| Description |
1 online resource (473 pages) |
| Series |
Diatoms : biology and applications |
| Contents |
Cover -- Title Page -- Copyright Page -- Contents -- List of Figures -- List of Tables -- Preface -- Part I: Diatom Form and Size Dynamics -- Chapter 1 Modeling the Stiffness of Diploneis Species Based on Geometry of the Frustule Cut with Focused Ion Beam Technology -- 1.1 Introduction -- 1.2 Material and Methods -- 1.2.1 Focused Ion Beam (FIB) Milling -- 1.2.2 Modeling -- 1.3 Results -- 1.3.1 FIB Processing -- 1.3.2 Modeling -- 1.4 Discussion -- 1.4.1 Practical Meaning of the Frustule Geometric Characters -- 1.4.2 Documenting the Mechanical Strength of the Diatom Frustule -- Acknowledgments -- References -- Chapter 2 Size-Resolved Modeling of Diatom Populations: Old Findings and New Insights -- 2.1 Introduction -- 2.2 The MacDonald-Pfitzer Rule and the Need for Matrix Descriptions -- 2.3 Cardinal Points and Cycle Lengths -- 2.3.1 Considered Cardinal Parameters -- 2.3.2 Factors Determining Cardinal Points -- 2.3.3 Experimental Data -- 2.4 Asymmetry, Delay and Fibonacci Growth -- 2.4.1 The Müller Model -- 2.4.2 The Laney Model -- 2.5 Continuous vs. Discrete Modeling -- 2.5.1 Discrete Dynamical Systems -- 2.5.2 The Perron-Frobenius Theorem -- 2.5.3 Continuous Dynamical Systems -- 2.5.4 Extensions and Generalizations -- 2.5.5 Individual-Based Models -- 2.6 Simulation Models -- 2.6.1 The Schwarz et al. Model -- 2.6.2 The D'Alelio et al. Model -- 2.6.3 The Hense-Beckmann Model -- 2.6.4 The Terzieva-Terziev Model -- 2.6.5 The Fuhrmann-Lieker et al. Model -- 2.7 Oscillatory Behavior -- 2.7.1 Reproduction of Experimental Data -- 2.7.2 Coupling to External Rhythms -- 2.8 Conclusion -- Acknowledgment -- References -- Chapter 3 On the Mathematical Description of Diatom Algae: From Siliceous Exoskeleton Structure and Properties to Colony Growth Kinetics, and Prospective Nanoengineering Applications -- 3.1 Introduction |
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3.2 Hierarchical Structuring of Matter: Diatom Algae and the Bio-Assisted Nanostructured Additive Manufacturing Paradigm -- 3.3 Structural Design of Diatom Frustules -- 3.4 Mechanical Performance of Diatom Frustules -- Experimental Characterization -- 3.4.1 Nanoindentation Testing of Diatom Frustules -- 3.4.2 AFM Studies of Diatom Frustules -- 3.5 Engineering Applications of Diatomaceous Earth -- 3.6 NEMS/MEMS Perspective -- 3.7 On the Mathematical Description of Self-Organized Diatom Frustule Growth -- 3.8 On the Kinetics of Diatom Colony Growth -- 3.9 Advanced Pattern Analysis of the Hierarchical Structure of Diatom Frustules -- 3.10 Concluding Remarks -- Acknowledgement -- References -- Part II: Diatom Development, Growth and Metabolism -- Chapter 4 Ring to the Linear: Valve Ontogeny Indicates Two Potential Evolutionary Pathways of Core Araphid Diatoms -- 4.1 Introduction -- 4.2 Material and Methods -- 4.2.1 Fragilaria mesolepta -- 4.2.2 Staurosira binodis -- 4.2.3 Induction of Synchronous Division -- 4.2.4 Electron Microscopy -- 4.3 Results -- 4.3.1 Fragilaria mesolepta -- 4.3.2 Staurosira binodis -- 4.4 Discussion -- 4.5 Conclusion -- References -- Chapter 5 Mathematical Basis for Diatom Growth Modeling -- 5.1 Introduction -- 5.2 General Physiology of Diatoms -- 5.3 Mathematical View of Diatom Growth -- 5.4 Physical Basis for Diatom Modeling -- 5.4.1 Diatom Dimensions -- 5.4.2 Ambient Temperature -- 5.4.3 Light Intensity and Duration -- 5.5 Review of Existing Mathematical Models -- 5.5.1 Gompertz Model -- 5.5.2 Monod Model -- 5.5.3 Michaelis-Menten Model -- 5.5.4 Droop Model -- 5.5.5 Aquaphy Model -- 5.5.6 Mechanistic Model -- 5.6 Results -- 5.7 Conclusion -- 5.8 Prospects -- References -- Chapter 6 Diatom Growth: How to Improve the Analysis of Noisy Data -- 6.1 Introduction -- 6.1.1 What is a Growth Curve? -- 6.1.2 Why Measure Growth? |
