Inhibition of Viability, Proliferation, Cytokines Secretion, Surface Antigen Expression, and Adipogenic and Osteogenic Differentiation of Adipose‐Derived Stem Cells by Seven‐Day Exposure to 0.5 T Static Magnetic Fields
Bibliographic record
Abstract
After seven-day exposure to 0.5-Tesla Static Magnetic Field (SMF), Adipose-derived Stem Cells (ASCs) and those labeled by superparamagnetic iron oxide (SPIO) nanoparticles were examined for viability by methyl thiazol tetrazolium (MTT) assay, proliferation by cell counting and bromodeoxyuridine (BrdU) incorporation, DNA integrity by single cell gel electrophoresis, surface antigen by flow cytometry analysis, and the expression of cytokines and genetic markers by reverse transcription-PCR and underwent adipogenic and osteogenic differentiation assessed by quantifying related specific genes expression. The SMF slightly reduced cell viability and proliferation and inhibited the expression of CD49d, CD54, and CD73 but did not damage DNA integrity. The SMF slightly downregulated the expression of cytokines including Vascular Endothelial Growth Factor (VEGF), Insulin-like Growth Factor-1 (IGF-1), Transforming Growth Factor Beta 1 (TGF-β1), genetic markers comprising Stem Cell Antigen-1 (Sca1), Octamer-4 (Oct-4), ATP-binding Cassette Subfamily B Member 1 (ABCB1), adipogenic marker genes containing Lipoprotein Lipase (LPL), Peroxisome Proliferator-Activated Receptor Gamma (PPAR-γ), and osteogenic marker genes including Secreted Phosphor-protein 1 (SPP1) and Osterix (OSX). Exposure to 0.5 T SMF for seven days inhibited viability, proliferation, surface antigen expression, cytokine secretion, stem cell genetic marker expression, and adipogenic and osteogenic differentiation but did not affect the DNA integrity in ASCs with or without SPIO labeling.
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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".