An ultrasonic assisted extraction procedure to free fatty acids from the liver samples of mice

Visualization of hydrocarbon chain length and degree of saturation of fatty acids in mouse livers by combining near-infrared hyperspectral imaging and machine learning

Fatty acids play various physiological roles owing to their diverse structural characteristics, such as hydrocarbon chain length (HCL) and degree of saturation (DS). Although the distribution of fatty acids in biological tissues is associated with lipid metabolism, in situ imaging tools are still lacking for HCL and DS. Here, we introduce a framework of near-infrared (1000-1400 nm) hyperspectral label-free imaging with machine learning analysis of the fatty acid HCL and DS distribution in the liver at each pixel, in addition to the previously reported total lipid content. The training data of 16 typical fatty acids were obtained by gas chromatography from liver samples of mice fed with various diets. A two-dimensional mapping of these two parameters was successfully performed. Furthermore, the HCL/DS plot exhibited characteristic clustering among the different diet groups. Visualization of fatty acid distribution would provide insights for revealing the pathophysiological conditions of liver diseases and metabolism.

Gas chromatography/mass spectrometry analysis of organic acid profiles in human serum: A protocol of direct ultrasound-assisted derivatization

RATIONALE

Low-molecular-weight organic acids that generally contain one to three carboxyl groups are involved in many important biological processes; therefore, it is important to develop a quantitative method for analyzing organic acids in serum in order to allow an evaluation of metabolic changes. In this study, we evaluated a protocol for detecting 26 organic acids in serum based on ultrasound-assisted derivatization by gas chromatography/mass spectrometry (GC/MS).

METHODS

Serum samples were prepared using ultrasound-assisted silane derivatization before GC/MS analysis to quantify concentrations of organic acids. Additionally, we investigated the variables affecting derivatization yields, including the extraction solvent, derivatization reagents, and derivatization conditions (reaction temperature, duration, and sonication parameters). The protocol was ultimately applied to detect organic acid profiles related to obesity.

RESULTS

We used acetone as the extraction solvent and determined suitable derivatization conditions, as follows: BSTFA + 1% TMCS, 50°C, 10 min, and 100% ultrasound power. The protocol showed satisfactory linearity (r = 0.9958-0.9996), a low limit of detection (0.04-0.42 μmol/L), good reproducibility (coefficient of variation (CV) %: 0.32-13.76%), acceptable accuracy (recovery: 82.97-114.96%), and good stability within 5 days (CV%: 1.35-12.01% at room temperature, 1.24-14.09% at 4°C, and 1.01-11.67% at -20°C). Moreover, the protocol was successfully applied to obtain the organic acid profiles from obese and healthy control subjects.

CONCLUSIONS

We identified and validated a protocol for ultrasound-assisted derivatization prior to GC/MS analysis for detecting 26 kinds of organic acids in serum. The results suggest the efficacy of this protocol for clinical applications to determine metabolic changes related to fluctuations in organic acid profiles.

Visualization of quantitative lipid distribution in mouse liver through near-infrared hyperspectral imaging

Lipid distribution in the liver provides crucial information for diagnosing the severity of fatty liver and fatty liver-associated liver cancer. Therefore, a noninvasive, label-free, and quantitative modality is eagerly anticipated. We report near-infrared hyperspectral imaging for the quantitative visualization of lipid content in mouse liver based on partial least square regression (PLSR) and support vector regression (SVR). Analysis results indicate that SVR with standard normal variate pretreatment outperforms PLSR by achieving better root mean square error (15.3 mg/g) and higher determination coefficient (0.97). The quantitative mapping of lipid content in the mouse liver is realized using SVR.

Gas chromatography-mass spectrometry-based analytical strategies for fatty acid analysis in biological samples

Fatty acids play critical roles in biological systems. Imbalances in fatty acids are related to a variety of diseases, which makes the measurement of fatty acids in biological samples important. Many analytical strategies have been developed to investigate fatty acids in various biological samples. Due to the structural diversity of fatty acids, many factors need to be considered when developing analytical methods including extraction methods, derivatization methods, column selections, and internal standard selections. This review focused on gas chromatography-mass spectrometry (GC-MS)-based methods. We reviewed several commonly used fatty acid extraction approaches, including liquid-liquid extraction and solid-phase microextraction. Moreover, both acid and base derivatization methods and other specially designed methods were comprehensively reviewed, and their strengths and limitations were discussed. Having good separation efficiency is essential to building an accurate and reliable GC-MS platform for fatty acid analysis. We reviewed the separation performance of different columns and discussed the application of multidimensional GC for improving separations. The selection of internal standards was also discussed. In the final section, we introduced several biomedical studies that measured fatty acid levels in different sample matrices and provided hints on the relationships between fatty acid imbalances and diseases.