Integrating Metabolomics and Network Pharmacology to Decipher the Hepatoprotective Effect Mechanisms of Magnesium Isoglycyrrhizinate Injection.

This study aimed to explore the liver protective effects of a fourth-generation glycyrrhizic acid product (magnesium isoglycyrrhizinate injection, MII) in the treatment of mice with drug-induced liver injury-specifically, to determine its effects on plasma metabolites. Moreover, the possible mechanism of its intervention in lipid metabolism and amino acid metabolism through the liver protective effect was preliminarily explored, combined with network pharmacology. The liver injury model of mice was established using acetaminophen (APAP). The protective effect of MII on the mice model was evaluated using pathological tissue sections and biochemical indices such as alanine transaminase (ALT), aspartate aminotransferase (AST), and superoxide dismutase (SOD). Metabolomics analysis of plasma was performed using the UHPLC-QTOF/MS technique to screen for potential biomarkers and enriched metabolic pathways. The potential targets and pathways of MII were predicted by network pharmacology, and the mechanism was verified by Western blot analysis. MII significantly improved the pathological liver changes in mice with liver injury. The content of ALT and AST was decreased, and the activity of SOD was increased significantly (p < 0.05, 0.01). A total of 29 potential biomarkers were identified in the metabolomics analysis, mainly involving seven pathways, such as lipid metabolism and amino acid metabolism. A total of 44 intersection targets of MII in the treatment of liver injury were obtained by network pharmacology, involving lipid metabolism and other related pathways. Western blot analysis results showed that MII could significantly reduce the expression of JAK2 and STAT3. MII can effectively ameliorate liver injury in modeled mice through related pathways such as lipid metabolism and amino acid metabolism. This study could provide not only a scientific basis for the elucidation of the mechanism of action of MII in exerting a hepatoprotective effect, but also a reference for its rational clinical application.

Artificial neural network-based shelf life prediction approach in the food storage process: A review.

The prediction of food shelf life has become a vital tool for distributors and consumers, enabling them to determine storage and optimal edible time, thus avoiding unexpected food waste. Artificial neural network (ANN) have emerged as an effective, fast and accurate method for modeling, simulating and predicting shelf life in food. ANNs are capable of tackling nonlinear, complex and ill-defined problems between the variables without prior knowledge. ANN model exhibited excellent fit performance evidenced by low root mean squared error and high correlation coefficient. The low relative error between actual values and predicted values from the ANN model demonstrates its high accuracy. This paper describes the modeling of ANN in food quality prediction, encompassing commonly used ANN architectures, ANN simulation techniques, and criteria for evaluating ANN model performance. The review focuses on the application of ANN for modeling nonlinear food quality during storage, including dairy, meat, aquatic, fruits, and vegetables products. The future prospects of ANN development mainly focus on optimal models and learning algorithm selection, multiple model fusion, self-learning and self-correcting shelf-life prediction model development, and the potential utilization of deep learning techniques.

ANN-based food shelf life prediction methods are reviewed.This paper discusses application of ANN in the food storage process.BPNN is the mainstream ANN architecture used for the prediction of food quality.ANNs are useful for prediction of outputs with high accuracy.Future trends of ANN in the agri-supply chain are evaluated.

High Value-Added Reutilization of Waste-Printed Circuit Boards Non-Metallic Components in Sustainable Polymer Composites.

The reutilization non-metallic components from a waste-printed circuit board (WPCB) has become one of the most significant bottlenecks in the comprehensive reuse of electronic wastes due to its low value and complex compositions, and it has received great attention from scientific and industrial researchers. To effectively address the environmental pollution caused by inappropriate recycling methods, such as incineration and landfill, extensive efforts have been dedicated to achieving the high value-added reutilization of WPCB non-metals in sustainable polymer composites. In this review, recent progress in developing sustainable polymer composites based on WPCB non-metallic components was systematically summarized. It has been demonstrated that the WPCB non-metals can serve as a promising reinforcing and functional fillers to significantly ameliorate some of the physical and chemical properties of polymer composites, such as excellent mechanical properties, enhanced thermal stability, and flame retardancy. The recovery strategies and composition of WPCB non-metals were also briefly discussed. Finally, the future potentials and remaining challenges regarding the reutilization of WPCB non-metallic components are outlined. This work provides readers with a comprehensive understanding of the preparation, structure, and properties of the polymer composites based on WPCB non-metals, providing significant insights regarding the high value-added reutilization of WPCB non-metals of electronic wastes.

