Number Of Double Bonds Research Articles

Using Subcritical Water to Obtain Polyphenol-Rich Extracts with Antimicrobial Properties.

The use of green extraction methods that meet the criteria of sustainable and environmentally friendly technologies has been increasing in recent decades due to their many benefits. In this respect, extracts obtained using subcritical water are also gaining increased attention because of their potential antioxidant and antimicrobial properties. Their antimicrobial activity is mainly due to the presence of various polyphenolic compounds. Although the exact mechanism of the antibacterial action of polyphenolic compounds has not yet been fully investigated and described, polyphenols are known to affect the bacterial cell at several cellular levels; among other things, they cause changes and ruptures in the cell membranes of the bacterial cell, affect the inactivation of bacterial enzymes and damage bacterial DNA. The difference in the strength of the antimicrobial activity of the extracts is most likely a result of differences in their lipophilicity and in the number and position of hydroxyl groups and double bonds in the chemical structure of polyphenols. By changing the extraction conditions, especially the temperature, during subcritical water extraction, we affect the solubility of the compounds we want to extract. In general, as the temperature increases, the solubility of polyphenolic compounds also increases, and the reduction of the surface tension of subcritical water at higher temperatures also enables faster dissolution of polyphenolic compounds. Different bacterial strains have different sensitivity to different extracts. However, extracts obtained with subcritical water extraction demonstrate strong antimicrobial activity compared to extracts obtained with conventional methods.

Analysis of the microstructure of high viscosity components in Tahe ultra heavy oil based on the combination of ESI (±) FT-ICR/MS

In addressing the challenge of high viscosity in Xinjiang Tahe heavy oil, crucial for optimizing extraction processes, this study focuses on identifying and analyzing the microstructure of key components influencing oil viscosity. The aim is to uncover the underlying reasons for its high viscosity and guide research towards effective viscosity reduction techniques. Electrospray ionization (ESI) combined with fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) characterizes the molecular-level constituents contributing to oil viscosity. The investigation covers the composition and distribution of oxygen-containing, nitrogen-containing, and organometallic compounds, developing a molecular structure model for these critical viscosity-inducing components. Findings reveal Xinjiang Tahe extra heavy oil as a solid mass at room temperature, with significant viscosity reduction observed post-deasphalting, highlighting asphaltenes' pivotal role in viscosity. Analysis indicates a higher content of metal elements (such as V and Ni) in asphaltenes compared to the crude oil itself, with an abundance of porphyrin structures in asphaltenes markedly influencing oil viscosity. Cyclic, aromatic, and unsaturated compound structures are predominantly found in the asphaltenes of heavy oil. Through combined ESI (±) FT-ICR/MS analysis, the crude oil is determined to mainly comprise acidic compounds, non-basic nitrogen compounds, and basic nitrogen compounds, offering significant insight into heavy oil's complex chemical composition. Specifically, non-basic nitrogen compounds in Tahe crude oil, including alkylcarbazoles, alkylbenzocarbazoles, and alkylpolybenzocarbazoles, are identified as key components, with molecular carbon numbers ranging from C12 to C56 and a predominance near C27. Additionally, asphaltenes in Tahe heavy oil exhibit a higher double bond equivalence (DBE) than the crude oil, indicating a greater degree of condensation with an increased number of double bonds and heterocyclic structures. The significant difference in DBE values between asphaltenes and crude oil underscores their impact on viscosity. A detailed molecular structure model of the asphaltenes in Tahe extra heavy oil has been constructed based on FT-ICR/MS analysis, providing a foundational understanding for developing viscosity reduction strategies.

Linoelaidic acid gavage has more severe consequences on triglycerides accumulation, inflammation and intestinal microbiota in mice than elaidic acid

This work aims to study the effects of oral gavage (0.2 mg/g body weight) of elaidic acid (C18:1–9 t, EA) and linoelaidic acid (C18:2–9 t,12 t, LEA) on lipid metabolism, inflammation and gut homeostasis of mice. Results showed that both EA and LEA gavage significantly increased LDL-c, TC and oxidative stress levels in the liver and serum and may stimulate liver inflammation via NF-κB and MAPK signaling pathway. Compared with EA, LEA gavage significantly promoted TAG accumulation and inflammatory signaling. Serum lipidomics revealed that LEA intake significantly increased the concentration of ∼50 TAGs, while EA gavage primarily caused significant decreases in several SMs. 16S rRNA demonstrated that LEA ingestion markedly changed fecal microbiota by enriching Lactobacillus (phylum Firmicutes), however, EA treatment did not affect it. Overall, LEA gavage has more severe consequences on TAG accumulation, inflammation and microbial structure than EA, highlighting that the number of trans double bonds affects these processes.

