Role of T cells in intrauterine administration of activated peripheral blood mononuclear cells in recurrent implantation failure
Bibliographic record
Abstract
Abstract Over the last few years, intrauterine administration of autologous peripheral blood mononuclear cells (PBMC) has been proposed as new immunotherapy for patients with unexplained recurrent implantation failure (RIF). In these patients, administration of activated PBMC before embryo transfer results in a 2-fold increase in live birth rates(Yang et al., 2020). In this study we evaluated the role of T cells to promotes human endometrial receptivity. On the day of ovulation, PBMC were isolated from and activated with T cells mitogen, the phytohemagglutinin (PHA) and hCG for 48-h in a conditioned culture medium. Distributions of CD4 + T cells were characterized in 157 patients by flow cytometry before and after PHA/hCG activation. Cytokine production was analyzed by cytometric beads array. We observed in RIF patients a significant decrease in Th2 and natural Treg cells before activation with PHA/hCG and an increase of Th17 cells after activation compared to intrauterine sperm insemination (IUI) and in vitro fertilization (IVF) groups. Furthermore, the hCG/PHA treatment increases anti-inflammatory T cells (Th2 and Treg cells) compared to non-treated T cells. Principal component analysis (PCA) performed on CD4 T cell subtypes revealed a different cellular profile in the RIF compared to the IUI and IVF groups. This inflammatory state change could explain how endometrium immunomodulation by hCG-activated PBMC helps patients with unexplained RIF to reach implantation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".