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The research of frontier orbit and active site of penicillin molecule has theoretical and practical significance to better understand the physical and chemical properties of penicillin molecule, to synthesize penicillin molecule and to develop its new pharmacological properties. In this paper, based on density functional theory, the spatial structure of penicillin molecules was firstly constructed by using Gaussian View 6.0 software, and the configuration optimization and frequency calculation of penicillin molecules were performed by using Gaussian09 software at the B3LYP/ 6-311g (D, P) basis set level. On the basis of structural optimization, based on time-dependent density functional theory, 25 excited states of penicillin molecules in aqueous solution were calculated, and then the frontier orbitals and active sites of penicillin molecules were analyzed by Multiwfn3.6 software, Fukui function method and frontier orbital theory method. The UV spectrum was plotted with Origin2017 software. The results show that the highest occupied molecular orbital (HOMO) and the lowest unoccpied molecular orbital (LUMO) of penicillin molecule are the 88th and 89th electron orbital, respectively. The maximum absorption peak of penicillin molecule UV spectrum is at 220.89nm, and its absorption mole coefficient is 6960.18L/mol/cm. It is mainly formed by the transition from the ground state S0 of the electronic state to the excited state S2, S4, S9, S11 and S12 of the electronic state, and the transition from S0 to the excited state S4 is the biggest contributor to the UV spectrum. The nucleophile site of penicillin molecule is C35 and the potentiophile site is S25.

Supplemental material, sj-pdf-1-smm-10.1177_09622802211060520 for Censored quantile regression based on multiply robust propensity scores by Xiaorui Wang, Guoyou Qin, Xinyuan Song and Yanlin Tang in Statistical Methods in Medical Research

Supplemental material, sj-pdf-1-smm-10.1177_09622802211060520 for Censored quantile regression based on multiply robust propensity scores by Xiaorui Wang, Guoyou Qin, Xinyuan Song and Yanlin Tang in Statistical Methods in Medical Research

Background The identification of tea varieties is essential to obtain high-quality tea that can command a high price. To identify tea varieties quickly and non-destructively, and to fight against counterfeit and inferior products in the tea market, a new method of visible / near-infrared spectrum processing based on competitive adaptive reweighting algorithms-stepwise regression analysis (CARS-SWR) variable optimization is proposed in this paper. Results The spectral data of five different tea varieties were obtained by visible / near-infrared spectrometry. The spectral data were preprocessed by the multivariate scattering correction (MSC) algorithm. First, 20 wavelength variables were selected by CARS, and then six optimal wavelength variables were selected using the SWR method, based on the CARS optimal variables. The generalized regression neural network (GRNN) classification model and probabilistic neural network (PNN) classification model were established, based on spectral information from the full wavelength, the CARS preferred wavelength variable, the SWR preferred wavelength variable, and the CARS-SWR preferred wavelength variable. Conclusion It was found that the CARS-SWR-PNN model had the best classification effect by comparing different modeling results. The classification accuracy of its training set and test set reached 100%. This shows that the CARS-SWR preferred variable method combined with the visible / near-infrared spectrum is feasible for the rapid and non-destructive identification of tea varieties. © 2019 Society of Chemical Industry.

The aim of our study was to evaluate the therapeutic effect of antiviral drugs on COVID‐19 pneumonia. Patients confirmed with COVID‐19 pneumonia were enrolled and divided into 7 groups according to the treatment option. Information including age, gender and duration from illness onset to admission, clinical manifestations and laboratory data at admission, and length of hospital stay were evaluated. The chest CT imaging obtained at admission and after a 5‐d treatment cycle were assessed. The clinical symptoms and laboratory tests at discharge were also assessed. At admission, no significant differences were found among the groups, including duration from illness onset to admission, clinical symptoms and main laboratory results. No significant differences were found among the groups in terms of the proportion of patients with pneumonia resolution (P=0.151) after treatment or the length of hospital stay (P=0.116). At discharge, 7/184 (4%) patients had a mild cough while their other symptoms had disappeared, and the proportion of patients with abnormal liver function and with increased leucocytes, neutrophils or erythrocyte sedimentation rate among the 184 patients were close to those at admission. According to the results, the inclusion of antiviral drugs in therapeutic regimens based on symptomatic treatment had no significant additional impact on the improvement in COVID‐19 patients. In addition, the results of chest CT imaging, clinical manifestations, and laboratory tests at discharge were not completely consistent. This article is protected by copyright. All rights reserved.

Community structure and throughfall erosivity of artificial rainforest were compared with rubber forest and seasonal rainforest in this study.After 16 years grown without any management,the Shannon-Wiener index of artificial rainforest has increased to 3.652,which was much closer to local seasonal rainforest.A calculation of throughfall erosivity based on 6 years′ data shown that the throughfall erosivity of artificial rainforest in July was 962.2 MJ mm hm-2 h-1 a-1,and the amount of rainfall erosivity reduction to clear surface was2.08 times higher than rubber forest.Artificial rainforest has similar community structure and leaf area index(LAI) to tropical seasonal rainforest,and decreasing throughfall erosivity efficiently,which were very useful for soil conservation and vegetation restoration.Artificial rainforest is a feasible restoration type for degraded ecosystem in tropical area.

This study was engaged in a new algorithm which was used to solve the problem of protein folding. The conformation of hydrophobic core of protein was key factor of structure of protein. So, in our algorithm, we set a hydrophobic core which was restricted by new aggregate. Then, the hydrophilic residues between two hydrophobic residues were ranged, the optimal conformation was gained if all residues were not overlap and continuous. The algorithm in this study can be prevented effectively falls into partially smallest energy.