Serratia marcescens LYGN1 Reforms the Rhizosphere Microbial Community and Promotes Cucumber and Pepper Growth in Plug Seedling Cultivation.

The vegetable plug seedling plays an important role in improving vegetable production. The process of plug seedling contributes to high-quality vegetable seedlings. The substrate composition and chemical fertilizer are widely studied to promote seedling growth. However, little is known about the effect of beneficial bacteria in the rhizosphere microbial community and vegetables' growth during plug seedling. The use of beneficial microbes to promote vegetable seedling growth is of great potential. In this study, we showed that the Serratia marcescens strain LYGN1 enhanced the growth of cucumber and pepper seedlings in plug seedling cultivation. The treatment with LYGN1 significantly increased the biomass and the growth-related index of cucumber and pepper, improving the seedling quality index. Specifically, LYGN1 also improved the cucumber and pepper root system architecture and increased the root diameter. We applied high-throughput sequencing to analyze the microbial community of the seedlings' rhizosphere, which showed LYGN1 to significantly change the composition and structure of the cucumber and pepper rhizosphere microbial communities. The correlation analysis showed that the Abditibacteriota and Bdellovibrionota had positive effects on seedling growth. The findings of this study provide evidence for the effects of Serratia marcescens LYGN1 on the cucumber and pepper rhizosphere microbial communities, which also promoted seedling quality in plug seedling cultivation.

Stable-Isotope N-Me Aziridination Enables Accurate Quantitative C═C Isomeric Lipidomics.

Accurate lipid quantification is essential to revealing their roles in physiological and pathological processes. However, difficulties in the structural resolution of lipid isomers hinder their further accurate quantification. To address this challenge, we developed a novel stable-isotope N-Me aziridination strategy that enables simultaneous qualification and quantification of unsaturated lipid isomers. The one-step introduction of the 1-methylaziridine structure not only serves as an activating group for the C═C bond to facilitate positional identification but also as an isotopic inserter to achieve accurate relative quantification. The high performance of this reaction for the identification of unsaturated lipids was verified by large-scale resolution of the C═C positions of 468 lipids in serum. More importantly, by using this bifunctional duplex labeling method, various unsaturated lipids such as fatty acids, phospholipids, glycerides, and cholesterol ester were accurately and individually quantified at the C═C bond isomeric level during the mouse brain ischemia. This study provides a new approach to quantitative structural lipidomics.

EEG diagnosis of depression based on multi-channel data fusion and clipping augmentation and convolutional neural network.

Depression is an undetectable mental disease. Most of the patients with depressive symptoms do not know that they are suffering from depression. Since the novel Coronavirus pandemic 2019, the number of patients with depression has increased rapidly. There are two kinds of traditional depression diagnosis. One is that professional psychiatrists make diagnosis results for patients, but it is not conducive to large-scale depression detection. Another is to use electroencephalography (EEG) to record neuronal activity. Then, the features of the EEG are extracted using manual or traditional machine learning methods to diagnose the state and type of depression. Although this method achieves good results, it does not fully utilize the multi-channel information of EEG. Aiming at this problem, an EEG diagnosis method for depression based on multi-channel data fusion cropping enhancement and convolutional neural network is proposed. First, the multi-channel EEG data are transformed into 2D images after multi-channel fusion (MCF) and multi-scale clipping (MSC) augmentation. Second, it is trained by a multi-channel convolutional neural network (MCNN). Finally, the trained model is loaded into the detection device to classify the input EEG signals. The experimental results show that the combination of MCF and MSC can make full use of the information contained in the single sensor records, and significantly improve the classification accuracy and clustering effect of depression diagnosis. The method has the advantages of low complexity and good robustness in signal processing and feature extraction, which is beneficial to the wide application of detection systems.

Gear Fault Diagnosis Method Based on Multi-Sensor Information Fusion and VGG.

