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Biomedical translational research : technologies for improving healthcare / / R. C. Sobti and Aastha Sobti
| Biomedical translational research : technologies for improving healthcare / / R. C. Sobti and Aastha Sobti |
| Autore | Sobti R. C. |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (500 pages) |
| Disciplina | 610.28 |
| Soggetto topico |
Biomedical engineering
Enginyeria biomèdica Investigació mèdica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
981-16-4344-X
981-16-4345-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- 1: Introduction to Emerging Technologies in Biomedical Sciences -- 1.1 Introduction -- 1.2 Imaging Cells to Molecules in 3D -- 1.3 Genetic Engineering with Precision -- 1.4 Omics Technologies -- 1.5 Next-Generation Sequencing -- 1.6 Spectroscopy of Single-Molecule and Mixtures -- 1.7 Informatics and Simulations -- 1.8 Automation and Miniaturization of Experiments (Robotic Liquid Handling Systems and Microfluidics) -- 1.9 Microelectromechanical Systems in Biology (Bio-MEMS) -- 1.10 Personalized Medicine -- 1.11 Exosomes in Cancer Immunotherapy -- 1.12 Neuronal Tracing Techniques -- 1.13 Miniaturized Bioreactors -- 1.14 Transcranial Magnetic Stimulation (TMS) -- 1.15 Bionic Organism or Cyborg Cells -- 1.16 Conclusion -- References -- 2: Bioprospecting: Boon or Curse -- 2.1 United Nations Convention on Biological Diversity. -- 2.2 Virtues of Bioprospecting -- 2.3 Demons of Bioprospecting -- 2.4 Resolution to the Concerns -- 2.5 Conclusions and Future Prospects -- References -- 3: Growing Need for Interdisciplinary Biomedical Research -- 3.1 Introduction -- 3.2 Interdisciplinary Research -- 3.2.1 Cardiovascular Health and Diseases -- 3.2.2 Studies on Pathogens -- 3.2.3 Schizophrenia -- 3.3 Increasing Urgency in Some Fields of Research -- 3.4 Why Do We Need Interdisciplinary Research? -- 3.5 Future Directions for Interdisciplinary Research -- 3.6 Concluding Remarks -- References -- 4: Interplay Between Theory and Experiment: A Future Approach for Biomedical Research -- 4.1 History -- 4.2 Introduction -- 4.2.1 Cytochrome P450 (P450) -- 4.3 Experiment That Created Doubt -- 4.3.1 Site-Directed Mutagenesis -- 4.3.1.1 Ethylene Epoxidation by CPD 0 and CPD I -- 4.3.2 DFT and QM/MM Studies of Alkyl Sulfide -- 4.3.2.1 Sulfoxidation by Cpd 0 and Cpd I -- 4.3.2.2 Radical Clock Experiment.
Rebound Controversy and Its Resolution by TSR Scenarios -- 4.3.2.3 Products Isotope Effect and TSR -- 4.3.2.4 Quantum Mechanical and Molecular Mechanical Application in Biomedical -- 4.4 Establishing and Testing Reaction Mechanisms -- 4.4.1 Lysozymes -- 4.4.2 Citrate Synthase -- 4.5 QM/MM Modeling of Drug Target Enzyme -- 4.5.1 Fatty-Acid Amide Hydrolase (FAAH) -- 4.5.2 Zn Enzymatic Drug Metabolism: Antibiotic Hydrolysis by Metallo-β-Lactamases Enzymes -- 4.6 Summary -- References -- 5: Past, Present, and Future Perspective of Biomedical Innovation in India -- 5.1 Introduction -- 5.2 Background to Biomedical Innovation in India -- 5.3 Biomedical Innovation in India: Lessons Learned from the Past -- 5.4 Contemporary Advancements in Biomedical Innovation -- 5.5 Lessons Learnt from Pre-COVID Biomedical Innovation in India -- 5.6 ``Innovations´´ Stimulated by the COVID-19 Pandemic -- 5.7 Lessons from