Artificial intelligence technique in detection of early esophageal cancer.

Due to the rapid progression and poor prognosis of esophageal cancer (EC), the early detection and diagnosis of early EC are of great value for the prognosis improvement of patients. However, the endoscopic detection of early EC, especially Barrett's dysplasia or squamous epithelial dysplasia, is difficult. Therefore, the requirement for more efficient methods of detection and characterization of early EC has led to intensive research in the field of artificial intelligence (AI). Deep learning (DL) has brought about breakthroughs in processing images, videos, and other aspects, whereas convolutional neural networks (CNNs) have shone lights on detection of endoscopic images and videos. Many studies on CNNs in endoscopic analysis of early EC demonstrate excellent performance including sensitivity and specificity and progress gradually from in vitro image analysis for classification to real-time detection of early esophageal neoplasia. When AI technique comes to the pathological diagnosis, borderline lesions that are difficult to determine may become easier than before. In gene diagnosis, due to the lack of tissue specificity of gene diagnostic markers, they can only be used as supplementary measures at present. In predicting the risk of cancer, there is still a lack of prospective clinical research to confirm the accuracy of the risk stratification model.

Immunomodulatory therapies for acute pancreatitis.

It is currently difficult for conventional treatments of acute pancreatitis (AP), which primarily consist of anti-inflammatory therapies, to prevent the progression of AP or to improve its outcome. This may be because the occurrence and progression of AP, which involves various inflammatory cells and cytokines, includes a series of complex immune events. Considering the complex immune system alterations during the course of AP, it is necessary to monitor the indicators related to immune cells and inflammatory mediators and to develop more individualized interventions for AP patients using immunomodulatory therapy. This review discusses the recent advances in immunomodulatory therapies. It has been suggested that overactive inflammatory responses should be inhibited and excessive immunosuppression should be avoided in the early stages of AP. The optimal duration of anti-inflammatory therapy may be shorter than previously expected (< 24 h), and appropriate immunostimulatory therapies should be administered during the period from the 3(rd) d to the 14(th) d in the course of AP. A combination therapy of anti-inflammatory and immune-stimulating drugs would hopefully constitute an alternative to anti-inflammatory drug monotherapy. Additionally, the detection of the genotypes of critical inflammatory mediators may be useful for screening populations of AP patients at high risk of severe infections to enable the administration of early interventions to improve their prognosis.

[Study on medicinal plant allelopathy and soil sickness based on ecological niche].

Based on the conception and theory of ecological niche, authors analyzed the cause of the allelopathy and soil sickness of medicinal plants and the relationship between them. Methods to resolve problems in the cultivating medicinal plant was found, that is to construct the ecological niche based on allelopathy theory and avoid the soil sickness.