Development of an Orthotopic Medulloblastoma Zebrafish Model for Rapid Drug Testing

Medicine, Pediatrics, Neurology, Oncology,
medulloblastoma   zebrafish model   drug testing   neural stem cells   tumor growth  

Academic Background Medulloblastoma (MB) is one of the most common malignant brain tumors in children. Although recent advances in molecular characterization and multimodal treatment have significantly improved patient survival rates, the prognosis of medulloblastoma remains closely related to molecular subtypes, particularly for patients with Grou...

Efficacy of 3D-TSE Sequence-Based Radiosurgery in Prolonging Time to Distant Intracranial Failure: A Session-Wise Analysis in a Histology-Diverse Patient Cohort

Medicine, Neurology, Medical Imaging, Oncology,
Radiosurgery   3D-TSE sequence   Distant Intracranial Failure   Brain Metastases   Imaging Protocol  

Efficacy of 3D-TSE Sequence in Prolonging Time to Distant Intracranial Failure: A Session-Wise Analysis in a Histology-Diverse Patient Cohort Academic Background Brain metastases (BM) represent the majority of intracranial malignancies and significantly contribute to cancer-related morbidity and mortality. At the initial diagnosis of systemic cance...

Alternative Lengthening of Telomere-Based Immortalization Renders H3G34R-Mutant Diffuse Hemispheric Glioma Hypersensitive to PARP Inhibitor Combination Regimens

Medicine, Neurology, Oncology,
alternative lengthening of telomeres   H3G34R mutation   diffuse hemispheric glioma   PARP inhibitors   DNA damage stress  

Background Introduction Diffuse Hemispheric Glioma (DHG) is a highly aggressive and poorly prognostic high-grade glioma, particularly prevalent in children and adolescents. The H3G34R/V mutation is one of the common genetic alterations in this type of tumor, often accompanied by the inactivation of the ATRX (Alpha-Thalassemia/Mental Retardation Syn...

Phase II Trial of Pathology-Based Tripartite Treatment Stratification for Patients with CNS Germ Cell Tumors: A Long-Term Follow-Up Study

Medicine, Neurology, Neurosurgery, Oncology,
CNS germ cell tumors   long-term follow-up   tripartite treatment   pathology   survival rates   relapse   complications  

Long-Term Follow-Up Study of Central Nervous System Germ Cell Tumors: Pathology-Based Tripartite Treatment Stratification Academic Background Central nervous system germ cell tumors (CNS GCTs) are rare tumors primarily occurring in adolescents, especially males aged 12 to 16. These tumors are believed to originate from primordial germ cells (PGCs),...

Targeted Delivery of Napabucasin with Radiotherapy Improves Outcomes in Diffuse Midline Glioma

Medicine, Neurology, Oncology,
Diffuse Midline Glioma   Radiotherapy   Napabucasin   Targeted Delivery   Blood-Brain Barrier   Oxidative Stress   Survival Rate  

Targeted Delivery of Napabucasin with Radiotherapy in Diffuse Midline Glioma Background Introduction Diffuse Midline Glioma (DMG) is the most aggressive primary brain tumor in children, with a median survival typically less than one year. Although radiation therapy (RT) is the current standard treatment, it only provides transient symptom relief an...

Prospective Longitudinal Analysis of Physiologic MRI-Based Tumor Habitat Predicts Short-Term Patient Outcomes in IDH-Wildtype Glioblastoma

Medicine, Neurology, Neurosurgery, Medical Imaging, Oncology,
glioblastoma   tumor habitat   physiologic MRI   prognosis prediction   IDH-wildtype  

Prospective Longitudinal Analysis of Physiologic MRI-Based Tumor Habitat Predicts Short-Term Patient Outcomes in IDH-Wildtype Glioblastoma Academic Background Glioblastoma (GBM) is a highly malignant brain tumor characterized by significant intratumoral heterogeneity, which is evident not only in gene expression and histopathology but also in macro...

ABVS Breast Tumour Segmentation via Integrating CNN with Dilated Sampling Self-Attention and Feature Interaction Transformer

Information Science, Artificial Intelligence, Medicine, Medical Imaging,
Breast Tumour Segmentation   Automated Breast Volume Scanner   3D Transformer-CNN Segmentation Network   Mask Image Modelling   Deep Learning   Medical Image Analysis   Self-Supervised Learning  

ABVS Breast Tumor Segmentation Research Based on CNN and Dilated Sampling Self-Attention Academic Background Breast cancer is the second most common cancer worldwide, and early and accurate detection is crucial for improving patient prognosis and reducing mortality. Although various imaging techniques (such as X-ray mammography, magnetic resonance ...

A General Debiasing Framework with Counterfactual Reasoning for Multimodal Public Speaking Anxiety Detection

Information Science, Computer Science, Artificial Intelligence,
public speaking anxiety detection   multimodal debiasing   spurious correlation   counterfactual reasoning   dataset  

Academic Background and Problem Introduction In the field of education today, Public Speaking Anxiety (PSA) is a widespread phenomenon, especially among non-native language learners. This anxiety not only affects learners’ ability to express themselves but may also hinder their personal development. To help learners overcome this issue, researchers...

Rehearsal-Based Continual Learning with Dual Prompts

Information Science, Computer Science, Artificial Intelligence,
Continual Learning   Dual Prompts   Knowledge Distillation   Catastrophic Forgetting   Neural Networks  

Academic Background In the fields of machine learning and neural networks, continual learning is an important research direction. The goal of continual learning is to enable models to continuously learn new knowledge across a series of tasks while avoiding forgetting previously acquired knowledge. However, existing continual learning methods face a...

Complex Quantized Minimum Error Entropy with Fiducial Points: Theory and Application in Model Regression

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
fixed-point algorithm   quantized technique   regression analysis   linear-in-parameters model   convergence   complex domain  

Theory and Application of Complex Quantized Minimum Error Entropy with Fiducial Points: Breakthroughs in Model Regression Academic Background In the fields of machine learning and signal processing, the presence of non-Gaussian noise often adversely affects model performance. Although the traditional Mean Squared Error (MSE) is theoretically and co...