Life Science Automation Fundamentals and Applications

Name: Life Science Automation Fundamentals and Applications
Brand: Artech House
Price: 139.99 EUR
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Mingjun Zhang(Editor)

Artech House (Publisher)

1st Edition

Published on 1. January 2007

530 pages

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978-1-59693-106-0 (ISBN)

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Life Science Automation Fundamentals and Applications
Contents v
Preface xv
Part I Life Science Basis for Automation 1
Chapter 1 Introduction to Nucleic Acids and ClinicalLaboratory Testing 3
1.1 Basics of Nucleic Acid Structure 4
1.1.1 General Principles 4
1.1.2 In Vitro Aspects of DNA 5
1.1.3 Unidirectional Flow of Genetic Information: The Central Dogma 9
1.2 Manipulation of DNA Under Testing Conditions 10
1.2.1 Extraction 10
1.2.2 Amplification 10
1.2.3 Detection 13
1.3 Statistics and Test Utilization Used in Medical Decision Making 16
1.3.1 Sensitivity and Specificity 17
1.3.2 Predictive Values 18
1.3.3 Preanalytical Versus Analytical Stages of Testing 19
1.4 Summary 20
Reference 21
Chapter 2 Basic Analytical Chemistry for Engineers 23
2.1 Introduction 23
2.2 Chromatographic Separation Methods 24
2.2.1 General Principles 24
2.2.2 Gas Chromatographic Methods 25
2.2.3 Liquid Chromatographic Methods 26
2.2.4 Electrophoresis 27
2.3 Bioanalytical Detection Methods 30
2.3.1 Protein Anal 30
2.3.2 DNA and RNA Analysis 36
2.3.3 Enzymatic Analysis 40
2.3.4 Immunological Methods 49
2.4 Physical Detection Methods 52
2.4.1 Atomic Spectroscopy 53
2.4.2 Optical Molecule Spectroscopy 54
2.4.3 Nuclear Magnetic Resonance Spectroscopy 58
2.4.4 Mass Spectrometry 59
2.5 Future Challenges 63
References 63
Chapter 3 Basic Health Care Delivery for Engineers 67
3.1 Introduction 67
3.2 The Health Care System: A Holistic Perspective 68
3.2.1 The Department of Veterans Affairs 70
3.2.2 The Military Health Services System 70
3.2.3 Indian Health Service 71
3.2.4 Public Health Service 72
3.3 Health Care Subsystems 72
3.4 Evidence-Based Decision Making in Health Care Delivery 74
3.4.1 The Structure of Clinical Decision Making 75
3.4.2 Automation Applied to Types of Clinical Decision Making 76
3.4.3 Automation Applied to the Clinical Decision Process 78
3.5 Care Providers 80
3.5.1 Health Professionals 80
3.5.2 Organizational Providers 81
3.5.3 Automated Devices: Control and Oversight 83
3.5.4 Value Migration in the Health System 84
3.6 The Mandate for Improved Clinical Outcomes 86
3.7 The Support Function of the Health System 88
3.7.1 Financing the Health Care System 88
3.7.2 Development and Diffusion of Medical Technology 92
3.8 Conclusions 95
References 95
Part II Engineering Basis for Life Science Automation
Chapter 4 Principles of Human-Machine Interfacesand Interactions 101
4.1 Introduction 101
4.2 Fundamentals of Human-Machine Interaction 102
4.2.1 Robotics and Machines for Life Science Automation 103
4.2.2 Design of Automation Systems 103
4.2.3 Performance of Human-Machine Systems 106
4.2.4 Human-Machine Teaming 108
4.2.5 Communication 109
4.3 Current Research 110
4.3.1 HMI Interaction Via Haptic Devices 110
4.3.2 Teamwork 112
4.3.3 Robots for Performance 113
