Clinical Application of Cell Therapy in the Treatment of Female Reproductive Diseases: A Systematic Review
Bibliographic record
Abstract
Reproductive disorders affect millions of women worldwide, playing a crucial role in determining female fertility health and quality of life. Conventional methods such as surgery, hormone therapy, and assisted reproductive technologies can be successful in some cases, but are limited by adverse effects, and limited effectiveness. In recent years, cell therapy has provided new possibilities for treating various infertility disorders. The articles extracted from PubMed and Scopus databases were based on cell therapy premature ovarian failure (POF), intrauterine adhesions, Asherman syndrome (AS), recurrent implantation failure (RIF), repeat implantation failure, polycystic ovary syndrome (PCOS), endometriosis, preeclampsia, and clinical trials. The collected articles were added to EndNote X7, and review articles along with duplicate studies were eliminated. Several studies have indicated that peripheral blood mononuclear cells, autologous platelet-rich plasma, mesenchymal stem cells (MSCs), hematopoietic stem cells (HSCs), adipose-derived stromal vascular fraction, and umbilical cord stem cells can be used to treat reproductive diseases, including POF, AS, and RIF. PCOS, endometriosis, and preeclampsia were deleted from the study, because there were no clinical cell therapy studies for these diseases. Among the 210 studies, 28 were selected as eligible for further evaluation. Various clinical trials have supported the role of cell therapy in treating reproductive disorders. Although the information from this systematic review is promising, further studies are needed to evaluate the efficacy and safety of these and other cells in treating infertility.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".