SlideShare a Scribd company logo
Fingerprick Testing
Physics and Problems
Presented By
Achal Singh
Mtech 2nd Sem.(Nanotechnology)
Scholar No.-222105102
Seminar-2
Contents
Introduction: Story so far (Summary: Seminar1)
Biosensors and Low Dimensional Systems
Luminescence
Surface Plasmon Resonance
Drop to drop Variations
Conclusion and Current Technologies
References
The story so far
Inspiration from Theranos Story
Blood components
Traditional Blood Test Procedure
Simple Molecules
Blood Sugar Testing
Theranos Edison(conceptual)
Ref. NYT
Elizabeth Holmes(famous 1drop picture
SteveJobsesque)
Ref.WSJ
Biosensors and Low Dimensional Systems
Biosensors
Analyte
Bioreceptors
Transducers
Electronics
Display
Quantum Phenomena
Quantum Conductance
Kondo Effect
Coulomb Blockade
Biosensors and their components (Ref.-MDPI)
QPC and Quantum Conductance
(Ref.-Science)
Resistivity in Low Dimensions (Ref.-Springer)
Luminescence
Electron excitations
Characterisation
Imaging
Bioluminescence
Photoluminescence
Phosphorescence
Fluorescence
Jablonski Diagram (Ref.-Horiba)
Overall concept and design of multiplexed, real-time plasmonic RT-PCR.
(Ref.-nature)
Absorption and Scattering from whole blood.
(Ref.-NCBI)
Surface Plasmon Resonance(SPR)
Plasmons
Surface Plasmon Resonance
SPR and Nanoparticles
Localised Surface Plasmon Resonance
SPR imaging
Plasmon Resonance Energy Transfer
Charge Separation due to light wave in a material. (Ref.-eng.libetexts)
Light-Biomolecule interaction and image formation. (Ref.-eng.libretexts)
Drop to drop variation
Using Haematology Analyser: Variation in Haemoglobin Levels
A. Venous Blood: Drop Wise. B. Fingerprick blood: Drop Wise. C. Variability of Finger prick
blood : cumulative addition, running average decreases D. Comparison of A-Venous B-
Fingerpick blood donor wise (Ref.-academic.oup))
Using Point-Of-Care(POC) Device, Haemoglobinometer: Variation in
Haemoglobin Levels
A. Venous Blood: Drop Wise. B. Fingerprick blood: Drop Wise. C. Variability of Finger
prick blood : cumulative addition, running average decreases (Ref.-academic.oup))
Conclusion and Concurrent Technologies
Problems and scepticism
Complicated structures of biomolecules
Minimum amount of sample required
Stability and time
Concurrent Technologies
Sight
2drops - computer vision
Karius
cfDNA - Non-invasive testing
~1000 pathogen testing:5ml blood Ref.-Researchgate
References
Bhalla, N., Jolly, P., Formisano, N., & Estrela, P. (2016). Introduction
to biosensors. Essays in biochemistry, 60(1), 1–8.
Anon, Technology | Sight Diagnostics
Anon, Karius Test FAQs - Karius
Bond, M.M. & Richards-Kortum, R.R., 2015. Drop-to-Drop Variation
in the Cellular Components of Fingerprick Blood. American Journal
of Clinical Pathology, 144(6), pp.885–894
Anon, Plasmon Resonance - Engineering LibreTexts
Anon, 10.6: Photoluminescence Spectroscopy - Chemistry LibreTexts
Thank You

More Related Content

Similar to Finger prick testing- physics and problems

Cells & Cellphones - Looking deep at the molecular level
Cells & Cellphones - Looking deep at the molecular levelCells & Cellphones - Looking deep at the molecular level
Cells & Cellphones - Looking deep at the molecular level
The Radiation Doctor
 