COVID-Related Innovations -- 5.8 Future Perspectives: The Way Forward -- 5.9 Conclusion -- References -- 6: Systems Biology Approaches to Study Disease Comorbidities -- 6.1 Introduction -- 6.2 Systems Network Biology Perspective to Study Disease Co-occurrence -- 6.3 Analysis of Disease Co-occurrence Using Biological Networks -- 6.3.1 Using Protein-Protein Interaction to Study Diseases -- 6.3.2 Using Gene-Gene Interaction Networks to Study Diseases -- 6.3.3 Pathway Enrichment Analysis or Functional Enrichment Analysis -- 6.3.4 Disease-Gene Interaction -- 6.4 Identifying Critical Hub Proteins and Probable Therapeutic Targets -- 6.5 Concluding Remarks -- References -- 7: Bioinformatics: The Interactome of Multidisciplinary Approaches -- 7.1 Introduction -- 7.2 Bioinformatics Databases -- References -- 8: Role of Artificial Intelligence in Diagnosis of Infectious Diseases -- 8.1 Impact of Infectious Diseases -- 8.2 New Technologies for Infectious Diseases. 8.3 History of Artificial Intelligence -- Box 8.1 Definitions -- 8.4 Clinical Microbiology and Artificial Intelligence -- 8.4.1 Microscopy Image Analysis -- 8.4.2 Digital Plate Reading (DPR) -- 8.4.3 Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDITOF MS) -- 8.4.4 Antimicrobial Resistance Prediction by Whole Genome Sequencing (WGS) -- 8.5 AI in Infection Prevention and Control (IPC) -- 8.5.1 Surveillance of Healthcare Associated Infections (HAI) -- 8.5.2 Improved Laboratory Diagnosis to Facilitate IPC Interventions -- 8.5.3 Hand Hygiene -- 8.6 Disease Surveillance and Epidemiology -- 8.7 Role of Artificial Intelligence in COVID-19 Pandemic -- 8.7.1 Predicting and Monitoring the Infection -- 8.7.2 Early Detection and Diagnosis of Infection -- 8.7.3 Monitoring Treatment -- 8.7.4 Surveillance -- 8.7.5 Real-Time Spread Tracking and Contact Tracing -- 8.7.6 Projection of Cases and Mortality -- 8.7.7 Creating Chatbots -- 8.7.8 Treatment Through AI -- 8.8 Summary, Conclusion, and Future Prospects -- References -- 9: DNA Digital Data Storage: Breakthroughs in Biomedical Research -- 9.1 Introduction -- 9.2 Why Scientist Selected DNA for Data Storage System -- 9.3 How Data Can Be Stored in DNA -- 9.4 Related Work -- 9.5 Conclusion -- References -- 10: Biomedical Applications Cloud-Based IoT -- 10.1 Introduction -- 10.2 Related Work -- 10.3 Internet of Things Model -- 10.3.1 Internet -- 10.3.2 Processing -- 10.3.3 Things -- 10.3.4 Hierarchical Architecture -- 10.3.4.1 Physical Layer -- 10.3.4.2 Network Layer -- 10.3.4.3 Middleware Layer -- 10.3.4.4 Application Layer -- 10.3.5 Cloud Model -- 10.3.5.1 Software as a Service (SaaS) -- 10.3.5.2 Platform as a Service (Paas) -- 10.3.5.3 Infrastructure as a Service (IaaS) -- 10.4 Integrated Cloud with IoT (Cloud IoT) -- 10.4.1 Features of Integrated Cloud IoT -- 10.4.1.1 Storage Space. 