Prediction of the cold flow properties of biodiesel using the FAME distribution and Machine learning techniques

Burning fossil fuels is a significant contributor to global warming due to CO2 emissions. To mitigate these emissions, alternative bio-based fuels, such as biodiesel, have been developed. The cold flow properties of biodiesel, including pour point (PP), cold filter plugging point (CFPP), and cloud point (CP), are crucial. Predicting these properties can aid in selecting bio-oils for biodiesel production. Machine learning techniques were utilized to reveal intricate connections between the content of fatty acid methyl esters (FAME) in biodiesel and its cold flow properties. This study created three machine learning models based on a database of over 200 biodiesel samples to predict the aforementioned cold flow properties. The models' performance was assessed using three standard regression metrics: mean absolute error, mean squared error, and coefficient of determination. The experimental results show that the optimal algorithm for PP, CFPP, and CP has an average error of 4.51 °C, 3.56 °C, and 4.17 °C, respectively. The study also investigated the significance of various biodiesel attributes in making precise predictions, revealing that the distribution of FAME and the number of double bonds in the biodiesel are crucial factors for accurate predictions.

Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Deregulation of lipid composition in adipose tissue adjacent to breast tumour is observed in ex vivo and animal models. Novel non-invasive magnetic resonance imaging (MRI) allows rapid lipid mapping of the human whole breast. We set out to elucidate the spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive (ER +) breast cancer. Thirteen participants (mean age, 62 ± [SD] 6 years) with ER + breast cancer and 13 age-matched postmenopausal healthy controls were scanned on MRI. The number of double bonds in triglycerides was computed from MRI images to derive lipid composition maps of monounsaturated, polyunsaturated, and saturated fatty acids (MUFA, PUFA, SFA). The spatial heterogeneity measures (mean, median, skewness, entropy and kurtosis) of lipid composition in the peri-tumoural region and the whole breast of participants and in the whole breast of controls were computed. The Ki-67 proliferative activity marker and CD163 antibody on tumour-associated macrophages were assessed histologically. Mann Whitney U or Wilcoxon tests and Spearman’s coefficients were used to assess group differences and correlations, respectively. For comparison against the whole breast in participants, peri-tumoural MUFA had a lower mean (median (IQR), 0.40 (0.02), p < .001), lower median (0.42 (0.02), p < .001), a negative skewness with lower magnitude (− 1.65 (0.77), p = .001), higher entropy (4.35 (0.64), p = .007) and lower kurtosis (5.13 (3.99), p = .001). Peri-tumoural PUFA had a lower mean (p < .001), lower median (p < .001), a positive skewness with higher magnitude (p = .005) and lower entropy (p = .002). Peri-tumoural SFA had a higher mean (p < .001), higher median (p < .001), a positive skewness with lower magnitude (p < .001) and lower entropy (p = .012). For comparison against the whole breast in controls, peri-tumoural MUFA had a negative skewness with lower magnitude (p = .01) and lower kurtosis (p = .009), however there was no difference in PUFA or SFA. CD163 moderately correlated with peri-tumoural MUFA skewness (rs = − .64), PUFA entropy (rs = .63) and SFA skewness (rs = .59). There was a lower MUFA and PUFA while a higher SFA, and a higher heterogeneity of MUFA while a lower heterogeneity of PUFA and SFA, in the peri-tumoural region in comparison with the whole breast tissue. The degree of lipid deregulation was associated with inflammation as indicated by CD163 antibody on macrophages, serving as potential marker for early diagnosis and response to therapy.

Monitoring of Fatty Acid Derivatives and Vegetable Oils by the Quartz Crystal Microbalance.

