Upload
others
View
5
Download
0
Embed Size (px)
Citation preview
Dai biomateriali ai sistemi olfattivi artificiali per la caratterizzazione di
campioni biologici
Arnaldo D’Amico, Marco Santonico, Giorgio Pennazza
XCVIII Congresso Nazionale Napoli, 17-21 Settembre 2012
About us
Roma Downtown
Fiumicino airport Roma - Napoli
highway
Tor Vergata University
GRA highway
Campus Bio-Medico
Laurentina
ROME
Outline
Introduction
Sensors and nanosensors definitions
Chemical interactive materials
Artificial olfactory systems
Medical applications
About us
• Tor Vergata University • Campus Bio-Medico • Founded in 1980
• 6 faculties
– Human sciences; Engineering, Sciences, Economics, Law, and Medicine
• ≈ 20000 students
• The largest campus in Italy
Founded in 1993
2 faculties
Medicine and Biomedical Engineering
As university it is a unique case in Italy promoting a close collaboration between Physicians and Engineers
SENSORS AND NANOSENSORS: OVERVIEW
Quantities
physical
chemical
biological
nanosensors
sensors
Environmental
Bio- suffix: Devices having the
sensing part made by biological
material
Scale [m]
1
10-9
10-6
10-3
Interactions
Physical sensors:
Devices able to sense
physical quantities.
Example: acceleration
Sensors and Sensors and nanosensorsnanosensors definitionsdefinitions
Physical nanosensors:
Nanodevices able to sense
physical quantities
ST three-axis accelerometer
(A Sanz-Velasco et al. 2006 Solid-State
Electron. 50 S865)
Nanoindentor:The force range is up
to 500 µN and 1 mN for the two main
designs, with a force resolution of to
0.3 µN.
Example: Force
Nanotube: force sensors
Chemical sensors: Devices
able to sense chemical
quantities.
Sensors and Sensors and nanosensorsnanosensors definitionsdefinitions
Chemical nanosensors:
Nanodevices able to sense
chemical quantities.
CMOS
MOSFET(Pd)
Nanosensors used
to measure cancer
biomarkers in whole
blood.
Nanowire Pd
Biological sensors
devices able to sense
biological quantities.
Biological nanosensors
Nanodevices able to sense
biological quantities.
Surface plasmon resonance detection of
ligand binding
Localized plasmon resonance
Plasmon resonance
Sensors and Sensors and nanosensorsnanosensors definitionsdefinitions
BBIOSENSORSIOSENSORS DEFINITIONDEFINITION Biosensors: devices having the sensing part made
by biologic materials;
Chemical biosensors Devices
having the sensing part made by
biologic materials and sensitive
to chemical quantities. Dioxin sensor
Biological biosensors
Devices having the
sensing part made by
biologic materials and
sensitive to
biomaterials. Penicillin sensitive Enzyme
modified FET (EnFET)
Physical biosensors Devices having
the sensing part made by biologic
materials and sensitive to physical
quantities.
Pressure sensitivity of luminescent porphyrins: pressure
sensitive paint
NNANOSENSORSANOSENSORS DDEFINITIONEFINITION Nanobiosensors: Nanodevices having the sensing part
made by biologic materials
Chemical nanobiosensors
Nanodevices having the sensing
part made by biologic materials
and sensitive to chemicals. Example:Heavy metal detection by peptide
modified SWNT based FET Sensitivity to Ni2+
Biological nanobiosensors:
nanodevices having the
sensing part made by biologic
materials and sensitive to
biomaterials.
Physical nanobiosensors:
Nanodevices having the
sensing part made by
biologic materials and
sensitive to physical
quantities.
Diazotation of sulfanilic acid with NO2 at slopes on (010)
SNOM image
SSENSORSENSORS ANDAND NANOSENSORSNANOSENSORS: : OVERVIEWOVERVIEW
SSENSORSENSORS ANDAND NANOSENSORSNANOSENSORS: : OVERVIEWOVERVIEW
Many devices are today available to induce a property change (r, s, ..) from
a change of concentration of a given volatile compound
CCHEMICALHEMICAL INTERACTIVEINTERACTIVE MATERIALSMATERIALS
Numerous may be the effects deriving from the interactions between
the CIM and the Enviroment:
heat generation followed by a temperature increase;
changes of one of the following parameters: electronic charge,
mass, conductivity, refractive index, work function, photon
emission.
