Methods for detection and quantification of gelatin from different sources.

Gelatin is a water-soluble protein obtained from the collagen of various animal origins (porcine, bovine, fish, donkey, horse, and deer hide) and has diverse applications in the food, pharmaceutical, and cosmetics industries. Porcine and bovine gelatins are extensively used in food and non-food products; however, their acceptance is limited due to religious prohibitions, whereas fish gelatin is accepted in all religions. In Southeast Asia, especially in China, gelatin obtained from donkey and deer skins is used in medicines. However, both sources suffer from adulteration (mixing different sources of gelatin) due to their limited availability and high cost. Unclear labeling and limited information about actual gelatin sources in gelatin-containing products cause serious concern among societies for halal and fraud authentication of gelatin sources. Therefore, authenticating gelatin sources in gelatin-based products is challenging due to close similarities between the composition differences and degradation of DNA and protein biomarkers in processed gelatin. Thus, different methods have been proposed to identify and quantify different gelatin sources in pharmaceutical and food products. To the best of our knowledge, this systematic and comprehensive review highlights different authentication techniques and their limitations in gelatin detection and quantification in various commercial products. This review also describes halal authentication and adulteration prevention strategies of various gelatin sources, mainly focussing on research gaps, challenges, and future directions in this research area.

Smartphone-Assisted EY@MOF-5-Based Dual-Emission Fluorescent Sensor for Rapid On-Site Detection of Daclatasvir and Nitenpyram.

Fluorescent metal-organic frameworks (MOFs) are promising sensing materials with tunable and robust structural properties and remarkable luminescent capabilities. In this study, a novel dual-emission fluorescent metal-organic framework (EY@MOF-5) composite is synthesized by a one-pot bottle-around-ship approach. Eosin Y (EY) is encapsulated in MOF-5 to enhance its fluorescence properties and selectivity, effectively addressing typical MOF-5 limitations. EY@MOF-5 serves as a versatile dual-functional fluorescent sensor for two different analytes, daclatasvir (DCT) and nitenpyram (NTP), showing an impressive linear range of 10-200 nM and 0.1-300 µM, with detection limits of 233 pM and 65 nM, respectively. The established method is ultrafast, highly sensitive, and extremely selective for DCT and NTP detection in complex biological and food samples. Fluorescence results are compared and validated with the recommended UPLC method. Then, a smartphone-integrated sensing system is introduced for on-site, real-time, and quantitative analysis of DCT and NTP. The smartphone-assisted intelligent sensing method manifests promising results for DCT and NTP monitoring in biological and food samples, demonstrating its promising potential for the on-site detection of biologically and environmentally significant analytes.

Enhancement in photocatalytic selectivity of TiO2-based nano-catalyst through molecular imprinting technology.

Improvement in the photocatalytic selectivity is imperative for the effective and efficient utilization of catalysts. In this study, a molecularly imprinted polymer-coated iron-doped titanium dioxide (Fe-TiO2@MIP) nanocomposite was successfully synthesized by precipitation polymerization while using RB-19 as a template. The synthesized nanocomposites (Fe-TiO2@MIP and Fe-TiO2@NIP) were characterized by Fourier transform infrared spectroscopy (FT-IR), atomic force microscopy (AFM), field emission scanning electron microscopy (FESEM) with energy dispersive X-ray (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Brunauer-EMMETT-Teller (BET), and UV-visible spectrophotometry. The optimized binding experiments revealed a high imprinting factor of 5.0 for RB-19. The catalytic degradation efficiency and selectivity of Fe-TiO2@MIP enhanced to almost complete degradation of RB-19 from 70% for the parent Fe-TiO2 and 76% for Fe-TiO2@NIP. An outstanding degradation selectivity of RB-19 was achieved compared to other competitive dyes. Finally, the analysis of the non-degraded and degraded RB-19 by ESI-MS revealed the presence of different intermediates that fits well with the proposed degradation mechanism. The study opens new possibilities of selective photo-degradation of targeted contaminants that may ultimately lead to efficient use of photocatalysts.