10.4.1.2 Computing Power -- 10.4.1.3 Communication -- 10.4.1.4 New Security Model -- 10.4.2 Cloud IoT Applications -- 10.4.2.1 Smart Health Care -- 10.4.2.2 Internet of Robotic Things (IoRT) -- 10.4.2.3 Signal Processing -- 10.4.2.4 Smart Medical Devices -- 10.4.2.5 Wearable IoT (WIoT) -- 10.4.3 Open Challenges in Integrated Cloud IoT -- 10.4.3.1 Privacy and Security -- 10.4.3.2 Need for Standard Architecture of Protocol -- 10.4.3.3 Efficient Power Consumption -- 10.4.3.4 Limited Bandwidth -- 10.4.3.5 Delayed Services -- 10.5 Conclusion -- References -- 11: Next-Generation Sequencing in Cancer Research -- 11.1 Introduction -- 11.2 Overview of the Experimental Approach for DNA/RNA Sequencing Platforms -- 11.2.1 Whole-Exome Sequencing (WES) -- 11.2.2 Whole-Genome Sequencing (WGS) -- 11.2.3 Targeted Panel Sequencing -- 11.2.4 RNA Sequencing (RNA-seq) -- 11.2.5 Single-Cell DNA/RNA Sequencing -- 11.3 NGS Utility in Clinical Oncology in Solid Tumors -- 11.4 NGS Utility in Clinical Oncology in Liquid Biopsies -- 11.5 Challenges of NGS Technologies -- 11.6 Concluding Remarks -- References -- 12: CRISPR: Genome Editing and Beyond -- 12.1 Introduction -- 12.2 Discovery -- 12.3 Classification -- 12.3.1 Class 1 -- 12.3.2 Class 2 -- 12.4 Molecular Mechanism -- 12.4.1 Adaptation -- 12.4.2 crRNA Biogenesis -- 12.4.3 Interference -- 12.5 Applications -- 12.5.1 Genome Editing -- 12.5.2 Transcriptional Regulation -- 12.5.3 Post-transcriptional Engineering -- 12.5.4 Programmable DNA and RNA Imaging -- 12.5.5 Nucleic Acid Detection and Diagnostics -- 12.6 Future Prospects -- References -- 13: Omics in Tuberculosis Diagnosis: Today and Tomorrow -- 13.1 Introduction -- 13.2 Genomics in TB Diagnosis -- 13.2.1 TB Diagnostic Tests Available in the Clinics Based on Genomics -- 13.2.2 Recent Advances and Future Prospective in Genomics for Tuberculosis Diagnosis. 13.3 Proteomics in TB Diagnosis -- 13.3.1 TB Diagnostic Tests Available in the Clinics Based on Proteomics -- 13.3.2 Recent Advances and Future Prospective in Proteomics for Tuberculosis Diagnosis -- 13.3.2.1 Pathogen Proteomic Biomarkers as Candidates for TB Diagnosis -- 13.3.2.2 Host Proteomic Biomarkers Candidate for TB Diagnosis -- 13.4 Other Omics Technologies for Potential Use for TB Diagnosis -- 13.5 Concluding Remarks -- References -- 14: Advances in Proteomics Approaches and Chronic Kidney Disease -- 14.1 Introduction -- 14.2 Historical Background -- 14.3 Proteomics Advancements and Chronic Kidney Disease -- 14.3.1 Advancements in Proteomics Analysis -- 14.3.2 Chronic Kidney Disease and Proteomics -- 14.4 Conclusion -- References -- 15: 3D Bioprinting of Tissues and Organs: A New Paradigm in Regenerative Medicine and Biomedical Engineering -- 15.1 Introduction -- 15.2 History -- 15.3 3D Bioprinting Procedure -- 15.4 Bioinks -- 15.5 Hydrogels for Bioprinting -- 15.6 Methods of 3D Bioprinting -- 15.6.1 Inkjet-Based Bioprinting -- 15.6.2 Laser-Based Bioprinting -- 15.6.3 Extrusion Bioprinting/Direct Writing -- 15.6.4 Bioplotting -- 15.6.5 Fused-Deposition Modeling (FDM) -- 15.6.6 Stereolithography (SL) -- 15.7 Applications of 3D Bioprinting -- 15.7.1 Tissues and Organs Printing -- 15.7.2 Customized Implants and Prostheses -- 15.7.3 Anatomical Models -- 15.7.4 3D-Printed Dosage Forms and Drug Delivery Devices -- 15.7.5 Unique Dosage Forms -- 15.7.6 Drug Testing -- 15.7.7 Other Applications with Some Challenges -- 15.8 Tissue Engineering and Regenerative Medicine -- 15.8.1 Components of Tissue Engineering -- 15.8.1.1 Scaffold -- 15.8.1.2 Cells -- 15.8.1.3 Growth Factors -- 15.8.2 Limitations -- 15.8.3 3D Bioprinting and Tissue Engineering -- 15.8.4 Tissue Engineering of Different Organs -- 15.8.4.1 Cardiac -- 15.8.4.2 Liver. 15.8.4.3 Cartilage Bone. |
| Record Nr. | UNINA-9910743225003321 |
Sobti R. C.