Varieties of CIMs are available for chemical and biosensing such as:
metal oxide semiconductors (SnOx,TiOx,Ta2O5,IrOx,WO2..), Metals
(Pt,Pd,Ni,Ag,Cr,Sb,K,);
ionic conductors (ZrO2, LaFx, CaFx, CeO2, Nasicon);
polymers (polipirrole, poliphenilacetilene, cellulose, poliuretane,
policarbonate, porphyrines, phtalocianines, polisiloxenes,..);
enzimatic systems (glucose-oxidase, lattosio-oxidase, urease, anti-
IgG, anilisteria,..)
Sensing:
CIM Transducing:
QMB Metallo
porphyrins
Film deposition
Molecular
film molecule
s
mA
ff D×-=D
rm
2
0
02
TTOROR VVERGATAERGATA ELECTRONICELECTRONIC NOSENOSE
Olfactive neuron::
many non specific many non specific
receptors receptors
of the same kindof the same kind
Artificial olfaction sensor::
many non specific many non specific
Receptors Receptors
of the same kindof the same kind
L. Buck and R. Axel; Cell 1991
N N
N N
N N
N N
N N
N N
N N
N N
OOLFACTIVELFACTIVE MAPSMAPS COMPARISONCOMPARISON
WWHYHY GASGAS SENSORSENSOR ARRAYARRAY??
It emerges that there is a number of molecular families whose alteration in concentration may be related to the presence of specific diseases.
The presence of the disease then produces a pattern of VOCs that are distinct (in concentration) from that found in healthy subjects.
This is a typical situation where a chemical sensor array can be applied.
VOCVOCSS ANALYSISANALYSIS ININ MEDICINEMEDICINE
Metabolic profile
Basic cellular functions including maintenance of cell membrane integrity, energy metabolism and especially oxidative stress are all known to be linked with VOC formation.
(Horvath et al., Eur Respir J 2009; 34: 261–
275)
VOCVOCSS ANALYSISANALYSIS ININ MEDICINEMEDICINE
D'Amico, A., et al. Detection and identification of cancers by the electronic nose. 2012. Expert Opinion on
Medical Diagnostics 6 (3) , pp. 175-185
TTOROR VVERGATAERGATA--CCAMPUSAMPUS BBIOIO--MEDICOMEDICO DIDI RROMAOMA
MEDICALMEDICAL APPLICATIONSAPPLICATIONS
DISEASE ANALYTE MEDICAL PARTNER
(ALL BASED IN ROME)
Schizophrenia sweat Italian Hospital Group
Lung cancer breath C. Forlanini Hospital
Asthma breath Catholic University of
Sacred Hearth
COPD breath Campus Bio-Medico di Roma
Bladder cancer urine Villa Pia Private Hospital
Prostate cancer urine “Tor Vergata” Hospital
Breast cancer skin San Eugenio Hospital
Melanoma skin Italian Dermopathic
Institute
Tumor cells :
in vitro and xenografted on animal
models
headspace Sant’Andrea Hospital
LLUNGUNG CANCERCANCER
Lung cancer studies with gas sensor arrays
2012
2010
LUNG CANCER Five research groups
Tor Vergata University,
Rome, Italy
Campus Bio-Medico di Roma
Rome, Italy
The Cleveland Clinic,
Cleveland, Ohio, United States
Zhejiang University, Hangzhou, China
Israel Institute of Technology, Haifa, Israel
Academic Medical Center, Amsterdam, Netherlands
LUNG CANCER, 2012
LUNG CANCER, 2012
METHOD
For
VOCs extraction
Via
endoscopy
Lung Cancer, 2012
Population Classification
NEGATIVE vs CANCER
ADK vs SCC
PPEOPLEEOPLE WITHWITH AASTHMASTHMA
Asthma is a common life-long chronic disease characterised by inflammation and narrowing of the airways. The narrowing does not occur all the time in mild asthma, but it happens more often as asthma gets more severe. It may also vary over short periods of time by itself or as a result of treatment
Symptoms can be controlled Symptoms of asthma include: Wheezing shortness of breath chest tightness and cough. Symptoms improve with appropriate treatment, so much so that treatment fails to control symptoms in only 5% of patients.