Determination of vitamin D metabolites in various biological samples through an improved chemical derivatization assisted liquid chromatography-tandem mass spectrometry approach.

Vitamin D (VD) metabolites are involved in a variety of important metabolic processes and physiological effects in organisms. Profiling of VD metabolites favors a deep understanding of the physiological role of VD. However, VD metabolites are difficult to detect due to their high chemical structural rigidity, structural similarity, and low sensitivities under liquid chromatography-tandem mass spectrometry (LC-MS). Herein, we present a chemical derivatization assisted LC-MS/MS strategy for the detection of VDs, in which 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) is employed to derivatize the conjugated diene of VD metabolites and provides sensitizing reporters for MS detection. After PTAD derivatization, the sensitivities of seven VD metabolites increased by 24-276 folds, with the limits of detection ranging from 3 to 20 pg mL-1. Using this method, we achieved a sensitive and accurate quantification of 7 VD metabolites (vitamin D2, vitamin D3, 25-hydroxyvitamin D2, 25-hydroxyvitamin D3, 1,25-dihydroxyvitamin D2, 1,25-dihydroxyvitamin D3, and 1,24,25-trihydroxyvitamin D3) of the VD metabolic pathway in different trace biological samples, including human serum, mouse tissues (namely liver, kidney, lung, and spleen), and cells. We believe that the present method can provide a promising tool for an in-depth analysis of VD metabolism.

Analytical Strategy for Oxylipin Annotation by Combining Chemical Derivatization-Based Retention Index Algorithm and Feature Tandem Mass Spectrometric Fragmentation as a Biomarker Discovery Tool.

Accurate oxylipin annotation is crucial for advancing our understanding of physiological processes in health and disease and identifying biomarkers. However, a full view of oxylipins for early diagnosis needs further attention due to the lack of proper analytical methods, which may be attributed to the wide dynamic range, poor sensitivity, extreme molecular complexity, and limited commercially available standards of oxylipins. Here, we devised a novel method by combining a chemical derivatization (CD)-based retention index (RI) algorithm and feature tandem mass spectrometric fragmentation annotation (CD-RI-LC-MS/MS) for identification and quantification of oxylipins. To this end, N,N-diethyl-1,3-diaminopropane (DEPA) was used for fast labeling of oxylipin (within 0.5 min at room temperature) to improve separation resolution and detection sensitivity. The RI algorithm was established to calibrate the retention time variances and assist the identification of oxylipins during liquid chromatography-tandem mass spectrometry (LC-MS) analysis. MS/MS analysis of in total 58 DEPA derivatives of authentic oxylipin standards was subsequently employed to obtain the tandem mass spectrometric feature fragmentation rules for further structure elucidation of the unknown regio-isomers. Finally, a method based upon CD-RI-LC-MS/MS was established for profiling oxylipins from Standard Reference Material (SRM) 1950 human plasma and nonalcoholic fatty liver disease (NAFLD) mouse liver tissue samples. A total of 87 and 96 potential oxylipins including 12 and 14 unreported oxylipins were detected and identified from human plasma and mouse liver tissues, respectively. The results showed that compared to the control group, in the liver samples of the NAFLD mouse, the content levels of prostaglandin (PG) E2, PGF2a, 8-hydroxy-eicosatrienoic acid (8-HETrE), and the newly discovered 2-hydroxy-octadecatrienoic acid (2-HOTrE) were remarkably increased, while the oxidation product of n-3 PUFA (p < 0.05) and all hydroperoxy oxylipins significantly decreased. On balance, this method contributes to future studies on oxylipin screening and application in other biological samples for facilitating the understanding of oxylipin roles in metabolic regulation of numerous diseases.