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6.1.3 Diatoms and Their Growth -- 6.1.4 Growth Data Analysis and Growth Parameter Estimation -- 6.2 Simulation Trials -- 6.2.1 Methodology for the Simulation Trials -- 6.2.2 Candidate Methods for Estimating the Specific Growth Rate -- 6.2.3 Simulation Trials Results -- 6.2.3.1 Results with Only the Noise Challenge -- 6.2.3.2 Results when Crashing Occurs -- 6.2.3.3 Results when Censoring Occurs -- 6.2.3.4 Overall Results and Ranking of the Methods -- 6.3 Empirical Example -- 6.4 Conclusions and Recommendations -- References -- Chapter 7 Integrating Metabolic Modeling and High-Throughput Data to Characterize Diatoms Metabolism -- 7.1 Introduction -- 7.2 Characterization of Diatom Genomes -- 7.2.1 Available Genomics Data -- 7.2.2 Computational Tools to Allocate Gene Functions by Subcellular Localization -- 7.3 Metabolic Modeling of Diatoms: Data and Outcomes -- 7.3.1 Using Genomic Information to Build Genome-Scale Metabolic Models -- 7.3.2 Comprehensive Diatom Omic Datasets Are Useful to Constrain Metabolic Models -- 7.3.3 Unraveling New Knowledge About Central Carbon Metabolism of Diatoms -- 7.3.4 Light-Driven Metabolism that Enables Acclimation to High Light Intensities -- 7.4 Modeling Applications to Study Bioproduction and Genome Changes in Diatoms -- 7.4.1 Predicting Diatom-Heterotroph Interactions and Horizontal Gene Transfer Using Community Metabolic Models -- 7.4.2 Optimization and Scale-Up of the Production of Valuable Metabolites -- 7.4.3 Potential for the Study of Proteome Allocation in Diatoms -- 7.5 Conclusions -- References -- Part III: Diatom Motility -- Chapter 8 Modeling the Synchronization of the Movement of Bacillaria paxillifer by a Kuramoto Model with Time Delay -- 8.1 Introduction -- 8.2 Materials and Methods -- 8.3 Time Dependence of the Relative Motion of Adjacent Diatoms |
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8.4 Modeling Interacting Oscillators of a Bacillaria Colony -- 8.4.1 Observation of the Movement Activity at Uncovered Rhaphes -- 8.4.2 Interaction of Neighboring Diatoms -- 8.4.3 Coupled Oscillators -- 8.5 Kuramoto Model -- 8.5.1 Adaptation of the Kuramoto Model for a Bacillaria Colony -- 8.5.2 Analyses and Approximations -- 8.5.3 Critical Coupling -- 8.5.3.1 Uncoupled Oscillators -- 8.5.3.2 Two Oscillators -- 8.5.3.3 Chains without Retardation -- 8.5.3.4 Identical Oscillator Frequencies and Sufficiently Small Delay -- 8.5.3.5 Remarks on the General Case -- 8.5.4 Statistical Considerations and Monte Carlo Simulations -- 8.5.4.1 Expected Value and Standard Deviation -- 8.5.4.2 Distribution of Critical Coupling -- 8.5.5 Simulation of Non-Synchronous States -- 8.5.5.1 Numerical Integration -- 8.5.5.2 Visualization of the Transient -- 8.5.5.3 Discrete Fourier Transform -- 8.5.6 Coupling to a Periodic Light Source -- 8.6 Discussion -- Acknowledgment -- References -- Chapter 9 The Psychophysical World of the Motile Diatom Bacillaria paradoxa -- Abbreviations -- 9.1 Introduction -- 9.1.1 Aneural Architecture of Bacillaria -- 9.1.2 Aneural Cognition in a Broader Context -- 9.1.3 Psychophysics as Diatom Information Processing -- 9.1.4 Information Processing and Aneural Cognition -- 9.1.5 Hebbian Intelligence and Predictive Processing -- 9.2 Measurement Techniques -- 9.2.1 Weber-Fechner Law -- 9.2.2 Connectionist Network -- 9.2.3 Algorithmic Information -- 9.2.4 Collective Pattern Generator -- 9.2.5 Dynamical States of the CoPG -- 9.3 CPGs vs. CoPGs -- 9.3.1 Potential of Predictive Processing -- 9.3.2 Phase Transitions in Bacillaria Movement -- 9.4 Aneural Regulation -- 9.5 Broader Picture of Intelligence and Emergence -- 9.5.1 Pseudo-Intelligence -- 9.6 Discussion -- Acknowledgments -- References |
