Abstract 363: Toll-Like Receptor 3 Activation Promotes Efficient Nuclear Reprogramming and Endothelial Differentiation
Bibliographic record
Abstract
Introduction: Stem cell therapy for vascular regeneration has been investigated using embryonic stem cells. We recently generated endothelial cells (ECs) from human induced pluripotent stem cells (hiPSCs) and investigated their potential to promote the perfusion of ischemic tissue in a murine model of peripheral arterial disease (PAD). However, to utilize iPSCs therapeutically, the cells should be generated via non-integrating approaches to avoid integration of foreign DNA into the genome. Objective: The present study highlights underlying mechanisms of reprogramming and investigates the role of novel pathways in enhancing nuclear reprogramming for potential clinical application. Results: Since the initial discovery, different non-integrating approaches have been developed to generate iPSCs. One such approach is to deliver the pluripotent factors (Oct4, Sox2, Klf4 and cMyc) as cell-permeant proteins (CPPs). However, human cells have not been reprogrammed using purified CPPs. In seeking to develop this approach, we discovered a striking difference in the pattern of gene expression induced by viral versus protein-based delivery of the reprogramming factors. This suggested that a signaling pathway required for efficient nuclear reprogramming was activated by the retroviral, but not CPP approach. In both gain- and loss-of function studies, we find that activation of toll-like receptor 3 (TLR3) plays a role in the efficient reprogramming of human cells using viral approaches. Stimulation of TLR3 causes rapid changes in the expression of epigenetic modifiers, with chromatin remodeling and changes in gene expression that favors induction of pluripotency. Importantly, knowing that this pathway is critical, we were able to generate human iPSCs using CPPs by adding a TLR3 agonist (Poly IC) to the reprogramming protocol. Conclusion: Recognition of the role of innate immunity signaling in reprogramming may advance the therapeutic application of iPSCs. We intend to develop an efficient protein-based system to generate EC and determine their therapeutic potential in animal models of PAD. Furthermore, we have discovered an important signaling pathway in reprogramming, which may have implications in cancer biology and regenerative medicine.
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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 | 0.001 | 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 | 0.000 |
| 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".