Down-Regulation of Lnc-CYP7A1-1 Rejuvenates Aged Human Mesenchymal Stem Cells to Improve Their Efficacy for Heart Repair Through SYNE1
Bibliographic record
Abstract
Background: Several long non-coding RNAs (lncRNAs) have been associated with cell senescence, termed senescence-associated lncRNAs (SAL-RNAs). However, the mechanisms involved for SAL-RNAs in aging are not fully elucidated. In the present study, we investigated the effects of SAL-RNAs on aged human bone marrow-derived mesenchymal stem cells (hBM-MSCs), and the possible means to counteract such effects to improve the regenerative capacity of aged hBM-MSCs. Methods: By comparing the lncRNAs expression of hBM-MSCs derived from young and old individuals, lnc-CYP7A1-1 was identified as being significantly increased with age. Using predictive software, the expression of Spectrin Repeat Containing Nuclear Envelope Protein 1 (SYNE1), was found to be decreased with age. Next, through lentiviral constructs, we downregulated the expression of lnc-CYP7A1-1 or SYNE1 in hBM-MSCs separately. Additionally, hBM-MSCs proliferation, survival, migration, and senescence were investigated in vitro. In vivo, lnc-CYP7A1-1 downregulated aged hBM-MSCs were implanted into infarcted mouse hearts after myocardial infarction (MI), and cardiac function was measured. Through lentivirus-mediated downregulation of lnc-CYP7A1-1 in aged hBM-MSCs, we revealed that cell senescence was decreased, whereas cell proliferation, migration, and survival were increased. On the other hand, downregulation of SYNE1, the target gene of lnc-CYP7A1-1, in young hBM-MSCs increased cell senescence, yet decreased cell proliferation, migration, and survival. Downregulation of lnc-CYP7A1-1 in aged hBM-MSCs induced cell rejuvenation, yet this effect was attenuated by repression of SYNE1. In vivo, transplantation of lnc-CYP7A1-1 downregulated old hBM-MSCs improved cardiac function after MI. Conclusion: Down-regulation of lnc-CYP7A1-1 rejuvenated aged hBM-MSCs and improved cardiac function when implanted into the infarcted mouse hearts, possibly through its target gene SYNE1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".