Visualizing Radiation Physics Concepts with photon electron particle tracks
Visualizing Radiation Physics Concepts with photon electron particle tracksVisualizing Radiation Physics Concepts with photon electron particle tracks
Visualizing Radiation Physics Concepts with photon electron particle tracks
Shahid Naqvi
 
defense_2013
defense_2013defense_2013
defense_2013
Doug Breden
 
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
Kim Solez ,
 
Lecture at the C3BI 2018
Lecture at the C3BI 2018Lecture at the C3BI 2018
Lecture at the C3BI 2018
Nicolas Le Novère
 
Radiation detector and measurement tech.pdf
Radiation detector and measurement tech.pdfRadiation detector and measurement tech.pdf
Radiation detector and measurement tech.pdf
ssuserb523ad
 
The stuff that proteins are made of
The stuff that proteins are made ofThe stuff that proteins are made of
The stuff that proteins are made of
khinsen
 
Nenopartical optical sensors
Nenopartical optical sensorsNenopartical optical sensors
Nenopartical optical sensors
Ram Niwas Bajiya
 
Averitt slides
Averitt slidesAveritt slides
Averitt slides
Aakriti Raj
 
Spatial Distribution of Copper and Iron in Cardiac Tissue
Spatial Distribution of Copper and Iron in Cardiac TissueSpatial Distribution of Copper and Iron in Cardiac Tissue
Spatial Distribution of Copper and Iron in Cardiac Tissue
Grant Allen
 
Talk device approach to biology march 29 1 2015
  Talk device approach to biology march 29 1 2015  Talk device approach to biology march 29 1 2015
Talk device approach to biology march 29 1 2015
Bob Eisenberg
 
L1 introduction and history
L1  introduction and historyL1  introduction and history
L1 introduction and history
Anupam Banerjee
 
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
Yi Lin
 
Introduction to nanoscience and nanotechnology
Introduction to nanoscience and nanotechnologyIntroduction to nanoscience and nanotechnology
Introduction to nanoscience and nanotechnology
aimanmukhtar1
 
Talk multiscale analysis of ionic solutions is unavoidable
  Talk multiscale analysis of ionic solutions is unavoidable  Talk multiscale analysis of ionic solutions is unavoidable
Talk multiscale analysis of ionic solutions is unavoidable
Bob Eisenberg
 
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
piero scaruffi
 
TCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
TCSPC( Time-Correlated Single -Photon Counting) By Halavath RameshTCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
TCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
Halavath Ramesh
 
Ab Initio Thermometry For Long-Term Unattended Space Reactor Operation
Ab Initio Thermometry For Long-Term Unattended Space Reactor OperationAb Initio Thermometry For Long-Term Unattended Space Reactor Operation
Ab Initio Thermometry For Long-Term Unattended Space Reactor Operation
Joe Andelija
 
Magnetism at oxide interface final
Magnetism at oxide interface finalMagnetism at oxide interface final
Flow basics2.ppt2
Flow basics2.ppt2Flow basics2.ppt2
Flow basics2.ppt2
viviansareno
 

Similar to Finger prick testing- physics and problems (20)

Cells & Cellphones - Looking deep at the molecular level
Cells & Cellphones - Looking deep at the molecular levelCells & Cellphones - Looking deep at the molecular level
Cells & Cellphones - Looking deep at the molecular level
 
Visualizing Radiation Physics Concepts with photon electron particle tracks
Visualizing Radiation Physics Concepts with photon electron particle tracksVisualizing Radiation Physics Concepts with photon electron particle tracks
Visualizing Radiation Physics Concepts with photon electron particle tracks
 
defense_2013
defense_2013defense_2013
defense_2013
 
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long...
 