QD-based fluorescent nanosensors: Production methods, optoelectronic properties, and recent food applications.

Food quality and safety are crucial public health concerns with global significance. In recent years, a series of fluorescence detection technologies have been widely used in the detection/monitoring of food quality and safety. Due to the advantages of wide detection range, high sensitivity, convenient and fast detection, and strong specificity, quantum dot (QD)-based fluorescent nanosensors have emerged as preferred candidates for food quality and safety analysis. In this comprehensive review, several common types of QD production methods are introduced, including colloidal synthesis, self-assembly, plasma synthesis, viral assembly, electrochemical assembly, and heavy-metal-free synthesis. The optoelectronic properties of QDs are described in detail at the electronic level, and the effect of food matrices on QDs was summarized. Recent advancements in the field of QD-based fluorescent nanosensors for trace level detection and monitoring of volatile components, heavy metal ions, food additives, pesticide residues, veterinary-drug residues, other chemical components, mycotoxins, foodborne pathogens, humidity, and temperature are also thoroughly summarized. Moreover, we discuss the limitations of the QD-based fluorescent nanosensors and present the challenges and future prospects for developing QD-based fluorescent nanosensors. As shown by numerous publications in the field, QD sensors have the advantages of strong anti-interference ability, convenient and quick operation, good linear response, and wide detection range. However, the reported assays are laboratory-focused and have not been industrialized and commercialized. Promising research needs to examine the potential applications of bionanotechnology in QD-based fluorescent nanosensors, and focus on the development of smart packaging films, labeled test strips, and portable kits-based sensors.

A Network-Pharmacology-Combined Integrated Pharmacokinetic Strategy to Investigate the Mechanism of Potential Liver Injury due to Polygonum multiflorum.

Polygonum multiflorum (PM) has been used as a tonic and anti-aging remedy for centuries in Asian countries. However, its application in the clinic has been hindered by its potential to cause liver injury and the lack of investigations into this mechanism. Here, we established a strategy using a network pharmacological technique combined with integrated pharmacokinetics to provide an applicable approach for addressing this issue. A fast and sensitive HPLC-QQQ-MS method was developed for the simultaneous quantification of five effective compounds (trans-2,3,5,4'-tetrahydroxystilbene-2-O-ß-d-glucoside, emodin-8-O-ß-d-glucoside, physcion-8-O-ß-d-glucoside, aloe-emodin and emodin). The method was fully validated in terms of specificity, linearity, accuracy, precision, extraction recovery, matrix effects, and stability. The lower limits of quantification were 0.125-0.500 ng/mL. This well-validated method was successfully applied to an integrated pharmacokinetic study of PM extract in rats. The network pharmacological technique was used to evaluate the potential liver injury due to the five absorbed components. Through pathway enrichment analysis, it was found that potential liver injury is primarily associated with PI3K-Akt, MAPK, Rap1, and Ras signaling pathways. In brief, the combined strategy might be valuable in revealing the mechanism of potential liver injury due to PM.

Discovery of Hepatotoxic Equivalent Markers and Mechanism of Polygonum multiflorum Thunb. by Metabolomics Coupled with Molecular Docking.

Polygonum multiflorum Thunb. (PMT), a commonly used Chinese herbal medicine for treating diseases such as poisoning and white hair, has attracted constant attention due to the frequent occurrence of liver injury incidents. To date, its hepatotoxic equivalent markers (HEMs) and potential hepatotoxic mechanisms are still unclear. In order to clarify the HEMs of PMT and further explore the potential mechanisms of hepatotoxicity, firstly, the chemical constituents in PMT extract were globally characterized, and the fingerprints of PMT extracts were established along with the detection of their hepatotoxicity in vivo. Then, the correlations between hepatotoxic features and component contents were modeled by chemometrics to screen HEMs of PMT, which were then further evaluated. Finally, the hepatotoxic mechanisms of PMT were investigated using liver metabolomics and molecular docking. The results show that the chemical combination of 2,3,5,4-tetrahydroxystilbene-2-O-ß-D-glucoside (TSG) and emodin-8-O-glucoside (EG) was discovered as the HEMs of PMT through pre-screening and verifying process. Liver metabolomics revealed that PMT caused liver injury by interfering with purine metabolism, which might be related to mitochondrial function disorder and oxidative injury via the up-regulations of xanthosine and xanthine, and the down-regulation of 5' nucleotidase (NT5E) and adenylate kinase 2 (AK2). This study not only found that the HEMs of PMT were TSG and EG, but also clarified that PMT might affect purine metabolism to induce liver injury, which contributed to our understanding of the underlying mechanisms of PMT hepatotoxicity.

