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STATISTIC AND BIOPHYSICAL PHYSICS

Academic year and teacher
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Versione italiana
Academic year
2018/2019
Teacher
MICHELE MARZIANI
Credits
12
Didactic period
Primo Semestre

Training objectives

PHYSICS
The goal of the Physics module is to introduce the magnitudes and basic principles of Classical Physics. In particular, the topics covered aim to provide the tools necessary for understanding the physical phenomena underlying motor activities. The lessons and guided exercises will allow you to acquire the skills required to set the resolution of simple problems in this area in a scientific and quantitative way.
BIOPHYSICS
The objective of the Biophysics module is to present principles of Cellular Physiology, in particular regarding excitable cells (nerve and muscle), to discuss the phenomena that lead to the genesis and propagation of nerve impulses and to explain how these are transformed into contractions. muscles following the activation of nerve-muscle synapses. The topics covered aim to provide the tools necessary for understanding the biophysical phenomena underlying motor activities. The lessons will allow you to acquire the skills required to deal with adequate preparation courses that will follow in the three years.
STATISTICS AND DATA ANALYSIS
The aim of the course is the training of the students to the use of scientific methodology in describing and interpreting the natural phenomena of concern for the medicine applied to motion sciences. The topics of the course are chosen with reference to their usefulness in the subsequent learning activity.

Prerequisites

Elements of algebra and trigonometry. Basic functions of interest in the medical sciences.
Basic knowledge of calculus and functional analysis. Principles of cell biology

Course programme

PHYSICS
Physical quantities: scalar and vector quantities, unit of measurement: the International System. Kinematics: uniform and uniformly varied linear motion; uniform circular motion; harmonic motion; planar motions.Dynamics: forces and laws of dynamics, gravity: mass, weight and density; examples of other fundamental forces; work, potential and kinetic energy, energy conservation. Point-like particle: center of mass; rigid body; conservation of energy, linear and angular momentum; harmonic oscillator; simple pendulum. Static and dynamics of fluids: equilibrium of a fluid, pressure, Archimedes' law, effects of cohesion forces: surface tension and capillarity; continuity equation and Bernoulli's theorem; motion of a perfect fluid and a viscous fluid, examples of hydrodynamics in the bloodstream.Thermodynamics: perfect gases, heat and temperature, first principle of thermodynamics, notes on the second principle of thermodynamics.Electromagnetism: Coulomb's law, insulators and conductors; electrical circuits: current, resistance and capacity, Ohm's law.
BIOPHYSICS
BASIC PRINCIPLES: Definition of Biophysics. Water and solutions. Molecular structure of lipids, proteins and membranes. Recall of electricity: ionic and electronic conduction, current and resistance. Conductors and insulators. Ohm’s law. Resistivity and reactance. Proteins in membrane and in solution. Diffusion and osmosis. Nernst potential and Goldman-Hodgkin-Katz equation.
NERVOUS SIGNALS: Membrane channels. Resting potential. Hodgkin-Huxley model. Voltage-clamp and patch-clamp. Action potential. Graded potential and conduction of nerve fibers. Neuromuscolar junction. Excitatory and inhibitory synapses. Spatial and temporal integration of synaptic signals. Pharmacology and synapses. Receptors.
ADVANCED TECHNIQUES: Electric, magnetic and electromagnetic fields. Extracellular recording. Static and dynamic tissue imaging: PET, fPET, TAC, NMR e fNMR; temporal and spatial resolution. Fluorescence imaging and fluorophores.
STATISTICS AND DATA ANALYSIS
The course consists of two parts, a theoretical part explaining the common techniques of statistical analysis for univariate and bivariate data, and a practical part allowing the student to become familiar with some simple data analysis software code.
During the theoretical part we will introduce graphing techniques of qualitative and quantitative data, and numerical techniques for computing the common location, dispersion and shape statistics. After introducing the element of probabilistic computing, we will describe the probability distributions of discrete and continuous random variables (Binomial Distribution, Normal distribution and Standard distribution) commonly used for the analysis of qualitative and quantitative data.

Didactic methods

Lectures
STATISTICS AND DATA ANALYSIS
Lectures and Exercises to be done at home with the help of Excel programs

Learning assessment procedures

PHYSICS
Written exam consisting of 15 multiple choice questions with 5 possible answers of which only one is correct. Each correct answer is worth 2 points, each answer is not given 0 points, -0.5 points for each wrong answer. Duration 45 minutes.
BIOPHYSICS
Written exam consisting of 60 questions with answer “True” or “False”. Each correct answer represents 1 point, each wrong answer represents -1 points, each answer not given represents 0 points. A sufficient judjement (18/30) is reached obtaining 36 points. Duration 60 minutes.
STATISTICS AND DATA ANALYSIS
Written exam to be performed via the "Moodle". The student will answer to a series multiple choice and open questions, and solve some numeric exercises designed to assess the knowledge, competence and skills acquired during the lectures and computer exercises. Questions and exercises are randomly extracted from a suitable database and the assessment varied from 1 to 4 points depending on the difficulty degrees. The difficulty degrees are stated in the evaluation grid included in the task. The time allowed for the exam is one hour and the maximum possible score is 31 (30 cum laude).
THE FINAL GRADE IS A WEIGHTED AVERAGE OF THE MARKS OBTAINED IN EACH OF THE TESTS.

Reference texts

PHYSICS
Borsa, F., & Lascialfari, A., PRINCIPI DI FISICA: per indirizzo biomedico e farmaceutico, II ed. (2014) EdiSES
BIOPHYSICS
Reference texts will be provided by the teacher during the course
STATISTICS AND DATA ANALYSIS
P.S. Mann, Introductory Statistics, VIII Eds, Wiley N.Y.(2012). From the book have been made of handouts, summary slides, and a series of exercises that are available to the student.