Lecture at the C3BI 2018
Lecture at the C3BI 2018Lecture at the C3BI 2018
Lecture at the C3BI 2018
 
Radiation detector and measurement tech.pdf
Radiation detector and measurement tech.pdfRadiation detector and measurement tech.pdf
Radiation detector and measurement tech.pdf
 
The stuff that proteins are made of
The stuff that proteins are made ofThe stuff that proteins are made of
The stuff that proteins are made of
 
Nenopartical optical sensors
Nenopartical optical sensorsNenopartical optical sensors
Nenopartical optical sensors
 
Averitt slides
Averitt slidesAveritt slides
Averitt slides
 
Spatial Distribution of Copper and Iron in Cardiac Tissue
Spatial Distribution of Copper and Iron in Cardiac TissueSpatial Distribution of Copper and Iron in Cardiac Tissue
Spatial Distribution of Copper and Iron in Cardiac Tissue
 
Talk device approach to biology march 29 1 2015
  Talk device approach to biology march 29 1 2015  Talk device approach to biology march 29 1 2015
Talk device approach to biology march 29 1 2015
 
L1 introduction and history
L1  introduction and historyL1  introduction and history
L1 introduction and history
 
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
Kilohertz-Rate MeV Ultrafast Electron Diffraction for Time-resolved Materials...
 
Introduction to nanoscience and nanotechnology
Introduction to nanoscience and nanotechnologyIntroduction to nanoscience and nanotechnology
Introduction to nanoscience and nanotechnology
 
Talk multiscale analysis of ionic solutions is unavoidable
  Talk multiscale analysis of ionic solutions is unavoidable  Talk multiscale analysis of ionic solutions is unavoidable
Talk multiscale analysis of ionic solutions is unavoidable
 
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
Birgitta Whaley (Berkeley Quantum Computation) at a LASER http://www.scaruffi...
 
TCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
TCSPC( Time-Correlated Single -Photon Counting) By Halavath RameshTCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
TCSPC( Time-Correlated Single -Photon Counting) By Halavath Ramesh
 
Ab Initio Thermometry For Long-Term Unattended Space Reactor Operation
Ab Initio Thermometry For Long-Term Unattended Space Reactor OperationAb Initio Thermometry For Long-Term Unattended Space Reactor Operation
Ab Initio Thermometry For Long-Term Unattended Space Reactor Operation
 
Magnetism at oxide interface final
Magnetism at oxide interface finalMagnetism at oxide interface final
Magnetism at oxide interface final
 
Flow basics2.ppt2
Flow basics2.ppt2Flow basics2.ppt2
Flow basics2.ppt2
 

Recently uploaded

LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Anant Corporation
 
AI assisted telemedicine KIOSK for Rural India.pptx
AI assisted telemedicine KIOSK for Rural India.pptxAI assisted telemedicine KIOSK for Rural India.pptx
AI assisted telemedicine KIOSK for Rural India.pptx
architagupta876
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
Nada Hikmah
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
ydzowc
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
171ticu
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Victor Morales
 
Material for memory and display system h
Material for memory and display system hMaterial for memory and display system h
Material for memory and display system h
gowrishankartb2005
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
KrishnaveniKrishnara1
 
Software Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.pptSoftware Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.ppt
TaghreedAltamimi
 
Hematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood CountHematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood Count
shahdabdulbaset
 
Engineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdfEngineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdf
abbyasa1014
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
co23btech11018
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
bijceesjournal
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
jpsjournal1
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
RamonNovais6
 
artificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptxartificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptx
GauravCar
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
gerogepatton
 
Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
AjmalKhan50578
 

Recently uploaded (20)

LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
 
AI assisted telemedicine KIOSK for Rural India.pptx
AI assisted telemedicine KIOSK for Rural India.pptxAI assisted telemedicine KIOSK for Rural India.pptx
AI assisted telemedicine KIOSK for Rural India.pptx
 
Curve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods RegressionCurve Fitting in Numerical Methods Regression
Curve Fitting in Numerical Methods Regression
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
 
Material for memory and display system h
Material for memory and display system hMaterial for memory and display system h
Material for memory and display system h
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
 
Software Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.pptSoftware Quality Assurance-se412-v11.ppt
Software Quality Assurance-se412-v11.ppt
 
Hematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood CountHematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood Count
 
Engineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdfEngineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdf
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
 
artificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptxartificial intelligence and data science contents.pptx
artificial intelligence and data science contents.pptx
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
 
Welding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdfWelding Metallurgy Ferrous Materials.pdf
Welding Metallurgy Ferrous Materials.pdf
 