•Breath sampling for dead space (blu)
•Alaveolar space (red)
Alveolar volume segregation:Alveolar volume segregation:
ENOSEENOSE--GCGC--MS sampling protocolMS sampling protocol
Montuschi et al., Chest 2010
ENOSEENOSE--GC/MS: SGC/MS: SAMPLINGAMPLING PROTOCOLPROTOCOL
Total volume
Alveolar
breath
Montuschi et al., Chest 2010
COMPARISON OF DIFFERENT TECNIQUES
USED FOR ASTHMA DIAGNOSIS
Montuschi et al., Chest 2010
AASTHMASTHMA: GC: GC--MS MS RESULTSRESULTS
Principal component analysis (PCA) of mass spectrometry fingerprinting of patients with asthma and healthy subjects
Montuschi et al., Chest 2010
COPD DIAGNOSIS
Raffaele, Antonelli Incalzi, et al, Reproducibility and respiratory
function correlates of exhaled breath fingerprint in chronic
obstructive pulmonary disease , PLoS ONE (2012) in press
o Capuano, R., Santonico, M., Martinelli, E., Pennazza, G.,
Paolesse, R., Bergamini, A., et al. (2010). COPD diagnosis
by a gas sensor array. Paper presented at the Procedia
Engineering, , 5 484-487
COPD in elderly
REPRODUCIBILITY CONTROL INDIVIDUAL
COPD in elderly
REPRODUCIBILITY GOLD 4
COPD in elderly
TEST
CONFUSION MATRIX
predicted
0 1-2-3 4
real 0 5 0 0
1-2-3 0 12 3
4 0 0 5
Melanoma
Scientific background
Melanoma
Experiment
flow-chart
Melanoma
Measure phase
Cleaning phase
General overview
Sampling protocol
Melanoma
Measure strategy
Melanoma
1 2 3 4 5 6 7
0
20
40
60
80
100
120
140
Hz
Sensors
1 2 3 4 5 6 7
0
20
40
60
80
100
120
140
Hz
Sensors
diffe
rential df
nevi boxplot melanoma boxplot
BOXPLOTS OF ENOSE PATTERNS
diffe
rential df
Ref. Bernabei, M., Pennazza, G., Santonico, M., Corsi, C., Roscioni, C., Paolesse, R., et al. (2008). A preliminary study on the possibility to diagnose urinary tract cancers by an electronic nose. Sensors and Actuators, B: Chemical, 131(1), 1-4.
Analyte : urine
BLADDER CANCER
TNM Classification
Jewett-Strong Marshall
Definition
Tis 0 Limited to mucosa, flat insitu
Ta 0 Limited to mucosa, papillary
T1 A Lamina propria invaded
T2a B1 < halfway through muscularis
T2b B2 > halfway through muscularis
T3 C Perivesical fat
T4a C Prostate, uterus or vagina
T4b C Pelvic wall or abdominal wall
N1-N3 D1 Pelvic lymph node(s) involved
M1 D2 Distant metastases
Classification proposed by Jewett on 1946 and
revised by Marshall in 1956 (American Urologic
System).
Extr. From: http://training.seer.cancer.gov/
35-47%
50 %
(5%)
95%
recidivism mortality
development of disease and mortality
STATISTICAL
0: control
1: disease
6: post surgical
-0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
1 1
1
1
1 1
1 1
1
1
1
1 1 1
1 1 1
1 1 1
1 1
1 1 1 1 1
1 1
1 6 6
1
1
1 1
1
1 1 1 1
1
1
1
1
1 1 1 1 1 1 1 1
1 1 6 6 6
6 6 6
1
1
1 1
1
6 6
1 1
1
1 1
1 1 6 6
1 1 1 1 1 1
1
1
1 1 1 1 1
1
1 1
1 1 1 1 1
1
1
1
1
1
1 1
1 1 1 1 1 1
6 6
6 0 0 0
0 0 0 0
0
0 0
0
0
0
0 0 0
0 0
1
PC 1 (50.19%)
PC
2 (
27.5
4%
)
Scores Plot
desease
Healthy
Post surgery
patients
Scores plot of the first two components of PCA model
ELECTRONIC NOSE RESULTS
Analyte : urine
A NOVEL APPROACH FOR
PROSTATE CANCER
DIAGNOSIS USING A GAS
SENSOR ARRAY
Digital rectal
examination is the
first diagnostic
approach
transrectal
ultrasound Biopsy Prostate Specific
Antigene
Diagnostic Diagnostic iteriter
Non invasive
approach
Canine
olfaction
Invasive
approach
Artificial olfactory system
Pilot study:primliminary resultsPilot study:primliminary results
ENOSE
reference
sample
200 sec 600 sec
Scores plot of the first two
latent variables obtained
by PLS-DA model.
The result has been
obtained considering the
first part of urine.
In this case two control
subjects have been
misclassified as ill
subjects.
D'Amico, A., et al. Detection and identification of cancers by
the electronic nose. 2012. Expert Opinion on Medical
Diagnostics 6 (3) , pp. 175-185