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| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Molecular Biomarkers for Cancer Diagnosis and Therapy
| Molecular Biomarkers for Cancer Diagnosis and Therapy |
| Autore | Sobti Ranbir Chander |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (770 pages) |
| Disciplina | 616.994075 |
| Altri autori (Persone) |
SugimuraHaruhiko
SobtiAastha |
| Soggetto topico |
Early Detection of Cancer
Biomarkers, Tumor Neoplasms - diagnosis Neoplasms - therapy |
| ISBN | 9789819937462 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Introduction -- References -- Contents -- Editors and Contributors -- 1: Molecular Biomarkers of Cancer and Their Diagnostic Applications -- 1.1 Introduction -- 1.2 Advancement and Challenges in Cancer Biomarker Science -- 1.2.1 Specificity of the Biomarkers -- 1.2.2 Screening Strategies -- 1.2.3 Inheritance of Particular Cancer -- 1.2.4 Identification and Monitoring of Biomarkers -- 1.3 Clinical Implications of Various Cancer Biomarkers -- 1.3.1 DNA Methylation as an Epigenetic Cancer Biomarker -- 1.3.2 Noncoding RNAs (MicroRNAs) as Cancer Biomarkers -- 1.3.3 Protein Biomarkers in various cancers -- 1.3.4 Fusion Genes in Cancer Diagnostics -- 1.4 Concluding Remarks -- References -- 2: Statistical Models in Cancer Management -- 2.1 Introduction -- 2.2 Markov Framework Model for Cancer Screening -- 2.3 Analytical Models -- 2.4 The Standardized Regression Model in Cancer -- 2.5 Ordinary Differential Equations (ODEs) -- 2.6 PARADIGM -- 2.6.1 Generalized Diagram of Working of PARADIGM -- 2.7 Logistic Model -- 2.8 Cox Survival Model -- 2.9 Continuous Growth Model -- 2.10 Conclusion -- References -- 3: Cancer: Epidemiology, Racial, and Geographical Disparities -- 3.1 Epidemiology -- 3.1.1 Cancer and Age Group -- 3.1.2 Cancer and Gender -- 3.1.3 Cancer Type and Risk Factor -- 3.1.4 Cancer and Sex Ratio -- 3.1.5 Cancer and Mortality Rate -- 3.2 Racial Disparities -- 3.3 Geographical Disparities -- 3.3.1 Lung and Bronchus -- 3.3.2 Colon and Rectum -- 3.3.3 Female Breast -- 3.3.4 Prostate -- 3.3.5 Stomach -- 3.3.6 Liver -- 3.3.7 Oesophagus -- 3.3.8 Cervix Uteri -- 3.4 Conclusion -- References -- 4: Protein Markers in the Detection of Cancer -- 4.1 Introduction -- 4.1.1 Tumor Markers Used in Cancer -- 4.1.1.1 Two Types of Tumor Markers Are Used Clinically -- 4.2 Circulating Tumor Markers -- 4.3 Tumor Tissue Markers.
4.3.1 Some Important Tumor Markers Are Currently Being Used for Detection of Cancer -- 4.3.2 Proteomic Signatures of Cancer -- 4.3.3 Heat Shock Proteins -- 4.3.4 Carcino Embryonic Antigen -- 4.3.5 Tissue Inhibitor of Matrix Metalloproteinase 1 -- 4.3.6 Enzymes -- 4.3.7 MiRNAs -- 4.3.8 Cytokines -- 4.3.9 Chemokines -- 4.3.10 Stem Cell Associated Markers -- 4.3.10.1 Test Routinely Used for Cancer Detection -- 4.3.11 Prostate-Specific Antigen (PSA) -- 4.3.12 Liquid Biopsy Based Assays Test -- 4.3.12.1 Future Prospective of Protein Markers in Cancer Treatment -- References -- 5: Computer-Aided Diagnosis System for Early Detection of Malignant Tissues -- 5.1 Introduction -- 5.2 CAD for Different Types of Cancers -- 5.2.1 Prostate Cancer -- 5.2.2 Cervical Cancer -- 5.2.3 Pancreatic Cancer -- 5.2.4 Colon Polyps -- 5.2.5 Kidney -- 5.2.6 Skin Cancer -- 5.2.7 Breast Cancer -- 5.3 Conclusion -- References -- 6: Molecular Mechanisms of Oncogenesis -- 6.1 Oncogenesis: A