Mesenchymal Stem Cells Ameliorated Glucolipotoxicity in HUVECs through TSG-6
Bibliographic record
Abstract
Glucolipotoxicity is one of the critical causal factors of diabetic complications. Whether mesenchymal stem cells (MSCs) have effects on glucolipotoxicity in human umbilical vein endothelial cells (HUVECs) and mechanisms involved are unclear. Thirty mM glucose plus 100 μM palmitic acid was used to induce glucolipotoxicity in HUVECs. MSCs and HUVECs were co-cultured at the ratio of 1:5 via Transwell system. The mRNA expressions of inflammatory factors were detected by RT-qPCR. The productions of reactive oxygen species (ROS), cell cycle and apoptosis were analyzed by flow cytometry. The tumor necrosis factor-α stimulated protein 6 (TSG-6) was knockdown in MSCs by RNA interference. High glucose and palmitic acid remarkably impaired cell viability and tube formation capacity, as well as increased the mRNA expression of inflammatory factors, ROS levels, and cell apoptosis in HUVECs. MSC co-cultivation ameliorated these detrimental effects in HUVECs, but no effect on ROS production. Moreover, TSG-6 was dramatically up-regulated by high glucose and fatty acid stimulation in both MSCs and HUVECs. TSG-6 knockdown partially abolished the protection mediated by MSCs. MSCs had protective effects on high glucose and palmitic acid induced glucolipotoxicity in HUVECs, and TSG-6 secreted by MSCs was likely to play an important role in this process.
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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 | 0.001 |
| 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".