Evidence map›Paper›PMID 39846200›Full record

ReviewZoological research2025

Advances and applications of genome-edited animal models for severe combined immunodeficiency.

Xiao Zheng, Chun-Hui Huang, Sen Yan, Ming-Deng Rong

Abstract readReview
In one paragraph

Review in Zoological research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Epigenetic editing of marine medaka (Zoological research · 2026
    Article
  4. 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

4 authors.

Xiao ZhengStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong 510280, China.
Chun-Hui HuangGuangdong Key Laboratory of Non-Human Primate Models, Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, Guangdong 510632, China.
Sen YanGuangdong Key Laboratory of Non-Human Primate Models, Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, Guangdong 510632, China.
Ming-Deng RongStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong 510280, China. E-mail: rmdeng@smu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe combined immunodeficiency disease (SCID), characterized by profound immune system dysfunction, can lead to life-threatening infections and death. Animal models play a pivotal role in elucidating biological processes and advancing therapeutic strategies. Recent advances in gene-editing technologies, including zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), CRISPR/Cas9, and base editing, have significantly enhanced the generation of SCID models. These models have not only deepened our understanding of disease pathophysiology but have also driven progress in cancer therapy, stem cell transplantation, organ transplantation, and infectious disease management. This review provides a comprehensive overview of current SCID models generated using novel gene-editing approaches, highlighting their potential applications in translational medicine and their role in advancing biomedical research.

Indexed as

Disease Models, AnimalGene EditingSevere Combined ImmunodeficiencyAnimalsCRISPR-Cas SystemsAnimal modelGene-editing technologySevere combined immunodeficiency diseaseTranslational biomedicine

Identifiers

PMID39846200
PMCPMC11891005

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.