Immunomodulation for unexplained recurrent implantation failure: where are we now?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In brief: Immune dysfunction may contribute to or cause recurrent implantation failure. This article summarizes normal and pathologic immune responses at implantation and critically appraises currently used immunomodulatory therapies. Abstract: Recurrent implantation failure (RIF) may be defined as the absence of pregnancy despite the transfer of ≥3 good-quality blastocysts and is unexplained in up to 50% of cases. There are currently no effective treatments for patients with unexplained RIF. Since the maternal immune system is intricately involved in mediating endometrial receptivity and embryo implantation, both insufficient and excessive endometrial inflammatory responses during the window of implantation are proposed to lead to implantation failure. Recent strategies to improve conception rates in RIF patients have focused on modulating maternal immune responses at implantation, through either promoting or suppressing inflammation. Unfortunately, there are no validated, readily available diagnostic tests to confirm immune-mediated RIF. As such, immune therapies are often started empirically without robust evidence as to their efficacy. Like other chronic diseases, patient selection for immunomodulatory therapy is crucial, and personalized medicine for RIF patients is emerging. As the literature on the subject is heterogenous and rapidly evolving, we aim to summarize the potential efficacy, mechanisms of actions and side effects of select therapies for the practicing clinician.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it