Fully connected-convolutional (FC-CNN) neural network based on hyperspectral images for rapid identification of P. ginseng growth years.

P. ginseng is a precious traditional Chinese functional food, which is used for both medicinal and food purposes, and has various effects such as immunomodulation, anti-tumor and anti-oxidation. The growth year of P. ginseng has an important impact on its medicinal and economic values. Fast and nondestructive identification of the growth year of P. ginseng is crucial for its quality evaluation. In this paper, we propose a FC-CNN network that incorporates spectral and spatial features of hyperspectral images to characterize P. ginseng from different growth years. The importance ranking of the spectra was obtained using the random forest method for optimal band selection. Based on the hyperspectral reflectance data of P. ginseng after radiometric calibration and the images of the best five VNIR bands and five SWIR bands selected, the year-by-year identification of P. ginseng age and its identification experiments for food and medicinal purposes were conducted, and the FC-CNN network and its FCNN and CNN branch networks were tested and compared in terms of their effectiveness in the identification of P. ginseng growth years. It has been experimentally verified that the best year-by-year recognition was achieved by utilizing images from five visible and near-infrared important bands and all spectral curves, and the recognition accuracy of food and medicinal use reached 100%. The FC-CNN network is significantly better than its branching model in the effect of edible and medicinal identification. The results show that for P. ginseng growth year identification, VNIR images have much more useful information than SWIR images. Meanwhile, the FC-CNN network utilizing the spectral and spatial features of hyperspectral images is an effective method for the identification of P. ginseng growth year.

Antithrombin III activity is associated with prognosis, infection, and inflammation in patients with hepatitis B virus-related acute-on-chronic liver failure.

OBJECTIVE: Patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) are characterized by severe liver function impairment, coagulation disorder, and multiple organ function impairment. The aim of this study was to explore the predictive value of antithrombin Ⅲ activity to the prognosis of HBV-ACLF patients. METHODS: A total of 186 HBV-ACLF patients were included in the analysis, and the baseline clinical data of patients were recorded to analyze the risk factors affecting the 30-day survival outcome of patients. Bacterial infection, sepsis, and hepatic encephalopathy were observed in ACLF patients. Antithrombin Ⅲ activity and serum cytokine levels were determined. RESULTS: The antithrombin Ⅲ activity of ACLF patients in the death group was significantly lower than that in the survival group, and antithrombin Ⅲ activity was independent factors affecting the 30-day outcome. The areas under the receiver operation characteristic (ROC) curve of antithrombin Ⅲ activity to predict the 30-day mortality of ACLF was 0.799. Survival analysis showed that the mortality of patients with antithrombin Ⅲ activity less than 13% was significantly increased. Patients with bacterial infection and sepsis had lower antithrombin Ⅲ activity than those without infection. Antithrombin Ⅲ activity was positively correlated with platelet count, fibrinogen, interferon (IFN)-γ, interleukin (IL)-13, IL-1ß, IL-4, IL-6, tumor necrosis factor-α, IL-23, IL-27, and IFN-α, but negatively correlated with C-reactive protein, D dimer, total bilirubin, and creatinine levels. CONCLUSION: As a natural anticoagulant, antithrombin Ⅲ can be regarded as a marker of inflammation and infection in patients with HBV-ACLF, and as a predictor of survival outcome in patients with ACLF.