An axial flow cyclone to remove nanoparticles at low pressure conditions

In this study, the axial flow cyclone used in Tsai et al. (2004) was further tested for the collection efficiency of both solid (NaCl) and liquid (OA, oleic acid) nanoparticles. The results showed that the smallest cutoff aerodynamic diameters achieved for OA and NaCl nanoparticles were 21.7 nm (cyclone inlet pressure: 4.3 Torr, flow rate: 0.351 slpm) and 21.2 nm (5.4 Torr, 0.454 slpm), respectively. The collection efficiencies for NaCl and OA particles were close to each other for the aerodynamic diameter ranging from 25 to 180 nm indicating there was almost no solid particle bounce in the cyclone. The 3-D numerical simulation was conducted to calculate the flow field in the cyclone and the flow was found to be nearly paraboloid. Numerical simulation of the particle collection efficiency based on the paraboloid flow assumption showed that the collection efficiency was in good agreement with the experimental data with less than 15% of error. A semi-empirical equation for predicting the cutoff aerodynamic diameter at different inlet pressures and flow rates was also obtained. The semi-empirical equation is able to predict the cutoff aerodynamic diameter accurately within 9% of error. From the empirical cutoff aerodynamic diameter, a semi-empirical square root of the cutoff Stokes number, , was calculated and found to be a constant value of 0.241. This value is useful to the design of the cyclone operating in vacuum to remove nanoparticles.     

CP violations in predictive neutrino mass structures

We study the CP-violation effects from two types of neutrino mass matrices with (i) \((M_\nu )_{ee}=0\), and (ii) \((M_\nu )_{ee}=(M_\nu )_{e\mu }=0\), which can be realized by the high-dimensional lepton number violating operators \(\bar{\ell }_R^c\gamma ^\mu L_L (D_\mu \Phi )\Phi ^2\) and \(\bar{\ell }_R^c l_R (D_\mu {\Phi })^2\Phi ^2\), respectively. In (i), the neutrino mass spectrum is in the normal ordering with the lightest neutrino mass within the range \(0.002\,\mathrm{eV}\lesssim m_0\lesssim 0.007\,\mathrm{eV}\). Furthermore, for a given value of \(m_0\), there are two solutions for the two Majorana phases \(\alpha _{21}\) and \(\alpha _{31}\), whereas the Dirac phase \(\delta \) is arbitrary. For (ii), the parameters of \(m_0\), \(\delta \), \(\alpha _{21}\), and \(\alpha _{31}\) can be completely determined. We calculate the CP-violating asymmetries in neutrino–antineutrino oscillations for both mass textures of (i) and (ii), which are closely related to the CP-violating Majorana phases.     

Biosynthesis of Streptolidine Involved Two Unexpected Intermediates Produced by a Dihydroxylase and a Cyclase through Unusual Mechanisms

Streptothricin‐F (STT‐F), one of the early‐discovered antibiotics, consists of three components, a β‐lysine homopolymer, an aminosugar D ‐gulosamine, and an unusual bicyclic streptolidine. The biosynthesis of streptolidine is a long‐lasting but unresolved puzzle. Herein, a combination of genetic/biochemical/structural approaches was used to unravel this problem. The STT gene cluster was first sequenced from a Streptomyces variant BCRC 12163, wherein two gene products OrfP and OrfR were characterized in vitro to be a dihydroxylase and a cyclase, respectively. Thirteen high‐resolution crystal structures for both enzymes in different reaction intermediate states were snapshotted to help elucidate their catalytic mechanisms. OrfP catalyzes an Fe^II‐dependent double hydroxylation reaction converting L ‐Arg into (3R,4R)‐(OH)₂‐L ‐Arg via (3S)‐OH‐L ‐Arg, while OrfR catalyzes an unusual PLP‐dependent elimination/addition reaction cyclizing (3R,4R)‐(OH)₂‐L ‐Arg to the six‐membered (4R)‐OH‐capreomycidine. The biosynthetic mystery finally comes to light as the latter product was incorporation into STT‐F by a feeding experiment.     

X‐Ray Emission Spectroscopy: A Spectroscopic Measure for the Determination of NO Oxidation States in Fe–NO Complexes

Extensive study of the electronic structure of Fe‐NO complexes using a variety of spectroscopic methods was attempted to understand how iron controls the binding and release of nitric oxide. The comparable energy levels of NO π* orbitals and Fe 3d orbitals complicate the bonding interaction within Fe? NO complexes and puzzle the quantitative assignment of NO oxidation state. Enemark–Feltham notation, {Fe(NO)_x}ⁿ, was devised to circumvent this puzzle. This 40‐year puzzle is revisited using valence‐to‐core X‐ray emission spectroscopy (V2C XES) in combination with computational study. DFT calculation establishes a linear relationship between ΔE_σ2s*‐σ2p of NO and its oxidation state. V2C Fe XES study of Fe? NO complexes reveals the ΔE_σ2s*‐σ2p of NO derived from NO σ_2s*/σ_2p→Fe_1s transitions and determines NO oxidation state in Fe? NO complexes. Quantitative assignment of NO oxidation state will correlate the feasible redox process of nitric oxide and Fe‐nitrosylation biology.     

