Local administration has many advantages for treating diseases. However, the surface mucus layer becomes a major obstacle that easily traps and fast removes local administrated drugs and genes in mucosal tissues. Fortunately, the rapidly developing nanocarriers with special physical and chemical properties may help to refine the treatment of mucosal tissues via delivering drugs and genes to the target tissue, and prolong the drug action time. Therefore, this review focuses on the strategies to apply different nanocarriers for drug-delivery in mucosal tissues, including mucoadhesive and mucus-penetrating types. Delivering drugs and genes to anatomical sites with high mucus turnover becomes more feasible and effective, and maintains sufficient local drug concentration to improve treatment efficacy.
The Sox family plays essential roles as transcription factors in vertebrates; however, little is known about the Sox family in Lutraria sieboldii. L. sieboldii are pleasant to eat with a short growth cycle and have become one of the best bottom-seeded enrichment species in Guang Xi. In this study, Sox2 (named LsSox2) and Sox9 (named LsSox9) from L. sieboldii were cloned, and their expression patterns were analyzed. The length of the LsSox2 gene coding sequence was 1011 bp, encoding 336 amino acids, and LsSox9 was 1449 bp, encoding 482 amino acids. LsSox2 had its highest expression levels in the ovary, which were 356 times those in testis, whereas LsSox9 presented higher expression in testis, which was 6 times more highly expressed than in the ovary. LsSox2 exhibited the highest expression during the morula stage, which was 20 times that of the D-shaped larvae or zygote. LsSox9 exhibited two expression peaks, one at the four-cell stage and the other at the trochophore stage, while the lowest expression was in the zygote. LsSox9 was 73 times more highly expressed in the four-cell stage than in the zygote stage. During gonadal development, LsSox2 presented the highest expression in the mature ovary, which was 756 times more highly expressed than in mature testis. LsSox9 presented higher expression in testis at the emission stage which was 6 times more highly expressed than in the ovary. These results indicate that LsSox2 and LsSox9 may play important roles in embryonic and gonadal development.
In recent years, with the increasing frequency of international exchanges, people have gradually realized that language is a tool of communication and communication, and language learning should attach importance to oral teaching. However, in traditional classrooms, one of the problems faced by oral teaching is the mismatch of the teacher-student ratio: a teacher has to deal with dozens of students, one-on-one oral teaching and pronunciation guidance is impossible, and it is also affected by the teachers and the environment constraints. Therefore, the research on how to efficiently automate pronunciation training is becoming more and more popular. Many phonemes in English have different facial visual features, especially vowels. Almost all of them can be distinguished by the roundness and tightness of the lips in appearance. In order to give full play to the role of lip features in oral pronunciation error detection, this paper proposes a multimodal feature fusion model based on lip angle features. The model interpolates the lip features constructed based on the opening and closing angles and combines audio and video in time series. Feature alignment and fusion and feature learning and classification are realized through the two-way LSTM SOFTMAX layer, and finally, end-to-end pronunciation error detection is realized through CTC. It is verified on the GRID audio and video corpus after phoneme conversion and the self-built multimodal test set. The experimental results show that the model has a higher false pronunciation recognition rate than the traditional single-modal acoustic error detection model. The increase in error detection rate is more obvious. Verification by the audio and video corpus with white noise was added, and the proposed model has better noise immunity than the traditional acoustic model.
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