Role of poly(ADP-ribose) polymerase-1 in regulating human islet cell differentiation
Bibliographic record
Abstract
Poly(ADP-ribose) polymerase-1 (PARP1), a fundamental DNA repair enzyme, is known to regulate β cell death, replication, and insulin secretion. PARP1 knockout (KO) mice are resistant to diabetes, while PARP1 overactivation contributes to β cell death. Additionally, PARP1 inhibition (PARPi) improves diabetes complications in patients with type-2 diabetes. Despite these beneficial effects, the use of PARP1 modulating agents in diabetes treatment is largely neglected, primarily due to the poorly studied mechanistic action of PARP1 catalytic function in human β cell development. In the present study, we evaluated PARP1 regulatory action in human β cell differentiation using the human pancreatic progenitor cell line, PANC-1. We surveyed islet census and histology from PARP1 wild-type versus KO mice pancreas in a head-to-head comparison with PARP1 regulatory action for in-vitro β cell differentiation following either PARP1 depletion or its pharmacological inhibition in PANC-1-differentiated islet cells. shRNA mediated PARP1 depleted (SiP) and shRNA control (U6) PANC-1 cells were differentiated into islet-like clusters using established protocols. We observed complete abrogation of new β cell formation with absolute PARP1 depletion while its inhibition using the potent inhibitor, PJ34, promoted the endocrine β cell differentiation and maturation. Immunohistochemistry and immunoblotting for key endocrine differentiation players along with β cell maturation markers highlighted the potential regulatory action of PARP1 and augmented β cell differentiation due to direct interaction of unmodified PARP1 protein elicited p38 MAPK phosphorylation and Neurogenin-3 (Ngn3) re-activation. In summary, our study suggests that PARP1 is required for the proper development and differentiation of human islets. Selective inhibition with PARPi can be an advantage in pushing more insulin-producing cells under pathological conditions and delivers a potential for pilot clinical testing for β cell replacement cell therapies for diabetes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".