Fruit ripening in citrus is not well-understood at the molecular level. Knowledge of the regulatory mechanism of citrus fruit ripening at the post-transcriptional level in particular is lacking. Here, we comparatively analyzed the miRNAs and their target genes in a spontaneous late-ripening mutant, “Fengwan” sweet orange (MT) (Citrus sinensis L. Osbeck), and its wild-type counterpart (“Fengjie 72-1,” WT). Using high-throughput sequencing of small RNAs and RNA degradome tags, we identified 107 known and 21 novel miRNAs, as well as 225 target genes. A total of 24 miRNAs (16 known miRNAs and 8 novel miRNAs) were shown to be differentially expressed between MT and WT. The expression pattern of several key miRNAs and their target genes during citrus fruit development and ripening stages was examined. Csi-miR156k, csi-miR159, and csi-miR166d suppressed specific transcription factors (GAMYBs, SPLs, and ATHBs) that are supposed to be important regulators involved in citrus fruit development and ripening. In the present study, miRNA-mediated silencing of target genes was found under complicated and sensitive regulation in citrus fruit. The identification of miRNAs and their target genes provide new clues for future investigation of mechanisms that regulate citrus fruit ripening.

Metal pollution in drinking water source has been under scrutiny as it seriously affects human health. This work examined 12 dissolved metals in the surface and overlying water of the Xiangjiang River, an important drinking water source in southern China, and characterized their distribution, identified their possible sources, assessed their toxicity load, and determined their potential ecological and health risk. No significant difference was found in the metal concentration between surface and overlying water. The average metal concentration fell in the order of Mg > Mn > Ba > Fe > Zn > As > Sb > Ni > Cd > V > Cr > Co, and all was lower than the safety threshold in the drinking water guideline of China. Anthropogenic activities were found to be the main source of metals from correlation analysis, principal component analysis (PCA), and cluster analysis (CA). According to the total heavy metal toxicity load (HMTL), 98.20%, 71.54%, 68.88%, and 7.97% of As, Cd, Sb, and Mn should be removed from the surface water to ensure safety. Most water samples from the surveyed area were found to have high ecological risk as was measured by the ecological risk index (RI). Health risk assessment showed that children are more susceptible than adults to the non-carcinogenic risk of dissolved metals, and the potential carcinogenic risk (CR) of As and Cd should be addressed. The results provide guidance for controlling the metal pollution of the Xiangjiang River and improving its quality as a drinking water source.

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Artificial intelligence technology has been widely used in various fields, and has become the inevitable trend of social development. Based on artificial intelligence technology, this paper studies the computer-aided translation. Firstly, the concept and development of artificial intelligence technology are briefly introduced. Secondly, the function and application of computer-aided translation under the background of artificial intelligence are analysed. Thirdly, the application of artificial intelligence in computer translation is expounded. Finally, the development of computer-aided translation is prospected.

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With the arrival of the era of big data, the traditional English education has been difficult to adapt to the needs of social development. Under the background of big data, college English teaching needs to keep pace with the times. By analyzing the impact of big data on college English education, this paper discusses the innovative strategies of college English teaching. Only by making full use of high-quality resources in the era of big data, changing teachers’ traditional ideas, using data platform or learning software reasonably, and promoting the integration and development of various teaching modes, can the quality of college English education be improved.

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