A novel comprehensive strategy for high-thoroughly studying released compounds during the combustion process of herbs. A case study for Artemisia argyi Levl. et Vant.

The comprehensive study of compound variations in released smoke during the combustion process is a great challenge in many scientific fields related to analytical chemistry like traditional Chinese medicine, environment analysis, food analysis, etc. In this work, we propose a new comprehensive strategy for efficiently and high-thoroughly characterizing compounds in the online released complex smokes: (i) A smoke capture device was designed for efficiently collecting chemical constituents to perform gas chromatography-mass spectrometry (GC-MS) based untargeted analysis. (ii) An advanced data analysis tool, AntDAS-GCMS, was used for automatically extracting compounds in the original acquired GC-MS data files. Additionally, a GC-MS data analysis guided instrumental parameter optimizing strategy was proposed for the optimization of parameters in the smoke capture device. The developed strategy was demonstrated by the study of compound variations in the smoke of traditional Chinese medicine, Artemisia argyi Levl. et Vant. The results indicated that more than 590 components showed significant differences among released smokes of various moxa velvet ratios. Finally, about 88 compounds were identified, of which phenolic compounds were the most abundant, followed by aromatics, alkenes, alcohols and furans. In conclusion, we may provide a novel approach to the studies of compounds in online released smoke.

Anisotropic Nonlocal Damping in Ferromagnet/α-GeTe Bilayers Enabled by Splitting Energy Bands.

The understanding and manipulation of anisotropic Gilbert damping is crucial for both fundamental research and versatile engineering and optimization. Although several works on anisotropic damping have been reported, no direct relationship between the band structure and anisotropic damping was established. Here, we observed an anisotropic damping in Fe/GeTe manipulated by the symmetric band structures of GeTe via angle-resolved photoemission spectroscopy. Moreover, the anisotropic damping can be modified by the symmetry of band structures. Our Letter provides insightful understandings of the anisotropic Gilbert damping in ferromagnets interfaced with Rashba semiconductors and suggests the possibility of manipulating the Gilbert damping by band engineering.

Surface coupling in Bi2Se3 ultrathin films by screened Coulomb interaction.

Single-particle band theory has been very successful in describing the band structure of topological insulators. However, with decreasing thickness of topological insulator thin films, single-particle band theory is insufficient to explain their band structures and transport properties due to the existence of top and bottom surface-state coupling. Here, we reconstruct this coupling with an equivalently screened Coulomb interaction in Bi2Se3 ultrathin films. The thickness-dependent position of the Dirac point and the magnitude of the mass gap are discussed in terms of the Hartree approximation and the self-consistent gap equation. We find that for thicknesses below 6 quintuple layers, the magnitude of the mass gap is in good agreement with the experimental results. Our work provides a more accurate means of describing and predicting the behaviour of quasi-particles in ultrathin topological insulator films and stacked topological systems.

Using UHPLC-HRMS-based comprehensive strategy to efficiently and accurately screen and identify illegal additives in health-care foods.

Accurately and high-thoroughly screening illegal additives in health-care foods continues to be a challenging task in routine analysis for the ultrahigh performance liquid chromatography-high resolution mass spectrometry based techniques. In this work, we proposed a new strategy to identify additives in complex food matrices, which consists of both experimental design and advanced chemometric data analysis. At first, reliable features in the analyzed samples were screened based on a simple but efficient sample weighting design, and those related to illegal additives were screened with robust statistical analysis. After the MS1 in-source fragment ion identification, both MS1 and MS/MS spectra were constructed for each underlying compound, based on which illegal additives can be precisely identified. The performance of the developed strategy was demonstrated by using mixture and synthetic sample datasets, indicating an improvement of data analysis efficiency up to 70.3 %. Finally, the developed strategy was applied for the screening of unknown additives in 21 batches of commercially available health-care foods. Results indicated that at least 80 % of false-positive results can be reduced and 4 additives were screened and confirmed.

Glutathione S-Transferase Highly Expressed in Holotrichia parallela Antennae Inactivates the Odorant Unsaturated Aldehyde Volatiles.

Odorant-degrading enzymes in insects play a vital role in maintaining olfactory sensitivity. However, the role and molecular mechanism of glutathione S-transferases (GSTs) in odorant inactivation has been rarely studied. In the present study, 31 GSTs were identified from the antennal transcriptome of Holotrichia parallela. HpGSTd1 possesses the highest transcriptome expression level. Recombinant HpGSTd1 showed degradation activity toward various unsaturated aldehyde volatiles. Furthermore, the metabolite of cinnamaldehyde was identified by high-resolution mass spectrometry (HRMS). The molecular docking analysis and site-directed mutagenesis revealed the key residues of HpGSTd1 in degrading odorants. In addition, the unsaturated aldehyde volatiles elicited the behavioral and electrophysiological responses of H. parallela. Taken together, our findings suggest that HpGSTd1 may play an essential role in inactivating odorants in H. parallela, which provides new insights for identifying molecular targets and exploring effective olfactory regulators for this underground pest.

A comparison of feature extraction capabilities of advanced UHPLC-HRMS data analysis tools in plant metabolomics.