Finger prick testing- physics and problems

  • 1. Fingerprick Testing Physics and Problems Presented By Achal Singh Mtech 2nd Sem.(Nanotechnology) Scholar No.-222105102 Seminar-2
  • 2. Contents Introduction: Story so far (Summary: Seminar1) Biosensors and Low Dimensional Systems Luminescence Surface Plasmon Resonance Drop to drop Variations Conclusion and Current Technologies References
  • 3. The story so far Inspiration from Theranos Story Blood components Traditional Blood Test Procedure Simple Molecules Blood Sugar Testing Theranos Edison(conceptual) Ref. NYT Elizabeth Holmes(famous 1drop picture SteveJobsesque) Ref.WSJ
  • 4. Biosensors and Low Dimensional Systems Biosensors Analyte Bioreceptors Transducers Electronics Display Quantum Phenomena Quantum Conductance Kondo Effect Coulomb Blockade Biosensors and their components (Ref.-MDPI) QPC and Quantum Conductance (Ref.-Science) Resistivity in Low Dimensions (Ref.-Springer)
  • 5. Luminescence Electron excitations Characterisation Imaging Bioluminescence Photoluminescence Phosphorescence Fluorescence Jablonski Diagram (Ref.-Horiba) Overall concept and design of multiplexed, real-time plasmonic RT-PCR. (Ref.-nature) Absorption and Scattering from whole blood. (Ref.-NCBI)
  • 6. Surface Plasmon Resonance(SPR) Plasmons Surface Plasmon Resonance SPR and Nanoparticles Localised Surface Plasmon Resonance SPR imaging Plasmon Resonance Energy Transfer Charge Separation due to light wave in a material. (Ref.-eng.libetexts) Light-Biomolecule interaction and image formation. (Ref.-eng.libretexts)
  • 7. Drop to drop variation Using Haematology Analyser: Variation in Haemoglobin Levels A. Venous Blood: Drop Wise. B. Fingerprick blood: Drop Wise. C. Variability of Finger prick blood : cumulative addition, running average decreases D. Comparison of A-Venous B- Fingerpick blood donor wise (Ref.-academic.oup)) Using Point-Of-Care(POC) Device, Haemoglobinometer: Variation in Haemoglobin Levels A. Venous Blood: Drop Wise. B. Fingerprick blood: Drop Wise. C. Variability of Finger prick blood : cumulative addition, running average decreases (Ref.-academic.oup))
  • 8. Conclusion and Concurrent Technologies Problems and scepticism Complicated structures of biomolecules Minimum amount of sample required Stability and time Concurrent Technologies Sight 2drops - computer vision Karius cfDNA - Non-invasive testing ~1000 pathogen testing:5ml blood Ref.-Researchgate
  • 9. References Bhalla, N., Jolly, P., Formisano, N., & Estrela, P. (2016). Introduction to biosensors. Essays in biochemistry, 60(1), 1–8. Anon, Technology | Sight Diagnostics Anon, Karius Test FAQs - Karius Bond, M.M. & Richards-Kortum, R.R., 2015. Drop-to-Drop Variation in the Cellular Components of Fingerprick Blood. American Journal of Clinical Pathology, 144(6), pp.885–894 Anon, Plasmon Resonance - Engineering LibreTexts Anon, 10.6: Photoluminescence Spectroscopy - Chemistry LibreTexts

