Biotechnologies in molecular diagnostics and fundamental of statistics

A.Y. 2018/2019
Overall hours
BIO/12 MED/01 MED/05 MED/36
Learning objectives
Acquire knowledge on the organization of the clinical diagnostic laboratory and of principles and methodologies associated to the most advanced diagnostic techniques.
Definition of diagnostic biomarker, characteristics of the main biomarkers currently used in clinical diagnostics of different human diseases and in clinical and traslational research.
Acquire the knowledge related to the basic principles of the main non-invasive diagnostic techniques (RX, TAC, Nuclear-based techniques, Ultrasound, MRI, Optical imaging) and the biomarkers assessed by using these procedures
Understand the potential of different imaging techniques and potential applications in clinical and preclinical / experimental settings.
Acquire basic knowledge on the relationship between scientific and statistical method with reference to the problems of measurement in biomedicine with the basics of the planning of experiments.
Expected learning outcomes
To know the limits and applicability of the different methods used in advanced clinical diagnostics. To be able to choose between different methodologies.
To apply the use of different biomarkers and diagnostic criteria related to different human diseases.
To understand the potential of different imaging techniques and potential applications in clinical and preclinical / experimental settings.
Knowing how to interpret the results of the different clinical diagnostic methods on a statistical basis. Knowing how to use the basic statistical methods for data analysis in biomedical research.
Course syllabus and organization

Single session

Lesson period
First semester
Modulo: Biotecnologie in diagnostica
Course syllabus
Clinical Biochemistry:
Definition and purposes. Organization of the clinical diagnostic laboratory. Collection and storage of biological samples.
Sample preparation
Capillary zone electrophoresis (CZE): principles and applications
HPLC / nano HPLC: principles and applications.
Coating techniques of surfaces for CZE and ELISA applications
ELISA: principles and applications
Proteomics and metabolomics: principles
Mass spectrometry: principles
Mass spectrometry: applications

Clinical Pathology:
definition of biomarkers and their characteristics
metalloproteinases as biomarkers of bony pathologies
metalloproteinases as biomarkers of cardiovascular diseases
chemokines as pathology biomarkers
tumor biomarkers
introduction to osteoimmunology and osteoimmunology biomarkers
biomarkers of prosthetic infection
Modulo: Statistica nella sperimentazione biomedica
Course syllabus
Diagnostic Imaging
Non-invasive techniques: anatomical and functional studies, difference between structure and function, advantages and disadvantages, possible combinations.
Principles and applications of X-Ray based techniques: principles, imaging biomarkers, instrumentation, applications
Ultrasound imaging: principles and applications: principles, Doppler effect, imaging biomarkers, available instrumentation, applications
Principles and applications of nuclear imaging techniques: principles about radioactivity, radioactive decays, decay products, instrumentation available, uses in diagnostics and therapy
Principles and applications of Imaging with Magnetic Resonance: principles of the technique, available instrumentation, possible applications
Principles and applications of optical imging: Bioluminescence and fluorescence concept, available instrumentation, preclinical applications
Overview of molecular and cellular imaging: tracer concept, reporter genes for non-invasive imaging, cell labelling.

Foundations of Statistics
Statistics and Scientific Method
The problem of measurement: variables and scales
Data summaries: central tendency and variability indices (descriptive statistics).
Measurements: measurement errors (Accuracy and Precision).
Biological and analytical variability
Measurements and statistical models (statistical sampling)
Statistics as a measurement method: estimation (Statistical Inference 1)
Confidence intervals
Testing hypotheses on a statistical basis (Statistical Inference 2)
Association and dependence (the linear model)
Calibration of measurement methods and regression
Experimental design and Analysis of Variance
Concordance between measurement methods.
Diagnostic test 1: sensitivity, specificity and ROC.
Diagnostic test 2: predictive values and diagnostic likelihood ratios
Clinical Epidemiology: evaluation of the effectiveness of a diagnostic or therapeutic procedure
Bioprofiles from genomic analysis.
Modulo: Biotecnologie in diagnostica
Practicals: 16 hours
Lessons: 32 hours
Modulo: Statistica nella sperimentazione biomedica
Practicals: 24 hours
Lessons: 20 hours
By appointment via e-mail
LITA Segrate - Via F.lli Cervi 93, 20090 Segrate (MI)
Monday 10am-13pm
LITA Segrate