ReviewCells2026
From Biomaterials to Biological State Engineering: Reframing Advanced Wound Dressings as Adaptive Therapeutic Interfaces in Translational Medicine.
Review in Cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic wounds remain a major global health challenge despite substantial advances in biomaterials, regenerative medicine, and wound-care technologies. Current therapeutic strategies are largely based on the assumption that chronic wounds represent impaired or incomplete healing responses and therefore require augmentation of regenerative processes. This paradigm has driven the development of increasingly sophisticated wound dressings incorporating extracellular matrix analogs, growth factors, stem cells, extracellular vesicles, biosensors, and bioelectronic components. However, the clinical impact of these innovations has often fallen short of expectations. In this review, we propose a conceptual framework intended to generate experimentally testable hypotheses rather than provide a definitive mechanistic model. Persistent alterations in immune, stromal, vascular, extracellular matrix, metabolic, mechanical, and microbial networks create interconnected feedback systems that resist transition toward regeneration. From this perspective, successful therapy requires not only stimulation of repair mechanisms but also disruption of the processes that stabilize chronicity. We discuss how advances in systems biology, immunomodulatory biomaterials, bioelectronics, artificial intelligence, and precision medicine support the emergence of adaptive therapeutic interfaces capable of sensing, interpreting, and reprogramming pathological tissue behavior. Unlike previous reviews that primarily summarize emerging wound dressings or regenerative biomaterials, this Review proposes a systems-level conceptual framework in which chronic wounds are interpreted as stable pathological tissue states maintained by multiscale biological memory. This perspective integrates biomaterials, systems biology, artificial intelligence, and tissue-state dynamics into a unified translational model that has not previously been presented in the wound-healing literature. Previous reviews have predominantly focused on the design, biological activity, or clinical performance of individual biomaterials. In contrast, the present Review proposes a systems-level framework that integrates wound biology, biological memory, tissue-state dynamics, artificial intelligence, and adaptive biomaterials into a unified conceptual model for precision wound medicine. This state-based model reframes advanced wound dressings as tools for biological state engineering and provides a translational framework for the future of chronic wound management.
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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.