Editor's Notes

  1. Summary of first seminar: We drew inspiration from Theranos story. Theranos promised 1 blood drop-300 tests. A desktop testing device for housing all tests. This was revolutionary promise and a boon to people subjected to frequent blood tests. We have seen the blood components and saw that they contains ions, which can be used for signal transfer in electronics. We have overviewed the traditional blood testing procedure, amount of blood required and problems. We have seen some simple molecules such as proteins, dna which form the signal carriers of blood. Also we have overviewed the blood sugar testing procedure, as it is the most widely used fingerprick method.
  2. Biosensors: A biosensor is a device that measures biological or chemical reactions by generating signals proportional to the concentration of an analyte in the reaction. Biosensors are employed in applications such as disease monitoring, drug discovery, and detection of pollutants, disease-causing micro-organisms and markers that are indicators of a disease in bodily fluids (blood, urine, saliva, sweat). A typical biosensor is represented in figure, it consists of the following components. Analyte: A substance of interest that needs detection. For instance, glucose is an ‘analyte’ in a biosensor designed to detect glucose. Bioreceptor: A molecule that specifically recognises the analyte is known as a bioreceptor. Enzymes, cells, aptamers, deoxyribonucleic acid (DNA) and antibodies are some examples of bioreceptors. The process of signal generation (in the form of light, heat, pH, charge or mass change, etc.) upon interaction of the bioreceptor with the analyte is termed bio-recognition. Transducer: The transducer is an element that converts one form of energy into another. In a biosensor the role of the transducer is to convert the bio-recognition event into a measurable signal. This process of energy conversion is known as signalisation. Most transducers produce either optical or electrical signals that are usually proportional to the amount of analyte–bioreceptor interactions. Electronics: This is the part of a biosensor that processes the transduced signal and prepares it for display. It consists of complex electronic circuitry that performs signal conditioning such as amplification and conversion of signals from analogue into the digital form. The processed signals are then quantified by the display unit of the biosensor. Display: The display consists of a user interpretation system such as the liquid crystal display of a computer or a direct printer that generates numbers or curves understandable by the user. This part often consists of a combination of hardware and software that generates results of the biosensor in a user-friendly manner. The output signal on the display can be numeric, graphic, tabular or an image, depending on the requirements of the end user. Low Dimensional Systems: In nanomaterials, the transport of electrons shows different behaviour than bulk. This is mainly because of the conductor size becomes comparable to the fermi wavelength of electrons. Quantum conductance: The conductance at quantum level is realised through Quantum Point of Contact (QPC). The size of gate for transport becomes comparable to Fermi wavelength of electrons, this leads to quantization of conductance. Kondo effect: Due to presence of magnetic impurities, the resistance at lower temperatures increase with decrease in temperature. This is due to pairing of electrons spin with that of magnetic impurities. Coulomb Blockade: It is the resistance to flow of electron in and out of the quantum dot. As size of quantum dot decreases, its capacitance energy increases so more nergy is required to add electron to it.
  3. Luminescence: When energy is incident on material, it excites its electrons to higher energy state. When electrons come back to lower energy levels, the radiate some of the energy, if this energy lies in visible region of electromagnetic spectrum, it is termed as luminescence. Each material gives it distinct absorption and emission spectra, this can be used for characterisation: quantitative and qualitative, and for imaging purposes. Image: Jablonski Diagram Photoluminescence: In luminescence, when the incident energy is in form of photons, it is termed as photoluminescence. It is of two types : phosphorescence- delayed luminescence, due to existence of intermediate triplet state, and fluorescence – instant luminescence. Image : Absorption and scattering of light by blood cells. Near-infrared light (700–2,500 nm) can penetrate biological tissues such as skin and blood more efficiently than visible light because these tissues scatter and absorb less light at longer wavelengths.This property is used in oximeters to determine the amount of oxygenated blood. Attenuation Coeffecient: The attenuation coefficient is a measure of how easily a material can be penetrated by an incident energy beam (e.g. ultrasound or x-rays). It quantifies how much the beam is weakened by the material it is passing through. RT-PCR Image Description: a, Schematic of multiplexed real-time plasmonic RT-PCR, with heating driven by IR LEDs acting on AuNRs and cooling aided