Search

Chinese cabbage (Brassica rapa ssp. pekinensis) has a long cultivation history and is one of the vegetable crops with the largest cultivation area in China. However, salt stress severely damages photosynthesis and hormone metabolism, nutritional balances, and results in ion toxicity in plants. To better understand the mechanisms of salt-induced growth inhibition in Chinese cabbage, RNA-seq and physiological index determination were conducted to explore the impacts of salt stress on carbon cycle metabolism and photosynthesis in Chinese cabbage. Here, we found that the number of thylakoids and grana lamellae and the content of starch granules and chlorophyll in the leaves of Chinese cabbage under salt stress showed a time-dependent response, first increasing and then decreasing. Chinese cabbage increased the transcript levels of genes related to the photosynthetic apparatus and carbon metabolism under salt stress, probably in an attempt to alleviate damage to the photosynthetic system and enhance CO2 fixation and energy metabolism. The transcription of genes related to starch and sucrose synthesis and degradation were also enhanced; this might have been an attempt to maintain intracellular osmotic pressure by increasing soluble sugar concentrations. Soluble sugars could also be used as potential reactive oxygen species (ROS) scavengers, in concert with peroxidase (POD) enzymes, to eliminate ROS that accumulate during metabolic processes. Our study characterizes the synergistic response network of carbon metabolism and photosynthesis under salt stress.

This study investigated the effect of a low protein (LP) diet on growth performance, nitrogen emission, carcass traits, meat quality, and gut microbiota in finishing pigs. Fifty-four barrows (Duroc × Landrace × Yorkshire) were randomly assigned to three treatments with six replicates (pens) of three pigs each. The pigs were fed with either high protein (HP, 16% CP), medium protein (MP, 12% CP), and LP diets (10% CP), respectively. The LP diets did not influence the growth performance, but significantly decreased the plasma urea nitrogen contents and fecal nitrogen emission (P < 0.05). The LP diet significantly decreased the plasma contents of malondialdehyde (MDA) and increased the plasma glutathione (GSH) contents (P < 0.05). The LP diets significantly increased the backfat thickness at the first and last ribs, L* (lightness) value of meat color, and muscle fiber density in the longissimus dorsi (P < 0.05). The messenger RNA (mRNA) expression of fatty acid synthetase (FAS), peroxisome proliferator-activated receptor-gamma (PPARγ), leptin, and acetyl-CoA carboxylase (ACC) was significantly downregulated, while that of carnitine palmitoyltransferase 1 (CPT1) and myosin heavy chain (MYHC) IIx in the longissimus Dorsi muscle was significantly upregulated by LP diets (P < 0.05). The 16S sequencing analysis showed that the abundance of unidentified Bacteria at the phylum level, and Halanaerobium and Butyricicoccusat at the genus level in the colonic digesta were significantly decreased by LP diet (P < 0.05). The LP diet significantly decreased the observed species of α-diversity in both ileal and colonic microbiota (P < 0.05). Spearman correlation analysis identified a significant positive correlation between the abundance of the ileal genera Streptococcus and L* value at 24 and 48 h, and a significant negative correlation between unidentified_Ruminococcasceae in both ileum and colon with L* value at 24 h (P < 0.05). Collectively, the LP diet supplemented with lysine, methionine, threonine, and tryptophan could reduce the fecal nitrogen emission without affecting growth performance and improve meat quality by regulating the antioxidant capacity and gene expression involved in fat metabolism as well as modulating the gut microbiota composition in finishing pigs.

This study investigated the effects of dietary compound antioxidants on growth performance, antioxidant capacity, carcass traits, meat quality, and gut microbiota in finishing pigs. A total of 36 barrows were randomly assigned to 2 treatments with 6 replicates. The pigs were fed with a basal diet (control) or the basal diet supplemented with 200 mg/kg vitamin E, 0.3 mg/kg selenium-enriched yeast, and 20 mg/kg soy isoflavone. Dietary compound antioxidants decreased the average daily feed intake (ADFI) and feed to gain ratio (F/G) at d 14–28 in finishing pigs (p < 0.05). The plasma total protein, urea nitrogen, triglyceride, and malondialdehyde (MDA) concentrations were decreased while the plasma glutathione (GSH) to glutathione oxidized (GSSG) ratio (GSH/GSSG) was increased by compound antioxidants (p < 0.05). Dietary compound antioxidants increased loin area and b* value at 45 min, decreased backfat thickness at last rib, and drip loss at 48 h (p < 0.05). The relative abundance of colonic Peptococcus at the genus level was increased and ileal Turicibacter_sp_H121 abundance at the species level was decreased by dietary compound antioxidants. Spearman analysis showed a significant negative correlation between the relative abundance of colonic Peptococcus and plasma MDA concentration and meat drip loss at 48 h. Collectively, dietary supplementation with compound antioxidants of vitamin E, selenium-enrich yeast, and soy isoflavone could improve feed efficiency and antioxidant capacity, and modify the backfat thickness and meat quality through modulation of the gut microbiota community.

The Mobile Crowd-sensing Network is a novel cyber−physical−social network which has received great attention recently and can be used as a powerful tool to monitor the phenomenon of the field of interest. Due to the limited budget, how to choose appropriate participants to maximize the coverage quality is one of the most important issues when the mobile crowd-sensing network applies to practical application, such as air quality monitoring. In this paper, given the number of available participants, the traverse path and the reward of each participant, we investigate the problem of how to choose suitable participants to monitor an environment of a critical region by a crowd-sensing network, while the total rewards for all selected participants is not larger than the limited budget. In our solution, we first divide a big critical region such as a city into smaller regions of different size, and select some sampling points in the smaller region; the collected data of those sampling points represents the collected data of the whole smaller region. Then, we design a greedy algorithm to select participants to cover the maximum sampling points while the total rewards of selected participants does not exceed the limited budget. Finally, we evaluate the validity and efficiency of the proposed algorithm by conducting extensive simulations. The simulation results show that the greedy algorithm outperforms an existing scheme.