The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.
Modelling the impact of decidual senescence on embryo implantation in human endometrial assembloids
Open accessAbstract
Decidual remodelling of midluteal endometrium leads to a short implantation window after which the uterine mucosa either breaks down or is transformed into a robust matrix that accommodates the placenta throughout pregnancy. To gain insights into the underlying mechanisms, we established and characterized endometrial assembloids, consisting of gland-like organoids and primary stromal cells. Single-cell transcriptomics revealed that decidualized assembloids closely resemble midluteal endometrium, harbouring differentiated and senescent subpopulations in both glands and stroma. We show that acute senescence in glandular epithelium drives secretion of multiple canonical implantation factors, whereas in the stroma it calibrates the emergence of anti-inflammatory decidual cells and pro-inflammatory senescent decidual cells. Pharmacological inhibition of stress responses in pre-decidual cells accelerated decidualization by eliminating the emergence of senescent decidual cells. In co-culture experiments, accelerated decidualization resulted in entrapment of collapsed human blastocysts in a robust, static decidual matrix. By contrast, the presence of senescent decidual cells created a dynamic implantation environment, enabling embryo expansion and attachment, although their persistence led to gradual disintegration of assembloids. Our findings suggest that decidual senescence controls endometrial fate decisions at implantation and highlight how endometrial assembloids may accelerate the discovery of new treatments to prevent reproductive failure.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
A new mathematical model for relative quantification in real-time RT-PCR
Pfaffl, M. W. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.9.e45 · Cited by 34,610
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
Tissue-based map of the human proteome
Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110
The Gene Ontology Resource: 20 years and still GOing strong
The Gene Ontology Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1055 · Cited by 4,747
Efremova, M., Vento-Tormo, M., Teichmann, S. A., & Vento-Tormo, R. (2020) · Nature Protocols · doi:10.1038/s41596-020-0292-x · Cited by 3,449
Cellular senescence: from physiology to pathology
Muñoz-Espín, D., & Serrano, M. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3823 · Cited by 2,818
The role of senescent cells in ageing
van Deursen, J. M. (2014) · Nature · doi:10.1038/nature13193 · Cited by 2,623
The Achilles' heel of senescent cells: from transcriptome to senolytic drugs
Zhu, Y., Tchkonia, T., Pirtskhalava, T., Gower, A. C., Ding, H., Giorgadze, N., Palmer, A. K., Ikeno, Y., Hubbard, G. B., Lenburg, M., et al. (2015) · Aging Cell · doi:10.1111/acel.12344 · Cited by 2,584
Cited by
Cellular senescence: the good, the bad and the unknown
Huang, W., Hickson, L. J., Eirin, A., Kirkland, J. L., & Lerman, L. O. (2022) · Nature Reviews Nephrology · doi:10.1038/s41581-022-00601-z · Cited by 1,150
Assembloid models of cell-cell interaction to study tissue and disease biology
Onesto, M. M., Kim, J.-I., & Pasca, S. P. (2024) · Cell Stem Cell · doi:10.1016/j.stem.2024.09.017 · Cited by 107
Cellular senescence in normal and adverse pregnancy
Farfán-Labonne, B., Leff-Gelman, P., Pellón-Díaz, G., & Camacho-Arroyo, I. (2023) · Reproductive Biology · doi:10.1016/j.repbio.2023.100734 · Cited by 19
Metadata
- Authors
- Rawlings, T. M., Makwana, K., Taylor, D. M., Molè, M. A., Fishwick, K. J., Tryfonos, M., Odendaal, J., Hawkes, A., Zernicka-Goetz, M., Hartshorne, G. M., Brosens, J. J., & Lucas, E. S.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2021-09-06
- Volume
- 10
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W3198684516
- Cited by
- 269
- References
- 84
- FWCI
- 11.97
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Modelling the impact of decidual senescence on embryo implantation in human endometrial assembloids. https://app.cochat.ai/papers/10.7554/elife.69603
- The paper
- Rawlings, T. M., Makwana, K., Taylor, D. M., Molè, M. A., Fishwick, K. J., Tryfonos, M., Odendaal, J., Hawkes, A., Zernicka-Goetz, M., Hartshorne, G. M., Brosens, J. J., & Lucas, E. S. (2021). Modelling the impact of decidual senescence on embryo implantation in human endometrial assembloids. eLife. https://doi.org/10.7554/elife.69603
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
