Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network.

Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a new perspective for understanding regulatory relationships in plant life processes. Recently, computational methods based on graph neural networks (GNNs) have been widely employed to predict lncRNA-miRNA interactions (LMIs), which compensate for the inadequacy of biological experiments. However, the low-semantic and noise of graph limit the performance of existing GNN-based methods.

Identification of Drought Stress-Responsive Genes in Rice by Random Walk with Multi-Restart Probability on MultiPlex Biological Networks.

Exploring drought stress-responsive genes in rice is essential for breeding drought-resistant varieties. Rice drought resistance is controlled by multiple genes, and mining drought stress-responsive genes solely based on single omics data lacks stability and accuracy. Multi-omics correlation analysis and biological molecular network analysis provide robust solutions.

Injectable and Sprayable Fluorescent Nanoprobe for Rapid Real-Time Detection of Human Colorectal Tumors.

The development of minimally invasive surgery has greatly advanced precision tumor surgery, but sometime suffers from restricted visualization of the surgical field, especially during the removal of abdominal tumors. A 3-D inspection of tumors could be achieved by intravenously injecting tumor-selective fluorescent probes, whereas most of which are unable to instantly distinguish tumors via in situ spraying, which is urgently needed in the process of surgery in a convenient manner. In this study, this work has designed an injectable and sprayable fluorescent nanoprobe, termed Poly-g-BAT, to realize rapid tumor imaging in freshly dissected human colorectal tumors and animal models.