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Essential oils (EOs) have promising applications as natural and environmentally friendly antimicrobial agents. Preparation of EOs into emulsions can improve the properties of EOs. The aim of this study was to investigate the mechanism underlying the antibacterial effects of Zanthoxylum bungeanum pericarp essential oil (ZBEO) against Staphylococcus aureus , Escherichia coli , Bacillus cereus , and Shigella boydii , and to determine the effect of nanoemulsions on antibacterial activity. ZBEO efficiently suppressed foodborne pathogenic bacteria, as determined by the minimum inhibitory concentration and survival rate. Based on analyses of bacterial morphology, the degree of leakage of proteins and nucleic acids, and lactate dehydrogenase activity, we found that ZBEO disrupted the integrity and permeability of cell membranes, resulting in the leakage of cellular contents and apoptotic cell death. Prepared ZBEO nanoemulsion (ZBEO-NE) had good dispersion and stability. Both ZBEO and ZBEO-NE inhibited the growth of S. aureus , E. coli , B. cereus , and Sh. boydii in mutton broth, and ZBEO-NE exhibited better inhibitory effects than those of ZBEO. These findings suggest that preparing EOs in the form of nanoemulsions improves the antibacterial properties of EOs, making them suitable for food applications. • Zanthoxylum bungeanum pericarp essential oil (ZBEO) suppressed four foodborne pathogens. • ZBEO disrupt the membrane structure of foodborne pathogenic bacteria. • Prepared ZBEO nanoemulsions had good dispersion and stability. • The ZBEO nanoemulsions showed better antibacterial activity in mutton broth than ZBEO. • Preparing essential oils into nanoemulsion can improve the antibacterial properties of essential oils. [ABSTRACT FROM AUTHOR]

Most existing gradient shimming methods for NMR spectrometers estimate field maps that resolve B 0 inhomogeneity spatially from dual gradient-echo (GRE) images acquired at different echo times. However, the distortions induced by B 0 inhomogeneity that always exists in the GRE images can result in estimated field maps that are distorted in both geometry and intensity, leading to inaccurate shimming. This work proposes a new gradient shimming method based on undistorted field map of B 0 inhomogeneity obtained by a more accurate field map estimation technique. Compared to the traditional field map estimation method, this new method exploits both the positive and negative polarities of the frequency encoded gradients to eliminate the distortions caused by B 0 inhomogeneity in the field map. Next, the corresponding automatic post-data procedure is introduced to obtain undistorted B 0 field map based on knowledge of the invariant characteristics of the B 0 inhomogeneity and the variant polarity of the encoded gradient. The experimental results on both simulated and real gradient shimming tests demonstrate the high performance of this new method. [ABSTRACT FROM AUTHOR]

Highlights: [•] Up-regulation of miR-34a inhibits cell viability. [•] Suppression of miR-34a enhances cell viability. [•] NOX2 is a target of miR-34a in A172 cells. [•] MiR-34a serves as a tumor suppressor in human glioma. [Copyright &y& Elsevier]

Highlights: [•] Inhibition of SOCE reduced H2O2-induced oxidative stress. [•] Inhibition of SOCE attenuated overload of Ca2+ after oxidative stress. [•] Inhibition of SOCE inhibited mitochondrial apoptosis after oxidative stress. [Copyright &y& Elsevier]

Highlights: [•] A new phase correction method which is suitable for complex spectra is proposed. [•] A new strategy combining ‘coarse tuning’ with ‘fine tuning’ is introduced. [•] ‘Coarse tuning’ is to minimize the height difference of tail ends of the peaks. [•] The phase parameters are further optimized by a custom negative penalty function. [Copyright &y& Elsevier]

Abstract: A new automatic baseline correction method for Nuclear Magnetic Resonance (NMR) spectra is presented. It is based on an improved baseline recognition method and a new iterative baseline modeling method. The presented baseline recognition method takes advantages of three baseline recognition algorithms in order to recognize all signals in spectra. While in the iterative baseline modeling method, besides the well-recognized baseline points in signal-free regions, the ‘quasi-baseline points’ in the signal-crowded regions are also identified and then utilized to improve robustness by preventing the negative regions. The experimental results on both simulated data and real metabolomics spectra with over-crowded peaks show the efficiency of this automatic method. [Copyright &y& Elsevier]