Assessing potential liver injury induced by Polygonum multiflorum using potential biomarkers via targeted sphingolipidomics.

CONTEXT: Polygonum multiflorum Thunb. (Polygonaceae) (PM) can cause potential liver injury which is typical in traditional Chinese medicines (TCMs)-induced hepatotoxicity. The mechanism involved are unclear and there are no sensitive evaluation indicators. OBJECTIVE: To assess PM-induced liver injury, identify sensitive assessment indicators, and screen for new biomarkers using sphingolipidomics. MATERIALS AND METHODS: Male Sprague-Dawley (SD) rats were randomly divided into four groups (control, model with low-, middle- and high-dose groups, n = 6 each). Rats in the three model groups were given different doses of PM (i.g., low/middle/high dose, 2.7/8.1/16.2 g/kg) for four months. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in the plasma and liver were quantitatively analyzed. Fixed liver tissue sections were stained with haematoxylin and eosin and examined under a light microscope. The targeted sphingolipidomic analysis of plasma was performed using high-performance liquid chromatography tandem mass spectrometry. RESULTS: The maximal tolerable dose (MTD) of PM administered intragastrically to mice was 51 g/kg. Sphingolipid profiling of normal and PM-induced liver injury SD rats revealed three potential biomarkers: ceramide (Cer) (d18:1/24:1), dihydroceramide (d18:1/18:0)-1-phosphate (dhCer (d18:1/18:0)-1P) and Cer (d18:1/26:1), at 867.3-1349, 383.4-1527, and 540.5-658.7 ng/mL, respectively. A criterion for the ratio of Cer (d18:1/24:1) and Cer (d18:1/26:1) was suggested and verified, with a normal range of 1.343-2.368 (with 95% confidence interval) in plasma. CONCLUSIONS: Three potential biomarkers and one criterion for potential liver injury caused by PM that may be more sensitive than ALT and AST were found.

Comparison of freshness prediction method for salmon fillet during different storage temperatures.

BACKGROUND: Many new forecasting models have been applied to fish freshness prediction like support vector regression (SVR) and radial basis function neural network (RBFNN). In this study, RBFNN, SVR, and Arrhenius models were established and compared for predicting and evaluating the quality of salmon fillets during storage at different temperatures, based on thiobarbituric acid (TBA), total volatile basic nitrogen (TVB-N), total viable counts (TVCs), K value, and sensory assessment (SA). RESULTS: The TBA, TVB-N, TVC, and K values increased during storage whereas SA decreased. Residuals of the three models are random and irregular, indicating that these models were suitable for predicting the freshness of salmon fillets. The RBFNN predicted quality of salmon fillets stored at different temperatures with relative errors all within ±5% (except for the TVC value at day 6). Relative errors of the SVR model for predicting TVB-N and K value were within 10%, while the relative errors of the Arrhenius model fluctuated greatly (ranging from ±0.46 to ±38.29%) and most of it exceeded 10%. RBFNN model had the best predictive performance by comparing the residual and relative errors of the three models. CONCLUSION: RBFNN is a promising method for predicting the freshness of salmon fillets stored at -2 to 10 °C in the cold chain. © 2021 Society of Chemical Industry.

Intelligent pH indicator films containing anthocyanins extracted from blueberry peel for monitoring tilapia fillet freshness.