This study investigated the characterization of fatty acid derivatives and vegetable oils by the quartz crystal microbalance (QCM). Resonant frequency and resistance were monitored for fatty acid derivatives and vegetable oils by a QCM sensor at 35℃ and 55℃. The resonant resistance depended on varieties of fatty acid derivatives, although the resonant frequency was similar for them. Oleic acid showed higher resonant resistance than methyl and ethyl oleate and oleyl alcohol. The resonant resistance of fatty acid methyl esters showed lower value according to the unsaturation (numbers of double bonds). Glyceryl oleate showed remarkably higher resonant resistance than oleic acid and its esters. Triolein showed the highest resonant resistance among glyceryl oleate. The resonant resistances of vegetable oils also depended on their varieties and iodine value (IV). Olive oil with the lowest IV showed the highest resonant resistance, while linseed oil with the highest IV showed the lowest resonant resistance among tested vegetable oils. The resonant resistances of vegetable oils reduced with their IV. These results suggested QCM may be effective for identification of vegetable oils.

2D-QSAR and molecular docking study on nitrofuran analogues as antitubercular agents

&lt;abstract&gt;&lt;sec&gt; &lt;title&gt;Background&lt;/title&gt; &lt;p&gt;Resistance to most of the antitubercular drugs has been on rising trends due to the misuse of existing drugs. This has encouraged us to explore a novel scaffold that has the potential for quick antimicrobial action with minimum side effects. Nitrofurans have attracted us due to their extensive biological activities, such as antibacterial and antifungal activities.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Objective&lt;/title&gt; &lt;p&gt;The antitubercular activities of 126 nitrofuran derivatives have been investigated by using indicator parameters and topological and structural fragment descriptors.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Methods&lt;/title&gt; &lt;p&gt;The different quantitative structure activity relationship (QSAR) models have been created and validated by using two different methodologies: combinatorial protocol in multiple linear regression (CP-MLR) and partial least-squares (PLS) analysis.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Results&lt;/title&gt; &lt;p&gt;The 16 descriptors identified in CP-MLR are from six different classes: Constitutional, Functional, Atom Centered Fragments, Topological, Galvez, and 2D autocorrelation. Indicator parameters and Dragon descriptors suggested that the presence of a furan ring substituted by nitro group is essential for antitubercular activity. Further descriptors from constitutional, and functional classes suggest that the number of double bonds, number of sulphur atoms and number of fragments like thiazole, morpholine and thiophene should be minimum, along with the positive influence of Kier-Hall electrotopological states (Ss) for improved activity. The ACF class descriptors, GALVEZ class descriptors, and 2D-AUTO descriptor GATS4p have also shown positive influence on the antitubercular activity. The TOPO class descriptor T(O…S) suggests that the minimum gap between sulphur and oxygen is favorable for activity.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Conclusions&lt;/title&gt; &lt;p&gt;The models acknowledged in the study have explained the variance between 72 to 76% in the training set and in the prediction of the test set compounds. Also, compounds &lt;bold&gt;122&lt;/bold&gt;, &lt;bold&gt;123&lt;/bold&gt; and &lt;bold&gt;82&lt;/bold&gt; were found to possess good binding affinity towards nitroreductase.&lt;/p&gt; &lt;/sec&gt;&lt;/abstract&gt;

Enhanced intramolecular charge transfer and near-infrared fluorescence in 4-dimethylamino-chalcone analogues through extended conjugation: synthesis, photophysical properties, and theoretical modelling.