Mass Spectrometry Based on Chemical Derivatization Has Brought Novel Discoveries to Lipidomics: A Comprehensive Review.

Lipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the "gold standard" analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.

Insights into the antibacterial activity and antibacterial mechanism of silver modified fullerene towards Staphylococcus aureus by multiple spectrometric examinations.

Clarifying the antibacterial mechanism of silver (Ag)-based materials is of great significance for the rational design, synthesis, and evaluation of antimicrobials. Herein, detailed description of the antibacterial mechanism of a synthesized silver deposited fullerene material (Ag(I)-C60) towards Staphylococcus aureus was surveyed from the point of view of DNA damage by ultraviolet-visible spectroscopy (UV-vis), inductively coupled plasma mass spectrometry (ICP-MS), and liquid chromatography-mass spectrometry (LC-MS). The model material, Ag(I)-C60, was prepared by liquid-liquid interfacial precipitation method, and characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), thermos-gravimetric analysis (TGA), and nitrogen adsorption/desorption analysis. Ultra-efficient bacteriostatic rate of Ag(I)-C60 was found to be 88.98% under light irradiation for 20 min. UV-vis measurement of the composition changes of four DNA bases showed that they changed in the presence of Ag(I)-C60 under light irradiation, suggesting Ag(I)-C60 could destroy the cells and genetic material of Staphylococcus aureus and thereby inhibit its growth and reproduction. ICP-MS analysis demonstrated the releasing behavior of Ag+ from Ag-based materials. Finally, the transformation pathway of G, A, C, and T were measured by LC-MS, demonstrating the conversion of Adenine (m/z 136.06) to 8-OH-Ade (m/z 174.04). These collective results suggested that Ag(I)-C60 was a new ultra-efficient antibacterial by slowly releasing Ag+ in water and producing a large amount of ROS under light.

Preoperative systemic immune-inflammation index may predict prolonged mechanical ventilation in patients with spontaneous basal ganglia intracerebral hemorrhage undergoing surgical operation.

Background: Prolonged mechanical ventilation (PMV) has been proven as a risk factor for poor prognosis in patients with neurocritical illness. Spontaneous basal ganglia intracerebral hemorrhage (ICH) is one common subtype of hemorrhagic stroke and is associated with high morbidity and mortality. The systemic immune-inflammation index (SII) is used as a novel and valuable prognostic marker for various neoplastic diseases and other critical illnesses. Objective: This study aimed to analyze the predictive value of preoperative SII for PMV in patients with spontaneous basal ganglia ICH who underwent surgical operations. Methods: This retrospective study was conducted in patients with spontaneous basal ganglia ICH who underwent surgical operations between October 2014 and June 2021. SII was calculated using the following formula: SII = platelet count × neutrophil count/lymphocyte count. Multivariate logistic regression analysis and receiver operating characteristics curve (ROC) were used to evaluate the potential risk factors of PMV after spontaneous basal ganglia ICH. Results: A total of 271 patients were enrolled. Of these, 112 patients (47.6%) presented with PMV. Multivariate logistic regression analysis showed that preoperative GCS (OR, 0.780; 95% CI, 0.688-0.883; P < 0.001), hematoma size (OR, 1.031; 95% CI, 1.016-1.047; P < 0.001), lactic acid (OR, 1.431; 95% CI, 1.015-2.017; P = 0.041) and SII (OR, 1.283; 95% CI, 1.049-1.568; P = 0.015) were significant risk factors for PMV. The area under the ROC curve (AUC) of SII was 0.662 (95% CI, 0.595-0.729, P < 0.001), with a cutoff value was 2,454.51. Conclusion: Preoperative SII may predict PMV in patients with spontaneous basal ganglia ICH undergoing a surgical operation.

Volume-Corrected Free Energy as a New Criterion for Structural Elucidation in Chemical-Tagging-Based Metabolomics.

