Endogenic Regulation of Proliferation and Zinc Transporters by Pigment Epithelial Cells Nonvirally Transfected with PEDF
Bibliographic record
Abstract
PURPOSE: Genetic modification of cells before transplantation may allow the delivery of neuroprotective and other functional molecules to patients with neurodegenerative diseases. To avoid complications associated with virally transfected cells, we have explored the use of nonviral methods to insert genetic material into RPE cells. METHODS: After transfection with plasmids encoding different pigment epithelium-derived factor (PEDF) fusion proteins, transfected cells were established and passaged up to 100 times. Gene expression of PEDF, ZnT3, ZIP2, CRALBP, CATD, and ZO-1 was determined by RT-PCR. Secretion dynamics were analyzed using ELISA and a spheroid-based assay was used to confirm the anti-angiogenic activity of the recombinant PEDF. RESULTS: Transfection efficiency reached up to 98.7% with a plasmid encoding PEDF and enhanced green fluorescent protein (EGFP) separately and 87.2% with a plasmid encoding an EGFP-PEDF fusion. Immunoblotting revealed that transfected RPE cells express the appropriate PEDF or EGFP-PEDF. Expression of recombinant PEDF is stable, as shown by its secretion for the 2 years and the 100 passages the cells have been followed. PEDF expression was overexpressed and the transfected cells exhibited increased proliferation, up-regulation of ZnT3 and ZIP2, and inhibited sprouting in human umbilical vein endothelial cell spheroids. CONCLUSIONS: Genetic in vitro modification of pigment epithelial cells using nonviral transfection protocols should improve the potential therapeutic treatment of neurodegenerative diseases by transplantation of genetically modified cells without the disadvantages of virally mediated transfection. Here we have shown that genetically modified RPE cells overexpress a functional human recombinant PEDF, as evidenced by the autogenic regulation of proliferation, up-regulation of two distinct zinc transporters, and in vitro inhibition of endothelial cell sprouting.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".