The role of assembly parameters on polyplex poly(beta-amino ester) nanoparticle transfections.

Intracellular delivery of nucleic acids to mammalian cells using polyplex nanoparticles (NPs) remains a challenge both in vitro and in vivo, with transfections often suffering from variable efficacy. To improve reproducibility and efficacy of transfections in vitro using a next-generation polyplex transfection material poly(beta-amino ester)s (PBAEs), the influence of multiple variables in the preparation of these NPs on their transfection efficacy was explored. The results indicate that even though PBAE/pDNA polyplex NPs are formed by the self-assembly of polyelectrolytes, their transfection is not affected by the manner in which the components are mixed, facilitating self-assembly in a single step, but timing for self-assembly of 5-20 min is optimal. In addition, even though the biomaterials are biodegradable in water, their efficacy is not affected by up to eight freeze-thaw cycles of the polymer. It was found that there is a greater stability of nucleic acid-complexed polymer as a polyplex nanoparticle compared with free polymer. Finally, by exploring multiple buffer systems, it was identified that utilization of divalent cation magnesium or calcium acetate buffers at pH 5.0 is optimal for transfection using these polymeric materials, boosting transfection several folds compared with monovalent cations. Together, these results can improve the reproducibility and efficacy of PBAE and similar polyplex nanoparticle transfections and improve the robustness of using these biomaterials for bioengineering and biotechnology applications.

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies.

Cellular senescence is a state of permanent growth arrest that plays an important role in wound healing, tissue fibrosis, and tumor suppression. Despite senescent cells' (SnCs) pathological role and therapeutic interest, their phenotype in vivo remains poorly defined. Here, we developed an in vivo-derived senescence signature (SenSig) using a foreign body response-driven fibrosis model in a p16-CreERT2;Ai14 reporter mouse. We identified pericytes and "cartilage-like" fibroblasts as senescent and defined cell type-specific senescence-associated secretory phenotypes (SASPs). Transfer learning and senescence scoring identified these two SnC populations along with endothelial and epithelial SnCs in new and publicly available murine and human data single-cell RNA sequencing (scRNAseq) datasets from diverse pathologies. Signaling analysis uncovered crosstalk between SnCs and myeloid cells via an IL34-CSF1R-TGFßR signaling axis, contributing to tissue balance of vascularization and matrix production. Overall, our study provides a senescence signature and a computational approach that may be broadly applied to identify SnC transcriptional profiles and SASP factors in wound healing, aging, and other pathologies.