Evidence map›Paper›PMID 39143064›Full record

ArticleCell death discovery2024

Generation of a conditional cellular senescence model using proximal tubule cells and fibroblasts from human kidneys.

Xiaohang Shao, Huaming Xu, Hyojin Kim, Sadaf Ljaz, Fabian Beier, Vera Jankowski, Michaela Lellig, Lucia Vankann, Jan Niklas Werner, Lu Chen and 7 more

Abstract read
In one paragraph

Article in Cell death discovery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Xiaohang Shao *Department of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Huaming Xu *Department of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.
Hyojin KimDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Sadaf LjazDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Fabian BeierDepartment of Hematology, Oncology, Hemostaseology, and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Vera JankowskiInstitute for Molecular Cardiovascular Research (IMCAR), RWTH Aachen University, Aachen, Germany.
Michaela LelligInstitute for Molecular Cardiovascular Research (IMCAR), RWTH Aachen University, Aachen, Germany.
Lucia VankannDepartment of Hematology, Oncology, Hemostaseology, and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Jan Niklas WernerDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Lu ChenDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Susanne ZieglerDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Christoph KuppeDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Martin ZenkeDepartment of Cell Biology, Institute of Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany.ORCID http://orcid.org/0000-0002-1107-3251
Rebekka K SchneiderInstitute of Cell and Tumorbiology, RWTH Aachen University, Medical Faculty, Aachen, Germany.
Sikander HayatDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany.ORCID http://orcid.org/0000-0001-5919-8371
Turgay SaritasDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany. tsaritas@ukaachen.de.ORCID http://orcid.org/0000-0002-6691-9218
Rafael KramannDepartment of Nephrology and Clinical Immunology, RWTH Aachen University, Medical Faculty, Aachen, Germany. rkramann@ukaachen.de.

Funding

CSC | Chinese Government Scholarship 202008080170CSC | Chinese Government Scholarship 202008230182Deutsche Forschungsgemeinschaft (German Research Foundation) 445703531Else Kröner-Fresenius-Stiftung (Else Kroner-Fresenius Foundation) 2022_EKES.03European Cooperation in Science and Technology (COST) 21165
6 · The paper itself

Abstract

Emerging evidence highlights cellular senescence's pivotal role in chronic kidney disease (CKD). Proximal tubule epithelial cells (PTECs) and fibroblasts are major players in CKD and serve as cellular sources of senescence. The generation of a conditionally immortalized human kidney cell model would allow to better understand the specific mechanisms and factors associated with cellular senescence in a controlled setting, devoid of potential confounding factors such as age and comorbidities. In addition, the availability of human kidney cell lines for preclinical research is sparse and most cell lines do not reflect their in vivo counterparts due to their altered behavior as immortalized cancer-like cells. In this study, PTECs and fibroblasts from human kidneys were isolated and transduced with doxycycline-inducible simian virus 40 large T antigen (SV40LT) vector. By comparing their gene expression with single-cell RNA sequencing data from human kidneys, the newly produced human kidney cell lines demonstrated significant resemblances to their in vivo counterparts. As predicted, PTECs showed functional activity and fibroblasts responded to injury with fibrosis. Withdrawal of the immortalizing factor doxycycline led to p21

Identifiers

PMID39143064
PMCPMC11324798

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.