Biology subjects

Ni, B. Y. X.

Publications and source records attributed to Ni, B. Y. X..

3 recordsLinked to original sources

bioRxiv2026

Fibroblast signaling influences macrophage-dependent, biomaterial-induced tissue remodeling

The ability to induce tissue regeneration on demand using biomaterials remains a major goal in biomedical research, yet significant challenges persist. Among the most advanced biomaterial models, the nanofiber-hydrogel composite has demonstrated a striking ability to induce soft adipose tissue remodeling at the injection site without incorporating exogenous biological cues.1,2 However, the underlying mechanisms that drive such a tissue response remain unclear. Here, we show that biomaterial-induced tissue remodeling is driven by sustained and controlled inflammation mediated by macrophages in strong communication with fibroblasts. Notably, both pro-inflammatory and anti-inflammatory signals remained elevated during this process in the long-term, challenging the prevailing notion that inflammation opposes remodeling. Using macrophage depletion in mice, we demonstrate that macrophages are essential for this process. Single-cell RNA sequencing further revealed robust fibroblast-to-macrophage signaling, contrasting with the conventional macrophage-to-fibroblast paradigm, and identified unique Spp1 macrophages and Ctla2a fibroblasts within the remodeling niche. These findings provide a comprehensive view of the immune landscape in biomaterial-induced tissue remodeling, highlighting key cellular interactions, prolonged kinetics, and unexpected signaling pathways. By defining key targets and fundamental principles, this work has broad implications for advancing biomaterial-induced tissue regeneration.

bioengineering↗

bioRxiv2026

Foundation cell segmentation models performance on live microscopy and spatial-omics data

Accurate cell segmentation is an essential step for quantitative analysis of biological imaging data. Recent advances in deep learning have led to the development of generalist segmentation models that perform robustly across multiple imaging modalities, including label-free phase contrast, fluorescence cell culture, and multiplexed fluorescence tissue imaging. However, systematic comparisons of these models at the level of downstream biological analysis remain limited. To address this gap, we evaluated several recent segmentation models, including Cellpose cyto3, Cellpose-SAM, {micro}SAM, and CellSAM, on phase contrast and fluorescence cell culture images. In addition, Mesmer and InstanSeg were included for benchmarking on multiplexed fluorescence tissue images generated using CO-Detection by IndEXing (CODEX). We found that Cellpose-SAM achieved strong performance on phase contrast images, while SAM-based models consistently performed well on fluorescence cell culture data. In contrast, no single model consistently outperformed others on CODEX datasets. Instead, each model exhibited distinct strengths and limitations, which led to differences in downstream analyses, including clustering and cell type identification. Together, our study emphasizes the importance of selecting segmentation models based on dataset characteristics and analytical goals, rather than relying on a single universal approach.

bioinformatics↗

bioRxiv2025

mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite generates a local immunostimulatory niche for cancer immunotherapy

Hydrogel materials have emerged as versatile platforms for various biomedical applications. Notably, the engineered nanofiber-hydrogel composite (NHC) has proven effective in mimicking the soft tissue extracellular matrix, facilitating substantial recruitment of host immune cells and the formation of a local immunostimulatory microenvironment. Leveraging this feature, here we report an mRNA lipid nanoparticle (LNP)-incorporated NHC microgel matrix, termed LiNx, by incorporating LNPs loaded with mRNA encoding tumour antigens. Harnessing the potent transfection efficiency of LNPs in antigen-presenting cells (APCs), LiNx demonstrates remarkable immune cell recruitment, antigen expression and presentation, and cellular interaction. These attributes collectively create an immunostimulating milieu and yield a potent immune response achievable with a single dose, comparable to the conventional three-dose LNP immunization regimen. Further investigations reveal that the LiNx not only generates heightened Th1 and Th2 responses but also elicits a distinctive Type 17 T helper cell-mediated response pivotal for bolstering antitumour efficacy. Our findings elucidate the mechanism underlying LiNxs role in potentiating antigen-specific immune responses, presenting a new strategy for cancer immunotherapy.

bioengineering↗