The gearbox is an important component in the mechanical transmission system and plays a key role in aerospace, wind power and other fields. Gear failure is one of the main causes of gearbox failure, and therefore it is very important to accurately diagnose the type of gear failure under different operating conditions. Aiming at the problem that it is difficult to effectively identify the fault types of gears using traditional methods under complex and changeable working conditions, a fault diagnosis method based on multi-sensor information fusion and Visual Geometry Group (VGG) is proposed. First, the power spectral density is calculated with the raw frequency domain signal collected by multiple sensors before being transformed into a power spectral density energy map after information fusion. Second, the obtained energy map is combined with VGG to obtain the fault diagnosis model of the gear. Finally, two datasets are used to verify the effectiveness and generalization ability of the method. The experimental results show that the accuracy of the method can reach 100% at most on both datasets.

Dual-resolving of positional and geometric isomers of C=C bonds via bifunctional photocycloaddition-photoisomerization reaction system.

The biological functions of lipids largely depend on their chemical structures. The position and configuration of C=C bonds are two of the essential attributes that determine the structures of unsaturated lipids. However, simultaneous identification of both attributes remains challenging. Here, we develop a bifunctional visible-light-activated photocycloaddition-photoisomerization reaction system, which enables the dual-resolving of the positional and geometric isomerism of C=C bonds in lipids when combines with liquid chromatography-mass spectrometry. The dual-pathway reaction mechanism is demonstrated by experiments and density functional theory calculations. Based on this bifunctional reaction system, a workflow of deep structural lipidomics is established, and allows the revealing of unique patterns of cis-trans-isomers in bacteria, as well as the tracking of C=C positional isomers changes in mouse brain ischemia. This study not only offers a powerful tool for deep lipid structural biology, but also provides a paradigm for developing the multifunctional visible-light-induced reaction.

High-Throughput Nano-Electrostatic-Spray Ionization/Photoreaction Mass Spectrometric Platform for the Discovery of Visible-Light-Activated Photocatalytic Reactions in the Picomole Scale.

Visible-light-activated photocatalysis has emerged as a green and powerful tool for the synthesis of various organic compounds under mild conditions. However, the expeditious discovery of novel photocatalysts and synthetic pathways remains challenging. Here, we developed a bifunctional platform that enabled the high-throughput discovery and optimization of new photochemical reactions down to the picomole scale. This platform was designed based on a contactless nano-electrostatic-spray ionization technique, which allows synchronized photoreactions and high-throughput in situ mass spectrometric analysis with a near-100% duty cycle. Using this platform, we realized the rapid screening of photocatalytic reactions in ambient conditions with a high speed of less than 1.5 min/reaction using picomolar materials. The versatility was validated by multiple visible-light-induced photocatalytic reactions, especially the discovery of aerobic C-H thiolation with low-cost organic photocatalysts without any other additives. This study provided a new paradigm for the integration of ambient ionization techniques and new insights into photocatalytic reaction screening, which will have broad applications in the development of new visible-light-promoted reactions.

Distinct lipid metabolic dysregulation in asymptomatic COVID-19.

Asymptomatic infection is a big challenge in curbing the spread of COVID-19. However, its identification and pathogenesis elucidation remain issues. Here, by performing comprehensive lipidomic characterization of serum samples from 89 asymptomatic COVID-19 patients and 178 healthy controls, we screened out a panel of 15 key lipids that could accurately identify asymptomatic patients using a new ensemble learning model based on stacking strategy with a voting algorithm. This strategy provided a high accuracy of 96.0% with only 3.6% false positive rate and 4.8% false negative rate. More importantly, the unique lipid metabolic dysregulation was revealed, especially the enhanced synthesis of membrane phospholipids, altered sphingolipids homeostasis, and differential fatty acids metabolic pattern, implicating the specific host immune, inflammatory, and antiviral responses in asymptomatic COVID-19. This study provides a potential prediagnostic method for asymptomatic COVID-19 and molecular clues for the pathogenesis and therapy of this disease.

Putative multiple reaction monitoring strategy for the comparative pharmacokinetics of postoral administration Renshen-Yuanzhi compatibility through liquid chromatography-tandem mass spectrometry.

