Postoperative accurate pain assessment of children and artificial intelligence: A medical hypothesis and planned study.

Although the pediatric perioperative pain management has been improved in recent years, the valid and reliable pain assessment tool in perioperative period of children remains a challenging task. Pediatric perioperative pain management is intractable not only because children cannot express their emotions accurately and objectively due to their inability to describe physiological characteristics of feeling which are different from those of adults, but also because there is a lack of effective and specific assessment tool for children. In addition, exposure to repeated painful stimuli early in life is known to have short and long-term adverse sequelae. The short-term sequelae can induce a series of neurological, endocrine, cardiovascular system stress related to psychological trauma, while long-term sequelae may alter brain maturation process, which can lead to impair neurodevelopmental, behavioral, and cognitive function. Children's facial expressions largely reflect the degree of pain, which has led to the developing of a number of pain scoring tools that will help improve the quality of pain management in children if they are continually studied in depth. The artificial intelligence (AI) technology represented by machine learning has reached an unprecedented level in image processing of deep facial models through deep convolutional neural networks, which can effectively identify and systematically analyze various subtle features of children's facial expressions. Based on the construction of a large database of images of facial expressions in children with perioperative pain, this study proposes to develop and apply automatic facial pain expression recognition software using AI technology. The study aims to improve the postoperative pain management for pediatric population and the short-term and long-term quality of life for pediatric patients after operational event.

Pseudolarix acid B, a new tubulin-binding agent, inhibits angiogenesis by interacting with a novel binding site on tubulin.

Tubulin-binding agents have received considerable interest as potential tumor-selective angiogenesis-targeting drugs. Herein, we report that pseudolarix acid B (PAB), isolated from the traditional Chinese medicinal plant Pseudolarix kaempferi Gordon, is a tubulin-binding agent. We further demonstrate that PAB significantly and dose-dependently inhibits proliferation, migration, and tube formation by human microvessel enthothelial cells. It is noteworthy that PAB eliminated newly formed endothelial tubes and microvessels both in vitro and in vivo. In addition, PAB dramatically arrested the cell cycle at G2/M phase. PAB also induced endothelial cell retraction, intercellular gap formation, and promoted actin stress fiber formation in conjunction with disruption of the tubulin and actin cytoskeletons. All of these effects occurred at noncytotoxic concentrations of PAB. We found that these effects of PAB are attributable to depolymerization of tubulin by direct interaction with a distinct binding site on tubulin compared with those of colchicine and vinblastine. Taken together, these findings show that PAB is a candidate antiangiogenic agent for use in cancer therapy, and they provide proof of principle for targeting this novel binding site on tubulin as a new strategy for treating cancer.