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Glioblastoma: State of the Art and Future Perspectives
Glioblastoma is an aggressive incurable primary tumor of the central nervous system. Median overall survival is in the range of 1.5 years even in selected clinical trials populations. Many features contribute to this therapeutic challenge including high intratumoral and intertumoral heterogeneity, resistance to therapy, migration and invasion, immunosuppression. With the access of novel highthroughput technologies, significant progress has been made to understand molecular and immunological signatures underlying the pathology of glioblastoma. Clinical trial designs have shifted from investigating broad “one-for-all” treatment approaches to precision oncology designs. The collection of contributions in this book aim at providing researchers and clinicians an update on different aspects of glioblastoma, i.e. progress in basic, preclinical and clinical research.
Prognostic Relevance of Tumor-infiltrating Lymphocytes and Immune Checkpoints in Pediatric Medulloblastoma
Abstract: Pediatric medulloblastomas are the most frequently diagnosed embryonal tumors of the central nervous system. Current therapies cause severe neurological and cognitive side effects including secondary malignancies. Cellular immunotherapy might be key to improve survival and to avoid morbidity. Efficient killing of tumor cells using immunotherapy requires to overcome cancer-associated strategies to evade cytotoxic immune responses. Here, we examined the immune response and immune evasion strategies in pediatric medulloblastomas. Cytotoxic T-cells, infiltrating medulloblastomas with variable activation status, showed no correlation with overall survival of the patients. We found limit...
Marijuana and Madness
This book provides a comprehensive overview of the psychiatry and neuroscience of Cannabis sativa (marijuana), with particular emphasis on psychotic disorders. It outlines developments in our understanding of the human cannabinoid system, and links this knowledge to clinical and epidemiological facts about the impact of cannabis on mental health. Clinically focused chapters review not only the direct psychomimetic properties of cannabis, but also the impact consumption has on the courses of evolving or established mental illness such as schizophrenia. A number of controversial issues are critically explored, including whether a discrete 'cannabis psychosis' exists, and whether cannabis can actually cause schizophrenia. Effects of cannabis on mood, notably depression, are reviewed, as are its effects on cognition. This book will be of interest to all members of the mental health team, as well as to neuroscientists and those involved in drug and alcohol research.
Molecular and Cellular Neurobiology
Presents an account of the remarkable progress made in different areas of neurobiology. This book introduces the structure and development of the brain, showing how they are specialized for the functions they serve. It is concerned with hormones and neurotransmitters.
Computational Logistics
This book constitutes the proceedings of the 11th International Conference on Computational Logistics, ICCL 2020, held in Enschede, The Netherlands, in September 2020. The 49 papers included in this book were carefully reviewed and selected from 73 submissions. They were organized in topical sections named: maritime and port logistics; vehicle routing and scheduling; freight distribution and city logistics; network design and scheduling; and selected topics in logistics. Due to the Corona pandemic ICCL 2020 was held as a virtual event.
Employee Engagement in Corporate Social Responsibility
Employee engagement in Corporate Social Responsibility focuses on engaging employees in socially responsible initiatives, using the existing literature, new empirical studies, case studies and thought-provoking insights.
Neural Networks for Pattern Recognition
Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.