BACKGROUND: Exploring the pharmacokinetic (PK) changes of various active components of single herbs and their combinations is necessary to elucidate the compatibility mechanism. However, the lack of chemical standards and low concentrations of multiple active ingredients in the biological matrix restrict PK studies. METHODS: A putative multiple reaction monitoring strategy based on liquid chromatography coupled with mass spectrometry (LC-MS) was developed to extend the PK scopes of quantification without resorting to the use of chemical standards. First, the compounds studied, including components with available reference standard (ARS) and components lacking reference standard (LRS), were preclassified to several groups according to their chemical structures. Herb decoctions were then subjected to ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry analysis with appropriate collision energy (CE) in MS2 mode. Finally, multiple reaction monitoring transitions transformed from MS2 of ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry were used for ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry to obtain the mass responses of LRS components. LRS components quantification was further performed by developing an assistive group-dependent semiquantitative method. RESULTS: The developed method was exemplified by the comparative PK process of single herbs Radix Ginseng (RG), Radix Polygala (RP), and their combinations (RG-RP). Significant changes in PK parameters were observed before and after combination. CONCLUSION: Results indicated that Traditional Chinese Medicine combinations can produce synergistic effects and diminish possible toxic effects, thereby reflecting the advantages of compatibility. The proposed strategy can solve the quantitative problem of LRS and extend the scopes of PK studies.

A visible-light activated [2 + 2] cycloaddition reaction enables pinpointing carbon-carbon double bonds in lipids.

The precise location of C[double bond, length as m-dash]C bonds in bioactive molecules is critical for a deep understanding of the relationship between their structures and biological roles. However, the traditional ultraviolet light-based approaches exhibited great limitations. Here, we discovered a new type of visible-light activated [2 + 2] cycloaddition of carbonyl with C[double bond, length as m-dash]C bonds. We found that carbonyl in anthraquinone showed great reactivities towards C[double bond, length as m-dash]C bonds in lipids to form oxetanes under the irradiation of visible-light. Combined with tandem mass spectrometry, this site-specific dissociation of oxetane enabled precisely locating the C[double bond, length as m-dash]C bonds in various kinds of monounsaturated and polyunsaturated lipids. The proof-of-concept applicability of this new type of [2 + 2] photocycloaddition was validated in the global identification of unsaturated lipids in a complex human serum sample. 86 monounsaturated and polyunsaturated lipids were identified with definitive positions of C[double bond, length as m-dash]C bonds, including phospholipids and fatty acids even with up to 6 C[double bond, length as m-dash]C bonds. This study provides new insights into both the photocycloaddition reactions and the structural lipidomics.

A target integration strategy for analyzing multidimensional chemical and metabolic substance groups of Ding-Zhi-Xiao-Wan prescription by using ultra-high performance liquid chromatography tandem mass spectrometry.

It is both challenging and meaningful for identifying the in vivo metabolites of the complex prescription owning to more complex chemical constituents and better therapeutic effect than those of the single medicine. In this paper, a target integration strategy combined with tandem mass spectrometry technology was developed for identification of metabolites from monomer composition of representative standard to Ding-Zhi-Xiao-Wan prescription (DZXW). The representative standards of each type in DZXW were utilized fully to explore the rule of mass fragmentation and the metabolism in vitro. These study were then extended to the single medicine and finally to the DZXW prescription. In addition, the order of metabolic research followed the metabolic order of oral drug in body, namely from in vitro, to intestine tract, to liver, to blood, and ultimately to target organs. As a result, a total of 150 prototypes and 51 metabolites of DZXW were effectively detected and identified in vivo. This result laid a material foundation for the better application of DZXW in treating Alzheimer's disease. More importantly, this analysis strategy provided a deep insight for the drug metabolism of traditional Chinese medicine.

A Simple and Accurate Method for the Determination of Related Substances in Coenzyme Q10 Soft Capsules.

