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Cell–cell interactions (CCIs) are essential for multicellular organisms to coordinate biological processes and functions. One classical type of CCI interaction is between secreted ligands and cell surface receptors, i.e. ligand-receptor (LR) interactions. With the recent development of single-cell technologies, a large amount of single-cell ribonucleic acid (RNA) sequencing (scRNA-Seq) data has become widely available. This data availability motivated the single-cell-resolution study of CCIs, particularly LR-based CCIs. Dozens of computational methods and tools have been developed to predict CCIs by identifying LR-based CCIs. Many of these tools have been theoretically reviewed. However, there is little study on current LR-based CCI prediction tools regarding their performance and running results on public scRNA-Seq datasets. In this work, to fill this gap, we tested and compared nine of the most recent computational tools for LR-based CCI prediction. We used 15 well-studied scRNA-Seq samples that correspond to approximately 100K single cells under different experimental conditions for testing and comparison. Besides briefing the methodology used in these nine tools, we summarized the similarities and differences of these tools in terms of both LR prediction and CCI inference between cell types. We provided insight into using these tools to make meaningful discoveries in understanding cell communications.

Central nervous system (CNS) injuries are often debilitating, and most currently have no cure. This is due to the formation of a neuroinhibitory microenvironment at injury sites, which includes neuroinflammatory signaling and non‐permissive extracellular matrix (ECM) components. To address this challenge, a viscous interfacial self‐assembly approach, to generate a bioinspired hybrid 3D porous nanoscaffold platform for delivering anti‐inflammatory molecules and establish a favorable 3D‐ECM environment for the effective suppression of the neuroinhibitory microenvironment, is developed. By tailoring the structural and biochemical properties of the 3D porous nanoscaffold, enhanced axonal growth from the dual‐targeting therapeutic strategy in a human induced pluripotent stem cell (hiPSC)‐based in vitro model of neuroinflammation is demonstrated. Moreover, nanoscaffold‐based approaches promote significant axonal growth and functional recovery in vivo in a spinal cord injury model through a unique mechanism of anti‐inflammation‐based fibrotic scar reduction. Given the critical role of neuroinflammation and ECM microenvironments in neuroinhibitory signaling, the developed nanobiomaterial‐based therapeutic intervention may pave a new road for treating CNS injuries.