Simple and Sensitive Method for the Quantitative Determination of Lipid Hydroperoxides by Liquid Chromatography/Mass Spectrometry

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics: Future challenges and perspectives

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

Mathematical Modeling of Alpha-Tocopherol Early Degradation Kinetics to Predict the Shelf-Life of Bulk Oils

The kinetics of lipid oxidation includes a lag phase followed by an exponential increase in oxidation products, which cause rancidity. Current models focus on the slope of this exponential curve for shelf-life estimation, which still requires the measurement of full oxidation kinetics. In this paper, we analyzed the formation of lipid oxidation products in stripped soybean oil containing different levels of α-tocopherol. The lag phases of lipid hydroperoxides and headspace hexanal formation were found to have a strong positive correlation with the α-tocopherol depletion time. We propose that the kinetics of antioxidant (α-tocopherol) depletion occur during the lag phase and could serve as an early shelf-life indicator. Our results showed that α-tocopherol degradation can be described by Weibull kinetics over a wide range of initial concentrations. Furthermore, we conducted in silico investigations using Monte Carlo simulations to critically evaluate the feasibility and sensitivity of the shelf-life prediction using early antioxidant degradation kinetics. Our results revealed that the shelf life of soybean oil may be accurately predicted as early as 20% of the overall shelf life. This innovative approach provides a more efficient and faster assessment of shelf life, ultimately reducing waste and enhancing product quality.

Lipoprotein Profile in Immunological Non-Responders PLHIV after Antiretroviral Therapy Initiation

Nuclear magnetic resonance (NMR)-based advanced lipoprotein tests have demonstrated that LDL and HDL particle numbers (LDL-P and HDL-P) are more powerful cardiovascular (CV) risk biomarkers than conventional cholesterol markers. Of interest, in people living with HIV (PLHIV), predictors of preclinical atherosclerosis and vascular dysfunction may be associated with impaired immune function. We previously stated that immunological non-responders (INR) were at higher CV risk than immunological responders (IR) before starting antiretroviral therapy (ART). Using Liposcale® tests, we characterized the lipoprotein profile from the same cohort of PLHIV at month 12 and month 36 after starting ART, intending to explore what happened with these indicators of CV risk during viral suppression. ART initiation dissipates the differences in lipoprotein-based CV risk markers between INR and IR, and only an increase in the number of HDL-P was found in INR + IR when compared to controls (p = 0.047). Interestingly, CD4+ T-cell counts negatively correlated with medium HDL-P concentrations at month 12 in all individuals (ρ = −0.335, p = 0.003). Longitudinal analyses showed an important increase in LDL-P and HDL-P at month 36 when compared to baseline values in both IR and INR. A proper balance between a proatherogenic and atherogenic environment may be related to the reconstitution of CD4+ T-cell count in PLHIV.