Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis.

Halide methyltransferases (HMTs) provide an effective way to regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine and reactive electrophiles, such as methyl iodide (MeI) and methyl toluene sulfonate (MeOTs). As compared with MeI, the cost-effective unnatural substrate MeOTs can be accessed directly from cheap and abundant alcohols, but shows only limited reactivity in SAM production. In this study, we developed a dynamic cross-correlation network analysis (DCCNA) strategy for quickly identifying hot spots influencing the catalytic efficiency of the enzyme, and applied it to the evolution of HMT from Paraburkholderia xenovorans. Finally, the optimal mutant, M4 (V55T/C125S/L127T/L129P), exhibited remarkable improvement, with a specific activity of 4.08 U/mg towards MeOTs, representing an 82-fold increase as compared to the wild-type (WT) enzyme. Notably, M4 also demonstrated a positive impact on the catalytic ability with other methyl donors. The structural mechanism behind the enhanced enzyme activity was uncovered by molecular dynamics simulations. Our work not only contributes a promising biocatalyst for the regeneration of SAM, but also offers a strategy for efficient enzyme engineering.

Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states.

BACKGROUND: Estimating the depth of anaesthesia (DoA) is critical in modern anaesthetic practice. Multiple DoA monitors based on electroencephalograms (EEGs) have been widely used for DoA monitoring; however, these monitors may be inaccurate under certain conditions. In this work, we hypothesize that heart rate variability (HRV)-derived features based on a deep neural network can distinguish different anaesthesia states, providing a secondary tool for DoA assessment. METHODS: A novel method of distinguishing different anaesthesia states was developed based on four HRV-derived features in the time and frequency domain combined with a deep neural network. Four features were extracted from an electrocardiogram, including the HRV high-frequency power, low-frequency power, high-to-low-frequency power ratio, and sample entropy. Next, these features were used as inputs for the deep neural network, which utilized the expert assessment of consciousness level as the reference output. Finally, the deep neural network was compared with the logistic regression, support vector machine, and decision tree models. The datasets of 23 anaesthesia patients were used to assess the proposed method. RESULTS: The accuracies of the four models, in distinguishing the anaesthesia states, were 86.2% (logistic regression), 87.5% (support vector machine), 87.2% (decision tree), and 90.1% (deep neural network). The accuracy of deep neural network was higher than those of the logistic regression (p < 0.05), support vector machine (p < 0.05), and decision tree (p < 0.05) approaches. Our method outperformed the logistic regression, support vector machine, and decision tree methods. CONCLUSIONS: The incorporation of four HRV-derived features in the time and frequency domain and a deep neural network could accurately distinguish between different anaesthesia states; however, this study is a pilot feasibility study. The proposed method-with other evaluation methods, such as EEG-is expected to assist anaesthesiologists in the accurate evaluation of the DoA.

Equatorial waves as useful precursors to tropical cyclone occurrence and intensification.

Understanding and prediction of tropical cyclone (TC) activity on the medium range remains challenging. Here, we find that the pre-existing westward-moving equatorial waves can inform the risk of TC occurrence and intensification, based on a dataset obtained by synchronising objectively identified TCs and equatorial waves in a climate reanalysis. Globally, westward-moving equatorial waves can be precursors to 60-70% of pre-tropical cyclogenesis events, and to >80% of the events with the strongest vorticity, related to the favourable environmental conditions within the pouch of equatorial waves. We further find that when storms are in-phase with westward-moving equatorial waves, the intensification rate of TCs is augmented, whilst in other phases of the waves, storm intensity grows more slowly, or even decays. Coherent wave packets associated with TCs are identifiable up to two weeks ahead. Our findings show that westward-moving equatorial waves can be useful medium-range precursors to TC activity.

Multipartite symbioses in fungus-growing termites (Blattodea: Termitidae, Macrotermitinae) for the degradation of lignocellulose.

Fungus-growing termites are among the most successful herbivorous animals and improve crop productivity and soil fertility. A range of symbiotic organisms can be found inside their nests. However, interactions of termites with these symbionts are poorly understood. This review provides detailed information on the role of multipartite symbioses (between termitophiles, termites, fungi, and bacteria) in fungus-growing termites for lignocellulose degradation. The specific functions of each component in the symbiotic system are also discussed. Based on previous studies, we argue that the enzymatic contribution from the host, fungus, and bacteria greatly facilitates the decomposition of complex polysaccharide plant materials. The host-termitophile interaction protects the termite nest from natural enemies and maintains the stability of the microenvironment inside the colony.

[Effect of Huchang Qingfei concentrated pellets on E-cadherin expression in lung tissue of mice infected with Mycoplasma pneumoniae].

OBJECTIVE: To investigate the effects of Huchang Qingfei concentrated pellets on the expression of E-cadherin (E-cd) in the lung tissue from mice infected with Mycoplasma pneumoniae (MP). METHOD: A mice model of Mycoplasmal pneumonia (MPP) was developed by repeatedly intranasal infectious route. Transmission electronic microscope (TEM) and immunohistochemistry stain were performed to observe the pathological changes and expression of E-cd in lung tissues. RESULT: Under TEM it was found that the cellular membrane was ruptured, mitochondria was denatured, crista was broken in the pulmonary cells of the model group; the all above parameters in Huchang medicated group were improved obviously. The immunohistochemistry test showed that strong positive brown stain of E-cd expression was found in the pulmonary epithelial cell membrane and bronchial periphery in the model group, however, in the medicated group, the E-cd expression level in the cellular membrane was decreased and the expression ratio was dropped significantly as compared with the model controls. CONCLUSION: Huchang Qingfei concentrated pellets can inhibit the overexpression of E-cd in the lung tissue of mice with MP-infection, which may be helpful for prevention and treatment of pulmonary injury caused by MPP.