BACKGROUND: Fish spoilage leads to an increase in the pH value of the fish. A colorimetric pH indicator can be used to monitor fish spoilage and has been exploited in intelligent packaging because of its simplicity, practicality and low cost. The aim of this study was to develop two pH-indicator films comprising starch (S), tara gum (TG), polyvinyl alcohol (PVA) and anthocyanins extracted from blueberry peel and the films were then used to monitor the freshness of tilapia fillets during storage at 25 and 4 °C. RESULTS: The ultraviolet-visible (UV-visible) spectra and color of anthocyanins changed within pH 2-10. Fourier-transform infrared spectroscopy, UV-visible spectrophotometry and scanning electron microscopy certified that blueberry peel extract (BPE) had been introduced into the S/PVA and TG/PVA matrices. Visual color changes in the films occurred at pH 2-8. A freshness application test was conducted in tilapia fillets stored at 4 and 25 °C, and visual color changes in the films were observed. The TG/PVA/BPE film had a greater color difference (ΔE) from pink and transparent to dark yellow at 25 °C and to dark purple at 4 °C than ΔE of S/PVA/BPE film, which sufficiently correlated with the change of total volatile base nitrogen (TVB-N) and total aerobic counts (TACs) of fillets. CONCLUSION: It can be concluded that the color changes of TG/PVA/BPE films were corresponded with TVB-N and TAC values of tilapia fillets, which presented great potential as a visual package label to monitor fish freshness at ambient and chilled temperatures. © 2020 Society of Chemical Industry.

Salidroside orchestrates metabolic reprogramming by regulating the Hif-1α signalling pathway in acute mountain sickness.

CONTEXT: Rhodiola crenulata (Hook. f. et Thoms.) H. Ohba (Crassulaceae) is used to prevent and treat acute mountain sickness. However, the mechanisms underlying its effects on the central nervous system remain unclear. OBJECTIVE: To investigate the effect of Rhodiola crenulata on cellular metabolism in the central nervous system. MATERIALS AND METHODS: The viability and Hif-1α levels of microglia and neurons at 5% O2 for 1, 3, 5 and 24 h were examined. We performed the binding of salidroside (Sal), rhodiosin, tyrosol and p-hydroxybenzyl alcohol to Hif-1α, Hif-1α, lactate, oxidative phosphorylation and glycolysis assays. Forty male C57BL/6J mice were divided into control and Sal (25, 50 and 100 mg/kg) groups to measure the levels of Hif-1α and lactate. RESULTS: Microglia sensed low oxygen levels earlier than neurons, accompanied by elevated expression of Hif-1α protein. Salidroside, rhodiosin, tyrosol, and p-hydroxybenzyl alcohol decreased BV-2 (IC50=1.93 ± 0.34 mM, 959.74 ± 10.24 µM, 7.47 ± 1.03 and 8.42 ± 1.63 mM) and PC-12 (IC50=6.89 ± 0.57 mM, 159.28 ± 8.89 µM, 8.65 ± 1.20 and 8.64 ± 1.42 mM) viability. They (10 µM) reduced Hif-1α degradation in BV-2 (3.7-, 2.5-, 2.9- and 2.5-fold) and PC-12 cells (2.8-, 2.8-, 2.3- and 2.0-fold) under normoxia. Salidroside increased glycolytic capacity but attenuated oxidative phosphorylation. Salidroside (50 and 100 mg/kg) treatment increased the protein expression of Hif-1α and the release of lactate in the brain tissue of mice. CONCLUSIONS: These results suggest that Sal induces metabolic reprogramming by regulating the Hif-1α signalling pathway to activate compensatory responses, which may be the core mechanism underlying the effect of Rhodiola crenulata on the central nervous system.

Pseudotargeted screening and determination of constituents in Qishen granule based on compound biosynthetic correlation using UHPLC coupled with high-resolution MS.