As a new dosage form, coenzyme Q10 (Co-Q10) soft capsules are easily absorbed and utilized by the human body. Co-Q10 soft capsules can effectively improve the bioavailability and reduce medical costs for patients. A main concern about Co-Q10 as an active pharmaceutical ingredient (API) is how to control the total quantity of related substances. In this article, according to the degradation pattern of the API, the most easily degradable impurity (impurity X) in the sample was prepared and its chemical structure was determined. Furthermore, a simple and accurate method was developed for the determination of related substances and to avert the interference of excipient ingredients in Co-Q10 soft capsules. The approach was validated adequately and the primary impurity X was confirmed accurately. The limit of total quantity of related substances (less than 1%) could be revised to the level of specific impurity X being no more than 0.5%, in this effective quality control method of Co-Q10 soft capsules. The revised level is suggested to be included in the corresponding standard of the supplement taken from the Pharmacopoeia of the People's Republic of China (2015 edition). This can provide a feasible method for the relevant enterprises and regulatory authorities to control the related substances of coenzyme Q10 soft capsules.

Stepwise targeted matching strategy from in vitro to in vivo based on ultra-high performance liquid chromatography tandem mass spectrometry technology to quickly identify and screen pharmacodynamic constituents.

The study of in vivo pharmacodynamic constituents (PCs) of traditional Chinese medicine (TCM) is important for providing new clues for TCM applications in clinical therapies in modern medicine. However, detecting and identifying PCs from complex biological samples remain a challenge. In this study, a practical and novel stepwise targeted matching and longitudinal analysis strategy from in vitro to in vivo was developed. This strategy combined with ultra-high performance liquid chromatography tandem mass spectrometry was applied to quickly discover PCs in TCM. This approach was developed based on a core perception that all drugs taken orally might be transformed progressively and orderly from the intestinal tract, liver, and blood to the target organ. Based on this core perception, stepwise targeted matching was orderly and efficiently accomplished by multiple screening processes that were based on a stepwise enriched in-house library. Ginseng (Panax ginseng) was set as the example of herbal medicine for validating the reliability and availability of this approach. By applying this novel strategy to the stepwise screening of metabolites, we successfully identified 113 metabolites, among which 59 compounds were defined as prototypes. Based on the in vivo metabolites, network pharmacology analysis was applied to screen the PCs of ginseng and clarified the action mechanism of ginseng for the treatment of Alzheimer's disease (AD). A total of 27 herbal constituents and 64 related targets shared commonly by compounds and AD were integrated via target network pharmacology analysis. These results demonstrated that this original approach will greatly improve high-throughput screening of metabolites and PCs on AD. It also can explicate the mechanism of action of TCM. Furthermore, this strategy is practicable to identify metabolites and screen PCs in other herbal medicines.

Comprehensive characterization of in vivo metabolic profile of Polygalae radix based on ultra-high-performance liquid chromatography-tandem mass spectrometry.

In this study, a novel analysis strategy for progressively targeted screening and characterization of drug ingredients from in vitro to in vivo was proposed based on ultra-high performance liquid chromatography-tandem mass spectrometry for comprehensive characterization of in vivo metabolic profile of Polygalae radix (PR). First, an in vitro chemical profile of PR was described with the assistance of UNIFI™ software. The characteristic neutral small molecule losses were summarized to distinguish different chemical structures in the PR extract. Second, the in vitro intestinal microflora metabolism model was applied to describe an in vitro metabolic profile of the main ingredients of PR. The metabolic rule and metabolites were integrated for subsequent targeted screening of metabolites in vivo. Finally, an integrated strategy was established and applied to screen and characterize the major absorbed components in vivo, including blood, urine, brain, feces, and liver, based on the prototypes and metabolic rules obtained in vitro. As a result, in vitro and in vivo metabolic profiles of PR were effectively depicted. A total of 136 compounds were isolated and identified from the crude extract in vitro, and 12 compounds were reported for the first time based on the proposed fragmentations. A total of 13, 32, and 3 compounds were identified and characterized in the dosed plasma, liver, and brain, respectively. A total of 40 and 73 compounds were identified in urine and feces, respectively. This strategy not only provided a comprehensive insight into the chemical and metabolic profiles of PR but also presented a new perspective for the discovery of new drugs for medicinal application.

A targeted strategy for analyzing untargeted mass spectral data to identify lanostane-type triterpene acids in Poria cocos by integrating a scientific information system and liquid chromatography-tandem mass spectrometry combined with ion mobility spectrometry.

