Indirect co‐culture of islet cells in 3D biocompatible collagen/laminin scaffold with angiomiRs transfected mesenchymal stem cells
Bibliographic record
Abstract
Abstract Diabetes is an autoimmune disease in which the pancreatic islets produce insufficient insulin. One of the treatment strategies is islet isolation, which may damage these cells as they lack vasculature. Biocompatible scaffolds are one of the efficient techniques for dealing with this issue. The current study is aimed to determine the effect of transfected BM‐MSCS with angiomiR‐126 and ‐210 on the survival and functionality of islets loaded into a 3D scaffold via laminin (LMN). AngiomiRs/Poly Ethylenimine polyplexes were transfected into bone marrow‐mesenchymal stem cells (BM‐MSCs), followed by 3‐day indirect co‐culturing with islets laden in collagen (Col)‐based hydrogel scaffolds containing LMN. Islet proliferation and viability were significantly increased in LMN‐containing scaffolds, particularly in the miRNA‐126 treated group. Insulin gene expression was superior in Col scaffolds, especially, in the BM‐MSCs/miRNA‐126 treated group. VEGF was upregulated in the LMN‐containing scaffolds in both miRNA‐treated groups, specifically in the miRNA‐210, leading to VEGF secretion. MiRNAs' target genes showed no downregulation in LMN‐free scaffolds; while a drastic downregulation was seen in the LMN‐containing scaffolds. The highest insulin secretion was recorded in the Oxidized dextran (Odex)/Col LMN+ group with miRNA‐126. LMN‐containing biocompatible scaffolds, once combined with angiomiRs and their downstream effectors, promote islets survival and restore function, leading to enhanced angiogenesis and glycemic status.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".