ReviewAdvanced healthcare materials2025
A Roadmap of Peptide-Based Materials in Neural Regeneration.
Review in Advanced healthcare materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Analysis of PTEN Antagonistic Peptides (PAPs) in Neuronal Growth and Traumatic Brain Injury (TBI).Biomacromolecules · 2026Article
- Peptide-Incorporated Biomaterials Promote Regeneration of Peripheral Nerve Injuries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Peptide Electrostatic Modulation Directs Human Neural Cell Fate.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Peptide Photoimmobilization by Thiol-ene Chemistry for Enhanced Neural Cell Adhesion.ACS biomaterials science & engineering · 2025Article
- Design of the Hydrophobic Core of Self-Assembling Peptide Fibrils for Enhanced Neural Regeneration.Small science · 2025Article
- A Roadmap of Peptide-Based Materials in Neural Regeneration.Advanced healthcare materials · 2025Review
- Emerging biomimetic biopolymer-based composites: advancing accessible and sustainable neural disease models and therapeutics.Frontiers in bioengineering and biotechnology · 2025Review
- Ocular-cerebral immune dialogue: a new perspective and therapeutic potential of regional lymphatic systems.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Injuries to the nervous system lead to irreversible damage and limited functional recovery. The peripheral nervous system (PNS) can self-regenerate to some extent for short nerve gaps. In contrast, the central nervous system (CNS) has an intrinsic limitation to self-repair owing to its convoluted neural microenvironment and inhibitory response. The primary phase of CNS injury, happening within 48 h, results from external impacts like mechanical stress. Afterward, the secondary phase of the injury occurs, originating from neuronal excitotoxicity, mitochondrial dysfunction, and neuroinflammation. No golden standard to treat injured neurons exists, and conventional medicine serves only as a protective approach to alleviating the symptoms of chronic injury. Synthetic peptides provide a promising approach for neural repair, either as soluble drugs or by using their intrinsic self-assembly propensity to serve as an extracellular matrix (ECM) mimic for cell adhesion and to incorporate bioactive epitopes. In this review, an overview of nerve injury models, common in vitro models, and peptide-based therapeutics such as ECM mimics is provided. Due to the complexity of treating neuronal injuries, a multidisciplinary collaboration between biologists, physicians, and material scientists is paramount. Together, scientists with complementary expertise will be required to formulate future therapeutic approaches for clinical use.
Indexed as
Identifiers
What Socratic 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 Socratic graph.