by a 12 V fan. The AuNRs are suspended in solution in a 0.2 ml PCR tube, rapidly absorbing light from the LEDs and converting it to heat, allowing for fast PCR thermal cycling. A 488 nm laser and spectrometer setup provides real-time fluorescence detection and takes a measurement at the end of each annealing/extension hold. b, Schematic of the instrument. A PCR tube is surrounded by low-cost optical components, without Peltier heating elements. The main components of the instrument include a thin-walled PCR tube surrounded by three IR LED modules, a cooling fan, and a 488 nm laser and spectrophotometer setup for fluorescence detection. The three IR LED modules consist of 850 nm IR LEDs attached to heat sinks as well as heat-sink fans and placed concentrically surrounding the PCR tube. Temperature control can be achieved through closed-loop sensing with a wire thermocouple or through contactless open-loop control. c, Schematic of the fluorometer system. Light coming from a 488 nm laser passes through a collimating lens and filter before reaching the PCR tube. Light emitted from the tube passes through a condensing lens and a 500 nm edge emission filter (Semrock) before travelling through an optical fibre to reach the spectrometer. d, Graph depicting non-overlapping optical spectra of various components within the system, namely, 488 nm excitation peak, three emissions (520, 555 and 610 nm), IR LED excitation and AuNR absorbance.
  4. Plasmons: The classical physics approach can be used to describe plasmons. In this analogy the free electrons in a metal are treated as a liquid, entirely composed of electrons, that has a very high density (plasma). The fluctuations of density that appear on the surface of this material are called plasmons or surface plasmons. Each plasmon represents the quantizations of classically oscillating plasma waves. This means the plasmons represent discreet values of an oscillating plasma wave, therefore most of their properties can be directly derived from Maxwell's equations. A plasmon is a quantum of plasma oscillation. Thus, plasmons are collective oscillations of the free electron gas density, for example, at optical frequencies. Surface plasmons are those plasmons that are confined to surfaces and that interact strongly with light resulting in a polariton. They occur at the interface of a vacuum and material with a small positive imaginary and large negative real dielectric constant (usually a metal or doped dielectric). Phonons, on the other side, are the quanta of the modes of vibrations of elastic structures of interacting particles. If charges are involved in the particle's vibrations, you can also have plasma oscillations but, all you see is the lattice contribution to the permittivity tensor, as observed in the LO-TO phonon mode splitting in infrared experiments - not a plasmon. Surface Plasmon Resonance: Surface plasmon resonance refers to the electromagnetic response that occurs when plasmons are oscillating with the same frequency on the surface of a material. As these plasmons oscillate at specific resonant frequencies, they move with periodic driving forces that can become large amplitude oscillations when they interact. This phenomenon is stimulated by a light source. The frequency of the incidence of light must be equal to the natrual frequency of the material or resonance will not occur. These oscillations travel on the surface between the material and air and travel in the direction of the negtaive dielectric material surface. Because these plasmons are on this boundary, they are very sensitive to a change in external stimuli such as the absorption of energy into the material. Nanopaticles:anoparticles are of interest to the scientific community for a multitude of reasons including their large surface area to volume ratio which makes them very reactive to external stimuli quickly, the fact that they operate on a quantum mechanics scale, and because the nanoscale is the level at which many biological processes occur. When electric fields of light are directed at nanoparticles, the surface plasmons become excited and begin to resonate. This electric field also creates a separation of charge, which can be seen in Figure 3, that then forms a dipole oscillation in the same direction as the electric field of light. Due to the face that the frequencies are the same, the SPR allows a strong abosrption of the incidence light while also allowing some scattering of light; these can be measured using a UV-VIs Spectrometer. The SPR band intensity and wavelength is dependent on the properties of the particle, including the shape, structure, metal type, size, and dielectric material surrounding the medium which can include air. SPR Imaging: Plasmon Resonance Energy Transfer occurs when nanoparticles are connected to molecular chromophores (an atom or molecule whose presence is responsible for the color of the compound), then the plasmon resonance energy can be transferred to the molecular chromophore. The transfer of this energy paired with the natural frequencies of the biomolecules causes an overlap of resonant energy peak positions. The overlap of these two frequencies can cause spectral quenching dips