Synaptotagmin-13 orchestrates pancreatic endocrine cell egression and islet morphogenesis
Synaptotagmin-13 orchestrates pancreatic endocrine cell egression and islet morphogenesis is a research paper published in Nature Communications (2022). On theSindex it has a DataRank of 0.708. It has been cited 25 times, with 19 citing works in its 1-hop citation network.
Abstract
During pancreas development endocrine cells leave the ductal epithelium to form the islets of Langerhans, but the morphogenetic mechanisms are incompletely understood. Here, we identify the Ca2+-independent atypical Synaptotagmin-13 (Syt13) as a key regulator of endocrine cell egression and islet formation. We detect specific upregulation of the Syt13 gene and encoded protein in endocrine precursors and the respective lineage during islet formation. The Syt13 protein is localized to the apical membrane of endocrine precursors and to the front domain of egressing endocrine cells, marking a previously unidentified apical-basal to front-rear repolarization during endocrine precursor cell egression. Knockout of Syt13 impairs endocrine cell egression and skews the α-to-β-cell ratio. Mechanistically, Syt13 is a vesicle trafficking protein, transported via the microtubule cytoskeleton, and interacts with phosphatidylinositol phospholipids for polarized localization. By internalizing a subset of plasma membrane proteins at the front domain, including α6β4 integrins, Syt13 modulates cell-matrix adhesion and allows efficient endocrine cell egression. Altogether, these findings uncover an unexpected role for Syt13 as a morphogenetic driver of endocrinogenesis and islet formation.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
0.489
From this paper's citation signal
Citation Network Contribution
0.219
From 12 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
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Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 69% comes from its base citations and 31% from the citation network (12 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
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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