Dental caries is the most common oral disease. The bacteriological aetiology of dental caries promotes the use of antibiotics or antimicrobial agents to prevent this type of oral infectious disease. Antibiotics have been developed for more than 80 years since Fleming discovered penicillin in 1928, and systemic antibiotics have been used to treat dental caries for a long time. However, new types of antimicrobial agents have been developed to fight against dental caries. The purpose of this review is to focus on the application of systemic antibiotics and other antimicrobial agents with respect to their clinical use to date, including the history of their development, and their side effects, uses, structure types, and molecular mechanisms to promote a better understanding of the importance of microbial interactions in dental plaque and combinational treatments.

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Objective We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS). Methods The HFRS morbidity data from January 1995 to December 2020 were taken, and subsequently, the data were split into six different training and testing segments (including 12, 24, 36, 60, 84, and 108 holdout monthly data) to investigate its predictive ability of the TBATS method, and its forecasting performance was compared with the seasonal autoregressive integrated moving average (SARIMA). Results The TBATS (0.27, {0,0}, -, {<12,4>}) and SARIMA (0,1,(1,3))(0,1,1) 12 were selected as the best TBATS and SARIMA methods, respectively, for the 12-step ahead prediction. The mean absolute deviation, root mean square error, mean absolute percentage error, mean error rate, and root mean square percentage error were 91.799, 14.772, 123.653, 0.129, and 0.193, respectively, for the preferred TBATS method and were 144.734, 25.049, 161.671, 0.203, and 0.296, respectively, for the preferred SARIMA method. Likewise, for the 24-, 36-, 60-, 84-, and 108-step ahead predictions, the preferred TBATS methods produced smaller forecasting errors over the best SARIMA methods. Further validations also suggested that the TBATS model outperformed the Error-Trend-Seasonal framework, with little exception. HFRS had dual seasonal behaviors, peaking in May–June and November–December. Overall a notable decrease in the HFRS morbidity was seen during the study period (average annual percentage change=−6.767, 95% confidence intervals: −10.592 to −2.778), and yet different stages had different variation trends. Besides, the TBATS model predicted a plateau in the HFRS morbidity in the next ten years. Conclusion The TBATS approach outperforms the SARIMA approach in estimating the long-term epidemic seasonality and trends of HFRS, which is capable of being deemed as a promising alternative to help stakeholders to inform future preventive policy or practical solutions to tackle the evolving scenarios.

Summary The high‐affinity cyclic adenosine monophosphate (cAMP) phosphodiesterase MoPdeH is important not only for cAMP signalling and pathogenicity, but also for cell wall integrity (CWI) maintenance in the rice blast fungus Magnaporthe oryzae . To explore the underlying mechanism, we identified MoImd4 as an inosine‐5′‐monophosphate dehydrogenase (IMPDH) homologue that interacts with MoPdeH. Targeted deletion of MoIMD4 resulted in reduced de novo purine biosynthesis and growth, as well as attenuated pathogenicity, which were suppressed by exogenous xanthosine monophosphate (XMP). Treatment with mycophenolic acid (MPA), which specifically inhibits MoImd4 activity, resulted in reduced growth and virulence attenuation. Intriguingly, further analysis showed that MoImd4 promotes the phosphodiesterase activity of MoPdeH, thereby decreasing intracellular cAMP levels, and MoPdeH also promotes the IMPDH activity of MoImd4. Our studies revealed the presence of a novel crosstalk between cAMP regulation and purine biosynthesis in M. oryzae , and indicated that such a link is also important in the pathogenesis of M. oryzae.

Summary Mitochondrial quality and quantity are essential for a cell to maintain normal cellular functions. Our previous study revealed that the transcription factor MoMsn2 plays important roles in the development and virulence of Magnaporthe oryzae. However, to date, no study has reported its underlying regulatory mechanism in phytopathogens. Here, we explored the downstream target genes of MoMsn2 using a chromatin immunoprecipitation sequencing (ChIP‐Seq) approach. In total, 332 target genes and five putative MoMsn2‐binding sites were identified. The 332 genes exhibited a diverse array of functions and the highly represented were genes involved in metabolic and catalytic processes. Based on the ChIP‐Seq data, we found that MoMsn2 plays a role in maintaining mitochondrial morphology, likely by targeting a number of mitochondria‐related genes. Further investigation revealed that MoMsn2 targets the putative 3‐methylglutaconyl‐CoA hydratase‐encoding gene (MoAUH1) to control mitochondrial morphology and mitophagy, which are critical for the infectious growth of the pathogen. Meanwhile, the deletion of MoAUH1 resulted in phenotypes similar to the ΔMomsn2 mutant in mitochondrial morphology, mitophagy and virulence. Overall, our results provide evidence for the regulatory mechanisms of MoMsn2, which targets MoAUH1 to modulate its transcript levels, thereby disturbing the mitochondrial fusion/fission balance. This ultimately affects the development and virulence of M. oryzae.

The cyclic adenosine monophosphate (cAMP) signalling pathway mediates signal communication and sensing during infection-related morphogenesis in eukaryotes. Many studies have implicated cAMP as a critical mediator of appressorium development in the rice blast fungus, Magnaporthe oryzae. The cAMP phosphodiesterases, MoPdeH and MoPdeL, as key regulators of intracellular cAMP levels, play pleiotropic roles in cell wall integrity, cellular morphology, appressorium formation and infectious growth in M. oryzae. Here, we analysed the roles of domains of MoPdeH and MoPdeL separately or in chimeras. The results indicated that the HD and EAL domains of MoPdeH are indispensable for its phosphodiesterase activity and function. Replacement of the MoPdeH HD domain with the L1 and L2 domains of MoPdeL, either singly or together, resulted in decreased cAMP hydrolysis activity of MoPdeH. All of the transformants exhibited phenotypes similar to that of the ΔMopdeH mutant, but also revealed that EAL and L1 play additional roles in conidiation, and that L1 is involved in infectious growth. We further found that the intracellular cAMP level is important for surface signal recognition and hyphal autolysis. The intracellular cAMP level negatively regulates Mps1-MAPK and positively regulates Pmk1-MAPK in the rice blast fungus. Our results provide new information to better understand the cAMP signalling pathway in the development, differentiation and plant infection of the fungus.

The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM.

The traditional single current sensor control strategy of a permanent magnet synchronous motor (PMSM) often adopts the DC bus method, which makes it difficult to eliminate the blind area of current reconstruction. Therefore, a current reconstruction method based on a sliding mode observer is proposed. Based on the current equation of the motor, the method takes the α-axis and β-axis currents as the observation objects and shares the same synovial surface, so that the α-axis current observation value and the β-axis current observation value converge to the actual current value at the same time and the unknown β-axis current information is obtained. The control system first tests the performance of the motor under different working conditions when the parameters are matched, and then tests the current reconstruction ability of the parameter mismatch. The results show that the current observer with a matched parameter can accurately and quickly reconstruct the β-axis current under various operating conditions, and the maximum current error does not exceed 4 mA. When the parameters are mismatched, high-performance control of the motor can still be achieved. The proposed method has excellent robustness.