Chemical tagging via possible derivatization reagents alters metabolites' retention times, leading to different retention behavior during liquid chromatography-mass spectrometry (LC-MS) analysis. Incorporation of the retention time dimension can dramatically reduce false-positive structural elucidation in chemical-tagging-based metabolomics. However, few studies predict the retention times of chemically labeled metabolites, especially requiring a simple, easy-to-access, accurate, and universal predictor or descriptor. This pilot study demonstrates the application of volume-corrected free energy (VFE) calculation and region mapping as a new criterion to describe the retention time for structure elucidation in chemical-tagging-based metabolomics. The universality of VFE calculation is first evaluated with four different types of submetabolomes including hydroxyl-group-, carbonyl-group-, carboxylic-group-, and amino-group-containing compounds and oxylipins with similar chemical structures and complex isomers on reverse-phase LC. Results indicate a good correlation (r > 0.85) between VFE values and their corresponding retention times using different technicians, instruments, and chromatographic columns, describing retention behavior in reverse-phase LC. Finally, the VFE region mapping is described for identifying 1-pentadecanol from aged camellia seed oil using three proposed steps, including public database searching, VFE region mapping for its 12 isomers, and chemical standard matching. The possibility of VFE calculation of nonderivatized compounds in retention time prediction is also investigated, demonstrating its effectiveness on retention times with different influence factors.

Fluoro-cotton assisted non-targeted screening of organic fluorine compounds from rice (Oryza sativa L.) grown in perfluoroalkyl substance polluted soil.

The toxicity and environmental persistence of perfluorooctanoic acid (PFOA), and perfluorooctane sulfonate (PFOS) are of great concern for food intake in humans. However, PFASs conversion or conjugation to other substances in rice grown on PFASs polluted soil has not been explored clearly. These unknown transformed or conjugated products of PFOA and PFOS could be harmful to human health. The restriction factor in evaluating the possible transformation of PFOA and PFOS is mainly attributed to the lack of an efficient method for screening PFOA and PFOS and their related metabolites. To circumvent this challenge, we established a non-targeted screening method by combining a fluoro-cotton fiber-based solid phase extraction (FC-SPE) and liquid chromatography-high resolution mass spectrometry (LC-HRMS) to monitor the formation of possible organic fluorine compounds from rice (Oryza sativa L.) grown on PFASs. We synthesized fluoro-cotton fibers to serve as the FC-SPE packing material and characterized by field-emission scanning electron-microscope, Fourier transform infrared, and X-ray photoelectron spectroscopy measurements. The optimal extraction conditions for the prepared FC-SPE were investigated. The performance of FC-SPE in LC-MS analysis was validated by linearity, precision, recovery, and matrix effect. Then the FC-SPE combined with LC-HRMS was used to specifically capture organic fluorine compounds from complex matrices via F-F interaction, including rice seedlings grown in PFOA and PFOS polluted soil and soil samples. By the established FC-SPE LC-HRMS method, in total 429 features were found as the possible organic fluorine compounds from rice seedlings grown in PFOA polluted soil among the 1781 features from the rice seedlings. Finally, we employed a13C metabolic tracing analysis of organic fluorine compounds in combination with the FC-SPE LC-HRMS method to further identify the features that detected from rice seedlings grown in PFOA polluted soil. The final result indicated that there were not any new organic fluorine metabolites screened out from rice grown in PFOA or PFOS polluted soil.

Profiling and spatial distribution of phenolic compounds in rapeseed by two-step extraction strategy and targeted metabolomics combined with chemometrics.

