Bridging endometrial receptivity and implantation: network of hormones, cytokines, and growth factors
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
The prerequisite of successful implantation depends on achieving the appropriate embryo development to the blastocyst stage and at the same time the development of an endometrium that is receptive to the embryo. Implantation is a very intricate process, which is controlled by a number of complex molecules like hormones, cytokines, and growth factors and their cross talk. A network of these molecules plays a crucial role in preparing receptive endometrium and blastocyst. Furthermore, timely regulation of the expression of embryonic and maternal endometrial growth factors and cytokines plays a major role in determining the fate of embryo. Most of the existing data comes from animal studies due to ethical issues. In this study, we comprehend the data from both animal models and humans for better understanding of implantation and positive outcomes of pregnancy. The purpose of this review is to describe the potential roles of embryonic and uterine factors in implantation process such as prostaglandins, cyclooxygenases, leukemia inhibitory factor, interleukin (IL) 6, IL11, transforming growth factor-β, IGF, activins, NODAL, epidermal growth factor (EGF), and heparin binding-EGF. Understanding the function of these players will help us to address the reasons of implantation failure and infertility.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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