Data analysis of ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) is an essential and time-consuming step in plant metabolomics and feature extraction is the fundamental step for current tools. Various methods lead to different feature extraction results in practical applications, which may puzzle users for selecting adequate data analysis tools to deal with collected data. In this work, we provide a comprehensive method evaluation for some advanced UHPLC-HRMS data analysis tools in plant metabolomics, including MS-DIAL, XCMS, MZmine, AntDAS, Progenesis QI, and Compound Discoverer. Both mixtures of standards and various complex plant matrices were specifically designed for evaluating the performances of the involved method in analyzing both targeted and untargeted metabolomics. Results indicated that AntDAS provide the most acceptable feature extraction, compound identification, and quantification results in targeted compound analysis. Concerning the complex plant dataset, both MS-DIAL and AntDAS can provide more reliable results than the others. The method comparison is maybe useful for the selection of suitable data analysis tools for users.

Dual Topology of Dirac Electron Transport and Photogalvanic Effect in Low-Dimensional Topological Insulator Superlattices.

Dual topological insulators, simultaneously protected by time-reversal symmetry and crystalline symmetry, open great opportunities to explore different symmetry-protected metallic surface states. However, the conventional dual topological states located on different facets hinder integration into planar opto-electronic/spintronic devices. Here, dual topological superlattices (TSLs) Bi2 Se3 -(Bi2 /Bi2 Se3 )N with limited stacking layer number N are constructed. Angle-resolved photoelectron emission spectra of the TSLs identify the coexistence and adjustment of dual topological surface states on Bi2 Se3 facet. The existence and tunability of spin-polarized dual-topological bands with N on Bi2 Se3 facet result in an unconventionally weak antilocalization effect (WAL) with variable WAL coefficient α (maximum close to 3/2) from quantum transport experiments. Most importantly, it is identified that the spin-polarized surface electrons from dual topological bands exhibit circularly and linearly polarized photogalvanic effect (CPGE and LPGE). It is anticipated that the stacked dual-topology and stacking layer number controlled bands evolution provide a platform for realizing intrinsic CPGE and LPGE. The results show that the surface electronic structure of the dual TSLs is highly tunable and well-regulated for quantum transport and photoexcitation, which shed light on engineering for opto-electronic/spintronic applications.

A study of flavor variations during the flaxseed roasting procedure by developed real-time SPME GC-MS coupled with chemometrics.

Volatile compound variations during the roasting procedure play an essential role in the flaxseed-related product. In this work, we proposed a new strategy to high-throughput characterize the dynamic variations of flavors in flaxseed. Volatile compounds released at various roasting times were comprehensively investigated by a newly developed real-time solid-phase microextraction coupled with gas chromatography-mass spectrometry (GC-MS). Raw data files were analyzed by our advanced GC-MS data analysis software AntDAS-GCMS. Chemometric methods such as principal component analysis and partial least squares-discrimination analysis have realized the differences of samples with various roasting times. Finally, a total of 51 compounds from 11 aromas were accurately identified and confirmed with standards, and their variations as a function of roasting time were studied. In conclusion, we provided a new solution for the online monitoring of volatile compounds during the industrial roasting process.

[Clinical significance of serum miRNA-146, OX-LDL and ROS expression in patients with primary ovarian insufficiency].

OBJECTIVE: To investigate the clinical significance of miRNA-146, OX-LDL and ROS in patients with primary ovarian insufficiency (POI). METHODS: 100 patients with POI were prospectively collected and 100 women with normal ovarian function were randomly selected as control group. Serum miRNA-146 expression level was detected by qRT-PCR and serum OX-LDL and ROS expression levels were detected by ELISA. Ovarian granulosa cells of mouse were transfected with miRNA-146 mimics or inhibitors, and then treated with OX-LDL. Cell viability, colony forming ability, apoptosis rate and toll like receptor 4 (TLR4)/nuclear factor-κB (NF-κB) of pathway proteins were evaluated respectively. RESULTS: Compared with control group, the expression level of miRNA-146 in POI group was significantly lower, the expression level of OX-LDL and ROS were significantly higher, and the ovarian volume and peak systolic blood flow velocity of ovarian artery were significantly decreased in POI group. Upregulation of miRNA-146 expression had a protective effect on OX-LDL injured ovarian granulosa cells, as evidenced by increased ovarian granulosa cell viability and colony number, reduced apoptosis, and downregulation of TLR4/NF-κB expression. CONCLUSION: miRNA-146 can target downstream TLR4/NF-κB signaling pathway affects oxidative stress and inflammatory response of POI induced by OX-LDL and ROS, and is expected to become a biomarker for early prediction of POI and a new target for treatment.

A chemometric strategy to automatically screen selected ion monitoring ions for gas chromatography-mass spectrometry-based pseudotargeted metabolomics.

The pseudotargeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) has the advantage of filtering out artifacts originating from sample treatment and accurately quantifying underlying compounds in the analyzed samples. However, this technique faces the problem of selecting high-quality selective ions for performing selected ion monitoring (SIM) on instruments. In this work, we proposed AntDAS-SIMOpt, an automatic untargeted strategy for SIM ion optimization that was accomplished on the basis of an experimental design combined with advanced chemometric algorithms. First, a group of diluted quality control samples was used to screen underlying compounds in samples automatically. Ions in each of the resolved mass spectrum were then evaluated by using the developed algorithms to identify the SIM ion. A Matlab graphical user interface (GUI) was designed to facilitate routine analysis, which can be obtained from http://www.pmdb.org.cn/antdassimopt. The performance of the developed strategy was comprehensively investigated by using standard and complex plant datasets. Results indicated that AntDAS-SIMOpt may be useful for GC-MS-based metabolomics.