Cross-species comparison of mouse and human preimplantation development with an emphasis on lineage specification
Bibliographic record
Abstract
In brief: Human embryogenesis still remains largely unexplored. This review helps identify some of our current gaps in knowledge pertaining to preimplantation development, which may have implications for understanding fundamental aspects of human development, assisted reproductive technologies, and stem cell biology. Abstract: Preimplantation development is arguably one of the most critical stages of embryogenesis. Beginning with the formation of the totipotent zygote post-fertilization, a series of cell divisions, and a complex coordination of physical cues, molecular signals and changes in gene expression lead to the formation of the blastocyst, a structure capable of implanting into the uterine wall. The blastocyst is composed of more specified cellular lineages, which will give rise to every tissue of the developing organism as well as the extra-embryonic lineages which support fetal growth. While the mouse has been used as a model to understand the events of preimplantation development for decades, in recent years, an expanding body of work has been conducted using the human embryo. These studies have identified some crucial species differences, particularly in the transcriptional and spatio-temporal expression of lineage markers and responses to cell signaling perturbations. This review compares recent findings on preimplantation development in mouse and human, with a focus on the specification of the first cellular lineages. Highlighting differences and noting mechanisms that require further examination in the human embryo is of critical importance for both the accurate translation of results from the mouse model and our overall understanding of mammalian development. We further highlight the latest advancement in reproductive research, the development of the 3D stem cell-based models known as 'blastoids'. The knowledge discussed in this review has major clinical implications for assisted reproductive technologies such as in vitro fertilization and for applications in stem cell biology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".