The distinctive characteristics of near-infrared fluorescent organic molecules render them indispensable across diverse applications, from energy harvesting to bioimaging and sensing technologies. In this work, we continue our investigation on the chalcone derivative, 4-dimethylamino-2'-hydroxychalcone (nDHC, n = 1; where n is the number of olefinic bonds), by expanding the number of central double bonds (n = 2 (2DHC) and n = 3 (3DHC)). Additionally, we also synthesized the structurally related chalcones lacking the OH group (DC, 2DC, 3DC) in order to obtain a comprehensive understanding of their effects on the intramolecular charge transfer (ICT). The results show remarkable bathochromic shifts in absorption and fluorescence peaks in solution as n increases. These shifts, 20 nm and 35 nm for absorption and 100 nm and 200 nm for fluorescence in 2DHC and 3DHC, respectively, signify enhanced ICT and a significant increase in the excited state's dipole moment. The presence of OH groups notably amplifies these shifts due to additional electron donation, influencing solute-solvent interactions in solution. Femtosecond fluorescence upconversion and transient absoprtion techniques unraveled distinct dynamics in these derivatives, exhibiting the dominance of vibrational cooling, solvation, and intramolecular motions, particularly in the larger conjugated systems 3DHC and 3DC. The observed changes in the femtosecond transinet absorption spectra suggest the existence of new active states in extended conjugation systems, indicating diverse intramolecular conformational states contributing to their relaxation dynamics. The results of this study provide invaluable insights into excited-state spectroscopy, offering a roadmap for tailoring chalcone derivatives for specific applications.

Retention time prediction and MRM validation reinforce the biomarker identification of LC-MS based phospholipidomics.

Dysfunctional lipid metabolism plays a crucial role in the development and progression of various diseases. Accurate measurement of lipidomes can help uncover the complex interactions between genes, proteins, and lipids in health and diseases. The prediction of retention time (RT) has become increasingly important in both targeted and untargeted metabolomics. However, the potential impact of RT prediction on targeted LC-MS based lipidomics is still not fully understood. Herein, we propose a simplified workflow for predicting RT in phospholipidomics. Our approach involves utilizing the fatty acyl chain length or carbon-carbon double bond (DB) number in combination with multiple reaction monitoring (MRM) validation. We found that our model's predictive capacity for RT was comparable to that of a publicly accessible program (QSRR Automator). Additionally, MRM validation helped in further mitigating the interference in signal recognition. Using this developed workflow, we conducted phospholipidomics of sorafenib resistant hepatocellular carcinoma (HCC) cell lines, namely MHCC97H and Hep3B. Our findings revealed an abundance of monounsaturated fatty acyl (MUFA) or polyunsaturated fatty acyl (PUFA) phospholipids in these cell lines after developing drug resistance. In both cell lines, a total of 29 lipids were found to be co-upregulated and 5 lipids were co-downregulated. Further validation was conducted on seven of the upregulated lipids using an independent dataset, which demonstrates the potential for translation of the established workflow or the lipid biomarkers.

Acute myocardial infarction preferentially alters low-abundant, long-chain unsaturated phospholipid and sphingolipid species in plasma high-density lipoprotein subpopulations

AimHigh-density lipoprotein (HDL) particles in ST-segment elevation myocardial infarction (STEMI) are deficient in their anti-atherogenic function. Molecular determinants of such deficiency remain obscure. MethodsFive major HDL subpopulations were isolated using density-gradient ultracentrifugation from STEMI patients (n = 12) and healthy age- and sex-matched controls (n = 12), and 160 species of phosphatidylcholine, lysophosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, phosphatidylglycerol, phosphatidylserine, phosphatidic acid, sphingomyelin and ceramide were quantified by LC-MS/MS. ResultsMultiple minor species of proinflammatory phosphatidic acid and lysophosphatidylcholine were enriched by 1.7–27.2-fold throughout the majority of HDL subpopulations in STEMI. In contrast, minor phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, phosphatidylethanolamine, sphingomyelin and ceramide species were typically depleted up to 3-fold in STEMI vs. control HDLs, while abundances of their major species did not differ between the groups. Intermediate-to-long-chain phosphatidylcholine, phosphatidylinositol and phosphatidylglycerol species were more affected by STEMI than their short-chain counterparts, resulting in positive correlations between their fold decrease and the carbon chain length. Additionally, fold decreases in the abundances of multiple lipid species were positively correlated with the double bond number in their carbon chains. Finally, abundances of several phospholipid and ceramide species were positively correlated with cholesterol efflux capacity and antioxidative activity of HDL subpopulations, both reduced in STEMI vs controls. KEGG pathway analysis tied these species to altered glycerophospholipid and linoleic acid metabolism. ConclusionsMinor unsaturated intermediate-to-long-chain phospholipid and sphingolipid species in HDL subpopulations are most affected by STEMI, reflecting alterations in glycerophospholipid and linoleic acid metabolism with the accumulation of proinflammatory lysolipids and maintenance of homeostasis of major phospholipid species.

