Efficiency of nutrient utilization is reduced in neonates with intrauterine growth restriction (IUGR) compared with those with a normal birth weight (NBW). However, the underlying mechanisms are largely unknown. In this study, we applied temporal proteomic approach, coupled with histological and biochemical analyses, to study dynamic changes of the proteome in the small intestinal mucosa of IUGR piglets during the nursing period (Days 1, 7 and 21). We identified 56 differentially expressed protein spots between IUGR and NBW piglets. These proteins participate in key biological processes, including (1) absorption, digestion and transport of nutrients; (2) cell structure and motility; (3) glucose and energy metabolism; (4) lipid metabolism; (5) amino acid metabolism; (6) mineral and vitamin metabolism; (7) cellular redox homeostasis; (8) stress response; and (9) apoptosis. The results of our temporal proteomics analysis reveal continuous impairment of intestinal development in neonatal piglets with IUGR. The findings have important implications for understanding metabolic defects in the small intestine of IUGR neonates and are expected to provide new strategies to improve their survival and growth.

In this paper, a new robot path planning algorithm based on Quantum-inspired Evolutionary Algorithm (QEA) is proposed. QEA is an advanced evolutionary computing scheme with the quantum computing features such as qubits and superposition. It is suitable for solving large scale optimization problems. The proposed QEA algorithm works in the discretized environment, and approximates the optimal robot planing path in a highly computationally efficient fashion. The simulation results indicate that the proposed QEA algorithm is suitable for both complex static and dynamic environment and considerably outperforms the conventional genetic algorithm (GA) for solving the robot path planning problem. Our algorithm runs in only about 2[Formula: see text]s, which demonstrates that it can well tackle the optimization problem in robot path planning.

This experiment was conducted to evaluate the development of T cells in intrauterine growth retarded (IUGR) piglets at different gestational stages, and tentatively explore the relationship between T cells development and the Notch signaling pathway. A total of 18 crossbred (Landrace×Large white) primiparous sows were mated at similar weights and estruses and euthanized at d 60, 90 and 110 of gestation with six replicates for each time point. One IUGR and one normal fetus were picked from each litter. The T-cell subsets, mRNA expression of Delta-like1, Delta-like4, Jagged1, and Notch2 genes in the thymus were investigated. Compared to normal piglets, CD3+CD4−CD8+ cells in IUGR fetuses at d 90 was 0.13% lower (p<0.05). At d 110 of gestation CD8+ T cells in IUGR fetuses was 0.19% lower (p<0.05). The percentage of CD8+ T cells was 3.14% lower (p<0.05) of the total T cells in IUGR pigs at d 60. The abundance of Notch2 and Delta-like4 mRNA at d 110 was 20.93% higher and 0.77% (p<0.05) lower, and Delta-like1 mRNA at d 90 was 0.19% (p<0.05) higher compared to normal pigs. These results suggested that normal fetuses had a greater proportion of T-cell subsets at earlier gestation periods, and the Notch signaling pathway was likely partially responsible for these differences to some degree.