Efficient Nonviral Transfection of Human Bone Marrow Mesenchymal Stromal Cells Shown Using Placental Growth Factor Overexpression
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Human mesenchymal stromal/stem cells (hMSCs) hold great therapeutic potential due to their immunomodulatory and tissue regenerative properties. Enhancement of biological features of hMSCs by transfection has become a focus of investigation for cell- and gene-based therapies. However, many of the current transient transfection methods result in either low transfection efficiency or high cytotoxicity. METHODS: In order to find a transfection method that would address the current issues of low transfection efficiency and high cytotoxicity, 6 commercially available cationic lipid and polymer reagents were tested on human bone marrow-derived MSCs (hBM-MSCs) using GFP as a reporter gene. One transfection method using TransIT-2020 was selected and tested with an emphasis on cell quality (viability, identity, and yield), as well as efficacy with a human placental growth factor (PlGF) plasmid. RESULTS: TransIT-2020 yielded the highest fluorescence signal per cell out of the methods that did not decrease cell recovery. Transfecting GFP to 5 hBM-MSC donors using TransIT-2020 yielded 24-36% GFP-expressing cells with a viability of 85-96%. hBM-MSC identity was unaffected as CD90, CD105, and CD73 markers were retained (>95%+) after transfection. When this method was applied to PlGF expression, there was up to a 220-fold increase in secretion. Both growth and secretion of PlGF in overexpressing hBM-MSC were sustained over 7 days, confirming the sustainability and applicability of the TransIT-2020 transfection system. DISCUSSION: We report a simple and efficient method for transient transfection that has not been reported for hBM-MSCs, encompassing high levels of plasmid expression without significant changes to fundamental hBM-MSC characteristics.
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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) | 0.005 | 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