General Overview
The Syncova project is creating a Lateral Flow Assay (LFA) capable of detecting both protein CD44 and CD117 using Gold Nanoparticles (GNP).
This diagnostic test will be similar to the COVID-19 test, where if you had COVID-19 two lines will get colored, the test line and the control line, whereas if you were COVID free then only the control line will get colored.
In this situation the cancer detection works on the same principle, if the patient has either CD44 or CD117 in their system it’ll get detected and both the test line and control line will get colored but if they’re cancer free then only the control line gets colored. This is a very interesting and new approach used to detect cancer, yet it is only capable of giving you a True/False answer.
The Dry Lab team was given the task to create a device that is capable of quantifying the information in the case where the patient has cancer and the test line ends up being colored. Since having actual data on hand and knowing the actual concentration of tumor cells in the sample given can indicate the severity of the cancer and better diagnose the patient if it’s still in the very early stages or it’s starting to evolve to a higher, more dangerous stage.
We used Thermal Contrast to significantly improve the analytical sensitivity of lateral flow assay. This method consists of heating up the test line to a certain temperature, which will eventually help us get more accurate results.
The steps taken for this experiment are:
1. Heating the test line with a laser
2. Detecting the heat with an IR sensor or a Heat Camera
3. Converting the Heat reading to concentration
First Step:
As mentioned before, in order to detect the proteins CD44 and CD117 we are using Gold Nanoparticles(GNP) and GNP resonates to the frequency of 532nm. Since our goal is to heat up the test line and detect the heat emitted from it, we have to heat up the GNP.
To do so, we are using a class 4 laser with 0.5w power and 532nm wavelength which is the same frequency for the GNP and the reason for that is, when the GNP are being hit by the green light emitted from the laser they’ll get excited and afterwards de-excited and this action will cause them to generate heat.
The laser will be turned on for a short period of time, ranging from 60 to 80 seconds allowing the GNP to reach their maximum heat emission.
Second Step:
Now we have the tools to create the heat we want, it’s time to read the heat emitted and that’s where the use of either an IR sensor or a thermal camera comes in hand.
Both of these devices are capable of reading the heat emitted from a certain area, in our case the IR we used can detect the temperature of an object that is directly in front of it, so we had to mount it directly on top of the test line to as much reading accuracy as possible.
The information given by the IR will go directly to a microcontroller called ESP32, that will generate a graph to show the heat change over time and that will assure us that the laser is effectively heating the GNP.
Third Step:
After getting the maximum heat dissipation emitted from the GNP, we can calculate the concentration of GNP in the area that the IR is facing, and since the GNP are attached to the proteins we want to detect then we can conclude the concentration of these proteins.
To get the total concentration of GNP (N) we are using an equation that relates the total heat emitted in the area(Q) and the contribution of single GNP to that heat (Qnano).
The equation can also be written using some of the laser parameters, where we use GNP absorption cross section (Cabs, m2), and laser intensity (I, W/m2) giving us the following equation :
Now the equation can be written in both ways :
All the calculations will be handled by the microcontroller mentioned above that will output the results with accurate precision.
Hardware Components
The hardware model has been meticulously developed to precisely and functionally fit all the device's critical components. It has been designed to safely and securely hold the ESP32 microprocessor, the LFA, and the IR sensor.
The hardware model consists of two separate components, each of which has a particular function.
The LFA is housed in the first component, referred to as the slider.
The second component is a bigger cage that the slider glides inside with ease.
The positioning of the microcontroller and LEDs inside of this larger container has been carefully planned out with strategic apertures. These apertures allow for seamless connections to the necessary devices while also keeping these components in their proper places.
The larger cage stands out for its properly positioned aperture, which enables the laser beam to enter and accurately target the LFA. Additionally, to ensure the gathering of extremely precise measurements, the IR sensor is intelligently positioned just above the area where the laser contacts the LFA.
A large spatial distance has been kept between the LFA and the microcontroller in order to preserve the microprocessor's integrity and reduce the potential effects of laser-generated heat.
This device will be produced using 3D printing using Polylactic Acid (PLA) as the material of choice. This choice was carefully considered since PLA offers a good balance of strength and ease of manufacture, which is in line with the project's overall goals.