Background Energy balance is closely related to reproductive function, wherein hypothalamic kisspeptin mediates regulation of the energy balance. However, the central mechanism of kisspeptin in the regulation of male reproductive function under different energy balance states is unclear. Here, high-fat diet (HFD) and exercise were used to change the energy balance to explore the role of leptin and inflammation in the regulation of kisspeptin and the hypothalamic-pituitary-testis (HPT) axis. Methods Four-week-old male C57BL/6 J mice were randomly assigned to a normal control group (n = 16) or an HFD (n = 49) group. After 10 weeks of HFD feeding, obese mice were randomly divided into obesity control (n = 16), obesity moderate-load exercise (n = 16), or obesity high-load exercise (n = 17) groups. The obesity moderate-load exercise and obesity high-load exercise groups performed exercise (swimming) for 120 min/day and 120 min × 2 times/day (6 h interval), 5 days/week for 8 weeks, respectively. Results Compared to the mice in the normal group, in obese mice, the mRNA and protein expression of the leptin receptor, kiss, interleukin-10 (IL-10), and gonadotropin-releasing hormone (GnRH) decreased in the hypothalamus; serum luteinizing hormone (LH), follicle-stimulating hormone (FSH), and testosterone levels and sperm quality decreased; and serum leptin, estradiol, and tumor necrosis factor-α (TNF-α) levels and sperm apoptosis increased. Moderate- and high-load exercise effectively reduced body fat and serum leptin levels but had the opposite effects on the hypothalamus and serum IL-10 and TNF-α levels. Moderate-load exercise had anti-inflammatory effects accompanied by increased mRNA and protein expression of kiss and GnRH in the hypothalamus and increased serum FSH, LH, and testosterone levels and improved sperm quality. High-load exercise also promoted inflammation, with no significant effect on the mRNA and protein expression of kiss and GnRH in the hypothalamus, serum sex hormone level, or sperm quality. Moderate-load exercise improved leptin resistance and inflammation and reduced the inhibition of kisspeptin and the HPT axis in obese mice. The inflammatory response induced by high-load exercise may counteract the positive effect of improving leptin resistance on kisspeptin and HPT. Conclusion During changes in energy balance, leptin and inflammation jointly regulate kisspeptin expression on the HPT axis.

Current subgenotype 2.1 isolates of classical swine fever virus (CSFV) play a dominant role in CSF outbreaks in China, and a novel sub-subgenotype 2.1g of CSFV was recently identified, but the complete genome sequence of this new sub-subgenotype has not been reported. In this study, complete genome of 2.1g isolate GD19/2011 collected from Guangdong province of China in 2011 was sequenced. It was found to be 12,298 nucleotides (nt) in length, including a 375-nt 5'UTR, a 11,697-nt opening reading frame (ORF), and a 227-nt 3'UTR. GD19/2011 shared 91.0-93.7 % and 95.6-97.5 % nt and amino acid sequence identity, respectively, with other subgenotype 2.1 isolates. The topology of a phylogenetic tree constructed based on complete genome sequences of GD19/2011 and other CSFV isolates was identical to that obtained with full-length E2 gene sequences, but it was significantly different from those obtained with the 5'UTR and core sequences. Serial passages of GD9/2011 in PK-15 cells generated a highly cell-adapted virus stock with an infectious titer of 10(7.8) TCID50/ml at the 12(th) passage in which two amino acid substitutions, S476R and N2494S, were observed in comparison with the complete polyprotein sequence of the original isolate from kidney tissue, GD19/2011. This is the first report of the complete genome sequence of a 2.1g isolate, and the GD19/2011 isolate will be useful for further analysis of the evolution and virulence of CSFV isolates.

In this paper, based on the definition of two-parameter joint entropy and the maximum entropy principle, a method was proposed to determine the prior distribution by using the maximum entropy method in the reliability evaluation of low-voltage Keywords: prior distribution, maximum entropy, low-voltage switchgear, reliability evaluationCopyright © 2017 Universitas Ahmad Dahlan. All rights reserved. IntroductionLow-voltage switchgear is responsible for power control, protection, measurement, transformation and distribution in low-voltage power supply system. For the reliability evaluation of low-voltage switchgear with high reliability and long life, traditional reliability assessment method needs to obtain sufficient data by a large number of sample life tests which is timeconsuming, costly and inefficient [1]. Therefore, the rational use of empirical and historical data to determine priori distribution can lay a solid theoretical foundation for the reliability evaluation of low-voltage switchgear.Bayes method can make good use of not only the field test information, but also priori information, such as historical test information, test information for similar models and the same type products with different conditions, and so on. And the priori information can be used to get the priori distribution which increases the failure data. This method has been applied in most fields, such as medical system [2], web [3], electrical engineering [4], finance [5], and speech recognition [6]. While, there is no discussion about low-voltage switchgear.In this paper, Bayes method is used to evaluate the reliability of low-voltage switchgear. The priori distribution of low-voltage switchgear is determined by maximum entropy method which avoids the introduction of other assumption information because of the using of priori information. According to maximum entropy principle, priori information can be taken as different contrains, and the optimal prior distribution can be selected by maximizing entropy under these constraints. The non-parametric bootstrap method is used to expand data capacity and then hyper-parameters of priori distribution is eatimated. Finally, with the bootstrap method, the prior distribution robustness and the posterior robustness is analyzed, and the posterior mean time between failures for the low-voltage switchgear is estimated.

No abstract

No abstract