Intrauterine Autologous PBMC Therapy: Effects on Endometrial Immunity and IVF Success in Repeated Implantation Failure
Bibliographic record
Abstract
Nearly 10% of IVF patients experience repeated implantation failure (RIF). Although several meta-analyses report improved outcomes following peripheral blood mononuclear cell (PBMC) administration, the uterine mechanisms remain poorly understood. We first analyzed PBMC composition and cytokine secretion in a preliminary cohort (n = 18), followed by endometrial immune profiling in a larger cohort (n = 70) before and after PBMC treatment. Embryo transfer was performed in 41 women, enabling the assessment of associations between immune profiles and implantation success. Successful implantation occurred in 16 of 41 embryo transfers (39%). PBMCs were predominantly composed of lymphocytes (60.7%), with T helper cells as the predominant T cell subset (Th/cytT ratio 1.44). Cytokine assays confirmed secretion of TNF-α, IL-6, IL-4, and IL-10. C-reactive protein levels remained below the threshold for systemic inflammation and were unaffected by PBMC administration. In the full cohort, PBMC infusion significantly enriched stromal macrophages and T helper cells, reflected by higher Th/T, Th/MΦ, and Th/cytotoxic T cell ratios and a reduced cytotoxic T/T cell ratio (all p ≤ 0.001). Importantly, women with successful implantation exhibited a significantly higher macrophage/T cell ratio (1.15 vs. 0.74; p = 0.024). These findings suggest that PBMC administration reshapes the endometrial immune landscape and that the macrophage/T cell ratio may serve as a promising biomarker of treatment efficacy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".