Anti-ageing glycoprotein promotes long-term survival of transplanted neurosensory precursor cells
Why this work is in the frame
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Bibliographic record
Abstract
Cell therapy, to replace lost tissue, is a promising approach for the treatment of various neurodegenerative diseases. Many studies suggest, however, that the percentage of transplanted cells that survive and undergo functional integration remains low as a result of immune rejection, suboptimal precursor cell type, trauma during cell transplantation, toxic compounds released by dying tissues or nutritional deficiencies. We recently developed an ex vivo system to facilitate identification of factors contributing to the death of transplanted neuronal (photoreceptor) cells and compounds that block these toxic effects. In this system, photoreceptor precursor cells (PPCs) are sandwiched between a neurosensory retinal explant and retinal pigment epithelium derived from human embryonic stem cells. Explant medium was collected to identify toxic components and PPC survival was assessed by flow cytometry. We also assessed the potential for AAGP™, a cryopreservative molecule, to improve PPC survival. We identified elevated prostaglandin E2 (PGE2) in the explant medium and demonstrated that AAGP™ reduced PGE2 levels by 2.6-fold. A pro-inflammatory stress assay suggested that this may result from AAGP™ inhibition of cyclo-oxygenase-2 (COX-2) expression. We confirmed that PGE2 reduced the viability of cultured PPCs by 44% and found that the survival rate of PPCs pretreated with AAGP™ was 2.8-fold higher than in untreated PPCs. These data suggest that PGE2 release from necrotic tissue may be one factor that reduces the survival of transplanted precursor cells and that the pro-survival molecule AAGP™ may improve long-term transplanted cell viability. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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 it