Multistep Process -- 6.1.1 Cell-Cycle Dysregulation -- 6.1.2 Alteration in Apoptosis, Senescence, and Cell Growth Arrest -- 6.1.3 Autonomous to Growth Factors Signaling -- 6.1.4 Metastasis and Invasion -- 6.2 Factors Triggering Oncogenesis -- 6.2.1 Carcinogenic Chemicals -- 6.2.2 Ionizing and Ultraviolet Radiation -- 6.2.3 Oncogenic Viruses -- 6.2.4 The Tumor Microenvironment -- 6.2.5 Chemotherapeutic Agents -- 6.2.6 Tumor Promoters -- 6.3 Molecular Mechanisms Underlying the Process of Oncogenesis -- 6.3.1 Activation of Oncogenes -- 6.3.2 Inactivation of Tumor-Suppressor Genes -- 6.3.3 Epigenetic Alterations -- 6.3.4 OncomiR (microRNA Genes) -- 6.3.5 Mutations in DNA Repair Genes/Genomic Stability Genes -- 6.3.6 Defects in Cell-Cycle Regulation -- References -- 7: Application of CRISPR in Cancer Research and Treatment -- 7.1 Introduction -- 7.2 CRISPR/Cas9 in Cancer Research. 7.2.1 Generation of Cancer Models -- 7.2.2 Target Discovery and Validation in Oncology -- 7.3 CRISPR/Cas9 for Diagnostics -- 7.4 Applications of CRISPR/Cas9 in Cancer Treatment -- 7.4.1 CRISPR/Cas9 System in CAR-T Cell Immunotherapy -- 7.4.2 CRISPR/Cas9 for Inhibition of Immune Checkpoint Signaling -- 7.5 Conclusions and Perspectives -- References -- 8: Nanobiosensing Platforms for Early Detection of Cancer -- 8.1 Introduction -- 8.2 Conventional Methods of Cancer Detection and Challenges -- 8.3 Biomarkers for Cancer Detection -- 8.3.1 Nanoparticle-Based Biosensor Platforms for Cancer Detection -- 8.4 Gold Nanoparticle-Based Biosensing Probe for Cancer Detection -- 8.5 Carbon-Based Nanobiosensors -- 8.6 Quantum Dot-Based Cancer Biosensing and Bioimaging Platform -- 8.6.1 Nanoparticle-Based Multiplexed Biosensing Assay -- 8.7 Conclusion -- References -- 9: Bionanotechnological Strategies and Tools for Cancer Prediction, Prevention and Therapy -- 9.1 Cancer Burden and Impact -- 9.2 Oral Cancer and Burden -- 9.2.1 Oral Cancer: Screening Accuracy, Efficacy and Harms -- 9.2.2 Oral Cancer: Role of Nanotechnology -- 9.2.3 Clinical Diagnosis: Oral Cancer -- 9.2.4 Management: Oral Cancer -- 9.2.5 Economics of Nano Strategies: Oral Cancer -- 9.3 Colon Cancer and Burden -- 9.3.1 Colon Cancer: Screening Accuracy, Efficacy and Harms -- 9.3.2 Colon Cancer: Role of Nanotechnology -- 9.3.3 Clinical Diagnosis: Colon Cancer -- 9.3.4 Management: Colon Cancer -- 9.3.5 Economics of Nano Strategies: Colon Cancer -- 9.4 Challenges in Bionanotechnological Interventions -- 9.5 Way Forward -- 9.6 Conclusion -- References -- 10: Central Nervous System Tumors -- 10.1 Part I: Gliomas -- 10.1.1 Background -- 10.1.2 Anatomical Location -- 10.1.3 Epidemiology -- 10.1.4 Clinical Presentation -- 10.1.5 History and Physical Examination -- 10.1.6 Investigations. 10.1.6.1 MR Spectroscopy -- 10.1.6.2 PET-CT Scan -- 10.1.7 Risk Factors -- 10.1.7.1 Environmental Factors -- 10.1.7.2 Hereditary Factors -- 10.1.8 Histology -- 10.1.9 Management -- 10.1.9.1 Low-Grade Gliomas (LGG) -- 10.1.9.1.1 Surgery -- Circumscribed Low-Grade Gliomas -- Infiltrative or Diffuse Low-Grade Gliomas -- 10.1.9.1.2 Radiotherapy (RT) -- Adjuvant Radiotherapy Alone -- Adjuvant Radiotherapy and Chemotherapy -- Dose/Fractionation -- Advanced Radiotherapy Modalities -- 10.1.10 Anaplastic Gliomas -- 10.1.11 Anaplastic Astrocytomas -- 10.1.12 Anaplastic Oligodendroglial Tumors -- 10.1.13 Grade IV Glial Tumors -- 10.1.14 Immunotherapy -- 