ReviewFrontiers in bioengineering and biotechnology2024
Peripheral nerve injury repair by electrical stimulation combined with graphene-based scaffolds.
Review in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled 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.
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
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Neuroimaging Findings of Psychosis in Alzheimer's Disease: A Systematic Review.Brain and behavior · 2025Pooled it
- Optimizing Electrical Stimulation Parameters to Enhance Viability of Dental Pulp Stem Cells in Graphene-Based Scaffolds.ACS omega · 2026Article
- Multiscale biomimetic design for peripheral nerve repair: Beyond passive bridging.Materials today. Bio · 2026Review
- Electrical gastrodin-polyurethane spiral conduits with micro/nano-structure for accelerating peripheral nerve regeneration.Bioactive materials · 2026Article
- Peripheral nerve repair: innovations and future directions.Journal of translational medicine · 2026Review
- Modulating Schwann cell behavior via functional nerve guidance conduits for enhanced peripheral nerve regeneration.NPJ Regenerative medicine · 2025Review
- Enhanced Supercapacitor Performance through Synergistic BaCOACS omega · 2025Article
- Conductive Chitosan-Graphene Oxide Scaffold with Applications in Peripheral Nerve Tissue Engineering.Polymers · 2025Article
- Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.Scientific reports · 2025Article
- Tuina promotes nerve myelin regeneration in SNI rats through Piezo1/YAP/TAZ pathway.Journal of orthopaedic surgery and research · 2025Article
- Advanced development of conductive biomaterials for enhanced peripheral nerve regeneration: a review.RSC advances · 2025Review
- Biomaterial-Based Additive Manufactured Composite/Scaffolds for Tissue Engineering and Regenerative Medicine: A Comprehensive Review.Polymers · 2025Review
- Molecular docking of Cu(II) and Zn(II) complexes for tyrosinase inhibition and drug loading on boron nitride nanotube scaffolds using Monte Carlo simulations.Journal of molecular modeling · 2025Article
- Advances in biomaterial-based tissue engineering for peripheral nerve injury repair.Bioactive materials · 2025Review
- Graphene-based materials: an innovative approach for neural regeneration and spinal cord injury repair.RSC advances · 2025Review
- Cytokine Signaling in Diabetic Neuropathy: A Key Player in Peripheral Nerve Damage.Biomedicines · 2025Review
- The stability and self-assembly of tri-calcium silicate and hydroxyapatite scaffolds in bone tissue engineering applications.Journal of biological engineering · 2025Article
- From innovation to clinic: Emerging strategies harnessing electrically conductive polymers to enhance electrically stimulated peripheral nerve repair.Materials today. Bio · 2025Article
- AI-Optimized Lattice Structures for Biomechanics Scaffold Design.Biomimetics (Basel, Switzerland) · 2025Article
- Comparison of Two Synthesis Methods for 3D PLA-Ibuprofen Nanofibrillar Scaffolds.Pharmaceutics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Peripheral nerve injury (PNI) is a common clinical problem, which due to poor recovery often leads to limb dysfunction and sensory abnormalities in patients. Tissue-engineered nerve guidance conduits (NGCs) that are designed and fabricated from different materials are the potential alternative to nerve autografts. However, translation of these NGCs from lab to commercial scale has not been well achieved. Complete functional recovery with the aid of NGCs in PNI becomes a topic of general interest in tissue engineering and regeneration medicine. Electrical stimulation (ES) has been widely used for many years as an effective physical method to promote nerve repair in both pre-clinical and clinical settings. Similarly, ES of conductive and electroactive materials with a broad range of electrical properties has been shown to facilitate the guidance of axons and enhance the regeneration. Graphene and its derivatives possess unique physicochemical and biological properties, which make them a promising outlook for the development of synthetic scaffolds or NGCs for PNI repair, especially in combination with ES. Considering the discussion regarding ES for the treatment of PNI must continue into further detail, herein, we focus on the role of ES in PNI repair and the molecular mechanism behind the ES therapy for PNI, providing a summary of recent advances in context of graphene-based scaffolds (GBSs) in combination with ES. Future perspectives and some challenges faced in developing GBSs are also highlighted with the aim of promoting their clinical applications.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.