NE 301 Lec 1 Sensors Notes

7/31/2019 NE 301 Lec 1 Sensors Notes

http://slidepdf.com/reader/full/ne-301-lec-1-sensors-notes 1/20

1B(NE102)Module1: NanomaterialsHealthRisk

Assessment

HazardIden*fica*on,RiskAssessment,Exposure

Assessment;ExternalandInternalDose;ReferenceDose;HazardIndex;Life*meCancerRisk;

2A(Ne201)Module2: Nanotoxicology

ADME;Inhala*onEffectsandTransloca*on;DermalEffects;Oxida*veStress;Cytotoxicity;Neurotoxicity;

Genotoxicity,MutagenicityandCancer;

PreviousMilestoneLectures

UniversityofWaterloo;NanomaterialHealthRiskMilestone;Dr.L.Deakin



2B(NE202)Module3:

NanomaterialsExposureAssessmentand

Ecotoxicology

Howtoprotectyourself :Occupa*onalExposure

Assessment;Sampling;Nanometrics;masks/gloves

Howtoprotecttheenvironment :Environmental

FateandTransportProcesses,Ecotoxicology;

Aqua*cToxicology;Biopersistence;

Biomagnifica*on;


PreviousMilestoneLectures



3AModule4: NanomaterialsConsumerProducts

Whatdoweknowaboutthenanostuffoutthere?

SensorsandScreening;Sensi*vityandSpecificity;

Posi*ve/Nega*vePredic*veValues;ConsumerProducts(TiO2,Ag,CNT…);ConsumerExposureand

diseaserisks;Cosme*cs;ProductLifeCycleanalysis

3BModule5: NanomaterialsRisksandBenefits

Howwouldyouknowifitaffec;nghumans?

Epidemiology;Howtocomparedifferenthuman

groups;Rela*verisksandOddsra*os;Confounding;

Eng.andnon-engineeredUltrafines;DieselExhaust;

Current/FutureMilestoneLectures





Using Nanoparticles:

Making and Understanding Sensors and

Medical Screening Devices




Cash2010TrendsMolec.Med.16:584

BETTER SENSORS: CNT and Diabetes

Nanodevices are beingproposed as better

alternative to current

sensors:

Based on redox active

CNT/metal/metal oxide

electrode: enzymatic redox

conversion of glucose

Current sensors suffer from

limited lifetime immune

response to sensor.




NEW SENSORS: Gold and Cancer

Bind volatile organic compounds that are knownmarkers for cancer; based on chemoresistance

Au particles show different

patters from healthy and

lung cancer patients

Mazzone2009NatureNanotech4:621

DrHaickChemEng.NanotechInst,Ben-GurionUniv.,Israel




Thiol-capped

5 nm Au particles

~ 75% effectiveness

at catching those

with lung tumors

~ 25% falsenegative rate

…what is impact

of false negative?Peng2009Nature

Nanotech4:669

Healthy

Lung Cancer

Analysis by

GCMS

HS-CH2-CH2-R

NEW SENSORS: Gold and Cancer




When you compare your test (or device) toanother (say industry standard) or to the actual

state of patients, there are two important testresults; Sensitivity and Specificity

Comparing your test to the ‘real’ answer

Disease State or

standard test

+ -

# your

sensor

+

-

true +

false -

false +

true -




Sensitivity : is the probability that a test result ispositive when administered to someone who has

the disease.

SEN =


+ -

# your

sensor

+

-

true +

false -

false +

true -

Disease State or

standard test





Specificity: is the probability that a test result is

negative when administered to someone who does

not have the disease.

SPEC =

+ -

# your

sensor

+

-

true +

false -

false +

true -

Disease State or

standard test




Low sensitivity could mean that:

_______________________________________

Low specificity would mean that:

_______________________________________

+ -

# your

sensor

+

-

true +

false -

false +

true -

Which is

more

important,sensitivity or

specificity?


Disease State or standard test





Standard Yours1. - +

2. + +

3. - -4. + +

5. - -

6. + +

7. - -8. - -

9. - +

10. + -

You make a device to testfor a disease and compare

your test to the currently

used standard. 10 samples

compare the tests.

What is the sensitivity and

specificity for your device?




When you are handed a positive test, what you

want to know is whether it is real…

Positive Predictive Value PPV : the probability

that a person with a positive result actually has the

disease.

PPV = _______________

# Disease State+ -

# your

sensor

+

-

true +

false -

false +

true -

What if they told you your test was positive?




When you are handed a negative test, what you

want to know is whether it is real…

Negative Predictive Value NPV: the probability

that a person with a negative result actually has no

disease.

NPV = ___________

# Disease State+ -

# your

sensor

+

-

true +

false -

false +

true -

What if they told you your test was negative?




About Sensors: Specific Example HIV

You’ve made a sensor for HIV

It is used on 100,000 people. Of the 500 HIV-

positive people, 475 tested positive, and of the

HIV-negative group, 94,525 tested negative.

Determine the sensitivity, specificity, positive-

predictive and negative-predictive values.

What’s going on with the +’ve pred. value?




About Sensors: Specific Example HIV

Generally, if prevalence is low, PPV is also low.

Low PPV means lots of False Positives:

False positives: Type I errors:

- you rejected the null hypothesis when the null

hypothesis was true. You accused the wrong guy…

False negatives: Type II errors:- failure to reject the null hypothesis when the null

hypothesis is true. You let the bad guy go…




About Sensors: ELISA HIV

HIV antigen protein on a surface reacts with antibodies

in blood from someone infected with HIV. Antibodies

are enzyme linked for detection.

High sensitivity: even low levels of antibody detected.Some people without HIV will still have non-specific

binding (other antibodies) that leads to some

fluorescence: what is cutoff ? Lower specificity.

HIV test measuring fluorescence

from HIV antibody in enzyme-linked

immunosorbent assay (ELISA).




Op*caldensityra*o(fluorescenceintensity)

#people

HIV-free withHIV

ABC

A,B,C: cutoffs in optical density to separate positive

(high density) from negative (low density) result.

About Sensors: ELISA HIV

A: large number of false-positives, no FN

B: lower FP but now also FNC: no FP, but high FN

Forinfec*ous

diseases,choosenoFN;thenretest

allposi*ves




About Sensors: Western Blot

1 .Gel electropheresis separates out byelectropheretic mobility blood proteins and looks

for HIV proteins.

2. Proteins are moved from gel into separate

membrane by ‘blotting ’, by capillary action.

3. Expensive human antibodies are used to bind to

the HIV proteins.

4. Antibody is linked to fluorescent enzyme that isactivated upon binding.

Antibodies are very structure specific, wrong binding

does not occur; No false positives: High spec.




ELISA

TP + FP TN (no FN)

WESTERNBLOT

TP (no FP)

+ -

+ -

TN (+ FN)

HIGHSEN:strongbinding

HIGHSPEC:specificbinding

HIV: Run the Cheap Sensor First

NE 301 Lec 1 Sensors Notes

Documents

Transcript of NE 301 Lec 1 Sensors Notes