ReviewFrontiers in neuroscience2020
Neurorestoration Approach by Biomaterials in Ischemic Stroke.
Review in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Cell Membrane-Derived Nanovehicles for Targeted Therapy of Ischemic Stroke: From Construction to Application.Pharmaceutics · 2023Review
- Biomimetic nanoparticles in ischemic stroke therapy.Discover nano · 2023Review
- Cell Replacement Therapy for Brain Repair: Recent Progress and Remaining Challenges for Treating Parkinson's Disease and Cortical Injury.Brain sciences · 2023Review
- Non-human primate models of focal cortical ischemia for neuronal replacement therapy.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023Review
- The Role of Stem Cells in the Therapy of Stroke.Current neuropharmacology · 2022Review
- Construction of transplantable artificial vascular tissue based on adipose tissue-derived mesenchymal stromal cells by a cell coating and cryopreservation technique.Scientific reports · 2021Article
- Combination of Stem Cells and Rehabilitation Therapies for Ischemic Stroke.Biomolecules · 2021Review
- Characteristics of neural growth and cryopreservation of the dorsal root ganglion using three-dimensional collagen hydrogel cultureNeural regeneration research · 2021Article
- Are We Ready for Cell Therapy to Treat Stroke?Frontiers in cell and developmental biology · 2021Review
- Biosensing surfaces and therapeutic biomaterials for the central nervous system in COVID-19.Emergent materials · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ischemic stroke (IS) is the leading cause of disability in the western world, assuming a high socio-economic cost. One of the most used strategies in the last decade has been biomaterials, which have been initially used with a structural support function. They have been perfected, different compounds have been combined, and they have been used together with cell therapy or controlled release chemical compounds. This double function has driven them as potential candidates for the chronic treatment of IS. In fact, the most developed are in different phases of clinical trial. In this review, we will show the ischemic scenario and address the most important criteria to achieve a successful neuroreparation from the point of view of biomaterials. The spontaneous processes that are activated and how to enhance them is one of the keys that contribute to the success of the therapeutic approach. In addition, the different routes of administration and how they affect the design of biomaterials are analyzed. Future perspectives show where this broad scientific field is heading, which advances every day with the help of technology and advanced therapies.
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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.