TWIST1 controls cellular senescence and energy metabolism in mesenchymal stem cells
Bibliographic record
Abstract
Mesenchymal stem cells (MSCs) are promising cells for regenerative medicine therapies because they can differentiate towards multiple cell lineages. However, the occurrence of cellular senescence and the acquiring of the senescence-associated secretory phenotype (SASP) limit their clinical use. Since the transcription factor TWIST1 influences expansion of MSCs, its role in regulating cellular senescence was investigated. The present study demonstrated that silencing of TWIST1 in MSCs increased the occurrence of senescence, characterised by a SASP profile different from irradiation-induced senescent MSCs. Knowing that senescence alters cellular metabolism, cellular bioenergetics was monitored by using the Seahorse XF apparatus. Both TWIST1-silencing-induced and irradiation-induced senescent MSCs had a higher oxygen consumption rate compared to control MSCs, while TWIST1-silencing-induced senescent MSCs had a low extracellular acidification rate compared to irradiation-induced senescent MSCs. Overall, data indicated how TWIST1 regulation influenced senescence in MSCs and that TWIST1 silencing-induced senescence was characterised by a specific SASP profile and metabolic state.
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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".