Self-Healing Conductive Hydrogels with Dynamic Dual Network Structure Accelerate Infected Wound Healing via Photothermal Antimicrobial and Regulating Inflammatory Response.

Wound infections are an escalating clinical challenge with continuous inflammatory response and the threat of drug-resistant bacteria. Herein, a series of self-healing conductive hydrogels were designed based on carboxymethyl chitosan/oxidized sodium alginate/polymerized gallic acid/Fe3+ (CMC/OSA/pGA/Fe3+, COGFe) for promoting infected wound healing. The Schiff base and catechol-Fe3+ chelation in the dynamical dual network structure of the hydrogels endowed dressings with good toughness, conductivity, adhesion, and self-healing properties, thus flexibly adapting to the deformation of skin wounds. In terms of ultraviolet (UV) resistance and scavenging of reactive oxygen species (ROS), the hydrogels significantly reduced oxidative stress at the wound site. Additionally, the hydrogels with photothermal therapy (PTT) achieved a 95% bactericidal rate in 5 min of near-infrared (NIR) light radiation by disrupting the bacterial cell membrane structure through elevated temperature. Meanwhile, the inherent antimicrobial properties of GA could reduce healthy tissue damage caused by excessive heat. The composite hydrogels could effectively promote the proliferation and migration of fibroblasts and possess good biocompatibility and hemostatic effect. In full-thickness infected wound repair experiments in rats, the COGFe5 hydrogel combined with NIR effectively killed bacteria, modulated macrophage polarization (M1 to M2 phenotype) to improve the immune microenvironment of the wound, and shortened the repair time by accelerating the expression of collagen deposition (TGF-ß) and vascular factors (CD31). This combined therapy might provide a prospective strategy for infectious wound treatment.

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins.

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

SORC: an integrated spatial omics resource in cancer.

The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.

ImmReg: the regulon atlas of immune-related pathways across cancer types.

Immune system gene regulation perturbation has been found to be a major cause of the development of various types of cancer. Numbers of mechanisms contribute to gene expression regulation, thus, systematically identification of potential regulons of immune-related pathways is critical to cancer immunotherapy. Here, we comprehensively chart the landscape of transcription factors, microRNAs, RNA binding proteins and long noncoding RNAs regulation in 17 immune-related pathways across 33 cancers. The potential immunology regulons are likely to exhibit higher expressions in immune cells, show expression perturbations in cancer, and are significantly correlated with immune cell infiltrations. We also identify a panel of clinically relevant immunology regulons across cancers. Moreover, the regulon atlas of immune-related pathways helps prioritizing cancer-related genes (i.e. ETV7, miR-146a-5p, ZFP36 and HCP5). We further identified two molecular subtypes of glioma (cold and hot tumour phenotypes), which were characterized by differences in immune cell infiltrations, expression of checkpoints, and prognosis. Finally, we developed a user-friendly resource, ImmReg (http://bio-bigdata.hrbmu.edu.cn/ImmReg/), with multiple modules to visualize, browse, and download immunology regulation. Our study provides a comprehensive landscape of immunology regulons, which will shed light on future development of RNA-based cancer immunotherapies.