Rapid structural identification of natural compounds in the crude extract of traditional Chinese medicine by conventional liquid chromatography-mass spectrometry is complex and challenging. In particular, it is difficult to distinguish and identify structural isomers. In this work, we proposed a novel strategy that combines a typical ultrahigh-performance liquid chromatography-multidimensional mass spectrometry approach and the post-processing UNIFI scientific information system to rapidly identify lanostane analogs and isomers in Poria cocos. First, this strategy requires setting up a high-resolution key MS database and an in-house compound library. Then, ultrahigh-performance liquid chromatography coupled with high-resolution tandem data-independent mass spectrometry and ion mobility mass spectrometry was used to acquire untargeted multidimensional mass spectral data. Finally, a new and reliable multidimensional MS analytical workflow was developed to targeted filter the acquired data based on an in-house compound library via the UNIFI™ software. As result, a total of 121 lanostane-type triterpene acids were identified by high-resolution molecular mass, fragment ions, and collision cross-section values. Eight triterpene acids were unambiguously identified by comparing the retention time and MS/MS data with those of reference compounds. Three compounds were detected and reported for the first time based on their neutral losses, characteristic ions, and fragmentation pathways compared with those of known compounds. We anticipate that such an analytical approach can be extended to rapidly screen and characterize other herbal medicine compounds with multiple isomers.

Targeted Screening Approach to Systematically Identify the Absorbed Effect Substances of Poria cocos in Vivo Using Ultrahigh Performance Liquid Chromatography Tandem Mass Spectrometry.

Poria cocos are extensively used as nutritious food, dietary supplements, and oriental medicine in Asia. However, the effect substances are still not very clear. In this study, a targeted screening approach was developed to systematically identify absorbed constituents of Poria cocos in vivo using ultrahigh performance liquid chromatography tandem mass spectrometry combined with UNIFI software. First, incubation reactions in vitro with rat intestinal microflora and rat liver microsomes were conducted to sum up metabolic rules of main constituents. Second, the absorbed constituents in vivo were picked out and identified based on the results of metabolic study in vitro. Finally, the absorbed active constituents in the treatment of Alzheimer's disease were screened by targeted network pharmacology analysis. A total of 62 absorbed prototypes and 59 metabolites were identified and characterized in dosed plasma. Thirty potential active constituents were screened, and 86 drug-targets shared by absorbed constituents and Alzheimer's disease were discovered by targeted network pharmacology analysis. In general, this proposed targeted strategy comprehensively provides new insight for active ingredients of Poria cocos.

Study on the compatibility interactions of formula Ding-Zhi-Xiao-Wan based on their main components transport characteristics across Caco-2 monolayers model.

Influencing the absorption of effective components in the intestines is one of the important compatibility mechanisms of the traditional Chinese medicine. Simulation of drug absorption through an in vitro intestinal epithelial cell line is an important method to study the interaction of drug compatibility and bioavailability of drugs. In this study, the compatibility mechanism of Ding-Zhi-Xiao-Wan (DZXW) was investigated by using the in vitro Caco-2 cell monolayers model. Decomposing the formula into single herb and drug-pair to clarify the compatibility mechanism was firstly used. The transport characteristics of 20 major bioactive compounds including 8 ginsenosides, 6 poria triterpenes, 3 onjisaponins, one polygala oligosaccharide and two essential oils were selected as the main evaluation factor, and the absorption of these compounds by Caco-2 cells in the single herb group, drug-pair group and DZXW group were detected by ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ-MS). The results showed that the absorption of ginsenosides and polysaponins were related to the numbers of glycosyl groups, and the uptaken of poria triterpenes was dominated by lipophilicity. Polygala radix played a critical role in the permeability of gensenosides, and acorus tatarinowii rhizome dominated permeability of poria triterpenes. The apparent permeability coefficients of ginsenosides and poria triterpenes were greater than 14.0 × 10-6 cm s-1, indicating they could be absorbed well, and the ginseng and poria cocos might played the crucial role in the efficacy of DZXW. Herbal combination could remarkable improve the absorption of 18 compounds and the scientific rationality compatibility of DZXW formula was proved.

