Antibacterial characterization of Bacillus velezensis LG37 and mining of genes related to biosynthesis of antibacterial substances

Bacillus velezensis LG37 secretes various antibacterial substances and inhibits the growth of other bacteria. Here, we analyzed the antibacterial characteristics and the screening and verification of genes related to the synthesis of the antibacterial substance of LG37 by antibacterial activities experiment, Local BLAST+, and RT-PCR. LG37 was isolated from aquaculture water and preserved in our laboratory. The phylogenetic tree was used to analyze the genetic relationship between LG37 and the bacteriostatic test indicator strain. LG37 had a more substantial inhibitory effect on closely related strains, while the inhibitory effect on the more distantly related strains was weak. Combined with the results of genome sequencing, the ribosomal peptide (RP) bacteriocin gene and non-ribosomal peptide synthetase (NRPSs) related gene clusters were screened and analyzed. A total of six gene-coding RP bacteriocins and two genes coding surfactins and fengycin A NRPSs gene cluster were screened. Local BLAST+ analysis revealed a total of 11 NRPSs gene clusters. The active expression of the NRPSs and RP encoding genes was further validated by RT-PCR. The findings revealed various genes and gene clusters encoding RP bacteriocins and NRPSs in B. velezensis LG37. The bacterium is potentially valuable in diverse applications in aquaculture

Advancements and challenges in pharmacokinetic and pharmacodynamic research on the traditional Chinese medicine saponins: a comprehensive review

Recent research on traditional Chinese medicine (TCM) saponin pharmacokinetics has revealed transformative breakthroughs and challenges. The multicomponent nature of TCM makes it difficult to select representative indicators for pharmacokinetic studies. The clinical application of saponins is limited by their low bioavailability and short half-life, resulting in fluctuating plasma concentrations. Future directions should focus on novel saponin compounds utilizing colon-specific delivery and osmotic pump systems to enhance oral bioavailability. Optimizing drug combinations, such as ginsenosides with aspirin, shows therapeutic potential. Rigorous clinical validation is essential for practical applications. This review emphasizes a transformative era in saponin research, highlighting the need for clinical validation. TCM saponin pharmacokinetics, guided by traditional principles, are in development, utilizing multidisciplinary approaches for a comprehensive understanding. This research provides a theoretical basis for new clinical drugs and supports rational clinical medication

FPGA implementation of sensorless sliding mode observer with a novel rotation direction detection for PMSM drives

This paper proposes an field programmable gate array (FPGA) implementation of a sensorless controller for surface mounted permanent magnet synchronous machines. Position and speed are both estimated by a sliding mode observer (SMO) which is based on the PMSM stator frame model. The sliding mode manifold is chosen on the real stator current trajetory. In the SMO, a sign function of current error in the feedback correction is adopted. The estimated speed and position are realized on an FPGA controller by COordinate Rotation Digital Computer (CORDIC) algorithm. Using model-based design, with the tools of MATLAB/Simulink and hardware description language coder, the whole control system is designed and implemented in a single FPGA chip. Dedicated hardware optimization algorithms such as pipeline and resource sharing are developed for the implementation as well. The sign function is realized by fully hardware with a relatively high switching frequency. Meanwhile, a fast and practical rotation direction detection method which is based on back electromotive force information is proposed. Experimental results show that the proposed FPGA implemented sensorless SMO for PMSM drives is robust and has high performance.Published versio

Numerical Simulation of a Vortex Combustor Based on Aluminum and Steam

In this paper we report a new development in the numerical model for aluminum-steam combustion. This model is based on the diffusion flame of the continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in agreement with the experimental data. A new type of vortex combustor is proposed to increase the efficiency of the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow in this combustor is established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor, forming a swirling flow around the chamber, whose trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve highly efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied