Neural substrates of species-dependent visual processing of faces: use of morphed faces

Whole-body insulin resistance and energy expenditure indices, serum lipids, and skeletal muscle metabolome in a state of lipoprotein lipase overexpression

INTRODUCTION

Overexpression of lipoprotein lipase (LPL) protects against high-fat-diet (HFD)-induced obesity and insulin resistance in transgenic rabbits; however, the molecular mechanisms remain unclear. Skeletal muscle is a major organ responsible for insulin-stimulated glucose uptake and energy expenditure.

OBJECTIVES

The main purpose of the current study was to examine the effects of the overexpression of LPL on the skeletal muscle metabolomic profiles to test our hypothesis that the mitochondrial oxidative metabolism would be activated in the skeletal muscle of LPL transgenic rabbits and that the higher mitochondrial oxidative metabolism activity would confer better phenotypic metabolic outcomes.

METHODS

Under a HFD, insulin resistance index was measured using the intravenous glucose tolerance test, and total energy expenditure (TEE) was measured by doubly-labeled water in control and LPL transgenic rabbits (n = 12, each group). Serum lipids, such as triglycerides and free fatty acid, were also measured. The skeletal muscle metabolite profile was analyzed using capillary electrophoresis time-of flight mass spectrometry in the two groups (n = 9, each group). A metabolite set enrichment analysis (MSEA) with muscle metabolites and a false discovery rate q < 0.2 was performed to identify significantly different metabolic pathways between the 2 groups.

RESULTS

The triglycerides and free fatty acid levels and insulin resistance index were lower, whereas the TEE was higher in the LPL transgenic rabbits than in the control rabbits. Among 165 metabolites detected, the levels of 37 muscle metabolites were significantly different between the 2 groups after false discovery rate correction (q < 0.2). The MSEA revealed that the TCA cycle and proteinogenic amino acid metabolism pathways were significantly different between the 2 groups (P < 0.05). In the MSEA, all four selected metabolites for the TCA cycle (2-oxoglutaric acid, citric acid, malic acid, fumaric acid), as well as eight selected metabolites for proteinogenic amino acid metabolism (asparagine, proline, methionine, phenylalanine, histidine, arginine, leucine, isoleucine) were consistently increased in the transgenic rabbits compared with control rabbits, suggesting that these two metabolic pathways were activated in the transgenic rabbits. Some of the selected metabolites, such as citric acid and methionine, were significantly associated with serum lipids and insulin resistance (P < 0.05).

CONCLUSION

The current results suggest that the overexpression of LPL may lead to increased activities of TCA cycle and proteinogenic amino acid metabolism pathways in the skeletal muscle, and these enhancements may play an important role in the biological mechanisms underlying the anti-obesity/anti-diabetes features of LPL overexpression.

Facial identity influences facial expression recognition: A high-density ERP study

The relationship between facial identity and facial expression processing has long been debated. Although previous facial recognition models indicate that facial identity and facial expression processing are independent, psychological studies using the selective attention task (the Garner paradigm) have revealed an asymmetrical relationship between the perception of identity and emotional expressions in faces: while facial expression does not influence facial identity recognition, facial identity influences facial expression recognition. We used the Garner paradigm and recorded high-density event-related potentials (ERPs) to investigate the influence of facial identity on facial expression recognition. Twenty participants judged the expression of faces, while the irrelevant dimension of identity was either held constant (control condition) or varied (orthogonal condition). We recorded 128-channel EEGs while participants completed the facial expression task. We analyzed the two major components of early visual stages: P1 and N170. ERP results revealed a significant main effect of condition on the N170 latency. These results suggest that facial identity influences facial expression recognition in the N170 that reflects the structural encoding of faces. Thus, information on facial expression might be computed based on the unique structure of individual faces.