ArticleAging2023
Systemic changes induced by autologous stem cell ovarian transplant in plasma proteome of women with impaired ovarian reserves.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07376460 (Biological and Proteomic Characterisation of Platelet-rich Plasma), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Biological and Proteomic Characterisation of Platelet-rich Plasma (PRP) Before and After Mobilisation of Haematopoietic Stem Cells in Peripheral Blood From Women With Low Ovarian Response (Low Responders) and in Vitro Evaluation in Human Ovarian Cell Models
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Cellular therapies in primary ovarian insufficiency and poor ovarian reserve: a systematic review.Journal of assisted reproduction and genetics · 2025Pooled it
- Spontaneous Premature Ovarian Insufficiency: Methods Under Research for Infertility Treatment.Journal of clinical medicine · 2026Review
- Observational
- Dual-Double Stem Cell Ovarian Therapy: A Comprehensive Approach in Regenerative Medicine.International journal of molecular sciences · 2024Review
- The Reproductive Lifespan of Ovarian Follicle.Reproductive sciences (Thousand Oaks, Calif.) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with poor ovarian response (POR) and premature ovarian insufficiency (POI) are challenging to treat, with oocyte donation remaining as the only feasible option to achieve pregnancy in some cases. The Autologous stem cell ovarian transplantation (ASCOT) technique allows follicle development, enabling pregnancies and births of healthy babies in these patients. Previous results suggest that growth factors and cytokines secreted by stem cells are partially responsible for their regenerative properties. Indeed, ASCOT beneficial effects associate with the presence of different bone marrow derived stem cell- secreted factors in plasma. Therefore, the aim of this study was to assess whether ASCOT induce any modifications in the plasma proteomic profile of patients with impaired ovarian reserves. Discriminant analysis highlighted clear distinctions between the plasma proteome before (PRE), during stem cell mobilization and collection (APHERESIS) and three months after ASCOT (POST) in patients with POR and POI. Both the stem cell mobilization and ASCOT technique induced statistically significant modifications in the plasma composition, reversing some age-related protein expression changes. In the POR group, functional analysis revealed an enrichment in processes related to the complement cascade, immune system, and platelet degranulation, while in the POI group, enriched processes were also associated with responses to oxygen-containing compounds and growth hormones, and blood vessel maturation. In conclusion, our findings highlight the potential proteins and biological processes that may promote the follicle activation and growth observed after ASCOT. Identifying plasma proteins that regenerate aged or damaged ovaries could lead to more effective, targeted and/or preventive therapies for patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.