Biomedical translational research : technologies for improving healthcare / R. C. Sobti and Aastha Sobti.

Format:

Book

Author/Creator:

Sobti, R. C., author.

Sobti, Aastha, author.

Language:

English

Subjects (All):

Biomedical engineering.

Biomedical engineering--Handbooks, manuals, etc.

Physical Description:

1 online resource (500 pages)

Place of Publication:

Springer Nature Singapore

Singapore : Springer, [2022]

Summary:

This book, which is the first volume of Biomedical Translational Research, summarizes emerging technologies in healthcare. The book reviews the advancements in biomedical sciences in genomics, immunology, stem cell, tissue engineering, nanotechnology, computational and structural biology, biomedical engineering, and telemedicine biology. The book highlights the applications of artificial intelligence in the diagnosis of infectious diseases and examines the role of system biology approaches for understanding human complexity, variability, and its influence on health and diseases. It presents the applications of flow cytometry in monitoring the progression and treatment of disease. It covers emerging technologies in cancer research, including CRISPR-Cas9, NGS, and nanotechnology. This book is a useful source of information for clinical researchers, basic scientists, biomedical engineers, and computational biologists.

Contents:

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

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

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

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

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

7: Bioinformatics: The Interactome of Multidisciplinary Approaches

7.1 Introduction

7.2 Bioinformatics Databases

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

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

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

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

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

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

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

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.

Notes:

Description based on print version record.

Other Format:

Print version: Sobti, R. C. Biomedical Translational Research

ISBN:

981-16-4344-X

981-16-4345-8