Automatically Predicting Material Properties with Microscopic Images: Polymer Miscibility as an Example.

Many material properties are manifested in the morphological appearance and characterized using microscopic images, such as scanning electron microscopy (SEM). Polymer miscibility is a key physical quantity of polymer materials and is commonly and intuitively judged using SEM images. However, human observation and judgment of the images is time-consuming, labor-intensive, and hard to be quantified. Computer image recognition with machine learning methods can make up for the defects of artificial judging, giving accurate and quantitative judgment. We achieve automatic miscibility recognition utilizing a convolutional neural network and transfer learning methods, and the model obtains up to 94% accuracy. We also put forward a quantitative criterion for polymer miscibility with this model. The proposed method can be widely applied to the quantitative characterization of the microstructure and properties of various materials.

Negative feedback and modern anti-cancer strategies targeting the ER stress response.

Endoplasmic reticulum (ER) stress is a cell state in which misfolded or unfolded proteins are aberrantly accumulated in the ER. ER stress induces an evolutionarily conserved adaptive response, named the ER stress response, that deploys a self-regulated machinery to maintain cellular proteostasis. However, compared to its well-established canonical activation mechanism, the negative feedback mechanisms regulating the ER stress response remain unclear and no accepted methods or markers have been established. Several studies have documented that both endogenous and exogenous insults can induce ER stress in cancer. Based on this evidence, small molecule inhibitors targeting ER stress response have been designed to kill cancer cells, with some of them showing excellent curative effects. Here, we review recent advances in our understanding of negative feedback of the ER stress response and compare the markers used to date. We also summarize therapeutic inhibitors targeting ER stress response and highlight the promises and challenges ahead.