on the Rayleigh scattering spectrum of a single nanoparticle. This quenching allows for ultrasensitive nanoscopic absorption spectroscopy, which is much more specific as well as faster and more efficient than optical absorption spectroscopy. This transfer of energy through the material, allows for SPR imaging. A very simple form of this is shown in Figure 4. This demonstrates the basic principle that the energy is transferred to the ligands and biomolecules which in turn, change the amount of reflectivity of light and reflect back a gradient of absorbed spectra that helps to understand the composition of the material. Imaging technology today uses a p-polarized HeNe laser beam as a light source and the reflected light is directed at a CCD camera. By using this camera, 3D images of binding techniques of biomolecules can be observed as well as being able to identify specific versus non-specific adsorption processes, biocharacterizaion, and understanding where the molecule is in space based on the light intensity gradient. This method of imaging is high speed and reactions and binding can be observed in real-time, which helps to better understand the behavior of the molecules.
  5. Abstract of paper on drop to drop variation in blood Objectives Blood obtained via fingerprick is commonly used in point-of-care assays, but few studies have assessed variability in parameters obtained from successive drops of fingerprick blood, which may cause problems for clinical decision making and for assessing accuracy of point-of-care tests. Methods We used a hematology analyzer to analyze the hemoglobin concentration, total WBC count, three-part WBC differential, and platelet count in six successive drops of blood collected from one fingerprick from each of 11 donors, and we used a hemoglobinometer to measure the hemoglobin concentration of 10 drops of fingerprick blood from each of 7 donors. Results The average percent coefficient of variation (CV) for successive drops of fingerprick blood was higher by up to 3.4 times for hemoglobin, 5.7 times for WBC count, 3 times for lymphocyte count, 7.7 times for granulocyte count, and 4 times for platelets than in venous controls measured using a hematology analyzer. The average percent CV for fingerprick blood was up to 5 times higher for hemoglobin than venous blood measured using a point-of-care hemoglobinometer. Fluctuations in blood parameters with increasing volume of fingerprick blood are within instrument variability for volumes equal to or greater than 60 to 100 μL. Conclusions These data suggest caution when using measurements from a single drop of fingerprick blood.
  6. Problems: Simple molecules such as glucose test, ions: potassium, sodium level test are much easier. But when it comes to complex viral or bacterial structures, all kind of methods rely on quantitative test. This requires some minimal sample amount. Also there is a question of stability of molecules inside blood, coagulation due to platelets, and cell dying time complicates the testing procedure. So, from sampling to display the method must be stable and fast. Concurrent Technologies: Sight: Sight’s digital pathology and AI-based hematology platform achieves lab-grade diagnostic accuracy using only two drops of blood. No external reagent management, no maintenance, and no manual calibration required by manufacturer. Their system collects over 1,000 microscope images of each blood sample, in order to count cells and identify anomalies. Blood is dense with cells, whereas microscopy works best when cells are neatly arranged in a flat layer. Sight solved this problem uniquely using our patented Live Monolayer Imaging (LMI™) method: single-use cartridge permits elegantly simple sample preparation, which preserves cell morphology, ensuring that their algorithms can achieve precise results. And because cell shape information is preserved,they will be able to provide even more data in the future—including valuable insight into blood cell morphology. Novel Blood Staining Approach How to clearly tell one cell type from another? Stain the cells with a patented combination of dyes that reveals normally-unseen chemical features, then use a combination of brightfield and fluorescence microscopy to collect over 1,000 “multispectral” images of each sample. Analyzers identify different cell populations through the combination of their optical and chemical signatures. Karius: The Karius Test,, uses proprietary sample preparation, next-generation sequencing (NGS), and analytics for the broad and rapid detection of microbial cell-free DNA from a standard blood draw. Unlike conventional culture and panel testing methods that identify a narrow range of pathogens, the Karius Test can detect more than 1000 pathogens. Their pathogen database is curated for sequence quality and clinical relevance. The test is broad-based, which means that co-infections can be detected. Pathogens we can detect are: bacteria, fungi, DNA viruses, and eukaryotes (including protozoa). Cell-free DNA from pathogens can be found in blood regardless of the site of infection. By sequencing cell-free DNA circulating in the plasma, biopsies to obtain intact pathogens may be avoided.