1. Overview
In order to enable people to detect and monitor the degree of atherosclerosis (AS) earlier and more conveniently, we developed a filter paper biosensor for detecting the concentration of trimethylamine N-oxide (TMAO), miR-17-5p and miR-146a-5p which are reported closely related to the degree of AS. In this page, we describe the development of a hardware for quantification the color changes on the paper strip biosensor. Due to the portable and convenience, it can provide early warning of the occurrence and progress of AS to elderly people at home.
2. Background
At present, there is no effective testing method for early warning and monitoring of AS. It is important especially for asymptomatic AS. Most people go to the hospital for examination when they have symptoms related AS. However, it is too late, and they lost the best opportunity for treatment. For this reason, we designed and constructed a detector that can detect and monitor AS development at home. The detector in our project is based on color rendering of the paper strip biosensor when detecting TMAO and miRNAs using urine samples.
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3. Detection Principle
The color of any object can be obtained by fitting the three primary colors of red, green, and blue in a certain proportion. Using the principle of color matching constant law for color quantitative analysis (please see https://www.hisour.com/grassmanns-laws-in-color-science-26936/ for more information). The number of three primary colors required to match the color to be tested is called the tri-stimulus value. If [C] represents the units of the matched color, [R], [G], and [B] represent the units of the red, green, and blue primary colors that produce the mixed color. R. G, B, and C represent the quantities of red, green, blue, and matched colors, respectively. In general, tri-stimulus values can be used to quantify color.
When the relative ratio of the three primary colors to the total amount of R+G+B is used to represent the color, the following equation is used:
Equation 1: C=[R/(R+G+B)] * (R)+[G/(R+G+B)] * (G)+[B/(R+G+B)] * (B)
From the equation, it can be seen that the chromaticity of a unit of color [C] only depends on the relative proportion of the stimulus values of the three primary colors in the total amount. This ratio is called the chromaticity coordinate, represented by x, y, z, and z+y+z=1. Those equation are as follows.
Equation 2: x=R/(R+G+B), y=G/(R+G+B), z=B/(R+G+B)
A plane diagram represented by chromaticity coordinates is called a chromaticity diagram. Therefore, you only need to provide x and y coordinates to determine the position of any color on the chromaticity map (Fig.1). The color saturation on the spectral trajectory is the highest. The color saturation of point D65 is the lowest. The closer the equal energy white point D65 on the graph, the lower the color saturation.
Fig.1 a x y chromaticity diagram.
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4. Detector design
Based on these principles mentioned above, we have established a technical flowchart for designing detector. The color on the detected sample passes through the light signal, passes through the color sensitivity detector, generates red, green and blue light, converts the light pixels into electrical signals, and amplifies the signals, and is analyzed by a single processor, and displays the values on the display. The technical flowchart of detector design is shown as follows (Fig.2).
Fig.2 Technical flowchart of detector design for color rendering.
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5. Detector construction
Based on Glassman's color theory and technical flowchart, we believed that the color produced by detecting TMAO and miRNAs can be analyzed very accurately and quickly. We built the color detecting single chip processor, the main component, that contains chips, resistance, capacitance, power standard, blue teeth, and power, etc. (Fig.3), which have the functions such as I/V transformation, voltage amplification, A/D conversion and Bluetooth serial port. The power supply, another main component, was built (Fig.4), which transform high voltage into weak current to provide power for single chip processor, Bluetooth and cameras, etc. A camera, the tool for obtaining images, is connected with the processor.
Fig.3 The single chip processor of the detector.
Fig.4 The power supply of detector.
When we have completed the preliminary construction of the detector, we conducted color detection experiments on the object and found that our detector could work well (Fig. 5).
Fig.5 Testing of the detector using different color objects.
Considering the widespread use of APP programs on smart phone nowadays, we decided to add Bluetooth module to the detector (Fig.6), which could connect the data obtained from the detector to the APP program on the phone, making it easier to determine the detection results. We constructed the Bluetooth serial port, and the data collected by the single chip processor is transmitted to APP program by Bluetooth. This Bluetooth facilitates data transmission between the single chip processor and smart phones for analysis.
Fig.6 Bluetooth module,smart phone and APP model for analysis.
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6. Detector test
The complete detector includes a camera, single chip processor, power supply, and Bluetooth (Fig.7). We separated the power supply from the processor. The processor is located on the posteromedial inner of the power supply. Bluetooth is placed on the top layer. The camera is mounted on the front of the detector and embedded in the casing. The paper strip biosensor is put in the front of camera to avoid the influence of light on the analysis of color. Through the collection of color signals, the single chip processor will receive the detection data. With Bluetooth connection between the processor and smart phone or computer, the data converted from the colors on the biosensor are analyzed quantitatively using smart phone APP or computer software (Fig.8). The data will be displayed and recorded.
Fig.7 Detector construction
Fig.8 Testing data analysis of the filter paper biosensor.
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7. Advantage
The precision is extremely high, and the detector can accurately distinguish similar colors, even different tones of the same color because the color measurement method is realized through the three primary colors of the object color.
Transferring data through Bluetooth is very convenient and fast.
The use of smart phone APP during the testing process not only facilitates viewing the test results for himself, but also facilitates transmission to his children and community doctors to jointly monitor the development of AS.
In addition, the detector is small in size, easy to carry, and can even be used during travel, maintaining the ability to monitor the development of AS every day.
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