispective study included 80 patients with a diagnosis of glioblastoma. Pre-operative MRI was elastically fused with an intraoperative CT scan (BodyTom; Samsung-Neurologica, Danvers, MA, USA) acquired at the end of the resection. Diagnostic specificity and the sensitivity of each tool was determined. The impact of brain shift on residual tumour was statistically analysed. An analysis of accuracy was performed through Target Registration Error (TRE) measurement after rigid image fusion (RIF) and EIF. A qualitative evaluation of each Virtual MRI image (VMRI) was performed. Results: VMRI identified residual tumour in 26/80 patients (32.5%), confirmed by post-operative MRI (true positive). Of these, 5 cases were left intentionally due to DES-positive responses, 8 cases underwent near maximal or subtotal resection, and 13 cases were not detected by iCT. However, in the other 27/80 cases (33.8%), VMRI reported residual tumour that was present neither on iCT nor on post-operative MRI (false positive). i-CT showed a sensitivity of 56% and specificity of 100%; VMRI demonstrated a sensitivity of 100% and specificity of 50%. Spearman correlation analysis showed a moderate correlation between pre-operative volume and VMRI tumour residual. Moreover, tumour involving insula or infiltrating more than one lobe displayed higher median values (p = 0.023) of virtual residual tumour. A statistically significant reduction towards lower TRE values after EIF was observed for test structures. Conclusions: Virtual iMRI was proven to be a feasible option to detect residual tumour. Its integration within a multimodal imaging protocol may provide neurosurgeons with intraoperatively updated imaging. Full article

Objective: Navigated transcranial magnetic stimulation (nTMS) has seldom been used to study visuospatial (VS) circuits so far. Our work studied (I) VS functions in neurosurgical oncological patients by using repetitive nTMS (rnTMS), (II) the possible subcortical circuits underneath, and (III) the correspondence between nTMS and direct cortical stimulation (DCS) during awake procedures. Methods: We designed a monocentric prospective study, adopting a protocol to use rnTMS for preoperative planning, including VS functions for lesions potentially involving the VS network, including neurosurgical awake and asleep procedures. nTMS-based-DTI tractography allowed the visualization of subcortical circuits. Statistical analyses on nTMS/DCS points were performed. Clinical results were collected pre- and postoperatively. Results: Finally, 27 patients with primitive intra-axial brain lesions were enrolled between April 2023 and March 2024. Specific tests and an experimental integrated VS test (VISA) were used. The clinical evaluation (at 5 ± 7, 30 ± 10, 90 ± 10 days after surgery) documented 33% of patients with neglect in the left hemisphere four days after surgery and, during the 3-month follow-up, preservation of visuospatial function/clinical recovery (90.62% in MMSE, 98.86% in the bell test, 80% in the clock test, and 98% in the OCS test). The surgical strategy was modulated according to the nTMS map. Subcortical bundles were traced to identify those most involved in these functions: SFLII > SLFII > SLFI. A comparison of the nTMS and DCS points in awake surgery (n = 10 patients) documented a sensitivity (Se) of 12%, a specificity (Sp) of 91.21%, a positive predictive value (PPV) of 42%, a negative predictive value (NPV) of 66%, and an accuracy of ~63.7%. Conclusions: Based on our preliminary results, nTMS is advantageous for studying cognitive functions, minimising neurological impairment. Further analyses are needed to validate our data. Full article

Background/Objectives: Brain cancer is notoriously resistant to traditional treatments, including radiotherapy. Microbeam radiation therapy (MRT), arrays of ultra-fast synchrotron X-ray beams tens of micrometres wide (called peaks) and spaced hundreds of micrometres apart (valleys), is an effective alternative to conventional treatments. MRT’s advantage is that normal tissues can be spared from harm whilst maintaining tumour control. Combining MRT with targeted radiosensitisers, such as nanoparticles, chemotherapeutic drugs, and halogenated pyrimidine drugs, can further improve radiotherapy by enhancing radiation damage. However, the underlying mechanisms of MRT are still being understood, which is essential to ensuring the reliable and successful use of MRT. Methods: An in vitro study was performed using γH2AX imaging, and quantification was performed via confocal microscopy and a clonogenic cell survival assay. Results: We show that methotrexate chemotherapeutics and iododeoxyuridine enhance MRT cell-killing and thulium oxide nanoparticles (TmNPs) broaden MRT peaks, and using γH2AX immunofluorescent confocal microscopy to quantify DNA damage, we further our knowledge of MRT mechanisms. γH2AX images verify the biological responses of cells aligning with the physical collimation of MRT, and we can accurately measure MRT microbeam characteristics bio-dosimetrically. The peak-to-valley dose ratio (PVDR), the ratio of the peak dose to the valley dose that characterises an MRT field, was accurately measured biologically using γH2AX imaging, despite studies previously finding this challenging. Conclusions: The measurement of biological PVDR has been performed for the first time with high-Z radiosensitisers, including nanoparticles, and several novel radiosensitiser-enhanced MRT mechanisms were discovered. Our results deepen our understanding of MRT with radiosensitisers, and can contribute to its accurate and future successful use in treating cancer. Full article