4.4 Future Issues 115
4.4.1 Challenges for Applications in Life Science Automation 116
4.4.2 Challenges for Micro- and Nanoscale Applications 116
References 120
Chapter 5 Fundamentals of Microscopy andMachine Vision 127
5.1 Introduction 127
5.2 Fundamentals of Light Microscopy 129
5.2.1 Basic Structure of Optical Microscopes 129
5.2.2 Contrast Generation in Microscopy 131
5.2.3 Resolution Configuration and Related Performance Metrics 134
5.2.4 Three-Dimensional Microscopy 136
5.2.5 Several Practical Issues in Microscopy 137
5.2.6 Discussion 138
5.3 Fundamentals of Machine Vision 139
5.3.1 Autofocusing 139
5.3.2 Image Alignment 140
5.3.3 Feature Tracking 143
5.3.4 Image Segmentation and Deformable Region Tracking 146
5.4 A Representative Application 147
5.5 Future Development and Challenges 148
Acknowledgments 148
References 149
Chapter 6 Control Mechanisms for Life Science Automation 153
6.1 Introduction 153
6.1.3 Discrete-Time State-Space Description 155
6.1.4 Characteristics of Continuous Linear Time-Invariant System 156
6.2 Control Mechanisms 158
6.2.1 PID Control 158
6.2.2 Optimal Control 160
6.2.3 Model Predictive Control 165
6.2.4 Adaptive Control 166
6.2.5 Fuzzy-Logic Control 168
6.2.6 Hybrid Control 170
6.3 Applications to Life Science Automation 171
6.3.1 Blood Pressure Control 172
6.3.2 Control Mechanism Design 173
6.3.3 Modeling and Control of an Insulin Delivery System 176
6.3.4 Discussion 194
6.4 Conclusions and Future Challenges 194
References 195
Robotics for Life Science Automation 197
7.1 Introduction 197
7.2 Cell Manipulation Techniques 197
7.2.1 Optical and Electric Micromanipulation 198
7.2.2 Magnetic Micromanipulation 199
7.2.3 Micromanipulation Using Acoustic Energy 199
7.2.4 MEMS and Mechanical Micromanipulation 200
7.3 Robotics in the Life Science Industry 202
7.3.1 Cell Injection 202
7.3.3 High Throughput Processing of Biological Samples 209
7.3.4 Production of DNA and Protein Microarrays 211
7.4 Discussions 213
References 214
Part III Device Design, Simulation, andFabrication for Automation
Chapter 8 Sensors and Actuators for Life Science Automation 221
8.1 Introduction 221
8.2 Sensors 222
8.2.1 Pressure and Volume Sensors for Medical Applications 222
8.2.2 Electrochemical Sensors: pH, CO2, and Dissolved Oxygen 226
8.2.3 Impedimetric Sensors 229
8.2.4 DNA/Antigen-Antibody Sensors (Cantilever Sensors) 234
8.2.5 Electromagnetic Sensors 236
8.3 Actuators 238
8.3.1 Micronozzles for Reagent Printing 239
8.3.2 Thermal Microactuators 242
8.3.3 Electroactive Polymer Actuators 245
8.4 Future Trends 250
Acknowledgments 251
References 251
Chapter 9 Dynamics Modeling and Analysis of aSwimming Microrobot for Drug Delivery 257
9.1 Introduction 257
9.1.1 Routes of Administration for Drug Delivery 258
9.1.2 Controlled Drug Delivery 259
9.1.3 Swimming Microrobots 260
9.1.4 Propulsion Under Low Re Number Environment 262
9.1.5 Features of the Proposed Swimming Microrobot 262
9.1.6 Implementation Issues 263
9.2 Nomenclature 264
9.3 Dynamics Modeling and Analysis 264
9.3.1 The Governing Equations 264
9.3.2 Tail Bifurcation 265
9.3.3 Before the Bifurcation 265
9.3.4 After the Bifurcation 268
9.4 Performance Analysis 270
9.5 Discussions and Conclusions 274
References 275