Detection and determination of many known/unknown compounds in traditional Chinese medicines have always been challenging. To comprehensively identify compounds in Qishen granule, which is a widely prescribed herbal formula for treating chronic heart failure, a pseudotargeted screening method was proposed based on compound biosynthetic correlation using ultra high-performance liquid chromatography coupled with high-resolution mass spectrometry. Firstly, all possible compounds of Qishen granule were classified into nine types according to their core skeletons, and potential analogue molecular formulas were predicted according to core compound-related biosynthetic correlations, such as methylation, hydroxylation, and glucosidation. Secondly, nine pseudocompound databases consisting of core compounds, deduced biosynthetic correlations, and predicted analogue molecular formulas were established. Then, compounds of interest were directly located by pseudotargeted screening of high resolution mass spectrometry data and further verified by target tandem mass spectrometry. As a result, 213 constituents were identified and 21 of them were determined as potential new compounds. This demonstrated that pseudotargeted screening based on compound biosynthetic correlations significantly facilitated the processing of extremely large information data and improved the efficiency of compound identification. This research provided essential data for exploration of effective substances in Qishen granule and enriched the methodology for comprehensive characterization of constituents in complex traditional Chinese medicines.

[Quantification of aristolochic acids and their DNA adducts in mice kidney and liver by HPLC-MS/MS].

This study aims to establish a quantitative method of 4 aristolochic acids-DNA adducts in mice kidney and liver based on high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS) for monitoring the content changes of aristolochic acids-DNA adducts. A Shiseido Capcellpak AQ C_(18) column(3 mm×100 mm, 3 µm) was used, with a mixture of 0.2% acetic acid-5 mmol·L~(-1) ammonium acetate as the aqueous phase and methanol as the organic phase for gradient elution. The multiple reaction monitoring(MRM) scanning method under positive mode by electrospray ionization(ESI) was performed for the detection of the aristolochic acids-DNA adducts which formed by combining aristolochic acid Ⅰ/Ⅱ with deoxyadenosine, deoxyguanosine, and deoxycytidine, respectively. Balb/c mice were given Guanmutong extract by gavage, and the relative content of aristolochic acids-DNA adducts in liver and kidney samples were analyzed within 60 days. It was found that the concentration of 4 aristolochic acids-DNA adducts in the kidney was significantly higher than that in the liver, and there were about 15.87 adducts in per 1×10~6 normal deoxynucleosides, which was 4.5-7.5 times than that of the liver. What's more, some adducts can still be detected on the 30 th day after administration. The concentration of the adducts in the liver was highest on the first day after administration, and a second peak appeared during the 7 th to 14 th days. The results indicated that aristolochic acids-DNA adducts are difficult to eliminate in vivo, and it is of great significance to study the mechanism of liver and kidney injury of aristolochic acid.

Profiling the constituents of Dachuanxiong decoction by liquid chromatography with high-resolution tandem mass spectrometry using target and nontarget data mining.

Comprehensive characterization of the large number of compounds existing in traditional Chinese medicines is still a great challenge. In this study, a strategy of precursor ion selected acquisition coupled with target and nontarget data mining was established to systematically characterize the chemical constituents of traditional Chinese medicines. This strategy consisted of four steps: (1) precursor ion selected acquisition was developed to trigger additional tandem mass spectrometry fragmentation reactions, especially for trace constituents; (2) in-house database of compounds was established and diagnostic characteristics were summarized; (3) compounds were identified by target and nontarget data mining; and (4) compound structures were elucidated based on accurate mass matching and comparison of fragment ions, and isomers were discriminated by the intensity of fragment ions, fragmentation pattern analysis, and calculated log P values. This strategy was successfully applied to comprehensively identify the constituents in Dachuanxiong decoction. Finally, a total of 218 compounds assigned to six categories were characterized, and 107 compounds were characterized by nontarget analysis for the first time. In addition, three new diagnostic characteristics of esters of citric acids were elucidated. This research enriched the material basis of Dachuanxiong decoction and provided a new strategy for identifying the chemical constituents of other traditional Chinese medicines.

Tire⁻Pavement Contact-Aware Weight Estimation for Multi-Sensor WIM Systems.

Accurately estimating the weight of a moving vehicle at normal speed remains a challenging problem due to the complex vehicle dynamics and vehicle-pavement interaction. The weighing technique based on multiple sensors has proven to be an effective approach to this task. To improve the accuracy of weigh-in-motion (WIM) systems, this paper proposes a neural network-based method integrating identification and predication. A backpropagation neural network for signal classification (BPNN-i) was designed to identify ideal samples acquired by load sensors closest to the tire-pavement contact area. After that, ideal samples were used to predict the gross vehicle weight by using another backpropagation neural network (BPNN-e). The dataset for training and evaluation was collected from a multiple-sensor WIM (MS-WIM) system deployed in a public road. In our experiments, 96.89% of samples in the test set had an estimation error of less than 5%.

