Diroleuton

Understanding metabolic adaptations to seasonal fluctuations in ectothermic organisms is challenging, especially in tropical species where physiological responses are more pronounced than in temperate or polar counterparts. Traditional analytical methods often fail to account for the complex metabolic adjustments that are present in these substantial responses, and the high-dimensional characteristics of metabolomic data complicate the interpretation process when using conventional statistical methods. We utilized Non-negative Matrix Factorization (NMF), an unsupervised machine learning algorithm, to analyze monthly serum metabolomics data from tilapia over a year in order to overcome these limits. A deeper analysis using NMF demonstrated that carbohydrates gained prominence during warmer months, as evidenced by consistently elevated weights of glycolysis intermediates in our quantitative analysis. Furthermore, fatty acids remained an important factor in both warm and cold seasons. Amino acids emerged as particularly versatile metabolites, exhibiting adaptability during seasonal transitions. This flexibility suggests their crucial role in coordinating energy-related adaptations and potentially facilitating epigenetic and reproductive responses to changing environments. Serum aspartate composition during the warm-cold transition indicated sex-specific metabolic strategies, as sexual dimorphism was observed in the seasonal utilization of fatty acids and aspartate. Collectively, NMF objectively assesses the metabolic tactics of tropical fish and reveals latent patterns in real-world metabolic dynamics. Consequently, it possesses the potential to facilitate metabolomics-driven species conservation in response to environmental changes.

Dihomo-gamma-linolenic acid (DGLA) is derived from linoleic acid. Its presence in red blood cell (RBC) membranes is mainly due to metabolism and not diet. RBC DGLA was negatively associated with all-cause mortality during 7 years follow-up in patients admitted with an acute coronary syndrome (ACS). We now present its 2-year cardiovascular prognostic utility compared to other n-6 fatty acids (FAs).

A total of 139 females and 259 males with a mean age of 71.9 ± 13.0 years were admitted consecutively in this study. Stepwise Cox regression models, applying continuous values of DGLA weight percent (wt %) and quartiles, were fitted for the biomarkers with cardiac death and a combined cardiovascular (CV) endpoint consisting of cardiac death or myocardial infarction (MI) or stroke as the dependent variables.

Cardiac death was recorded in 57 patients, and the composite CV endpoint in 144 patients, respectively. DGLA was negatively associated with both endpoints, each with a p-value of <0.001 in univariate analysis. The hazard ratio (HR, per 1 wt % increase) remained significant after multivariable adjustment [cardiac death HR 0.51 (95 %CI 0.27-0.98), p = 0.042, and composite CV endpoint HR 0.61 (95 %CI 0.41-0.92), p = 0.017]. A similar pattern was obtained in ACS patients presenting with an acute MI at admission. No association with any outcome was found with the other n-6 FAs [linoleic acid, arachidonic acid and adrenic acid].

Higher RBC DGLA predicts lower risk for cardiac death and cardiovascular outcomes at 2 years follow-up in ACS patients, whereas other n-6 FAs do not.

ClinicalTrials.gov Identifier: NCT00521976.