Porosity‐Controlled Eggshell Membrane as 3D SERS‐Active Substrate

We report on the fabrication of a surface‐enhanced Raman scattering (SERS) platform, comprised of a three‐dimensional (3D) porous eggshell membrane (ESM) scaffold decorated with Ag nanoparticles (NPs). Both native and treated ESM were used, where the treated ESM pore size and fiber crossing density was controlled by timed exposure to hydrogen peroxide (H₂O₂). Ag NPs were synthesized in situ by reduction of silver nitrate with ascorbic acid. Our results demonstrate that H₂O₂‐treated Ag‐ESM provides a more densely packed 3D network of active material, which leads to consistently higher SERS enhancement than untreated Ag‐ESM substrates.     

A Dynamic Model for Cellulosic Biomass Hydrolysis: a Comprehensive Analysis and Validation of Hydrolysis and Product Inhibition Mechanisms

The objective of this study is to perform a comprehensive enzyme kinetics analysis in view of validating and consolidating a semimechanistic kinetic model consisting of homogeneous and heterogeneous reactions for enzymatic hydrolysis of lignocellulosic biomass proposed by the U.S. National Renewable Energy Laboratory (Kadam et al., Biotechnol Prog 20(3):698–705, 2004) and its variations proposed in this work. A number of dedicated experiments were carried out under a range of initial conditions (Avicel® versus pretreated barley straw as substrate, different enzyme loadings and different product inhibitors such as glucose, cellobiose and xylose) to test the hydrolysis and product inhibition mechanisms of the model. A nonlinear least squares method was used to identify the model and estimate kinetic parameters based on the experimental data. The suitable mathematical model for industrial application was selected among the proposed models based on statistical information (weighted sum of square errors). The analysis showed that transglycosylation plays a key role at high glucose levels. It also showed that the values of parameters depend on the selected experimental data used for parameter estimation. Therefore, the parameter values are not universal and should be used with caution. The model proposed by Kadam et al. (Biotechnol Prog 20(3):698–705, 2004) failed to predict the hydrolysis phenomena at high glucose levels, but when combined with transglycosylation reaction(s), the prediction of cellulose hydrolysis behaviour over a broad range of substrate concentrations (50–150 g/L) and enzyme loadings (15.8–31.6 and 1–5.9 mg protein/g cellulose for Celluclast and Novozyme 188, respectively) was possible. This is the first study introducing transglycosylation into the semimechanistic model. As long as these type of models are used within the boundary of their validity (substrate type, enzyme source and substrate concentration), they can support process design and technology improvement efforts at pilot and full-scale studies.     

Nephrotoxicity assessments of benzo(a)pyrene during zebrafish embryogenesis

Benzo(a)pyrene is a chemical produced during the process of making fried, roasted, and smoked foods. It remains unclear whether benzo(a)pyrene affects the early development of human organs. In this study, we used the transgenic zebrafish line Tg(wt1b:GFP) as a model to assess benzo(a)pyrene-induced kidney malformation. By soaking zebrafish embryos in benzo(a)pyrene at various doses (2, 20, and 200 ppb), only a minor effect on the survival rate was detected (0 ppb: 97.8 ± 1.9 %; 2–200 ppb: 89.1 ± 5.8–91.5 ± 8.3 %). However, benzo(a)pyrene significantly affected the development of the kidney (malformation rates ranges from 50.0 ± 3.5 to 77.4 ± 5.3 %). Various abnormalities, such as unusual curving of pronephric tubes, swollen glomerulus, and incomplete development of pronephric ducts, were observed. This study provides a rapid and effective protocol for the evaluation of the notable effects of benzo(a)pyrene on embryonic kidney development.     

Comprehensive 1H and 13C NMR assignment of 13 protobassic acid saponins

This study aimed to carry out complete ¹H and ¹³C NMR assignment of 13 protobassic acid saponins, including arganins A–C ( 1 – 3 ) and F ( 4 ), butyrosides B–D ( 5 – 7 ), tieghemelin ( 8 ), 3′-O-glucosyl-arganin C ( 9 ), Mi-saponins A–C ( 10 – 12 ), and mimusopsin ( 13 ), recorded in methanol-d₄. This was accomplished by the analysis of high-resolution one-dimensional (1D) NMR (¹H and ¹³C), two-dimensional (2D) NMR (¹H–¹H COSY, HSQC, and HMBC), and selectively excited 1D TOCSY spectra. Before this study, ¹H and ¹³C NMR data of arganins A–C ( 1 – 3 ) and F ( 4 ) were partially assigned. Our effort leads to their complete assignment, especially the glycon residue, and revises some reported data. Some revisions of the ¹H and ¹³C NMR data in the glycon part of butyroside C ( 6 ), tieghemelin ( 8 ), Mi-saponin A ( 10 ), and mimusopsin ( 13 ) were made. Those data of butyrosides B and D ( 5 & 7 ) and Mi-saponin B ( 11 ), which had not been recorded in methanol-d₄, are provided. In addition, the ¹H and ¹³C NMR data of Mi-saponin C ( 12 ) are reported for the first time. These data, being recorded in methanol-d₄, should be more friendly for use as a reference for identifying the related triterpenoid saponins.