Establishment of a high-resolution 3D modeling system for studying pancreatic epithelial cell biology in vitro is a research paper published in Molecular Metabolism (2019). On theSindex it has a DataRank of 1.0. It has been cited 28 times, with 20 citing works in its 1-hop citation network.
ObjectiveTranslation of basic research from bench-to-bedside relies on a better understanding of similarities and differences between mouse and human cell biology, tissue formation, and organogenesis. Thus, establishing ex vivo modeling systems of mouse and human pancreas development will help not only to understand evolutionary conserved mechanisms of differentiation and morphogenesis but also to understand pathomechanisms of disease and design strategies for tissue engineering.MethodsHere, we established a simple and reproducible Matrigel-based three-dimensional (3D) cyst culture model system of mouse and human pancreatic progenitors (PPs) to study pancreatic epithelialization and endocrinogenesis ex vivo. In addition, we reanalyzed previously reported single-cell RNA sequencing (scRNA-seq) of mouse and human pancreatic lineages to obtain a comprehensive picture of differential expression of key transcription factors (TFs), cell-cell adhesion molecules and cell polarity components in PPs during endocrinogenesis.ResultsWe generated mouse and human polarized pancreatic epithelial cysts derived from PPs. This system allowed to monitor establishment of pancreatic epithelial polarity and lumen formation in cellular and sub-cellular resolution in a dynamic time-resolved fashion. Furthermore, both mouse and human pancreatic cysts were able to differentiate towards the endocrine fate. This differentiation system together with scRNA-seq analysis revealed how apical-basal polarity and tight and adherens junctions change during endocrine differentiation.ConclusionsWe have established a simple 3D pancreatic cyst culture system that allows to tempo-spatial resolve cellular and subcellular processes on the mechanistical level, which is otherwise not possible in vivo.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.505
From this paper's citation signal
Citation Network Contribution
0.535
From 19 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 49% comes from its base citations and 51% from the citation network (19 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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