Evidence mapPaperPMID 40911279Full record

ReviewCell regeneration (London, England)2025

Cutting-edge technologies in neural regeneration.

Chang-Ping Li, Ying-Ying Wang, Ching-Wei Zhou, Chen-Yun Ding, Peng Teng, Rui Nie, Shu-Guang Yang

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Advancing spine connectomics and neural integration through machine learning and neuroengineering: a narrative review.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Review
  2. 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

7 authors.

Chang-Ping Li *Center for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Ying-Ying Wang *Center for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Ching-Wei Zhou *Center for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Chen-Yun DingCenter for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Peng TengCenter for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Rui NieCenter for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China.
Shu-Guang YangCenter for Translational Neural Regeneration Research, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China. yangshuguang@srrsh.com.

Funding

The Leading Innovation and Entrepreneurship Team Program of Zhejiang Province 2023R01005The Pioneer and Leading Goose R&D Program of Zhejiang Province 2024C03028
6 · The paper itself

Abstract

Neural regeneration stands at the forefront of neuroscience, aiming to repair and restore function to damaged neural tissues, particularly within the central nervous system (CNS), where regenerative capacity is inherently limited. However, recent breakthroughs in biotechnology, especially the revolutions in genetic engineering, materials science, multi-omics, and imaging, have promoted the development of neural regeneration. This review highlights the latest cutting-edge technologies driving progress in the field, including optogenetics, chemogenetics, three-dimensional (3D) culture models, gene editing, single-cell sequencing, and 3D imaging. Prospectively, the advancements in artificial intelligence (AI), high-throughput in vivo screening, and brain-computer interface (BCI) technologies promise to accelerate discoveries in neural regeneration further, paving the way for more precise, efficient, and personalized therapeutic strategies. The convergence of these multidisciplinary approaches holds immense potential for developing transformative treatments for neural injuries and neurological disorders, ultimately improving functional recovery.

Indexed as

3D cell culture3D imagingChemogeneticsGene editingNeural regenerationOptogeneticsOrganoidSingle-cell sequencing

Identifiers

PMID40911279
PMCPMC12413387

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.