ArticleBiomaterials2013
The guidance of stem cell differentiation by substrate alignment and mechanical stimulation.
Article in Biomaterials, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 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
102 citing papers in PubMed, 1 synthesis or guideline pooled it, 277 citations in OpenAlex.
- Nanoscale Morphologies on the Surface of Substrates/Scaffolds Enhance Chondrogenic Differentiation of Stem Cells: A Systematic Review of the Literature.International journal of nanomedicine · 2024Pooled it
- Nanomaterial-enabled physical rehabilitation: mechanisms, evidence, and translational pathways.Frontiers in rehabilitation sciences · 2026Review
- Humanoid Robotic Loading Enhances Mechanotransduction in Tendon Tissue Engineering.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Pioneering Soundscapes: Investigating Commercial Fused Deposition Modelling Filament's Potential for Ultrasound Technology in Bone Tissue Scaffolds.Bioengineering (Basel, Switzerland) · 2025Article
- PIEZO1-mediated mechanotransduction regulates collagen synthesis on nanostructured 2D and 3D models of fibrosis.Acta biomaterialia · 2025Article
- Cell-based tissue engineered flexor tendon allograft: A canine in vivo study.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2024Article
- Mechanobiological Strategies to Enhance Ovine (Animals : an open access journal from MDPI · 2024Article
- A Hybrid Electrospun-Extruded Polydioxanone Suture for Tendon Tissue Regeneration.Tissue engineering. Part A · 2024Article
- Topographical cues of biomaterials and fibroblast activation: Are they related?Mechanobiology in medicine · 2024Review
- Cell-Derived Matrix: Production, Decellularization, and Application of Wound Repair.Stem cells international · 2024Review
- Plant Cellulose as a Substrate for 3D Neural Stem Cell Culture.Bioengineering (Basel, Switzerland) · 2023Article
- Neuro-regenerative behavior of adipose-derived stem cells in aligned collagen I hydrogels.Materials today. Bio · 2023Article
- Three-Dimensional Cell Culture System for Tendon Tissue Engineering.Tissue engineering and regenerative medicine · 2023Review
- Breakthrough treatments for accelerated wound healing.Science advances · 2023Review
- Mineralization of Bone Extracellular Matrix-like Scaffolds Fabricated as Silk Sericin-Functionalized Dense Collagen-Fibrin Hybrid Hydrogels.Pharmaceutics · 2023Article
- Recapitulation of growth factor-enriched microenvironment via BMP receptor activating hydrogel.Bioactive materials · 2023Article
- Applications of functionally-adapted hydrogels in tendon repair.Frontiers in bioengineering and biotechnology · 2023Review
- From mesenchymal niches to engineeredMaterials today. Bio · 2022Article
- Advances toward transformative therapies for tendon diseases.Science translational medicine · 2022Review
- Artificial neural network for cytocompatibility and antibacterial enhancement induced by femtosecond laser micro/nano structures.Journal of nanobiotechnology · 2022Article
42 more citing papers are in PubMed but not listed here.
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
Abstract
Mesenchymal stem cells (MSC) represent a promising and clinically relevant cell source for tissue engineering applications. As such, guiding MSCs toward specific lineages and maintaining these phenotypes have been particularly challenging as the contributions of mechanical, chemical and structural cues to the complex differentiation process are largely unknown. To fully harness the potential of MSCs for regenerative medicine, a systematic investigation into the individual and combined effects of these stimuli is needed. In addition, unlike chemical stimulation, for which temporal and concentration gradients are difficult to control, mechanical stimulation and scaffold-based cues may be relatively more biomimetic and can be applied with greater control to ensure fidelity in MSC differentiation. The objective of this study is to investigate the role of nanofiber matrix alignment and mechanical stimulation on MSC differentiation, focusing on elucidating the relative contribution of each parameter in guided regeneration of functional connective tissues. It is observed that nanofiber alignment directs MSC response to physiological loading and that fibroblastic differentiation requires a combination of physiologically-relevant cell-material interactions in conjunction with mechanical stimulation. Importantly, the results of this study reveal that systemic and readily controllable cues, such as scaffold alignment and optimized mechanical stimulation, are sufficient to drive MSC differentiation, without the need for additional chemical stimuli. Moreover, these findings yield a set of fundamental design rules that can be readily applied to connective tissue regeneration strategies.
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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.