CAREER: Decoding Chronic Wound Trajectory Through Real-Time Biomaterial-mediated Cytokine Sensing

Cytokines are proteins that regulate cell identity and function. Repair of wounds repair requires coordinated interactions among multiple cytokines. This CAREER project will address a fundamental question in wound repair: which inflammatory cytokines determine whether a wound heals or remains chronic. The project will develop a smart, biomaterial-based wound dressing that will monitor in real time various cytokine patterns in the wound environment. The data will enable machine learning predictions to distinguish healing versus nonhealing paths. The project will advance STEM education through (i) a game-based learning module for K–8 students in Southeast Michigan that teaches problem solving skills; (ii) a hands-on research model for K–12 students; and (iii) an art fair “show-and-tell” experience to reinforce engineering concepts for college-level students. The outreach initiatives will improve engagement with biotechnology, artificial intelligence, and other STEM fields. Chronic wounds are immunologically heterogeneous but share a common failure mode: the inability to transition from protective early inflammation to pro-repair resolution. Although there has been progress in defining inflammatory signals in wounds, understanding is limited because most assays are endpoint and often destructive. Thus, they provide only indirect or retrospective insight into the wound microenvironment. This critical challenge has limited understanding of when and how productive inflammation tips into self-sustaining, tissue-damaging immune activation. This CAREER project addresses this gap by integrating multiplex cytokine sensing into a wound dressing, enabling time-resolved immune readouts that can (i) signal whether a wound is progressing along a healing trajectory and (ii) determine when inflammation deviates toward chronicity. The hypothesis is that the engineered biomaterial will reveal distinct spatiotemporal cytokine patterns that differentiate wounds on a healing trajectory from those progressing toward chronicity. These data will clarify the transition point at which acute, protective inflammation becomes maladaptive and obstructs repair, offering predictive insight into wound fate. This project will (1) define longitudinal cytokine and cellular signatures of resolving versus non-resolving inflammation, (2) engineer and validate a multiplexed biomaterial with spatially organized sensor arrays and quantitative calibration against standard assays, and (3) employ machine-learning prediction of cytokine patterns associated with wound trajectory, and (4) deploy the patches in splinted excisional wounds in diabetic and control models to generate spatiotemporal cytokine trajectories that are mechanistically linked to immune-cell phenotype. Collectively, this research will establish a new biomaterial-enabled approach to measure and model wound immune dynamics in real time, with the long-term goal of informing when and how to intervene to resolve chronic immune activation during wound healing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2540484 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Maria Coronel | Institution: Regents of the University of Michigan - Ann Arbor, ANN ARBOR, MI | Award Amount: $629,903 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2540484 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2540484.html