Preparing the key metabolite of Z-ligustilide in vivo by a specific electrochemical reaction.

The key in vivo metabolites of a drug play an important role in its efficacy and toxicity. However, due to the low content and instability of these metabolites, they are hard to obtain through in vivo methods. Electrochemical reactions can be an efficient alternative to biotransformation in vivo for the preparation of metabolites. Accordingly, in this study, the metabolism of Z-ligustilide was investigated in vitro by electrochemistry coupled online to mass spectrometry. This work showed that five oxidation products of the electrochemical reaction were detected and that two of the oxidation products (senkyunolide I and senkyunolide H) were identified from liver microsomal incubation as well. Furthermore, after intragastric administration of Z-ligustilide in rats, senkyunolide I and senkyunolide H were detected in the rat plasma and liver, while 6,7-epoxyligustilide, a key intermediate metabolite of Z-ligustilide, was difficult to detect in vivo. By contrast, 6,7-epoxyligustilide was obtained from the electrochemical reaction. In addition, for the first time, 6 mg of 6,7-epoxyligustilide was prepared from 120 mg of Z-ligustilide. Therefore, electrochemical reactions represent an efficient laboratory method for preparing key drug metabolites.

[Studies on constituents of Polygonum multiflorum extract in vivo and in vitro based on UPLC-Q-TOF-MS].

To explore the drug-induced constituents in vivo of Polygonum multiflorum extract (PM). This study was the first to study the drug-induced constituents in target organ liver. Agilent MassHunter qualitative analysis software and Metabolite ID software were applied for the analysis of retention time, exact relative molecular mass, primary and secondary mass spectrum information based on ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and targeted-MS/MS. By comparison with literature and standards, a total of 5 prototypes and 6 metabolites were identified or tentatively elucidated from the liver samples. In addition, the drug-induced constituents in plasma and PM were also analyzed in this study and 8 prototypes and 19 metabolites were detected from the plasma samples, while 30 compounds were detected from the extract of PM. Emodin oxidative acetylation metabolites, hydroxyl methylation metabolites, carboxylation glucuronidation metabolites and ketone glucuronidation metabolites in this study were first reported. Through the comparative analysis between the in vivo and in vitro constituents of PM, the study preliminarily revealed the drug-induced constituents (prototypes and metabolites) in liver and clarified the transfer process and transmutation rules of constituents in PM, blood and liver, which would further deepen our understanding on constituents of PM in vivo.

Strategy for Comprehensive Profiling and Identification of Acidic Glycosphingolipids Using Ultra-High-Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Mass Spectrometry.

Acidic glycosphingolipids (AGSLs), which mainly consist of ganglioside and sulfatide moieties, are highly concentrated in the central nervous system. Comprehensive profiling of AGSLs has historically been challenging because of their high complexity and the lack of standards. In this study, a novel strategy was developed to comprehensively profile AGSLs using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Ganglioside isomers with different glycan chains such as GD1a/GD1b were completely separated on a C18 column for the first time to our knowledge, facilitated by the addition of formic acid in the mobile phase. A mathematical model was established to predict the retention times (RTs) of all theoretically possible AGSLs on the basis of the good logarithmic relationship between the ceramide carbon numbers of the AGSLs in the reference material and their RTs. A data set was created of 571 theoretically possible AGSLs, including the ceramide carbon numbers, RTs, and high-resolution quasi-molecular ions. A novel fast identification strategy was established for global AGSL profiling by comparing the high-resolution quasi-molecular ions and RTs of the tested peaks to those in the data set of 571 AGSLs. Using this strategy, 199 AGSL candidates were identified in rat brain tissue. MS/MS fragments were further collected for these 199 candidates to confirm their identity as AGSLs. This novel strategy was employed to profile AGSLs in brain tissue samples from control rats and model rats with bilateral common carotid artery (2-VO) cerebral ischemia. Forty AGSLs were significantly different between the control and model groups, and these differences were further interpreted.