10.1.15 Tumor Treating Fields -- 10.1.16 Elderly Patients with GBM -- 10.1.17 Pseudoprogression in Glioma -- 10.1.18 Recurrent Malignant Gliomas -- 10.1.18.1 Surgery -- 10.1.18.2 Reirradiation -- 10.1.18.2.1 Brachytherapy -- 10.1.18.2.2 Radiosurgery -- 10.1.18.2.3 Fractionated EBRT -- 10.1.18.2.4 Systemic Therapy -- 10.1.19 Irradiation Techniques and Toxicities -- 10.1.20 Toxicities of Radiotherapy -- 10.1.21 Radiotherapy for Grade III Gliomas -- 10.2 Part II: Other CNS Tumors -- 10.2.1 Meningioma -- 10.2.2 Clinical Features -- 10.2.3 Radiological Features -- 10.2.4 Histopathology -- 10.2.5 Management -- 10.2.6 Primitive Neuroectodermal (PNET) Tumors -- 10.2.7 Treatment -- 10.2.8 Vestibular Schwannoma -- 10.2.9 Pituitary Adenoma -- 10.2.10 Craniopharyngioma -- 10.2.11 Glomus Jugulare -- 10.2.12 Pineal Region Tumors -- 10.2.13 Ependymoma -- 10.2.14 Metastases -- References -- 11: Biomedical Approaches in the Research and Management of Head and Neck Squamous Cell Carcinoma -- 11.1 Introduction -- 11.2 Risk Factors for the Development of HNSCC -- 11.3 Overview of HNSCC Tumorigenesis and Biology -- 11.4 miRNA Deregulation in HNSCC and Circulating miRNAs in Liquid Biopsies -- 11.5 Machine-Learning (ML) Techniques. 11.6 Raman Spectroscopy (RS) -- 11.7 Organoid Models (Three-Dimensional [3D] Cancer Cell Cultures) -- 11.8 Conclusions -- References -- 12: Applications of Molecular Biology and Biomedical Advances in Ocular Oncology -- 12.1 Introduction -- 12.2 Retinoblastoma -- 12.2.1 Introduction -- 12.2.2 Genetics -- 12.2.3 Genomic Landscape in Retinoblastoma -- 12.2.4 Etiopathogenesis -- 12.2.5 Cell of Origin -- 12.2.6 Development of Three-Dimensional Organoid Models -- 12.2.7 Techniques to Test RB1 Mutations -- 12.2.8 New Heritable Marker in Retinoblastoma: p16INK4a -- 12.2.9 Surging Potential of Liquid Biopsy -- 12.2.10 Oncolytic Virus VCN-01: A New Ray of Hope in RB Treatment -- 12.2.11 Role of Negative Transcriptional Regulators: MicroRNAs (miRNAs) -- 12.2.11.1 Introduction -- 12.2.11.2 miRNAs in Retinoblastoma -- 12.2.12 p53 in Peripheral Blood of RB Patients as a Biomarker -- 12.2.13 Novel Targets for RB Treatment -- 12.2.14 Noncoding RNAs in RB -- 12.2.15 Prenatal Diagnostic Testing -- 12.2.16 Autofluorescence in RB -- 12.2.17 PDT for RB In Vitro Studies -- 12.2.18 Spectral Domain Optical Coherence Tomography in Retinoblastoma -- 12.2.19 Optical Coherence Tomography Angiography in RB -- 12.3 Uveal Melanoma -- 12.3.1 Introduction -- 12.3.2 Genetics of Uveal Melanoma -- 12.3.2.1 Genetic Prognostic Tests -- 12.3.3 Current Innovative Therapeutic Options for Metastatic Tumors -- 12.3.3.1 Targeted Therapy -- 12.3.3.2 Immunotherapy -- 12.3.3.2.1 Checkpoint Inhibitors -- 12.3.3.2.2 Innovative Immune-Based Approaches -- 12.3.3.2.3 Epigenetic Approach -- 12.3.4 Conclusion -- 12.4 Primary Vitreoretinal Lymphoma -- 12.4.1 Introduction -- 12.4.2 Genetics of Vitreoretinal Lymphoma -- 12.4.3 Diagnosis of Vitreoretinal Lymphoma -- 12.4.4 Advances in the Treatment of Vitreoretinal Lymphoma -- 12.5 Conclusion -- References -- 13: Molecular Biomarkers of Oral Cancer. 13.1 Introduction. |
| Record Nr. | UNINA-9910869175103321 |
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Sobti Ranbir Chander
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| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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