Free amino acids in response to salinity changes in fishes: relationships to osmoregulation.

Free amino acids (FAAs) are believed to play important roles in osmoregulation and buffer capacity in some aquatic animals, such as fishes. However, the potential roles of FAAs have not been systematically summarized and characterized until now. In the present study, the meta-analysis was conducted to investigate the relationships between FAAs and environmental salinities. Twenty published documents were included, accounting for 106 study cases. The effect sizes of total free amino acids (TFAAs), total essential amino acids (TEAAs), and total non-essential amino acids (TNEAAs) to salinity increase were calculated and determined by the restricted maximum likelihood (REML) method. It clearly showed that the elevated salinities significantly induced the contents of TFAAs, TEAAs, and TNEAAs at the ratio of 36%, 27%, and 29%, respectively. Faced to the salinity changes, the contents of FAAs in fishes under freshwater and seawater varied significantly, while the individuals under brackish water displayed relatively constant contents of FAAs. When salinity elevated, the contents of 17 amino acids in muscles significantly increased, suggesting the important roles of FAA metabolism in osmoregulation in fishes. The results also indicated that the effect sizes of TFAAs were positively related to the rates of salinity increases, and exhibited a significant quadratic linear relationship with temperatures. Additionally, the contents of FAAs also showed positive correlation with osmotic pressure, concentrations of plasma Na+, Cl-, and urea, implying their potential roles of FAAs in osmoregulation in fishes. These findings suggested that elevated salinities greatly induced the contents of FAAs in fishes, making a great contribution to maintaining the homeostasis of fishes in response to environmental salinity changes.

Dynamic transcriptome and LC-MS/MS analysis revealed the important roles of taurine and glutamine metabolism in response to environmental salinity changes in gills of rainbow trout (Oncorhynchus mykiss).

Recently, the frequent salinity fluctuation has become a growing threat to fishes. However, the dynamic patterns of gene expression in response to salinity changes remain largely unexplored. In the present study, 18 RNA-Seq datasets were generated from gills of rainbow trout at different salinities, including 0 ‰, 6 ‰, 12 ‰, 18 ‰, 24 ‰ and 30 ‰. Based on the strict thresholds, we have identified 63, 1411, 2096, 1031 and 1041 differentially expressed genes in gills of rainbow trout through pairwise comparisons. Additionally, weighted gene co-expression network analysis was performed to construct 18 independent modules with distinct expression patterns. Of them, green and tan modules were found to be tightly related to salinity changes, several hub genes of which are known as the important regulators in taurine and glutamine metabolism. To further investigate their potential roles in response to salinity changes, taurine, glutamine, and their metabolism-related glutamic acid and α-ketoglutaric acid were accurately quantitated using liquid chromatography-tandem mass spectrometry analysis. Results clearly showed that their concentrations were closely associated with salinity changes. These findings suggested that taurine and glutamine play important roles in response to salinity changes in gills of rainbow trout, providing new insights into the molecular mechanism of fishes in salinity adaptation.

[Stretched-exponential and mono-exponential diffusion-weighted imaging for assessing the aggressiveness of prostate cancer: A histogram analysis].

OBJECTIVE: To assess the value of stretched-exponential and mono-exponential diffusion-weighted imaging (DWI) in predicting the aggressiveness of PCa. METHODS: This retrospective study included 36 cases of PCa with 48 lesions in the peripheral zone diagnosed by DWI with b-values of 0, 500, 1000, and 2000 s/mm2. We reconstructed the apparent diffusion coefficient (ADC), distributed diffusion coefficient (DDC) and α maps on the post-processing workstation, performed a histogram analysis on the largest slice of PCa on T2WI and Spearman's rank-order analysis on the correlation of the histogram variables with Gleason grade grouping (GG). Then, we assessed the values of the histogram variables in differentiating low-grade from high-grade PCa using the receiver operating characteristic (ROC) curve. RESULTS: The percentile and mean ADCs and DDCs were correlated with GG (ρ: 0.392－0.641) but not the α value, skewnesses and kurtosises (ρ: 0.055－0.266). High-grade PCa exhibited significantly lower 10th-, 25th-, 50th- and 75th-percentile and mean ADCs (490 ± 141, 591 ± 137, 695 ± 137, 781 ± 139 and 888 ± 135 mm2/s) and DDCs (420 ± 146, 534 ± 167, 666 ± 182, 787 ± 190 and 912 ± 175 mm2/s) than low-grade PCa (ADCs: 636 ± 74, 727 ± 86, 825 ± 85, 907 ± 85 and 975 ± 117 mm2/s; DDCs: 542 ± 80, 666 ± 93, 806 ± 108, 910 ± 110 and 1023 ± 105 mm2/s), but there were no statistically significant differences between low- and high-grade PCa in the α value (0.67 ± 0.042 vs 0.64 ± 0.036), kurtosises (ADC 0.105 vs 0.078; DDC －0.027 vs －0.401) or skewnesses (ADC －0.042 vs 0.067; DDC －0.058 vs 0.162). Both 10th-percentile ADCs and DDCs showed a higher efficiency than the mean ones in differentiating high- from low-grade PCa, though with no statistically significant difference (P > 0.05). CONCLUSIONS: Histogram variables DDCs and ADCs, rather than the α value, can be used to predict the aggressiveness of PCa, even more efficiently at the 10th percentile than on the mean.