Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry.

Acylcarnitines are metabolic intermediates of fatty acids and branched-chain amino acids having vital biofunctions and pathophysiological significances. Here, we developed a high-throughput method for quantifying hundreds of acylcarnitines in one run using ultrahigh performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). This enabled simultaneous quantification of 1136 acylcarnitines (C0-C26) within 10-min with good sensitivity (limit of detection < 0.7 fmol), linearity (correlation coefficient > 0.992), accuracy (relative error < 20%), precision (coefficient of variation (CV), CV < 15%), stability (CV < 15%), and inter-technician consistency (CV < 20%, n = 6). We also established a quantitative structure-retention relationship (goodness of fit > 0.998) for predicting retention time (tR) of acylcarnitines with no standards and built a database of their multiple reaction monitoring parameters (tR, ion-pairs, and collision energy). Furthermore, we quantified 514 acylcarnitines in human plasma and urine, mouse kidney, liver, heart, lung, and muscle. This provides a rapid method for quantifying acylcarnitines in multiple biological matrices.

The Addition of an Ultra-Small Amount of Black Phosphorous Quantum Dots Endow Self-Healing Polyurethane with a Biomimetic Intelligent Response.

This study explores new applications of black phosphorus quantum dots (BPQDs) by adding them to self-healing material systems for the first time. Self-healing polyurethane with an ultra-small amount of BPQDs has biomimetic intelligent responsiveness and achieves balance between its mechanical and self-healing properties. By adding 0.0001 wt% BPQDs to self-healing polyurethane, the fracture strength of the material increases from 3.0 to 12.3 MPa, and the elongation at break also increases from 750% to 860%. Meanwhile, the self-healing efficiency remains at 98%. The addition of BPQDs significantly improves the deformation recovery ability of the composite materials and transforms the surface of self-healing polyurethane from hydrophilic to hydrophobic, making it suitable for applications in fields such as electronic skin and flexible wearable devices. This study provides a simple and feasible strategy for endowing self-healing materials with biomimetic intelligent responsiveness using a small amount of BPQDs.

Integrated metabolic and transcriptomic profiles reveal the germination-associated dynamic changes for the seeds of Cassia obtusifolia L.

INTRODUCTION: The seeds of Cassia obtusifolia L. (Cassiae [C.] semen) have been widely used as both food and traditional Chinese medicine in China. OBJECTIVES: We aimed to analyze the metabolic mechanisms underlying C. semen germination. MATERIALS AND METHODS: Different samples of C. semen at various germination stages were collected. These samples were subjected to 1 H-NMR and UHPLC/Q-Orbitrap-MS-based untargeted metabolomics analysis together with transcriptomics analysis. RESULTS: A total of 50 differential metabolites (mainly amino acids and sugars) and 20 key genes involved in multiple pathways were identified in two comparisons of different groups (36 h vs 12 h and 84 h vs 36 h). The metabolite-gene network for seed germination was depicted. In the germination of C. semen, fructose and mannose metabolism was activated in the testa rupture period, indicating more energy was needed (36 h). In the embryonic axis elongation period (84 h), the pentose and glucuronate interconversions pathway and the phenylpropanoid biosynthesis pathway were activated, which suggested some nutrient sources (nitrogen and sugar) were in demand. Furthermore, oxygen, energy, and nutrition should be supplied throughout the whole germination process. These global views open up an integrated perspective for understanding the complex biological regulatory mechanisms during the germination process of C. semen.

Rapid quantification of 50 fatty acids in small amounts of biological samples for population molecular phenotyping.

Efficient quantification of fatty-acid (FA) composition (fatty-acidome) in biological samples is crucial for understanding physiology and pathophysiology in large population cohorts. Here, we report a rapid GC-FID/MS method for simultaneous quantification of all FAs in numerous biological matrices. Within eight minutes, this method enabled simultaneous quantification of 50 FAs as fatty-acid methyl esters (FAMEs) in femtomole levels following the efficient transformation of FAs in all lipids including FFAs, cholesterol-esters, glycerides, phospholipids and sphingolipids. The method showed satisfactory inter-day and intra-day precision, stability and linearity (R2 > 0.994) within a concentration range of 2-3 orders of magnitude. FAs were then quantified in typical multiple biological matrices including human biofluids (urine, plasma) and cells, animal intestinal content and tissue samples. We also established a quantitative structure-retention relationship (QSRR) for analytes to accurately predict their retention time and aid their reliable identification. We further developed a novel no-additive retention index (NARI) with endogenous FAMEs reducing inter-batch variations to 15 seconds; such NARI performed better than the alkanes-based classical RI, making meta-analysis possible for data obtained from different batches and platforms. Collectively, this provides an inexpensive high-throughput analytical system for quantitative phenotyping of all FAs in 8-minutes multiple biological matrices in large cohort studies of pathophysiological effects.

Investigation on the stability in plant metabolomics with a special focus on freeze-thaw cycles: LC-MS and NMR analysis to Cassiae Semen (Cassia obtusifolia L.) seeds as a case study.

Metabolomics is a rapid and sensitive tool for the detection of dynamic metabolic compositions in the study of systemic metabolic consequences. However, it is also susceptible to a tiny variation of pre-analytical handling procedures. To provide reproducible results, specific knowledge on metabolites perturbance along with different freeze-thaw cycles (FTCs) is needed for further metabolomics studies. In this paper, five FTCs of germinated Cassiae Semen (CS) were chosen as a case study to investigate the influence of FTC effect based on UHPLC-Q-Orbitrap-MS and NMR technologies. A total of 108 metabolites were relatively quantified by LC-MS and NMR analyses. Principal component analysis (PCA) showed that the first and second FTC samples are welly separated from the other groups; however, the extent of FTC-induced effects are smaller after the third cycle. Upon five consecutive FTCs, alterations which consisted of decreased stachyose, sucrose, norrubrofusarin-6-O-ß-d-glucopyranoside, and quercetin 3-(3″-acetylgalactoside), as well as increased phenylalanine, leucine, isoleucine, methionine, phenylalanine, mannose, gluconic acid, and valine, could be observed. FTC does not exert the same effect on all metabolites. Although a large number of secondary metabolites were stable when subjected to five FTCs, FTC effects may lead to false-positive in the discovery of biomarker. In the case of reusing plant seed samples, no more than three consecutive freeze-thaw cycles were found advisable. This work provides unique perspectives on the FTC effects, which may fill in some existing gaps in the knowledge of the stability of plant metabolites during sample pre-handling.