Kinetics and Mechanism of <i>Candida </i><i>a</i><i>ntarctica</i> Lipase B Catalyzed Solution Polymerization of ε-Caprolactone

Studies of the kinetics and mechanism of Candida antarctica Lipase B (CALB) catalyzed ε-caprolactone (ε-CL) polymerizations in toluene were performed. The kinetic plot of ln ([M]0/[M]t) vs time was carried out to 96% ε-CL conversion and Mn 11 970. The plot is linear (r2 = 0.998), indicating that termination did not occur and the propagation rate is first order with respect to monomer concentration. Changes in the water (e.g., initiator) concentration did not change the polymerization rate but did change the number of chains [R−OH]. Thus, the polymerization is zero order with respect to [R−OH] and initiator concentration. A plot of ln kapp vs ln [enzyme] gave 0.7 as the reaction order of the enzyme concentration. The apparent activation energy for Novozyme-435 catalyzed ε-CL polymerization in toluene is 2.88 kcal mol-1. This is well below 10.3 kcal mol-1, the activation energy for aluminum alkoxide catalyzed ε-CL polymerization in toluene. Upward deviation from linearity for Mn vs fractional ε-CL conversion and decreases in the number of chains was accentuated by low enzyme water contents and high monomer conversion. These results are consistent with a competition between ring-opening chain-end propagation and chain growth by steplike polycondensations. CALB was irreversibly inhibited by modification with paraoxon at the lipase active site (Ser105). The modified enzyme was no longer active for the polymerization. This supports that the polymerizations studied herein occurred by catalysis at the active serine residue (Ser105) and not by other chemical or nonspecific protein-mediated processes

Probing Water-Temperature Relationships for Lipase-Catalyzed Lactone Ring-Opening Polymerizations

Polymerizations of ε-CL catalyzed by Novozyme-435 (immobilized Lipase B from Candida antarctica) were studied at temperatures between 20 and 108 °C. The monomer conversion to polymer was remarkably rapid at ambient temperature. At 20 °C by 7 h, ε-CL conversion and product Mn were >97% and 17 800, respectively. Contrary to previous reports, the number of chains formed, as well as the product molecular weight, was almost identical for polymerizations at constant enzyme water content between 60 and 108 °C. Thus, differences in reaction temperature over a 48 °C range did not “free” water from “bound” states so that it could function for chain initiation. At 60 °C, variation in the enzyme water content from 0.6 to 1.9% increased the number of chains formed but did not change the polymerization propagation kinetics. Therefore, the enzyme water content and not the reaction temperature regulated the product molecular weight. In contrast, at 108 °C, an increase in the reaction water content from 0.6 to 1.8% increased both the number of chains and the polymerization propagation kinetics. Explanations for these differences in behavior as a function of temperature and water contents are discussed

DataSheet1_Detrended fluctuation analysis based on best-fit polynomial.PDF

Detrended fluctuation analysis (DFA) can quantify long-range correlation (LRC) and fractal scaling behavior of signal. We compared the results of variant DFA methods by varying the order of the polynomial and found that the order of 6 was relatively better than the others when both the accuracy and computational cost were taken into account. An alternative DFA method is proposed to quantify the LRC exponent by using best-fit polynomial algorithm in each segment instead of the polynomial of the same order in all of segments. In this study, the best-fit polynomial algorithm with the maximum order of 6 is used to fit the local trend in each segment to detrend the trend of a time series, and then the revised DFA is used to quantify the LRC in the time series. A series of numerical studies demonstrate that the best-fit DFA performs better than regular DFA, especially for the time series with scaling exponent smaller than 0.5. This may be attributed to the improvement of the fitted trend at the end of each segment. The estimation results of variant DFA methods reach stable when the time series length is greater than 1,000.</p

Image1_Complexity of daily precipitation and its change in China during 1961–2015 based on approximate entropy.pdf