Comparative study on the anti-tumor effect of steroids derived from different organisms in H22 tumor-bearing mice and analysis of their mechanisms

This study aimed to comparatively investigate the anti-tumor mechanisms of steroids including ergosterol, β-sitosterol, cholesterol, and fucosterol. The model of H22 tumor-bearing mice was constructed based on histopathological data and biochemical parameters, while serums were subjected to metabolomics analysis to study the potential anti-tumor mechanisms. The results indicated that the four steroids exhibited different degrees of anti-tumor effects on H22 mice. The tumor inhibition rates were 63.25% for ergosterol, 56.41% for β-sitosterol, 61.54% for cholesterol, and 72.65% for fucosterol. Metabolomic analyses revealed that 87, 71, and 129 differential metabolites were identified in ergosterol, cholesterol, and fucosterol treatment groups, respectively. The fucosterol treatment group had the highest number of differential metabolites. At the same time, it mainly inhibited purine and amino acid metabolism to exert anti-tumor effects. Ergosterol enhanced immunity and affected pyruvate metabolism, and cholesterol inhibited purine metabolism. The chemical structure difference among ergosterol, cholesterol, and fucosterol is mainly at the number and position of sterol double bonds and the number and length of side chain carbons. Therefore, there is a structure-activity relationship between the structure of steroid compounds and their efficacy. This study provides a key foundation for the exploitation of the anti-tumor effects of steroids derived from different organisms.

Identification of Novel -Glucosidase Inhibitors from Syzygium jambos (L.) Using Spectroscopy and Molecular Docking.

Fruits ofSyzygiumjambos(L.) are recognized as a "food", exhibiting significant antidiabetic activities. However, the α-glucosidase inhibition of the components from Syzygiumjambos(L.) have not yet been investigated. In this study,a total of 14 compounds were isolated from Syzygium jambos (L.) Alston, eight of which showed significant inhibitory effects on α-glucosidase, with IC50 values in the range of 0.011-0.665mM. Notably, compounds 1-3 (IC50: 0.013, 0.011 and 0.030mM, respectively) exhibited much stronger activity than acarbose (IC50: 2.329 ± 0.109mM). The enzyme kinetics study indicated that compound 1 was an uncompetitive inhibitor, and compounds 2-8 were mixed-type inhibitors. Moreover, the interactions between compounds and α-glucosidase were investigated by molecular docking, which further revealed that the number of olefin double bonds and 2-COOH of heptadeca-phenols had a notable effect on the α-glucosidase inhibitory activity. This study demonstrated that Syzygiumjambos(L.) fruit might serve as a functional food for the prevention of diabetes mellitus.

Lipidomics analysis of impaired glucose tolerance and type 2 diabetes mellitus in overweight or obese elderly adults.

Aging, obesity, and type 2 diabetes mellitus (T2DM) form a metabolic disease continuum that has a continuously increasing prevalence. Lipidomics explains the complex interactions between lipid metabolism and metabolic diseases. We aimed to systematically investigate the plasma lipidome changes induced by newly diagnosed impaired glucose tolerance (IGT) and T2DM in overweight/obese elderly individuals and to identify potential biomarkers to differentiate between the IGT, T2DM, and control groups. Plasma samples from 148 overweight/obese elderly individuals, including 52 patients with IGT, 47 patients with T2DM, and 49 euglycemic controls, were analyzed using a high-coverage nontargeted absolute quantitative lipidomics approach. We quantified 1840 lipids from thirty-eight classes and seven lipid categories. Among overweight/obese elderly individuals, the lipidomic profiles of IGT and T2DM patients were significantly different from those of controls, while they were similar in the IGT and T2DM groups. The concentrations of diglycerides, triglycerides, phosphatidylcholines, and ceramides were obviously altered in the IGT and T2DM groups. Particularly, IGT and T2DM induced the accumulation of triglycerides with longer carbon atom numbers (C44-50) and saturated or lower double bond numbers (n (C=C) = 0-2). Furthermore, a total of 17 potential lipidic biomarkers were identified to successfully differentiate between the IGT, T2DM, and control groups. In overweight/obese elderly patients, IGT and T2DM induced apparent lipidome-wide changes. This study's results may contribute to explaining the complex dysfunctional lipid metabolism in aging, obesity, and diabetes.