Derivatization Strategy for the Comprehensive Characterization of Endogenous Fatty Aldehydes Using HPLC-Multiple Reaction Monitoring.

Fatty aldehydes are crucial substances that mediate a wide range of vital physiological functions, particularly lipid peroxidation. Fatty aldehydes such as acrolein and 4-hydroxynonenal (4-HNE) are considered potential biomarkers of myocardial ischemia and dementia, but analytical techniques for fatty aldehydes are lacking. In the present study, a comprehensive characterization strategy with high sensitivity and facility for fatty aldehydes based on derivatization and high-performance liquid chromatography-multiple reaction monitoring (HPLC-MRM) was developed. The fatty aldehydes of a biosample were derivatized using 2,4-bis(diethylamino)-6-hydrazino-1,3,5-triazine under mild and efficient reaction conditions at 37 °C for 15 min. The limit of detection (LOD) of the fatty aldehydes varied from 0.1 to 1 pg/mL, depending on the structures of these molecules. General MRM parameters were forged for the analysis of endogenous fatty aldehydes. "Heavy" derivatization reagents with 20 deuterium atoms were synthesized for both the discovery and comprehensive characterization of fatty aldehydes. More than 80 fatty aldehydes were detected in the biosamples. The new strategy was successfully implemented in global fatty aldehyde profiling of plasma and brain tissue of the bilateral common carotid artery (2VO) dementia rat model. Dozens of fatty aldehydes were significantly changed between the control and model groups. These findings further highlight the importance of endogenous fatty aldehydes.

Profile and quantification of human stratum corneum ceramides by normal-phase liquid chromatography coupled with dynamic multiple reaction monitoring of mass spectrometry: development of targeted lipidomic method and application to human stratum corneum of different age groups.

Skin, the largest organ of the human body, serves as the primary barrier to the external environment. Ceramides are one of the main constituents of stratum corneum (SC), playing an important role in skin barrier function. Therefore, comprehensive profiling and quantification of SC ceramide is important. Herein, a new targeted lipidomic method for human SC ceramide profiling and quantification is presented and tested. Normal-phase high-performance liquid chromatography coupled with dynamic multiple reaction monitoring mass spectrometry (NP-HPLC-dMRM-MS) was used to separate ceramides into subclasses and then characterize different ceramides within each subclass on the basis of their characteristics. In total, 483 ceramides were quantified in a single run within 20 min, covering 12 subclasses as well as some glycosylated ceramides not previously reported. Each subclass had typical standard substances (if available) that served to establish representative standard curves and were used for related substances with no standards. Linearity range, limit of quantification (LOQ), limit of detection (LOD), precision, accuracy, stability, and matrix effects were validated. dMRM increased sensitivity and accuracy greatly compared with common MRM (cMRM). This method was successfully applied to the study of human SC from different age groups. A total of 193 potential biomarkers were found to indicate age differences between children and adults. This method is an innovative approach for high-throughput quantification of SC ceramide. Graphical Abstract Method establishment (MRM spectra by the established method) and method application (score scatter plots of authentic samples).

Automatic identification approach for high-performance liquid chromatography-multiple reaction monitoring fatty acid global profiling.

Fatty acids (FAs) are a group of lipid molecules that are essential to organisms. As potential biomarkers for different diseases, FAs have attracted increasing attention from both biological researchers and the pharmaceutical industry. A sensitive and accurate method for globally profiling and identifying FAs is required for biomarker discovery. The high selectivity and sensitivity of high-performance liquid chromatography-multiple reaction monitoring (HPLC-MRM) gives it great potential to fulfill the need to identify FAs from complicated matrices. This paper developed a new approach for global FA profiling and identification for HPLC-MRM FA data mining. Mathematical models for identifying FAs were simulated using the isotope-induced retention time (RT) shift (IRS) and peak area ratios between parallel isotope peaks for a series of FA standards. The FA structures were predicated using another model based on the RT and molecular weight. Fully automated FA identification software was coded using the Qt platform based on these mathematical models. Different samples were used to verify the software. A high identification efficiency (greater than 75%) was observed when 96 FA species were identified in plasma. This FAs identification strategy promises to accelerate FA research and applications.