In this study, a two-step extraction strategy (TSES) and targeted metabolomics combined with chemometrics was successfully applied for profiling of phenolic compounds in different colored rapeseeds. To this end, organic solvent extraction followed by deep eutectic solvent extraction made up the TSES with improved extraction coverage of free phenolics and enhanced extraction yield of conjugated phenolics, which combined with liquid chromatography tandem mass spectrometry (LC-MS/MS) for further profiling of phenolics. TSES-LC-MS/MS method was established with determination coefficients for phenolic compounds greater than 0.9989. Finally, the relationship between color differences and phenolic compounds in rapeseeds was investigated upon TSES-LC-MS/MS method combined with chemometrics. Syringin, kaempferol, isorhamnetin, and sinapic acid were found to be the differential phenolics for the six different colored rapeseeds and their spatial distribution in rapeseeds were presented. Consequently, our method showed great potential for future studies based on comprehensive extraction and profiling of phenolics from complex matrices.

Comprehensive review of composition distribution and advances in profiling of phenolic compounds in oilseeds.

A wide range of phenolic compounds participate in oilseed growth, regulate oxidative stability of corresponding vegetable oil, and serve as important minor food components with health-promoting effects. Composition distribution of phenolic compounds varied in oilseeds. Isoflavones, sinapic acid derivatives, catechin and epicatechin, phenolic alcohols, chlorogenic acid, and lignans were the main phenolic compounds in soybean, rapeseed, peanut skin, olive, sunflower seed, sesame and flaxseed, respectively. Among which, the total isoflavones content in soybean seeds reached from 1,431 to 2,130 mg/100 g; the main phenolic compound in rapeseed was sinapine, representing 70-90%; chlorogenic acid as the predominant phenolic compound in sunflower kernels, represented around 77% of the total phenolic content. With the rapid development of analytical techniques, it is becoming possible for the comprehensive profiling of these phenolic compounds from oilseeds. This review aims to provide recently developments about the composition distribution of phenolic compounds in common oilseeds, advanced technologies for profiling of phenolic compounds by the metabolomics approaches based on mass spectrometry. As there is still limited research focused on the comprehensive extraction and determination of phenolics with different bound-forms, future efforts should take into account the non-targeted, pseudo-targeted, and spatial metabolomic profiling of phenolic compounds, and the construction of phenolic compound database for identifying and quantifying new types of phenolic compounds in oilseeds and their derived products.

Determination of estrogens in human serum using a novel chemical derivatization-assisted liquid chromatography-electrospray ionization-tandem mass spectrometry method.

RATIONALE: Assessing estrogen concentrations in biological systems can provide valuable information on physiological processes, which is crucial for the early diagnosis of many diseases. Because estrogens are present in the human body in low concentrations and in a wide dynamic range, analytical methods with high sensitivity and specificity are required for their determination in complex biological matrices. METHODS: To discover an appropriate derivatization reagent for estrogen mass spectrometry (MS) analysis, we compared five sulfonyl chloride derivatization reagents, namely 3-methyl-8-quinolinesulfonyl chloride (MQSCl) and 8-quinolinesulfonyl chloride (QSCl), 1-methyl-1H-pyrazole-4-sulfonyl chloride, 1,2-methyl-imidazole-5-sulfonyl chloride, and dansyl chloride. By selecting the derivatization reagent with the best performance, we developed and validated a novel chemical derivatization-assisted-liquid chromatography-electrospray ionization-tandem mass spectrometry (CD-LC-ESI-MS/MS) method to simultaneously determine the concentrations of estrone, estradiol, and estriol (E1, E2, and E3) in human serum. RESULTS: It was found that among the five investigated reagents, MQSCl-derivatized estrogens presented the highest sensitivity using LC-ESI-MS/MS. Based on this discovery, MQSCl was chosen to derivatize the analyzed estrogens to assist LC-ESI-MS/MS analysis. The limit of quantification of E1, E2, and E3 was measured as 2.7, 4.6, and 5.1 pg/mL, respectively. Inter- and intra-day precision, expressed as the coefficient of variation, was shown to be lower than 13.2% for all concentrations. The mean recovery was 72.4% overall, with good reproducibility at low, medium, and high concentrations in the calibration range. CONCLUSIONS: The developed method was successfully applied to the quantitative determination of estrogens in clinical human serum from pediatric and adult women, demonstrating the suitability of estrogen analysis in the biological matrix at low concentration (pg/mL).

