Emodin-mediated cross-linking enhancement for extracellular matrix homeostasis.

The extracellular matrix (ECM) is an essential element of mammalian organisms, and its cross-linking formation plays a vital role in ECM development and postnatal homeostasis. Defects in cross-link formation caused by aging, genetic, or environmental factors are known to cause numerous diseases in mammals. To augment the cross-linking formation of ECM, the present study established a ZsGreen reporter system controlled by the promoter of lysyl oxidase-like 1 gene (LOXL1), which serves as both a scaffold element and a cross-linking enzyme in the ECM. By using this system in a drug screen, we identified emodin as a strong enhancer of LOXL1 expression that promoted cross-linking formation of ECM in all the tested systems, including human fibroblast cells, cultured human skin tissues, and animals that received long-term emodin treatment. Collectively, the results suggest that emodin may serve as an effective drug or supplement for ECM homeostasis.

English Text Readability Measurement Based on Convolutional Neural Network: A Hybrid Network Model.

Text readability is very important in meeting people's information needs. With the explosive growth of modern information, the measurement demand of text readability is increasing. In view of the text structure of words, sentences, and texts, a hybrid network model based on convolutional neural network is proposed to measure the readability of English texts. The traditional method of English text readability measurement relies too much on the experience of artificial experts to extract features, which limits its practicability. With the increasing variety and quantity of text readability measurement features to be extracted, it is more and more difficult to extract deep features manually, and it is easy to introduce irrelevant features or redundant features, resulting in the decline of model performance. This paper introduces the concept of hybrid network model in deep learning; constructs a hybrid network model suitable for English text readability measurement by combining convolutional neural network, bidirectional long short-term memory network, and attention mechanism network; and replaces manual automatic feature extraction by machine learning, which greatly improves the measurement efficiency and performance of text readability.