Evidence map›Paper›PMID 41169200›Full record

ArticleNeural regeneration research2026

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Qiang Zhou, Zongren Zhao, Da Tan, Chenhao Fang, Zhaoli Shen, Shun Li, Xianzhen Chen

Abstract read
In one paragraph

Article in Neural regeneration research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

7 authors.

Qiang ZhouDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Zongren ZhaoDepartment of Neurology, Ulm University, Ulm, Germany.
Da TanDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Chenhao FangDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Zhaoli ShenDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.ORCID 0000-0002-7376-6862
Shun LiDepartment of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0000-0001-8601-2261
Xianzhen ChenDepartment of Neurosurgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.ORCID 0000-0003-1915-4686

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and approaches have been introduced for studying nerve injury and regeneration. This review highlights the application and progress of multi-omics in uncovering the mechanisms of nerve injury, guiding the development of regenerative strategies, and promoting clinical translation. By integrating multi-omics datasets, researchers can comprehensively track dynamic molecular changes following nerve injury, including abnormal gene expression, disrupted protein signaling, altered metabolic programs, and shifts in the immune microenvironment. Single-cell multi-omics technologies resolve cellular heterogeneity, revealing the distinct functions of neurons, glial cells, and immune cell subpopulations during the injury response. Spatially resolved transcriptomics maintain the spatial context of lesion and regeneration sites, enabling precise localization for targeted interventions. Multi-omics technologies not only identify key molecular players involved in nerve regeneration but also create opportunities for personalized medicine. Nonetheless, integrating multi-omics data poses technical challenges, including high dimensionality, batch effects, and algorithmic constraints, while ethical concerns related to stem cell therapy and gene editing require stringent oversight. To transition from structural reconstruction to functional remodeling, future research should emphasize artificial intelligence-driven data integration, organ-on-a-chip modeling, and cross-disciplinary collaboration to overcome existing technical barriers and accelerate the clinical application of neuroregenerative therapies.

Indexed as

artificial intelligencebiomarkersgene expression regulationgenomicsmetabolomicsnerve regenerationneural pathwaysproteomicssingle-cell analysistranscriptomics

Identifiers

PMID41169200
PMCPMC13557687

What Socratic holds

Textmetadata
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.