Hypoxia-preconditioned hUCMSCs protect frozen-thawed human ovarian tissue by modulating the HIF-1α/VEGF pathway
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether hypoxia-preconditioned human umbilical cord mesenchymal stem cells (hUCMSCs) can protect frozen-thawed human ovarian tissue via in vitro co-culture. METHODS: ‑MSCs group (normoxia‑preconditioned hUCMSCs co-culture), and H‑MSCs group (hypoxia‑preconditioned hUCMSCs co-culture). Tissues in the co-culture groups were subjected to 48 h indirect Transwell co-culture. Apoptosis was assessed by TUNEL. Metabolic changes in the culture medium were measured, such as glucose consumption and lactate production, and AMH levels were determined. Oxidative stress in ovarian tissue was evaluated by measuring ROS and TAC. RNA-seq was performed, and key pathways were analyzed by GSEA. The protein expression of HIF-1α, VEGFA, GDF9, AKT, and p-AKT was examined by Western blot. RESULTS: Compared with both the control and N-MSCs groups, co-culture with H‑MSCs significantly reduced follicular atresia and apoptosis, while preserving a greater proportion of resting follicles. The H‑MSCs group presented lower glucose consumption and lactate production and elevated AMH levels in the culture medium. H‑MSCs markedly decreased reactive oxygen species (ROS) and enhanced total antioxidant capacity (TAC). Transcriptomic analysis showed that H‑MSCs induced a distinct gene expression profile characterized by upregulation of the HIF‑1 signaling pathway. H‑MSCs significantly upregulated HIF‑1α, VEGFA, and phosphorylated AKT at the protein level. CONCLUSIONS: This in vitro study showed that co-culture of ovarian tissue with H-MSCs provides stronger protection than N-MSCs. This effect likely involves the HIF-1α/VEGFA pathway, with enhanced pro-angiogenic signaling, reduced apoptosis and oxidative stress, and preservation of the follicular reserve.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".