Simultaneous Analysis of Free/Combined Phytosterols in Rapeseed and Their Dynamic Changes during Microwave Pretreatment and Oil Processing.

Here, a simple, efficient, and rapid solid phase extraction-gas chromatography (SPE-GC) method was developed for the simultaneous analysis of free/combined phytosterols in rapeseed and their dynamic changes during microwave pretreatment and oil processing. First, by comparing different methods for extracting free/combined phytosterols from rapeseed and rapeseed cake, the Folch method was considered to be the optimal method and was selected in subsequent experiments. Subsequently, the extraction method was validated by determining the recoveries of standards (brassinosterol, campesterol, ß-sitosterol and cholesteryl oleate) spiked in rapeseed and rapeseed oil samples, and the recoveries were in the range from 82.7% to 104.5% and 83.8% to 116.3%, respectively. The established method was applied to study the dynamic changes of the form and content of phytosterols in rapeseed and its products (rapeseed oil and cake) during rapeseed microwave pretreatment and the oil production process. Additionally, the results showed that more than 55% of the free/combined phytosterols in rapeseed were transferred to rapeseed oil during the oil processing, and this proportion will increase after microwave pretreatment of rapeseed. This work will provide analytical methods and data support for a comprehensive understanding of phytosterols in rapeseed and its products during oil processing.

Quantitative analysis of the relationship of derivatization reagents and detection sensitivity of electrospray ionization-triple quadrupole tandem mass spectrometry: Hydrazines as prototypes.

Chemical derivatization-assisted electrospray ionization-triple quadrupole mass spectrometry (ESI-QqQ-MS) has become an efficient tool for the quantification of low-molecular-weight molecules. Many studies found that the derivatives of the same analytes derivatized by different derivatization reagents with the same reaction group had different detection sensitivity, even under the same conditions of electrospray ionization-mass spectrometry (ESI-MS). This phenomenon was suggested to be caused by the different modifying groups in the derivatization reagents. However, there is still a lack of systematic study on how modifying groups in the derivatization reagents affect the detection sensitivity of their corresponding derivatives of analytes, especially theoretical investigations. In this study, we employed a quantitative structure-activity relationship (QSAR) modeling approach to explore the relationship between modifying group structures and the detection sensitivity of derivatization reagents and their derivatives during ESI-MS detection. A total of 110 derivatization reagents of the hydrazine family and their hexanal derivatives (substituted hydrazones) were selected as the prototypes to construct QSAR models. The established models suggested that several molecular descriptors, related to hydrophobicity, electronegativity, and molecular shape, were related to the detection sensitivity of hexanal derivatives induced by different modifying groups in the derivatization reagents. Besides, we found that the detection sensitivity of compounds detected in selected ion mode (SIM) showed a positive correlation with that obtained in multiple reaction monitoring mode (MRM), and the ionization efficiency was the key factor on the detection sensitivity in both modes.

Simultaneous determination of short-chain fatty alcohols in aged oil and biodiesels by stable isotope labeling assisted liquid chromatography-mass spectrometry.