Chapter 10 DNA and Protein Microarray Fabrication Automation 279
10.1 Introduction 279
10.2 Microarray Printing Technologies 282
10.2.1 Contact Printing 282
10.2.2 Self-Sensing Pins 284
10.2.3 Semicontact Printing 288
10.2.4 Inkjet Technology for Fluid Dispensing 289
10.2.5 Bead-Based Microarray 291
10.3 Microarray Fabrication Automation 293
10.4 Examples of Automated Microarray Systems 296
10.4.1 Genomic Solutions OmniGrid 100 296
10.4.2 POSaM Inkjet Microarrayer 296
10.4.3 ACAPELLA Automated Fluid Handling System 297
10.4.4 Agilent's Biological Fluid Dispensing System 297
10.5 Future Trends of Microarray Fabrication 299
10.6 Conclusions 300
Acknowledgments 300
References 300
Appendix 10.A List of Commercial Microarray Technology Companies 302
Part IV System Integration
Chapter 11 Automation of Nucleic Acid Extractionand Real-Time PCR: A New Era forMolecular Diagnostics 305
11.1 Introduction 305
11.2 Nucleic Acids Extraction Automation 306
11.2.1 Generic Robotic Platforms Which Can Perform Automatic NA Extraction 307
11.2.2 Dedicated Robotic Platforms for Automated NA Extraction 309
11.3 Real-Time PCR Automation 312
11.4 Molecular Diagnostic Labeled Automated Platforms 315
11.5 Conclusions 318
Chapter 12 Bio-Instrumentation Automation 319
12.1 Introduction 319
12.1.1 Current Trends in Drug Development 319
12.1.2 High-Throughput Screening Market and Trends 320
12.1.3 High-Content Screening Market and Trends 320
12.1.4 Comparison Between HCS and HTS 321
12.2 Detection Systems for High-Throughput Screening 322
12.2.1 Typical HTS Assays 322
12.2.2 Detection Systems for High-Throughput Screening 323
12.3 Detection Systems for High-Content Screening Measurements 325
12.3.1 Principles of High-Content Screening 325
12.3.2 Typical HCS Assays 327
12.3.3 Detection Systems for High-Content Screening 328
12.4 Automation Systems for Mass Spectrometric Measurement 328
12.4.1 Introduction 328
12.4.2 Preferred Ionization Techniques 328
12.4.3 Throughput Levels 329
12.4.4 Mass Spectrometry Instrumentation 330
12.4.5 Automation of Mass Spectrometry for Bioanalytics 330
12.5 Current Developments in Parallel Chromatography 332
12.5.1 Parallel Chromatography 332
12.5.2 Parallel Capillary Electrophoresis 333
12.6 Other Methods 335
12.6.1 Lab-on-a-Chip Systems 335
12.6.2 Patch Clamp Technologies 338
12.7 Automation Systems 339
12.7.1 Dispensing Systems 341
12.7.2 Transportation Systems 342
12.7.3 Liquid Handling Workstations 342
12.8 Future Challenges 342
12.8.1 Challenges Facing HCS 342
12.8.2 Nanodosing 343
12.8.3 Automation and Miniaturization 343
References 344
Chapter 13 In Situ Imaging and Manipulation inNano Biosystems Using the Atomic Force Microscope 349
13.1 Introduction 349
13.1.1 AFM: A Promising Tool for Biological Research 349
13.1.2 Functionalization of AFM Probe: Paving a New Avenue 350
13.1.3 From Imaging to Manipulation: A Big Leap 350
13.2 Reviews of Biomolecular Recognition Using AFM 351
13.2.1 Surface Functionalization 351
13.2.2 Functionalization of AFM Probe 351
13.2.3 Force Interaction Measurement 352
13.2.4 Single Receptor Recognition by Force Mapping 353
13.2.5 Single Receptor Recognition by Phase Changing 353
13.3 Techniques for In Situ Probing Membrane Proteins 354
