Alternative means for drug delivery are needed to facilitate drug adherence and administration. Microneedles (MNs) have been previously investigated transdermally for drug delivery. To date, drug loading into MNs has been limited by drug solubility in the polymeric blend. We designed a highly drug-loaded MN patch to deliver macromolecules and applied it to the buccal area, which allows for faster delivery than the skin. We successfully delivered 1-mg payloads of human insulin and human growth hormone to the buccal cavity of swine within 30 s. In addition, we conducted a trial in 100 healthy volunteers to assess potential discomfort associated with MNs when applied in the oral cavity, identifying the hard palate as the preferred application site. We envisage that MN patches applied on buccal surfaces could increase medication adherence and facilitate the painless delivery of biologics and other drugs to many, especially for the pediatric and elderly populations.

SUMMARY The fundamental requirements for regeneration are poorly understood. Planarians can robustly regenerate all tissues after injury, involving stem cells, positional information, and a set of cellular and molecular responses collectively called the “missing tissue” or “regenerative” response. follistatin, which encodes an extracellular Activin inhibitor, is required for the missing tissue response after head amputation and for subsequent regeneration. We found that follistatin is required for the missing tissue response regardless of the wound context, but causes regeneration failure only after head amputation. This head regeneration failure involves follistatin-mediated regulation of Wnt signaling at wounds and is not a consequence of a diminished missing tissue response. All tested contexts of regeneration, including head regeneration, could occur with a defective missing tissue response, but at a slower pace. Our findings suggest that major cellular and molecular programs induced specifically by large injuries function to accelerate regeneration but are dispensable for regeneration itself.

Proper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here, we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis in Drosophila starting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study. With over 44,000 nuclei and 6000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers, in situ hybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for function in vivo.

Proper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis in Drosophila starting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study (Li et al., 2022). With over 44,000 nuclei and 6,000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers, in situ hybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for function in vivo.