Scientometric analysis of evolution in sex-specific MSC therapy for cardiovascular diseases
Bibliographic record
Abstract
Mesenchymal stem cell (MSC) therapy for cardiovascular diseases has shown promise; however, sex-specific differences remain understudied. This scientometric analysis provides the first comprehensive overview of sex-specific differences in mesenchymal stem cell (MSC) therapy for cardiovascular diseases, spanning from 1947 to 2024. We analyzed 61,029 publications using advanced bibliometric tools to identify research hotspots, publication trends, and collaborative networks. A significant shift in research focus has been observed in the field of mesenchymal stem cell (MSC) therapy for cardiovascular diseases, transitioning from broad cardiovascular concepts in the 20th century to specialized sex-specific considerations in the 21st century. Furthermore, in the 21st-century research landscape, the formation of two distinct clusters for “male” and “female” in VOSviewer-generated network visualizations is highly important, emphasizing the growing recognition of sex-specific differences in MSC therapy responses and outcomes. This shift was accompanied by a marked increase in terminology related to sex-specific differences, with keywords like “genetic association” and “body mass index” forming distinct clusters in recent years. This analysis underscores the critical need for sex-specific considerations in MSC therapy for cardiovascular disease. The emergence of distinct male and female clusters in research networks emphasizes the importance of tailoring approaches based on sex differences. Key areas identified for future investigation include the role of epigenetics in mediating sex-specific effects and the potential of sex-matched MSC-derived exosomes. These findings pave the way for more effective and personalized approaches in cardiovascular regenerative medicine, potentially leading to improved outcomes through sex-specific therapeutic strategies. • First comprehensive scientometric analysis of sex differences in MSC therapy for cardiovascular diseases. • Research shifted from broad cardiovascular topics to exploring specialized sex-specific considerations in the 21st century. • Underscored the critical need for sex-specific considerations in MSC therapy for cardiovascular diseases. • Future research may focus on epigenetics and sex-matched MSC exosomes in sex-specific therapy. • Presents a quantitative analysis of trends and gaps to guide personalized strategies in cardiovascular regeneration.
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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 | 0.010 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.088 | 0.106 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".