Synthesis control circuits can be used to effectively control biochemical molecule processes. In the controller design based on chemical reaction networks (CRNs), generally only the tracking set-point is considered. However, the influence of disturbances, which are frequently encountered in biochemical systems, is often neglected, thus weakening the control effect of the system. In this article, tracking set-point input and suppressing disturbance input are considered in the control effect. Firstly, CRNs are adopted to construct a two-degree-of-freedom PID controller by combining a one-degree-of-freedom PID controller with a feedforward controller for the first time. Then, CRN expressions of the two input functions (step function and ramp function) used as input signals are defined. Furthermore, the two-degree-of-freedom PID controller is founded by DNA strand displacement (DSD) reaction networks, because DNA is an ideal engineering material to constitute molecular devices based on CRNs. The overshoot of the two-degree-of-freedom PID control system is significantly reduced compared to the one-degree-of-freedom PID control system. Finally, a leak reaction is treated as an extraneous disturbance input to a subtraction gate. The influence of external disturbance is solved by the two-degree-of-freedom PID controller. It is worth noting that the two-degree-of-freedom subtraction gate control system better restrains the impact of a disturbance input (leak reaction).

Long non-coding RNA nuclear paraspeckle assembly transcript 1 (NEAT1) is a novel pro-inflammatory factor in severe human diseases. Since inflammatory plays important roles in periodontitis progression, we aimed to explore the role of NEAT1 in chronic periodontitis (CP) in vitro. We established a periodontitis cell model was established by Porphyromonas gingivalis lipopolysaccharide (Pg-LPS)-induced periodontal ligament cells (PDLCs). Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to detect the expression of NEAT1, microRNA (miR)-200c-3p, and tumor necrosis factor receptor-associated factor 6 (TRAF6). Cell viability, inflammatory factors, and protein expression of Bcl-2, Bax, and TRAF6 were analyzed by MTT, enzyme-linked immunosorbent assay, and Western blot. The target relationships among NEAT1, miR-200c-3p, and TRAF6 were predicted by the StarBase/TargetScan software, and further validated by dual-luciferase reporter assay. In this research, NEAT1 is up-regulated in CP tissues and periodontitis model group. Silencing of NEAT1 and over-expression of miR-200c-3p enhanced cell viability and repressed apoptosis in the periodontitis model group. NEAT1 targets miR-200c-3p, and miR-200c-3p further targets TRAF6. MiR-200c-3p inhibitor or over-expression of TRAF6 reversed the promoting effect of NEAT1 knockdown on cell viability, and the inhibiting effects on inflammatory cytokines and cell apoptosis. Consequently, the silencing of NEAT1 inhibits inflammation and apoptosis via targeting miR-200c-3p/TRAF6 axis, thereby contributing to alleviate the progression of CP. This finding could provide an underlying target for the treatment of CP.

Background: Bioinformatics is a subject produced by the combination of life science and computer science. It mainly uses computer technology to study the laws of biological systems. The design and realization of DNA circuit reaction is one of the important contents of bioinformatics. Results: In this paper, nonlinear dynamic system model with Lévy jump based on entropy-driven amplifier (EDA) circuit response is studied. Firstly, nonlinear biochemical reaction system model is established based on EDA circuit response. Considering the influence of disturbance factors on the system, nonlinear biochemical reaction system with Lévy jump is built. Secondly, in order to prove that the constructed system conforms to the actual meaning, the existence and uniqueness of the system solution is analyzed. Next, the sufficient conditions for the end and continuation of EDA circuit reaction are certified. Finally, the correctness of the theoretical results is proved by numerical simulation, and the reactivity of THTSignal in EDA circuit under different noise intensity is verified. Conclusions: In EDA circuit reaction, the intensity of external noise has a significant impact on the system. The end of EDA circuit reaction is closely related to the intensity of Lévy noise, and Lévy jump has a significant impact on the nature of biochemical reaction system.