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Record W3195453623 · doi:10.3389/fcell.2021.694276

Activation of Pancreatic Stellate Cells Is Beneficial for Exocrine but Not Endocrine Cell Differentiation in the Developing Human Pancreas

2021· article· en· W3195453623 on OpenAlexafffund
Jinming Li, Bijun Chen, George F. Fellows, Cynthia G. Goodyer, Rennian Wang

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsMcGill UniversityChildren’s Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsBiologyPancreasHepatic stellate cellExtracellular matrixPDX1IsletProgenitor cellMesenchymal stem cellCellular differentiationInternal medicineEndocrinologyCell biologyStem cellMedicineInsulin

Abstract

fetched live from OpenAlex

Pancreatic stellate cells (PaSCs) are non-endocrine, mesenchymal-like cells that reside within the peri-pancreatic tissue of the rodent and human pancreas. PaSCs regulate extracellular matrix (ECM) turnover in maintaining the integrity of pancreatic tissue architecture. Although there is evidence indicating that PaSCs are involved in islet cell survival and function, its role in islet cell differentiation during human pancreatic development remains unclear. The present study examines the expression pattern and functional role of PaSCs in islet cell differentiation of the developing human pancreas from late 1st to 2nd trimester of pregnancy. The presence of PaSCs in human pancreata (8–22 weeks of fetal age) was characterized by ultrastructural, immunohistological, quantitative RT-PCR and western blotting approaches. Using human fetal PaSCs derived from pancreata at 14–16 weeks, freshly isolated human fetal islet-epithelial cell clusters (hIECCs) were co-cultured with active or inactive PaSCs in vitro. Ultrastructural and immunofluorescence analysis demonstrated a population of PaSCs near ducts and newly formed islets that appeared to make complex cell-cell dendritic-like contacts. A small subset of PaSCs co-localized with pancreatic progenitor-associated transcription factors (PDX1, SOX9, and NKX6-1). PaSCs were highly proliferative, with significantly higher mRNA and protein levels of PaSC markers (desmin, αSMA) during the 1st trimester of pregnancy compared to the 2nd trimester. Isolated human fetal PaSCs were identified by expression of stellate cell markers and ECM. Suppression of PaSC activation, using all-trans retinoic acid (ATRA), resulted in reduced PaSC proliferation and ECM proteins. Co-culture of hIECCs, directly on PaSCs or indirectly using Millicell® Inserts or using PaSC-conditioned medium, resulted in a reduction the number of insulin+ cells but a significant increase in the number of amylase+ cells. Suppression of PaSC activation or Notch activity during the co-culture resulted in an increase in beta-cell differentiation. This study determined that PaSCs, abundant during the 1st trimester of pancreatic development but decreased in the 2nd trimester, are located near ductal and islet structures. Direct and indirect co-cultures of hIECCs with PaSCs suggest that activation of PaSCs has opposing effects on beta-cell and exocrine cell differentiation during human fetal pancreas development, and that these effects may be dependent on Notch signaling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.247
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2021
Admission routes2
Has abstractyes

Explore more

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