Short-chain fatty alcohols (SCFAs) are one of the reactants for the production of biodiesels. The SCFA residues at the trace level have a significant impact on biodiesel quality. However, the analysis of SCFAs in aged biodiesels has not been reported so far, which is probably due to the unavailability of an appropriate analytical method for the simultaneous determination of SCFAs. Herein, we developed a novel analytical approach with high sensitivity and selectivity for the simultaneous identification and determination of SCFAs in seed oil and biodiesel samples during the simulated real-time aging by stable isotope labeling assisted liquid chromatography-mass spectrometry (SIL-LC-MS). A pair of isotope labeling reagents, pyridine (Py) and [2H5]pyridine ([2H5]Py), were used to label SCFAs in biodiesels and standards, respectively. The [2H5]Py labeled SCFAs were used as internal standards to compensate for the detection of variances. The simultaneous determination of SCFAs was performed by LC-MS with an improved detection selectivity and sensitivity. The limits of detection (LODs) values were ranged from 0.2 to 0.5 ng mL-1 for the investigated SCFAs. Good linearity was observed in the studied ranges (R2 > 0.99) and good precision with relative standard deviations (RSDs) was in the range of 4.9-18.1%. Average recoveries were obtained in the range of 80.3%-115.4%. The matrix effects were in the range of 70.0-104.3%. The validated SIL-LC-MS method was applied to the simultaneous quantitative analysis of SCFAs in seed oil and biodiesel samples and the LC-MS analysis could be done within 3 min. The formation mechanism of SCFAs in aged oil and biodiesel samples was also investigated by this method. The results suggest that SCFAs were formed and their composition changed during the simulated real-time aging of long-chain fatty acid (LCFA), long-chain fatty acid methyl ester (FAME), seed oil, and biodiesels. Moreover, we found that the formation of 1-pentanol and 1-hexanol was associated with the number and position of double bonds in LCFAs and FAMEs.

A novel charge derivatization-direct infusion mass spectrometry method for the quantitative analysis of C1-C8 fatty acids in rubber seed oil-based biodiesel.

The free fatty acids that contain one to eight carbons (C1-C8) in biodiesel would affect the quality of biodiesel. It is still a matter of challenge to simultaneously determine the composition of C1-C8 fatty acids in seed oil and seed oil-based biodiesel. Herein, a novel method of charge derivatization coupling with direct infusion mass spectrometry (CD-DIMS) was developed for the determination of the C1-C8 fatty acids in biodiesels. A fixed-charge derivatization reagent, 1-cyclohexyl-3-(2-morpholinoethyl)carbodiimide (CMCT), was used to convert fatty acids into their cationic derivatives, which significantly improved the sensitivity and selectivity of detection. Good linearity was observed with the limits of detection (LODs) in the range of 0.0002-0.001 µg mL-1 for the investigated fatty acids. The recovery was in the range of 85.1%-101.9% and the matrix effect was within the range of 75.5-93.2%. The developed method was carried out to analyze C1-C8 fatty acids in rubber seed oil (RSO) and RSO-based biodiesels produced by different catalysts, including NaOH, TiO2, and carbodiimide. It was also applied to the dynamic monitoring of C1-C8 fatty acids in RSO and produced RSO biodiesels during the oxidation process. As results, formic acid, acetic acid, and propionic acid were detected in aged RSO and biodiesel samples. The contents of formic acid, acetic acid, and propionic acid all increased in aged RSO and biodiesels, but with different growth rates. These results demonstrated that the developed CD-DIMS method can provide a quick, accurate, and sensitive analysis of C1-C8 fatty acids in seed oil and biodiesel samples.

Comprehensive binding analysis of polybrominated diphenyl ethers and aryl hydrocarbon receptor via an integrated molecular modeling approach.

Polybrominated diphenyl ethers (PBDEs) are often suspected to activate the signal transduction pathway of aryl hydrocarbon receptor (AhR), a ligand-activated transcription factor, for the induction of toxicity. Hence, the binding property of PBDEs with AhR is assumed to be associated with the ligand-dependent activation of AhR that may introduce many drug-metabolizing enzymes of genes encoding. However, the binding mechanism and the structural effect of PBDEs on their binding properties of AhR still need to be unraveled for toxicology research. A comprehensive study of the PBDEs-AhR binding mechanism was investigated using an integrated molecular modeling approach with two-dimensional quantitative structure-activity relationships (2D-QSAR), three-dimensional QSAR (3D-QSAR), and molecular docking simulation. Molecular docking revealed the differences in binding domains among 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-AhR complex and two PBDE-AhR complexes. A 2D-QSAR model was developed to analyze the overall structural effects of PBDEs on the binding affinity of AhR. It provided an insight into major physico-chemical properties by multiple linear regression based on genetic algorithm with reasonable results. The 3D-QSAR modeling discovered the detailed interaction features of binding sites, configurations and interaction fields of AhR with different PBDE ligands. This study demonstrated that the descriptors of Smin69 and MoRSEC15 were related to electronic properties and had a great effect on the relative binding affinities. The position of Br substitutions exhibited a significant influence on the interactions between AhR and PBDEs, including halogen interaction, π-S interaction, π-π stacking interaction, and hydrophobic effect. This integrated molecular modeling approach provided a comprehensive analysis of the structural effects of PBDEs on their binding properties with AhR at molecular level.