Approximate entropy (ApEn) can measure the regularity and complexity of a nonlinear system. We find that the results of ApEn are relatively stable when the sample size of a time series exceeds 100, which indicates that the estimation results of the ApEn algorithm are robust to small sample data. In this study, the complexity of the daily precipitation records in China from 1961 to 2015 was first analyzed by using ApEn, and then we further investigated the spatial and temporal variability of the dynamical characteristics of precipitation. The results show that the ApEn values of daily precipitation in China during 1961–2015 present the following characteristics: larger in southern and eastern China and smaller in northern and western China. In addition, ApEn in Northwest China and the Tibetan Plateau has been increasing since 1961. However, since the 1970s, ApEn in the south of the middle and lower reaches of the Yangtze River shows a gradual decrease. The temporal instances of abrupt ApEn changes in daily precipitation occur from region to region. The number of stations with an abrupt ApEn shift has a statistically significant increase since 1984 at a significant level of α = 0.01, which means the complexity characteristic of daily precipitation in China has been more prone to abrupt shifts since 1984 than in the previous period.</p

A New Synthetic Method for Controlled Polymerization Using a Microfluidic System

While many parallel synthesis methods developed by the pharmaceutical and life science communities are being applied to polymer synthesis, there remains a need to construct “libraries” of polymeric materials that explore a wider range of polymer structures with accuracy, flexibility, and rapid, often small, changes. We report the use of microfluidics to create an environment for continuous controlled radical polymerization. Varying either the flow rate or the relative concentrations of reactants (i.e., stoichiometry) controls the molecular properties of the products. Molecular variables, here molecular weight, can then be varied continuously. Well-defined materials with narrow molecular weight distributions are produced inside the microfluidic reactor and are available for processing, such as further mixing, deposition, or coating on surfaces. Preliminary kinetic data appear to agree well with literature values reported for larger-scale reactions

Catalytic Reaction Intensification by a Novel Cryogenic Auxiliary Synthesized Fe-PAN Membrane

To solve the contradiction between the stability and activity of the catalytic membrane and achieve process intensification during the catalytic reaction, a novel porous Fe-polyacrylonitrile (PAN) membrane was synthesized by a one-step cryogenic auxiliary electrospinning method and tested for catalytic wet peroxide oxidation (CWPO). During synthesis, nanometals can be evenly entrapped in the PAN fiber and the porous fibrous structure can be formed simultaneously. Fe-PAN showed extraordinary catalytic activity and excellent stability and strongly strengthened the reaction due to the reduced diffusion resistance and high contact efficiency between nanoscale zerovalent iron and reactants. The reaction intensification mechanism of CWPO over Fe-PAN was experimentally and theoretically revealed by the intermediate detection and DFT calculation. The electronic attraction interaction and nucleophilic attack of the oxidative radicals occurred during pollutant degradation. This study reveals the excellent intensification property of Fe-PAN in the catalytic reaction and its potential in practical industrial application

Data_Sheet_1_Review of Abnormal Self-Knowledge in Major Depressive Disorder.docx

Background: Major depressive disorder (MDD) is an affective disorder that is harmful to both physical and mental health. Abnormal self-knowledge, which refers to abnormal judgments about oneself, is a core symptom of depression. However, little research has summarized how and why patients with MDD differ from healthy individuals in terms of self-knowledge.Objective: To gain a better understanding of MDD, we reviewed previous studies that focused on the behavioral and neurological changes of self-knowledge in this illness.Main Findings: On the behavioral level, depressed individuals exhibited negative self-knowledge in an explicit way, while more heterogeneous patterns were reported in implicit results. On the neurological level, depressed individuals, as compared with non-depressed controls, showed abnormal self-referential processing in both early perception and higher cognitive processing phases during the Self-Referential Encoding Task. Furthermore, fMRI studies have reported aberrant activity in the medial prefrontal cortex area for negative self-related items in depression. These results revealed several behavioral features and brain mechanisms underlying abnormal self-knowledge in depression.Future Studies: The neural mechanism of implicit self-knowledge in MDD remains unclear. Future research should examine the importance of others' attitudes on the self-concept of individuals with MDD, and whether abnormal self-views may be modified through cognitive or pharmacological approaches. In addition, differences in abnormal self-knowledge due to genetic variation between depressed and non-depressed populations remain unconfirmed. Importantly, it remains unknown whether abnormal self-knowledge could be used as a specific marker to distinguish healthy individuals from those with MDD.Conclusion: This review extends our understanding of the relationship between self-knowledge and depression by indicating several abnormalities among individuals with MDD and those who are at risk for this illness.</p

Additional file 1: of RIF1 promotes human epithelial ovarian cancer growth and progression via activating human telomerase reverse transcriptase expression

Table S1. Sequences of primers for quantitative real-time PCR. (DOCX 13 kb