Studies on the chemical and intestinal metabolic profiles of Polygalae Radix by using UHPLC-IT-MSn and UHPLC-Q-TOF-MS method coupled with intestinal bacteria incubation model in vitro.

Polygala Radix (PR) is one of the most commonly used traditional Chinese medicines (TCM), but its effective materials are still not very clear. In order to solve the existing problems, the chemical and intestinal metabolic profiles of PR were analyzed via intestinal bacteria incubation model. An integrated analysis method combined ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF MS) method and ultra-high performance liquid chromatography with ion-trap multi-stage tandem mass spectrometry (UHPLC-IT-MSn) method was established. As a result, a total of 115 polygala compounds were identified from the PR extract. Moreover, 44 metabolites via intestinal microflora were characterized, of which three compounds were formed from xanthone C-glycosides, 25 compounds were formed from polygala saponins and 16 compounds were formed from oligosaccharide multi-esters. To our knowledge, the metabolites of the PR via intestinal microflora metabolism, especially polygala saponins, are the first reported in vitro. The obtained results would provide the methodological support for further studying the effective materials of the PR in vivo.

A non-target urinary and serum metabolomics strategy reveals therapeutical mechanism of Radix Astragali on adjuvant-induced arthritis rats.

Radix Astragali has been used traditionally in China to treat rheumatoid arthritis (RA) in formulas. In this paper, we conducted a holistic evaluation of Radix Astragali acted on adjuvant-induced arthritis (AIA) rats by urinary and serum metabolomic studies. Histological results and hind paw swelling were used to assess the joint damage, while the levels of IL-1ß, TNF-α, SOD and MDA in serum were used to assess inflammation injury and oxidative stress. Metabolomic study and multivariate statistical analyses were used to investigate the differences between different groups. After processing with multivariate statistical analysis, 13 and 21 potential biomarkers were respectively found in urine and serum when Radix Astragali treatment group compared with model group. The main metabolism pathways in which Radix Astragali affected on AIA rats were tryptophan metabolism, phenylalanine metabolism, citrate cycle metabolism, fatty acid metabolism, vitamin B6 metabolism and so on. The present study demonstrates that urinary and serum metabolomics method could be a potentially powerful tool to understand the holistic therapeutic effect and the mechanisms of herb medicines.

A study on the effective substance of the Wu-tou formula based on the metabonomic method using UPLC-Q-TOF-HDMS.

The Wu-tou formula (WTF) is a Chinese medicine formula which has been applied to treat rheumatic arthritis (RA) and pain of joints for more than a thousand years. In this study, a pharmacodynamics combined urinary metabonomic study using UPLC-Q-TOF-HDMS was performed to assess the holistic efficacy of the Traditional Chinese Medicine (TCM) Wu-tou formula for treating RA in rats. Eighty male Sprague-Dawley rats were randomly divided into eight groups, named as the healthy control group (HG), the model group (AIA), the WTF group and five single herb groups. The treatment groups and the model group were induced for treating rheumatoid arthritis by using complete Freund's adjuvant. Histological results assessed the joint damage and several biochemical parameters such as IL-1ß, TNF-α, SOD and MDA were used to evaluate inflammation injury and oxidative stress. Based on the results, a metabonomic investigation was conducted to study the mechanism of the WTF and single herb treatment groups for treating RA. Multivariate statistical analyses such as PCA and OPLS-DA were used to identify potential biomarkers in urine. As a result, twenty-six potential biomarkers have been found by comparison with the model and the WTF treatment group. The potential biomarkers mainly affect the phenylalanine, tyrosine and tryptophan biosynthesis pathway and the taurine and hypotaurine metabolism pathway. Aconiti Radix Preparata and Ephedrae Herba showed better effects on treating RA from the integrated evaluation by histological results, biochemical parameters and pattern recognition analysis. A comprehensive evaluation of the different therapeutic effects and the mechanism of each herb in the WTF for treating RA was performed in this research.