13.3.1 Cell Fixation 354
13.4 In Situ Probing Angiotensin II Type 1 Receptor 356
13.4.1 Renin-Angiotensin System 356
13.4.2 Angiotensin II Type 1 Receptor and Its Antibody 357
13.4.3 Living Cell Sample Preparation 359
13.4.4 Functionalization of AFM Probe with AT1 Antibody 359
13.4.5 Single AT1 Receptor Recognition 361
13.5 Single Cell Surgery by AFM 361
13.6 Conclusion 364
References 365
Chapter 14 Biological Cell and Tissue Manipulation Automation 369
14.1 Introduction 369
14.2 Biological Cell Manipulation 370
14.2.1 Cell Manipulation Using Laser Trapping 370
14.2.2 Dielectrophoresis Cell Manipulation 371
14.2.3 Magnetic Cell Manipulation 373
14.2.4 Microrobotic Cell Manipulation 374
14.2.5 Computer Vision Microscopy 376
14.2.6 Microrobotic Visual Servo Control 381
14.2.7 Microrobots and MEMS/Microfluidic Manipulation Tools 382
14.2.8 Manipulation of Cells with Atomic Force Microscopy 384
14.3 Tissue Manipulation: Robotic Surgery 384
14.4 Future Challenges 387
References 388
Chapter 15 A General Robotic Approach forHigh-Throughput Automation in theHandling of Biosamples 395
15.1 Introduction 395
15.2 The Creation of a Robotic System by Integration 396
15.3 Delivery of Microliter Volumes of Biosolutions 398
15.3.1 Calibration Approaches 398
15.3.2 Experiment Using the Calibration Approach 400
15.4 Delivery of Nanovolumes of Viscous Biosamples 401
15.4.1 Physical and Theoretical Analysis of the Delivering Process 401
15.4.2 Experiment Verification 403
15.5 Mathematical Modeling of the Delivery of Viscous Biosamples 404
15.5.1 The Modeling Approach 404
15.5.2 Verification of the Model 406
15.6 Conclusions 408
References 408
Chapter 16 Biological Cell Sorting Automation 411
16.1 Introduction 411
16.2 Conventional Macroscale Cell Separation 413
16.3 On-Chip Cell Separation: Principles and Applications 413
16.3.1 Miniaturized Fluorescence Activated Cell Sorting ( -FACS) 414
16.3.2 Miniaturized Magnetic Activated Cell Sorting ( -MACS) 415
16.3.3 Micromachined Thermal Fractional Field Flow ( -TFFF) 417
16.3.4 Sedimentation Fractional Field Flow (SdFFF) 417
16.3.5 Gravitational Fractional Field Flow (GrFFF) 419
16.3.6 Flow Fractional Field Flow (FlFFF) 420
16.3.7 Dielectrophoresis Sorting 421
16.3.8 Ultrasonic Sorting 425
16.4 Design Considerations 427
16.5 Future Challenges 428
Acknowledgments 429
References 429
Part V Advanced Life Science Automation
Chapter 17 Modeling and Control ofElectroporation-Mediated Gene Deliveryfor Gene Therapy 437
17.1 Introduction 437
17.2 Dynamics Modeling 440
17.2.1 Chemical Effect 440
17.2.2 Electrical Field Effect 442
17.2.3 Mechanical Effect 444
17.2.4 Membrane Resealing 446
17.2.5 Integrated Chemo-Electro-Mechanical Model 446
17.3 Control Strategies 448
17.4 Simulation Results 452
17.4.1 Simulation Case One 452
17.4 2 Simulation Case Two 458
17.4.3 Discussion of the Two Case Studies 462
17.5 Discussions and Conclusions 465
References 465
Chapter 18 Nanotechnology for Advanced Life Science Automation
18.1 Introduction 469
18.2 Nanoimaging in an Aqueous Environment 471
18.3 Nanofabrication 474
18.4 Nanorobotic Manipulation 475
18.5 NEMS 482
References 487
About the Editors 491
Index 493

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