The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Progressive Recruitment of Mesenchymal Progenitors Reveals a Time-Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis
Open accessAbstract
Summary Mammalian nephrons arise from a limited nephron progenitor pool through a reiterative inductive process extending over days (mouse) or weeks (human) of kidney development. Here, we present evidence that human nephron patterning reflects a time-dependent process of recruitment of mesenchymal progenitors into an epithelial nephron precursor. Progressive recruitment predicted from high resolution image analysis and 3D reconstruction of human nephrogenesis was confirmed through direct visualization and cell fate analysis of mouse kidney organ cultures. Single-cell RNA sequencing of the human nephrogenic niche provided molecular insights into these early patterning processes and predicted developmental trajectories adopted by nephron progenitor cells in forming segment-specific domains of the human nephron. The temporal-recruitment model for nephron polarity and patterning suggested by direct analysis of human kidney development provides a framework for integrating signaling pathways driving mammalian nephrogenesis.
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
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Kidney organoids from human iPS cells contain multiple lineages and model human nephrogenesis
Takasato, M., Er, P. X., Chiu, H. S., Maier, B., Baillie, G. J., Ferguson, C., Parton, R. G., Wolvetang, E. J., Roost, M. S., Chuva de Sousa Lopes, S. M., et al. (2015) · Nature · doi:10.1038/nature15695 · Cited by 1,627
Cited by
Single-Cell Profiling Reveals Sex, Lineage, and Regional Diversity in the Mouse Kidney
Ransick, A., Lindström, N. O., Liu, J., Zhu, Q., Guo, J.-J., Alvarado, G. F., Kim, A. D., Black, H. G., Kim, J., & McMahon, A. P. (2019) · Developmental Cell · doi:10.1016/j.devcel.2019.10.005 · Cited by 429
Self-citationSubramanian, A., Sidhom, E.-H., Emani, M., Vernon, K., Sahakian, N., Zhou, Y., Kost-Alimova, M., Slyper, M., Waldman, J., Dionne, D., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-13382-0 · Cited by 211
Short and dysfunctional telomeres sensitize the kidneys to develop fibrosis
Saraswati, S., Martínez, P., Graña-Castro, O., & Blasco, M. A. (2021) · Nature Aging · doi:10.1038/s43587-021-00040-8 · Cited by 28
Metadata
- Authors
- Lindström, N. O., De Sena Brandine, G., Tran, T., Ransick, A., Suh, G., Guo, J., Kim, A. D., Parvez, R. K., Ruffins, S. W., Rutledge, E. A., Thornton, M. E., Grubbs, B., McMahon, J. A., Smith, A. D., & McMahon, A. P.
- Venue
- Developmental Cell
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 45
- Issue
- 5
- Pages
- 651-660.e4
- ISSN
- 1534-5807 (ISSN-L)
- OpenAlex
- W2806222066
- Cited by
- 212
- References
- 5
- FWCI
- 8.40
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Progressive Recruitment of Mesenchymal Progenitors Reveals a Time-Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis. https://app.cochat.ai/papers/10.1016/j.devcel.2018.05.010
- The paper
- Lindström, N. O., De Sena Brandine, G., Tran, T., Ransick, A., Suh, G., Guo, J., Kim, A. D., Parvez, R. K., Ruffins, S. W., Rutledge, E. A., Thornton, M. E., Grubbs, B., McMahon, J. A., Smith, A. D., & McMahon, A. P. (2018). Progressive Recruitment of Mesenchymal Progenitors Reveals a Time-Dependent Process of Cell Fate Acquisition in Mouse and Human Nephrogenesis. Developmental Cell. https://doi.org/10.1016/j.devcel.2018.05.010
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.
