Abstract 331: Conjugation of Graphene Oxide With Chitosan Improves Survival of Transplanted Allogeneic Stem Cells and Preserves Ventricular Function in the Infarcted Heart
Bibliographic record
Abstract
Allogeneic mesenchymal stem cells (MSCs) derived from bone marrow are considered to ideal candidate cell type for myocardial repair after a cardiac injury. However, recent reviews of allogeneic MSCs based clinical trials reported that transplanted cells were not able to survive for long term in the heart. Therefore, strategies to improve survival of transplanted cells would preserve the benefits of allogeneic MSCs therapy for heart repair. Recently, graphene oxide (GO) based biomaterials are being widely investigated for their ability to improve survival of transplanted MSCs in the heart. However, the presence of reactive oxygen functional groups (-OH, -COOH) in the structure of GO increases oxidative stress and activate cell death pathways, which impairs the benefits of GO based biomaterials. Therefore, to improve benefits of GO for stem cell delivery, we synthesized a thermosensitive hydrogel by conjugating GO with chitosan (CS). Our fourier transformed infrared spectrum (FTIR) analysis revealed an interaction between oxygen functional groups of GO and amino (-NH2) groups of chitosan. Our data demonstrate that CS masked the reactive functional groups of GO and prevented GO mediated ROS induction. This novel chitosan-graphene oxide (CS-GO) composite exhibited optimal porosity for cell conjugation and retention. Furthermore, CS-GO biomaterial was cyto-compatible as there was no cytotoxicity caused by CS-GO to MSCs. Furthermore, CS-GO also prevented hypoxia induced apoptosis of MSCs. We employed this novel biomaterial to deliver allogeneic MSCs to the infarcted heart in a rat model of myocardial infarction. After 5 weeks of cell transplantation, there was a significant improvement in the survival of implanted MSCs and cardiac function in CS-GO group. Therefore, conjugation of GO with chitosan prevented GO mediated ROS generation and cell death. Also, CS-GO mediated delivery of allogeneic MSCs to infarcted heart improved the survival of transplanted cells and preserved cardiac function.
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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 | 0.001 |
| 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".