ReviewFrontiers in cell and developmental biology2021
Conditional Cell Reprogramming in Modeling Digestive System Diseases.
Review in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Conditionally Reprogrammed Cells Preserve Cellular Diversity and Permit Genetic Manipulation: Implications for Cancer Heterogeneity and Tissue Regeneration.Serican journal of medicine · 2026Article
- Review
- Urine PD-L1 as a non-invasive biomarker for immune checkpoint inhibitor (ICI) therapy in bladder cancer.Advances in biomarker sciences and technology · 2025Article
- Modeling respiratory tract diseases for clinical translation employing conditionally reprogrammed cells.Cell insight · 2024Review
- Review
- Advances in Genetic Reprogramming: Prospects from Developmental Biology to Regenerative Medicine.Current medicinal chemistry · 2024Review
- Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research.Cells · 2023Review
- Review
- G Protein-Coupled Receptor GPR35 Suppresses Lipid Accumulation in Hepatocytes.ACS pharmacology & translational science · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digestive diseases have become an important source of morbidity and mortality. The considerable financial and health burdens caused by digestive diseases confirm the importance of extensive research to better understand and treat these diseases. The development of reliable preclinical models is essential for understanding the pathogenesis of digestive diseases and developing treatment and prevention methods. However, traditional established cell lines and animal models still have many limitations in the study of the digestive system. Conditional reprogramming (CR) cell culture is a newly developed primary technology that uses irradiated Swiss-3T3-J2 mouse fibroblast cells and the Rho-associated kinase (ROCK) inhibitor Y-27632 to rapidly and efficiently generate many cells from diseased and normal tissues. CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and recapitulate the histological and genomic features of the original tissue. Moreover, after removing these conditions, the phenotype was completely reversible. Therefore, CR technology may represent an ideal model to study digestive system diseases, to test drug sensitivity, to perform gene profile analysis, and to undertake xenograft research and regenerative medicine. Indeed, together with organoid cultures, CR technology has been recognized as one of the key new technologies by NIH precision oncology and also used for NCI human cancer model initiatives (HCMI) program with ATCC. In this article, we review studies that use CR technology to conduct research on diseases of the digestive system.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.