Evidence map›Paper›PMID 40140235›Full record

ReviewCell regeneration (London, England)2025

Cell reprogramming: methods, mechanisms and applications.

Fei Zhu, Guangjun Nie

Abstract readReview
In one paragraph

Review in Cell regeneration (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Regenerative Medicine: Advanced Therapy for Muscle Tissue Restoration.International journal of molecular sciences · 2026
    Review
  5. Article
  6. Review
  7. Review
  8. Mining the gaps: Deciphering Alzheimer's biology through AI-driven reconciliation.The journal of prevention of Alzheimer's disease · 2025
    Article
  9. Review
  10. Review
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

2 authors.

Fei ZhuWisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China. Fei.Zhu@xjtlu.edu.cn.ORCID http://orcid.org/0000-0002-1207-3675
Guangjun NieCAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center of Excellence in Nanoscience National Center for Nanoscience and Technology, Beijing, 100190, China. niegj@nanoctr.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell reprogramming represents a powerful approach to achieve the conversion cells of one type into cells of another type of interest, which has substantially changed the landscape in the field of developmental biology, regenerative medicine, disease modeling, drug discovery and cancer immunotherapy. Cell reprogramming is a complex and ordered process that involves the coordination of transcriptional, epigenetic, translational and metabolic changes. Over the past two decades, a range of questions regarding the facilitators/barriers, the trajectories, and the mechanisms of cell reprogramming have been extensively investigated. This review summarizes the recent advances in cell reprogramming mediated by transcription factors or chemical molecules, followed by elaborating on the important roles of biophysical cues in cell reprogramming. Additionally, this review will detail our current understanding of the mechanisms that govern cell reprogramming, including the involvement of the recently discovered biomolecular condensates. Finally, the review discusses the broad applications and future directions of cell reprogramming in developmental biology, disease modeling, drug development, regenerative/rejuvenation therapy, and cancer immunotherapy.

Indexed as

Biophysical regulationCancer immunotherapyCell reprogrammingCell therapyDisease modelingDrug development

Identifiers

PMID40140235
PMCPMC11947411

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.