Global Analysis of 2-Hydroxy Fatty Acids by Gas Chromatography-Tandem Mass Spectrometry Reveals Species-Specific Enrichment in Echinoderms.

Abnormal levels of 2-hydroxy fatty acids (2-OH FAs) are characterized in multiple diseases, and their quantification in foodstuffs is critical to identify the sources of supplementation for potential treatment. However, due to the structural complexity and limited available standards, the comprehensive profiling of 2-OH FAs remains an ongoing challenge. Herein, an innovative approach based on gas chromatography-tandem mass spectrometry (GC-MS/MS) was developed to determine the full profile of these FA metabolites. MS and MS/MS spectra of the trimethylsilyl (TMS) derivatives of 2-OH fatty acid methyl esters (FAMEs) were collected for peak annotation by their signature fragmentation patterns. The structures were further confirmed by validated structure-dependent retention time (RT) prediction models, taking advantage of the correlation between the RT, carbon chain length, and double bond number from commercial standards and pseudostandards identified in the whole-brain samples from mice. An in-house database containing 50 saturated and monounsaturated 2-OH FAs was established, which is expandible when additional molecular species with different chain lengths and backbone structures are identified in the future. A quantitation method was then developed by scheduled multiple reaction monitoring (MRM) and applied to investigate the profiling of 2-OH FAs in echinoderms. Our results revealed that the levels of total 2-OH FAs in sea cucumber Apostichopus japonicas (8.40 ± 0.28 mg/g dry weight) and starfish Asterias amurensis (7.51 ± 0.18 mg/g dry weight) are much higher than that in sea urchin Mesocentrotus nudus (531 ± 108 μg/g dry weight). Moreover, 2-OH C24:1 is the predominant molecular species accounting for 67.9% of the total 2-OH FA in sea cucumber, while 2-OH C16:0 is the major molecular species in starfish. In conclusion, the current innovative GC-MS approach has successfully characterized distinct molecular species of 2-OH FAs that are highly present in sea cucumbers and starfish. Thus, these findings suggest the possibility of developing future feeding strategies for preventing and treating diseases associated with 2-OH FA deficiency.

Prediction of cetane numbers of pure biodiesels based on various fuel properties using multiple non-linear correlations

Biodiesel has received considerable attention in recent years owing to its advantages over diesel fuel. Density, viscosity, flash point, heating value, and cetane number are among the most critical fuel properties of biodiesel. In the literature, using multiple linear regression, machine learning methods, and group contribution methods, some correlations have been derived to predict the cetane number of pure biodiesels depending on their properties (composition of fatty acid esters, number of carbon atoms, number of double bonds, molecular weight of the fatty acid esters, chain length, saponification number, iodine value, etc.). However, fewer researchers have attempted to establish a correlation between cetane number and other important fuel properties. Therefore, this study aims to employ multiple non-linear regression method for predicting the cetane number of pure biodiesels depending on the density, viscosity, flash point, and heating value. To obtain correlations, experimental data on fuel properties from the literature covering 100 different biodiesels (methyl and ethyl esters) were collected. The prediction performances of the suggested multiple non-linear correlations were compared to the multiple linear correlation frequently suggested in the literature. Reliable correlations with errors lower than 5% and high coefficient of determination values (r2) were derived.

Investigating Performance of the SLIM-Based High Resolution Ion Mobility Platform for Separation of Isomeric Phosphatidylcholine Species.