Evaluation of structurally different brominated flame retardants interacting with the transthyretin and their toxicity on HepG2 cells.

Brominated flame retardants (BFRs) are found at quantifiable levels in both humans and wildlife and may potentially cause a health risk. For BFRs and their derivatives, limited information regarding the relationship among the structure, binding affinity to the target protein and toxicity is currently available. In the present work, representative BFRs with different hydroxyl- or bromo-substituents, namely 2, 2', 4, 4'-tetrabromodiphenyl ether (BDE-47), 3-hydroxy-2, 2', 4, 4'-tetrabromodiphenyl ether (3-OH-BDE-47) and tetrabromobisphenol A (TBBPA), were selected to investigate the interactions with transthyretin (TTR) by electrospray ionization mass spectrometry (ESI-MS) and cytotoxicity on HepG2 cells. It was noted that BDE-47 had a weak binding affinity to TTR, while 3-OH-BDE-47 and TBBPA had a stronger binding affinity than BDE-47 and thyroxine (T4). Hence, 3-OH-BDE-47 and TBBPA could affect the binding of TTR with its native ligand T4 by competitive binding to TTR, even at equal concentrations, which might be associated with BFR toxicity of endocrine disruption. Negative cooperativity was found for 3-OH-BDE-47 and TBBPA binding to TTR, similar to T4 with a well-established negatively cooperative binding mechanism. The tendency of toxic effects on HepG2 cells for these three BFRs was, 3-OH-BDE-47 > TBBPA > BDE-47, and this order was in good agreement with the binding ability explored by ESI-MS experiments and molecular docking simulation. The observations obtained by this study demonstrate that the binding properties of these BFRs to TTR and their cytotoxicity are correlated with structure differentials and functional substituents.

Hydrogen-Deuterium Scrambling Based on Chemical Isotope Labeling Coupled with LC-MS: Application to Amine Metabolite Identification in Untargeted Metabolomics.

Identification of metabolites at the trace level in complex samples is still one of the major challenges in untargeted metabolomics. One formula in the metabolomic database is always corresponding to more than one candidate, which increases the difficulty and cost in the subsequent process of standard compound matching. In this study, we developed an effective method for amine metabolite identification by hydrogen-deuterium scrambling (HDS) based on chemical isotope labeling coupled with liquid chromatography-mass spectrometry (HDS-CIL-LC-MS). After d4-4-(N,N-dimethylamino)phenyl isothiocyanate (d4-DMAP) labeling, the labeled amine metabolites can produce HDS under collision-induced dissociation (CID). The HDS can effectively reflect the number of labile hydrogen atoms in amine metabolites and thus distinguish amine isomers with different functional groups. The developed HDS-CIL-LC-MS method was applied to the determination of amine metabolites in mice feces, in which the amine candidates obtained by the database based on chemical formula searching were reduced by 64% on average, which greatly reduces the cost of standard compound matching. Taken together, the developed HDS-CIL-LC-MS analysis was demonstrated to be a promising method for untargeted metabolomics and a novel strategy for deciphering tandem mass spectrometry (MS2) spectra.