Introduction

Considering the potential users of our OMEGA project may not be trained in the lab, the application location is mainly the shrimp farm. Moreover, AHPNED is a malignant illness, so quick detection is required. To overcome the difficulties above, portable, low-cost, and easy-use hardware, also integrated with software, is designed to satisfy the special requests to implement the OMEGA project better.

As shown in Fig. 1, the detection system collects samples of the pond, puts them into the syringe, and mixes them with the lysis solution for 1 min. Cell lysis was removed from the solution by injecting the sample solution into the second syringe. The nucleic acid in the water sample was then enriched with fiber paper while other components were discarded. The following steps were conducted in the thermostatic black box. The paper was put into the RPA reaction mix to amplify the target gene. After 10 min of RPA reaction, the sample was added to the cell-free system.

Fig. 1 The framework of detection system.

Then the reaction-finished cell-free system is mixed with the Nano-Glo® Luciferase Assay Substrate (FMZ) in the paper chip placed in the monitoring devices, the camera in the upper cover will record the whole luminescence decay kinetics after the device is under the dark environment inside (Fig. 2a). The recorded video is then processed in the software part using the back-end algorithm for paper-chip positioning (Fig. 2b) and data filtering (Fig. 2c). After the above process ends, the output data is ready for modeling and analysis (Fig. 2d), and the analysis result will be sent to the front-end software for visualization (Fig. 2e).

Fig. 2 The front and rear-ends separation structure of our software. a The monitoring device record the result of cell-free detection system. b The paper-chip positioning algrithm determinds the postion of samples. c The filter decreases the noise in the collected data. d Data modeling and analysis to mining the information hidden in the data. e The analysis result will be sent to the visualization software.

In the whole process above, the hardware consists of two main parts: the thermostat device and the monitoring device. The thermostat provides a constant temperature environment for the RPA system to amplify the target signal and the cell-free system to transform the target signal for visualization. The monitoring device captures the visual signals, which are sent to the software for future processing. If possible, integration between hardware and software will promote cooperation between shrimp farmers and us for prevention and treatment.

Thermostat Device

In the RPA reaction system, the temperature condition ranges between 37 ℃ to 42 ℃ while 37 ℃ for the cell-free system. A stable thermostat device guarentee success implementation of both two reaction. A demo device was built in the Fig. 3.

Fig. 3 The thermostat device. a Overview. b Device without float. c Device with float.

The demo device is controlled with ESP32 using the Micropythohn language. A heater whose voltage is 12V and power is 48W is used to heat the water to 37℃ in less than five minutes (Fig. 3a). The temperature sensor, with its driver, detects the water temperature all the time and is sent to ESP32 for control using the PID algorithm (Fig. 3b). The RPA system can be placed in the small hole in the float while the cell-free system in the big hole in the reaction process (Fig. 3c).

Two things are considered when building the thermostat device. One is how to maintain a stable temperature field. The size of our thermostat device is too large to diffuse heat quickly. A field mixer, a motor, is employed to stir the water, enhancing heat exchange in different regions. Comparing the situation that the mixer works or not in Fig. 4 and Fig. 5, the water is mixed so does heat when the mixer is working.

Fig. 4 Device with the working mixer.

Fig. 5 Device without the working mixer.

To test the homogeneity of the temperature field quantitatively, we shake the box heavily to enhance the exchange of temperature manually. The temperature change is recorded in Fig. 6. The temperature of the device without the working mixer has a great change after shaking. In contrast, the one with the working mixer is quite stable, which indicates our strategies work well.

Fig. 6 The temperature change in thermostat device. a Device with the working mixer. b Device without the working mixer.

The other thing is how to control the temperature precisely. PID is chosen as the control algorithm, and the control variable is the 0-1 state of the relay. The PID works well, and we successfully perform the RPA reactions in our hardware (Fig. 7).

Fig. 7 RPA in thermostat device.