Differences in the metabolomic signatures of porcine follicular fluid collected from environments associated with good and poor oocyte quality.

The microenvironment of the developing follicle is critical to the acquisition of oocyte developmental competence, which is influenced by several factors including follicle size and season. The aim of this study was to characterise the metabolomic signatures of porcine follicular fluid (FF) collected from good and poor follicular environments, using high-resolution proton nuclear magnetic resonance (1H-NMR) spectroscopy. Sow ovaries were collected at slaughter, 4 days after weaning, in summer and winter. The contents of small (3-4  mm) and large (5-8  mm) diameter follicles were aspirated and pooled separately for each ovary pair. Groups classified as summer-small (n=8), summer-large (n=15), winter-small (n=9) and winter-large (n=15) were analysed by 1H-NMR spectroscopy. The concentrations of 11 metabolites differed due to follicle size alone (P<0.05), including glucose, lactate, hypoxanthine and five amino acids. The concentrations of all these metabolites, except for glucose, were lower in large FF compared with small FF. Significant interaction effects of follicle size and season were found for the concentrations of glutamate, glycine, N-acetyl groups and uridine. Succinate was the only metabolite that differed in concentration due to season alone (P<0.05). The FF levels of progesterone, androstenedione and oestradiol were correlated with the concentrations of most of the metabolites examined. The results indicate that there is a distinct shift in follicular glucose metabolism as follicles increase in diameter and suggest that follicular cells may be more vulnerable to oxidative stress during the summer months. Our findings demonstrate the power of 1H-NMR spectroscopy to expand our understanding of the dynamic and complex microenvironment of the developing follicle.

Modeling Electro-Chemo-Mechanical Behaviors within the Dense BaZr0.8Y0.2O3-δ Protonic-Ceramic Membrane in a Long Tubular Electrochemical Cell.

This paper reports an extended Nernst-Planck computational model that couples charged-defect transport and stress in tubular electrochemical cell with a ceramic proton-conducting membrane. The model is particularly concerned with coupled chemo-mechanical behaviors, including how electrochemical phenomena affect internal stresses and vice versa. The computational model predicts transient and steady-state defect concentrations, fluxes, stresses within a thin BaZr0.8Y0.2O3-δ (BZY20) membrane. Depending on the polarization (i.e., imposed current density), the model predicts performance as a fuel cell or an electrolyzer. A sensitivity analysis reveals the importance of thermodynamic and transport properties, which are often not readily available.