Arbuscular mycorrhizal fungi enhanced cadmium uptake in Photinia frase through altering root transcriptomes and root-associated microbial communities / 生物工程学报

As a non-essential metal, cadmium (Cd) pollution poses severe threats to plant growth, environment, and human health. Phytoextraction using nursery stocks prior to their transplantation is a potential useful approach for bioremediation of Cd contaminated soil. A greenhouse pot experiment was performed to investigate the growth, Cd accumulation, profiles of transcriptome as well as root-associated microbiomes of Photinia frase in Cd-added soil, upon inoculation of two types of arbuscular mycorrhizal fungi (AMF) Sieverdingia tortuosa and Funneliformis mosseae. Compared with the control, inoculation of F. mosseae increased Cd concentrations in root, stem and leaf by 57.2%, 44.1% and 71.1%, respectively, contributing to a total Cd content of 182 μg/plant. KEGG pathway analysis revealed that hundreds of genes involved in 'Mitogen-activated protein kinase (MAPK) signaling pathway', 'plant hormone signal transduction', 'biosynthesis of secondary metabolites' and 'glycolysis/gluconeogenesis' were enriched upon inoculation of F. mosseae. The relative abundance of Acidobacteria was increased upon inoculation of S. tortuosa, while Chloroflexi and Patescibacteria were increased upon inoculation of F. mosseae, and the abundance of Glomerales increased from 23.0% to above 70%. Correlation analysis indicated that ethylene-responsive transcription factor, alpha-aminoadipic semialdehyde synthase, isoamylase and agmatine deiminase related genes were negatively associated with the relative abundance of Glomerales operational taxonomic units (OTUs) upon inoculation of F. mosseae. In addition, plant cysteine oxidase, heat shock protein, cinnamoyl-CoA reductase and abscisic acid receptor related genes were positively associated with the relative abundance of Patescibacteria OTUs upon inoculation of F. mosseae. These finding suggested that AMF can enhance P. frase Cd uptake by modulating plant gene expression and altering the structure of the soil microbial community. This study provides a theoretical basis for better understanding the relationship between root-associated microbiomes and root transcriptomes of P. frase, from which a cost-effective and environment-friendly strategy for phytoextraction of Cd in Cd-polluted soil might be developed.

Human activity recognition based on the inertial information and convolutional neural network / 生物医学工程学杂志

With the rapid improvement of the perception and computing capacity of mobile devices such as smart phones, human activity recognition using mobile devices as the carrier has been a new research hot-spot. The inertial information collected by the acceleration sensor in the smart mobile device is used for human activity recognition. Compared with the common computer vision recognition, it has the following advantages: convenience, low cost, and better reflection of the essence of human motion. Based on the WISDM data set collected by smart phones, the inertial navigation information and the deep learning algorithm-convolutional neural network (CNN) were adopted to build a human activity recognition model in this paper. The K nearest neighbor algorithm (KNN) and the random forest algorithm were compared with the CNN network in the recognition accuracy to evaluate the performance of the CNN network. The classification accuracy of CNN model reached 92.73%, which was much higher than KNN and random forest. Experimental results show that the CNN algorithm model can achieve more accurate human activity recognition and has broad application prospects in predicting and promoting human health.