Lipids are structurally diverse molecules that play a pivotal role in a plethora of biological processes. However, deciphering the biological roles of the specific lipids is challenging due to the existence of numerous isomers. This high chemical complexity of the lipidome is one of the major challenges in lipidomics research, as the traditional liquid chromatography-mass spectrometry (LC-MS) based approaches are often not powerful enough to resolve these isomeric and isobaric nuances within complex samples. Thus, lipids are uniquely suited to the benefits provided by multidimensional liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) analysis. However, many forms of lipid isomerism, including double-bond positional isomers and regioisomers, are structurally similar such that their collision cross section (CCS) differences are unresolvable via conventional IM approaches. Here we evaluate the performance of a high resolution ion mobility (HRIM) system based on structures for lossless ion manipulation (SLIM) technology interfaced to a high resolution quadrupole time-of-flight (QTOF) analyzer to address the noted lipidomic isomerism challenge. SLIM implements the traveling wave ion mobility technique along an ∼13 m ion path, providing longer path lengths to enable improved separation of isomeric features. We demonstrate the power of HRIM-MS to dissect isomeric PC standards differing only in double bond (DB) and stereospecific number (SN) positions. The partial separation of protonated DB isomers is significantly enhanced when they are analyzed as metal adducts. For sodium adducts, we achieve close to baseline separation of three different PC 18:1/18:1 isomers with different cis-double bond locations. Similarly, PC 18:1/18:1 (cis-9) can be resolved from the corresponding PC 18:1/18:1 (trans-9) form. The separation capacity is further enhanced when using silver ion doping, enabling the baseline separation of regioisomers that cannot be resolved when measured as sodium adducts. The sensitivity and reproducibility of the approach were assessed, and the performance for more complex mixtures was benchmarked by identifying PC isomers in total brain and liver lipid extracts.

Composition of galactolipids, betaine lipids and triglyceride‐associated fatty acids of the symbiotic dinoflagellate Zooxanthella (Brandtodinium) nutricula: A glimpse into polyunsaturated fatty acids available to its polycystine radiolarian host

SUMMARYZooxanthella nutricula is a photosynthetic dinoflagellate symbiont of polycystine radiolarians. As such, it is hypothesized to provide fixed organic carbon, including in the form of acylglycerolipids and sterols, to its non‐photosynthetic host. We have previously characterized the sterols of Z. nutricula that may be transferred to its host and, in the present study, have turned our attention to three classes of fatty acid‐containing lipids, chloroplast‐associated galactolipids, betaine lipids, which are non‐phosphorylated phospholipid analogs present in many eukaryotes, and triglycerides. Zooxanthella nutricula was observed using positive‐ion electrospray/mass spectrometry (ESI/MS) and ESI/MS/MS to produce the galactolipids mono‐ and digalactosyldiacylglycerol (MGDG and DGDG, respectively) enriched in octadecapentaenoic (18:5(n‐3)) and octadecatetraenoic (18:4(n‐3)) acid to place it within a group of peridinin‐containing dinoflagellates in a C18/C18 (sn‐1/sn‐2 fatty acid regiochemistry) cluster, as opposed to another cluster with C20/C18 MGDG and DGDG, where the C20 fatty acid is eicosapentaenoic acid (20:5(n‐3)) and the C18 fatty acid is either 18:5(n‐3) or 18:4(n‐3). Zooxanthella nutricula was also observed to produce 38:10 (total number of fatty acid carbons:total number of double bonds), 38:6, and 44:7 diacylglycerylcarboxyhydroxymethylcholine (DGCC) as the sole type of betaine lipid. Although it is more difficult to determine which fatty acids are present in the sn‐1 and sn‐2 positions on the glycerol backbone of DGCC using ESI/MS/MS, gas chromatography/mass spectrometry (GC/MS)‐based examination indicated the putatively DGCC‐associated polyunsaturated fatty acid (PUFA) docosahexaenoic acid (22:6(n‐3)). Coupled with the C18 PUFAs of MGDG and DGDG, and fatty acids associated with triglycerides (also examined via GC/MS), Z. nutricula could serve as a rich source of PUFAs for its radiolarian host. These data demonstrate that Z. nutricula produces a similar set of PUFA‐containing lipids as Symbiodinium microadriaticum, a photosynthetic dinoflagellate symbiont of cnidarians, indicating a metabolic commonality in these phylogenetically discrete dinoflagellate symbionts with unrelated host organisms.

