## Tomaso Zambelli: Catalogue data in Autumn Semester 2020 |

Name | Prof. Dr. Tomaso Zambelli |

Address | Inst. f. Biomedizinische Technik ETH Zürich, GLC F 12.2 Gloriastrasse 37/ 39 8092 Zürich SWITZERLAND |

Telephone | +41 44 632 45 75 |

zambelli@biomed.ee.ethz.ch | |

Department | Information Technology and Electrical Engineering |

Relationship | Adjunct Professor |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

227-0393-10L | Bioelectronics and Biosensors | 6 credits | 2V + 2U | J. Vörös, M. F. Yanik, T. Zambelli | |

Abstract | The course introduces the concepts of bioelectricity and biosensing. The sources and use of electrical fields and currents in the context of biological systems and problems are discussed. The fundamental challenges of measuring biological signals are introduced. The most important biosensing techniques and their physical concepts are introduced in a quantitative fashion. | ||||

Objective | During this course the students will: - learn the basic concepts in biosensing and bioelectronics - be able to solve typical problems in biosensing and bioelectronics - learn about the remaining challenges in this field | ||||

Content | L1. Bioelectronics history, its applications and overview of the field - Volta and Galvani dispute - BMI, pacemaker, cochlear implant, retinal implant, limb replacement devices - Fundamentals of biosensing - Glucometer and ELISA L2. Fundamentals of quantum and classical noise in measuring biological signals L3. Biomeasurement techniques with photons L4. Acoustics sensors - Differential equation for quartz crystal resonance - Acoustic sensors and their applications L5. Engineering principles of optical probes for measuring and manipulating molecular and cellular processes L6. Optical biosensors - Differential equation for optical waveguides - Optical sensors and their applications - Plasmonic sensing L7. Basic notions of molecular adsorption and electron transfer - Quantum mechanics: Schrödinger equation energy levels from H atom to crystals, energy bands - Electron transfer: Marcus theory, Gerischer theory L8. Potentiometric sensors - Fundamentals of the electrochemical cell at equilibrium (Nernst equation) - Principles of operation of ion-selective electrodes L9. Amperometric sensors and bioelectric potentials - Fundamentals of the electrochemical cell with an applied overpotential to generate a faraday current - Principles of operation of amperometric sensors - Ion flow through a membrane (Fick equation, Nernst equation, Donnan equilibrium, Goldman equation) L10. Channels, amplification, signal gating, and patch clamp Y4 L11. Action potentials and impulse propagation L12. Functional electric stimulation and recording - MEA and CMOS based recording - Applying potential in liquid - simulation of fields and relevance to electric stimulation L13. Neural networks memory and learning | ||||

Literature | Plonsey and Barr, Bioelectricity: A Quantitative Approach (Third edition) | ||||

Prerequisites / Notice | The course requires an open attitude to the interdisciplinary approach of bioelectronics. In addition, it requires undergraduate entry-level familiarity with electric & magnetic fields/forces, resistors, capacitors, electric circuits, differential equations, calculus, probability calculus, Fourier transformation & frequency domain, lenses / light propagation / refractive index, Michaelis-Menten equation, pressure, diffusion AND basic knowledge of biology and chemistry (e.g. understanding the concepts of concentration, valence, reactants-products, etc.). | ||||

227-0939-00L | Cell Biophysics | 6 credits | 4G | T. Zambelli | |

Abstract | A mathematical description is derived for a variety of biological phenomena at the molecular and cellular level applying the two fundamental principles of thermodynamics (entropy maximization and Gibbs energy minimization). | ||||

Objective | Engineering uses the laws of physics to predict the behavior of a system. Biological systems are so diverse and complex prompting the question whether we can apply unifying concepts of theoretical physics coping with the multiplicity of life’s mechanisms. Objective of this course is to show that biological phenomena despite their variety can be analytically described using only two concepts from statistical mechanics: maximization of the entropy and minimization of the Gibbs free energy. Starting point of the course is the probability theory, which enables to derive step-by-step the two pillars of statistical mechanics: the maximization of entropy according to the Boltzmann’s law as well as the minimization of the Gibbs free energy. Then, an assortment of biological phenomena at the molecular and cellular level (e.g. cytoskeletal polymerization, action potential, photosynthesis, gene regulation, morphogen patterning) will be examined at the light of these two principles with the aim to derive a quantitative expression describing their behavior according to experimental data. By the end of the course, students will also learn to critically evaluate the concepts of making an assumption and making an approximation. | ||||

Content | 1. Basics of theory of probability 2. Boltzmann's law 3. Entropy maximization and Gibbs free energy minimization 4. Two-state systems and the MWC model 5. Random walks and macromolecular structures 6. Electrostatics for salty solutions 7. Elasticity: fibers and membranes 8. Diffusion and crowding: cell signaling 9. Molecular motors 10. Action potential: Hodgkin-Huxley model 11. Photosynthesis 12. Gene regulation 13. Development: Turing patterns 14. Sequences and evolution | ||||

Literature | - Statistical Mechanics: K. Dill, S. Bromberg, Molecular Driving Forces, 2nd Edition, Garland Science, 2010. - Biophysics: R. Phillips, J. Kondev, J. Theriot, H. Garcia, Physical Biology of the Cell, 2nd Edition, Garland Science, 2012. | ||||

Prerequisites / Notice | Participants need a good command of differentiation and integration of a function with one or more variables (calculus) as well as of Newton's and Coulomb's laws (basics of mechanics and electrostatics). Notions of vectors in 2D and 3D are beneficial. Theory and corresponding exercises are merged together during the classes. |