ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024
X-Ray Visible Protein Scaffolds by Bulk Iodination.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 5 citations in OpenAlex.
- Microporous Self-Assembled Pd(II) Tetrahedral Cages for Rapid and Reversible Multi-Phase Sequestration of Iodine and Methyl Iodide.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Stimulated Raman Scattering Imaging Enabled Biomarker Discovery for Precision Medicine.Chemical & biomedical imaging · 2025Review
- Porous Aromatic Framework with Multifunctional Sites for Effective Recovery of Various Trace Iodine Species From Water.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Nanoparticle Contrast Agents for Dark-Field X-ray Imaging.Nano letters · 2025Article
- Composite Contrast Enhancement of Hydrogel-Based Implants for Photon-Counting Computed Tomography Studies.Gels (Basel, Switzerland) · 2024Article
- X-Ray Visible Protein Scaffolds by Bulk Iodination.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
Protein-based biomaterial use is expanding within medicine, together with the demand to visualize their placement and behavior in vivo. However, current medical imaging techniques struggle to differentiate between protein-based implants and surrounding tissue. Here a fast, simple, and translational solution for tracking transplanted protein-based scaffolds is presented using X-ray CT-facilitating long-term, non-invasive, and high-resolution imaging. X-ray visible scaffolds are engineered by selectively iodinating tyrosine residues under mild conditions using readily available reagents. To illustrate translatability, a clinically approved hernia repair mesh (based on decellularized porcine dermis) is labeled, preserving morphological and mechanical properties. In a mouse model of mesh implantation, implants retain marked X-ray contrast up to 3 months, together with an unchanged degradation rate and inflammatory response. The technique's compatibility is demonstrated with a range of therapeutically relevant protein formats including bovine, porcine, and jellyfish collagen, as well as silk sutures, enabling a wide range of surgical and regenerative medicine uses. This solution tackles the challenge of visualizing implanted protein-based biomaterials, which conventional imaging methods fail to differentiate from endogenous tissue. This will address previously unanswered questions regarding the accuracy of implantation, degradation rate, migration, and structural integrity, thereby accelerating optimization and safe translation of therapeutic biomaterials.
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.