Biotechnologies in molecular diagnostics and fundamental of statistics

A.Y. 2017/2018
Overall hours
BIO/12 MED/01 MED/05 MED/36
Learning objectives
Stressing the role of biotechnology in the health sector, the overall objective of the course is to increase our knowledge of the main techniques that have been used or will be used in the near future in the advanced diagnostics in vivo and ex vivo. This objective is supported by the study of the fundamental principles of statistics, essential for the understanding of the basic concepts of laboratory medicine.
Expected learning outcomes
The broader objective of this course is to provide, not only knowledge but, the capacity to integrate acquired information provided by different sections of the clinical diagnostic laboratory ( biochemistry, clinical pathology, statistical data analysis) to select methodologies, to analyse and interpret data and finally to transfer such findings into a to a final diagnostic management plan. Students will be able not only to demonstrate that they know but also to critically select their specific interest in different fields of the molecular diagnostic management.
Course syllabus and organization

Single session

Lesson period
First semester
Modulo: Biotecnologie in diagnostica
Course syllabus
Laboratory principles1: general laboratory techniques, procedures and safety
Laboratory principles 2: specimen collection and other preanalytical variables
Principles of clinical enzymology and diagnostic applications
Principles and immunochemical techniques and protein arrays
Nucleic Acids 1: gene espresssion profile and clinical applications
Nucleic acids 2: Metods for genotyping and epigenetic analysis
Principles of capillary zone electrophoresis and HPLC and clinical applications
Mass spectrometry
Proteomics techniques for proteome profiling of cell and tissue estracts
Proteomic techniques for proteome profiling of biological fluids and possible clinical - applications
Principles for post trasductional modifications analysis and their clinical significance
Techniques in surgical pathology
Techniques in immunohysto-cytochemistry
Techniques in molecular pathology and their clinical implication: Fluorescence in situ hybridization (FISH) analysis - Staining in pathology.
General introduction about "biomarkers" concept. Tumor biomarkers
Diagnostic biomarkers of metabolic disease
Cytokines and chemokines as disease biomarkers
Cytokines and chemokines as bone remodelling biomarkers.
The new concept of "Osteoimmunology"
Matrix metalloproteinases as new bone remodelling biomarkers.
General revision and course closure
Modulo: Statistica nella sperimentazione biomedica
Course syllabus
Non-invasive imaging techniques, Radiography Computed Tomography, PET/SPECT, MRI
Biomarker Imaging with contrast agents and tracers
Animal models and Molecular Imaging
Reporter genes and transgenic animals
Imaging of Reporter Gene expression (Bioluminescence, Fluorescence, PET, MRI)
Cell labeling and imaging
Statistics and the Scientific Method
Measurement scales
How to represent data: position and variability indexes.
Accuracy and precision.
Biological and analytical variability
Laboratory measurement and statistical models
Statistics as measurement method: model estimation
Confidence Intervals
Association and dependence
Calibration of measurement methods and Regression
Experimental design and Analysis of Variance
Concordance between measurement methods.
Diagnostic testing. Sensitivity, Specificity and ROC.
Diagnostic predictive values and likelihood ratios
Statistical hypothesis testing
Assessment of the efficacy of a diagnostic or therapeutic procedure.
Biostatistics and Genomic bioprofiling.

Calculus spreadsheet and Software R for Biostatistics: Descriptive Statistics, use of graphics and indexes in biomedical studies.
Sampling and Gaussian, Exponential and Poisson distributions in Biology
Point and interval estimation in the biotechnology lab
Bioanalitic use of regression: calibration.
Analysis of Variance and concordance between laboratory methods
Diagnostic test assessment, ROC and Fagan nomogram
Application of single and multiple statistical testing on experimental data,
Bioprofile analysis on genomic data: differential expression and cluster 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