Swertisin an Anti-Diabetic Compound Facilitate Islet Neogenesis from Pancreatic Stem/Progenitor Cells via p-38 MAP Kinase-SMAD Pathway: An In-Vitro and In-Vivo Study
Bibliographic record
Abstract
Transplanting islets serves best option for restoring lost beta cell mass and function. Small bio-chemical agents do have the potential to generate new islets mass, however lack of understanding about mechanistic action of these small molecules eventually restricts their use in cell-based therapies for diabetes. We recently reported "Swertisin" as a novel islet differentiation inducer, generating new beta cells mass more effectively. Henceforth, in the present study we attempted to investigate the molecular signals that Swertisin generate for promoting differentiation of pancreatic progenitors into islet cells. To begin with, both human pancreatic progenitors (PANC-1 cells) and primary cultured mouse intra-islet progenitor cells (mIPC) were used and tested for Swertisin induced islet neogenesis mechanism, by monitoring immunoblot profile of key transcription factors in time dependent manner. We observed Swertisin follow Activin-A mediated MEPK-TKK pathway involving role of p38 MAPK via activating Neurogenin-3 (Ngn-3) and Smad Proteins cascade. This MAP Kinase intervention in differentiation of cells was confirmed using strong pharmacological inhibitor of p38 MAPK (SB203580), which effectively abrogated this process. We further confirmed this mechanism in-vivo in partial pancreatectomised (PPx) mice model, where we could show Swertisin exerted potential increase in insulin transcript levels with persistent down-regulation of progenitor markers like Nestin, Ngn-3 and Pancreatic Duodenal Homeobox Gene-1 (PDX-1) expression, within three days post PPx. With detailed molecular investigations here in, we first time report the molecular mode of action of Swertisin for islet neogenesis mediated through MAP Kinase (MEPK-TKK) pathway involving Ngn-3 and Smad transcriptional regulation. These findings held importance for developing Swertisin as potent pharmacological drug candidate for effective and endogenous differentiation of islets in cell based therapy for diabetes.
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 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".