Spatial lipidomics reveals brain region-specific changes of sulfatides in an experimental MPTP Parkinson’s disease primate model

Metabolism of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) to the neurotoxin MPP+ in the brain causes permanent Parkinson’s disease-like symptoms by destroying dopaminergic neurons in the pars compacta of the substantia nigra in humans and non-human primates. However, the complete molecular pathology underlying MPTP-induced parkinsonism remains poorly understood. We used dual polarity matrix-assisted laser desorption/ionization mass spectrometry imaging to thoroughly image numerous glycerophospholipids and sphingolipids in coronal brain tissue sections of MPTP-lesioned and control non-human primate brains (Macaca mulatta). The results revealed specific distributions of several sulfatide lipid molecules based on chain-length, number of double bonds, and importantly, hydroxylation stage. More specifically, certain long-chain hydroxylated sulfatides with polyunsaturated chains in the molecular structure were depleted within motor-related brain regions in the MPTP-lesioned animals, e.g., external and internal segments of globus pallidus and substantia nigra pars reticulata. In contrast, certain long-chain non-hydroxylated sulfatides were found to be elevated within the same brain regions. These findings demonstrate region-specific dysregulation of sulfatide metabolism within the MPTP-lesioned macaque brain. The depletion of long-chain hydroxylated sulfatides in the MPTP-induced pathology indicates oxidative stress and oligodendrocyte/myelin damage within the pathologically relevant brain regions. Hence, the presented findings improve our current understanding of the molecular pathology of MPTP-induced parkinsonism within primate brains, and provide a basis for further research regarding the role of dysregulated sulfatide metabolism in PD.

Comprehensive utilization of Hainan cashew nut shell: Process optimization of cashew nut shell liquid extraction and cardanol refinement by catalytic transfer hydrogenation

In this work, an eco-friendly approach to the extraction of cashew nut shell liquid (CNSL) and the refinement of cardanol were explored for the first time using cashew nut produced in Hainan, China as raw material. Cashew nut shell (CNS) are usually disposed of as waste from agricultural processing, but CNSL extracted from CNS by solvent extraction or supercritical CO2 extraction has a high value. The composition of CNSL extracted by different conditions varies, and more CNSL is extracted by relatively less polar solvent. Supercritical CO2 extraction, as an environmentally friendly method, also showed good superiority in the extraction of CNSL. CNSL produced from Hainan cashew nuts contains high level of anacardic acid. The extracted CNSL can be decarboxylated and separated to obtain a mixture of cardanol consisting of four olefins containing different numbers of double bonds. Cardanol can be converted to saturated cardanol by catalytic hydrogenation and catalytic transfer hydrogenation, and the catalytic transfer hydrogenation also exhibits selectivity by selecting a suitable hydrogen donor to obtain high purity cardanol, monoene. Both saturated cardanol and cardanol, monoene have good prospects for utilization due to their chemical structure.

Step-by-Step Approach to Build Multiple Reaction Monitoring (MRM) Profiling Instrument Acquisition Methods for Class-based Lipid Exploratory Analysis by Mass Spectrometry.

Multiple reaction monitoring (MRM) profiling is a strategy for the exploratory analysis of small molecules and lipids by direct sample injection, ie, without the use of chromatographic separation. It is based on instrument methods that comprise a list of ion transitions (MRMs), in which the precursor ion is the expected ionized m/z of the lipid at its species level, ie, the description of lipid class and number of carbon and double bonds in the fatty acid chain(s), and the product ion is a fragment expected for the lipid class or for the fatty acid neutral loss. The Lipid Maps database is expanding constantly, and therefore the MRM-profiling methods associated with this database need to be continuously updated. Here, we provide a comprehensive overview and the key references for the MRM-profiling methodology and workflow, followed by a step-by-step approach to build MRM-profiling instrument acquisition methods for class-based lipid exploratory analysis based on the Lipid Maps database. The detailed workflow includes (1) importing the list of lipids from the database; (2) for a given class, combining isomeric lipids described at full structural level into 1 entry to obtain the neutral mass at species level; (3) attributing the standard Lipid Maps abbreviated nomenclature for the lipid at its species level; (4) predicting the ionized precursor ions; and (5) adding the expected product ion. We also describe how to simulate the precursor ion for the suspect screening of modified lipids using lipid oxidation and their expected product ions as an example. After determining the MRMs, information about collision energy, dwell time, and other instrument parameters are added to finalize the acquisition method. As an example of final method output, we describe the format for Agilent MassHunter v.B.06 and provide the parameters in which optimization can be performed by lipid class using one or more lipid standards.