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Chapter 10 Pattern Formation in Diatoma vulgaris Colonies: Observations and Description by a Lindenmayer-System -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Cultivation and Recording of Images -- 10.2.2 Formal Notation of Types of Concatenation and Splitting Processes -- 10.2.3 Methods to Observe the Processes -- 10.2.3.1 Basic Options -- 10.2.3.2 Long-Term Observations -- 10.2.3.3 Analysis of Single Images -- 10.3 Results -- 10.3.1 Observation of Elementary Splitting Processes -- 10.3.2 Observation of Synchronism -- 10.3.3 Observation of the Processes and Appearance of Colonies -- 10.3.3.1 Splitting of Elements of Types c and d -- 10.3.3.2 Splitting of Elements of Types a and b -- Dynamic Analysis -- 10.3.3.3 Separation of Elements of Types a and b -- Static Analysis -- 10.3.3.4 Dependence on Environmental Parameters -- 10.3.4 Theory Formation -- 10.3.4.1 Description of the Asymmetry -- 10.3.4.2 Lindenmayer System -- 10.3.5 Outer Shape of the Colonies -- 10.4 Discussion -- Acknowledgment -- Appendix 10A: Calculation Scheme -- Appendix 10B: Accordance with the D0L-System -- References -- Chapter 11 RAPHE: Simulation of the Dynamics of Diatom Motility at the Molecular Level -- The Domino Effect Hydration Model with Concerted Diffusion -- 11.1 Introduction -- 11.2 Parameters -- 11.3 Ising Lattice Modeling -- 11.4 Allowing Bias -- 11.5 Computer Representation -- 11.6 The Roles of the Cell Membrane, Canal Raphes, and the Diatotepum -- 11.7 Raphan and the Raphe -- 11.8 The Jerky Motion of Diatoms -- 11.9 Diffusion and Concerted Diffusion of Raphan -- 11.10 Shear and Janus-Faced Causation: Motility and Raphan Tilting -- 11.11 The Domino Effect Causes Size Independence of Diatom Speed -- 11.12 Quantitating the Swelling of Raphan in the Diatom Trail -- 11.13 A Schematic of Raphan Discharge -- 11.14 Transitions of Raphan |
| Summary |
THE MATHEMATICAL BIOLOGY OF DIATOMS This book contains unique, advanced applications using mathematics, algorithmic techniques, geometric analysis, and other computational methods in diatom research. Historically, diatom research has centered on taxonomy and systematics. While these topics are of the utmost importance, other aspects of this important group of unicells have been increasingly explored in the biological sciences. While mathematical applications are still rare, they are starting take hold and provide an extensive avenue of new diatom research, including applications in multidisciplinary fields. The work contained in this volume is an eclectic mix of analytical studies on diatoms. Mathematical treatment of the various biological disciplines covered in this book range from implicit, but succinct studies to more elaborate detailed computational studies. Topics include growth models, nanostructure, nanoengineering, cell growth, araphid diatoms, valve ontogeny, diatom metabolism, diatom motility, synchronization, diatom kinematics, photonics, biogenic sensors, photochemistry, diatom light response, colony growth, siliceous unicells, algal kinetics, diatom structure, diatom imaging, functional morphology, geometric structure, biomineralization, high-resolution imaging, non-destructive imaging, and 3D structure. This wide-ranging volume provides an introductory as well as an advanced treatment of recent interests in diatom research. The mathematical research in this volume may be applicable to studies of other unicells, biomechanics, biological processes, physio-chemical analyses, or nanoscience |
| Notes |
Description based on online resource; title from digital title page (viewed on April 27, 2023) |
| Subject |
Diatoms.
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Diatoms
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| Form |
Electronic book
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| Author |
Pappas, Janice L., editor
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| ISBN |
9781119751939 |
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1119751934 |
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9781119751922 |
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1119751926 |
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