The current study aimed to investigate the rejection and survival time of grafted skin, and the changes of Treg cells, interleukin 10 (IL-10) and transforming growth factor-β (TGF-β) in peripheral blood following skin transplantation with recombinant human interleukin-10 (rhIL-10) or cyclosporin A (CsA), as well as the role of IL-10 in immunological rejection mechanisms. A total of 36 rabbits were divided into two groups. The skin of a donor rabbit was transplanted onto the back of one receptor rabbit. Receptors were randomly divided into six groups, including rhIL-10 low-dose (5 μg/kg/d), rhIL-10 high-dose (10 μg/kg/d), CsA low-dose (5 mg/kg/d), CsA high-dose (10 mg/kg/d), rhIL-10 (5 μg/kg/d) and CsA (5 mg/kg/d) and negative control normal saline (NS; 1 ml/d). All groups received intramuscular drug injection for ten days, beginning one day prior to skin transplantation surgery. Following transplantation, each rabbit’s peripheral blood was collected at different times. The changes of CD4+CD25+ regulatory T cells, IL-10 and TGF-β were determined by flow cytometry and enzyme-linked immunosorbent assay. When compared with the control group, the rejection and survival times of the experimental groups were longer following skin graft. Compared with the two CsA groups and the control group, the proportion of CD4+CD25+ regulatory T cells of rhIL-10 groups was significantly upregulated on the 4th and 7th days following surgery. However, TGF-β levels were not significantly different. Data suggested that the concentration of IL-10 was positively correlated with the proportion of CD4+CD25+ regulatory T cells. In addition, IL-10 may delay the rejection time of rabbit skin transplantation and prolong the survival time. Thus, the role of IL-10 in inhibited allograft rejection may be associated with CD4+CD25+ regulatory T cells and IL-10, and may be independent of TGF-β.

In this paper, we develop a temperature control system based on DSP chip TMS320F28335 for a small real-time PCR instrument. In the system, PWM waves generated by the DSP passes through power amplifier circuit to drive the peltier, and a pt100 is used as a temperature sensor to build a Wheatstone bridge sensing circuit. The temperature signal from the pt100 is converted into voltage signal. Then the voltage signal goes through the A/D converted module and the Position PID algorithm to adjust the duty cycle of the PWM waves. Experimental results show that the system's rising and cooling rate can reach 4°C/s with an accuracy of 0.2°C.

In this paper we build up a set of simple urinary sediment detection device which is composed of a biological microscope, focusing mechanism, and CCD camera. We apply this device in urinary sediment detection to verify its feasibility. In our experiment, the urinary sediment quality control diluted 200 times is dropped into quantitative analysis plate to detect on the device. We watch and count the number of red and white blood cells in 30 counting pools. Microscopic images are clear and the number of red and white blood cells in these images fluctuates around the average value. Experimental results show that our device is feasible in urinary sediment detection.

In this paper, we design a temperature sensing system based on a DSP chip TMS320F2812 for a real-time PCR instrument. In this system, we design a 4-wire temperature sensing module with a thermal resistor PT100 to measure the temperature and convert it into a voltage signal. Then the voltage signal is digitalized by the ADC module. At last, the data are transferred to a PC through the serial port. The experimental results show that the linearity of the system is 0.99 with the standard deviation of 0.0419.

The purpose of this paper is to put up a device for urinary sediment detection with a homemade microscope and a CCD, and to test the feasibility of the device. In this study, we use a capillary to absorb the urinalysis control (UC) which is diluted 500 times, and drip it into a counting pool of a urinary sediment quantitative analysis board (USQAB). In this setup device, we detect 30 counting pools in this analysis board with microscopic examination in total. Further, we count the number of red blood cells (RBC) and white blood cells (WBC) of every counting pool, and calculate the average number of RBC and WBC of 30 counting pools. Though this detection device, we are able to get 30 groups of imaging results clearly while the number of RBC and WBC in each counting pool fluctuates around the mean value. The result indicates that the setup detection device in this experiment is simple and feasible.