ABSTRACT

Translating scientific discoveries in tissue engineering and regenerative medicine (TE/RM) into clinically adopted therapies is hindered by fragmented development pipelines, regulatory and manufacturing challenges, and limited funding. Despite substantial investment by the U.S. National Institutes of Health (NIH), few NIH-funded TE/RM projects achieve commercialization or regulatory approval by the US Food and Drug Administration. The gap between academic innovation and clinical implementation is particularly evident in the dental, oral, and craniofacial (DOC) domain, where market and reimbursement constraints further restrict translation. To address these barriers, the National Institute of Dental and Craniofacial Research established the Dental, Oral and Craniofacial Tissue Regeneration Consortium (DOCTRC), comprising two nationwide Resource Centers tasked with guiding promising technologies from universities and small businesses through preclinical validation toward clinical adoption. This translational science case study outlines DOCTRC’s translational model, highlighting lessons learned from five cohorts of interdisciplinary translational project teams, strategies for navigating manufacturing and regulatory pathways, and approaches for aligning academic innovation with clinical and market needs. The unique impact of the DOCTRC framework demonstrates how disciplined product development activities, non-dilutive funding mechanisms, and a comprehensive support ecosystem can accelerate technology translation, offering a scalable model for other biomedical fields.

It has been twenty years since the publication of Chomsky’s (2005) ‘Three factors in language design,’ which encouraged research into how human language is shaped by biological, physical, computational, and information structural ‘third factor’ principles, complementing genetics (first factor) and learned experience (second factor). Early research in this vein (e.g., Samuels 2009a,b) sought to build a phonological theory based entirely on the third factor and arrived at a version of substance-free logical phonology (SFLP). I argue that significant recent advances in neuroscience (e.g. Becker et al. 2025), genomics (e.g. Sebastianelli et al. 2024), and animal cognition (e.g. Lameira et al. 2024, Girard-Buttoz et al. 2025) bolster this case, shedding light on how the first and third factors are inextricably intertwined and yielding insights into how SFLP may have emerged in the human evolutionary lineage, remarkably convergently with birdsong (e.g. Samuels 2015, Gattoni & Tosches 2025, Güntürkün et al. 2024).

Abstract

The 2025 Eaton Fire in the San Gabriel Mountains, California, provides a compelling case to investigate the dynamics of wind-driven wildfires over the complex topography at the wildland–urban interface (WUI). Fueled by intense Santa Ana winds, low humidity, and dry fuels, the fire rapidly spread into urban neighborhoods, causing extensive damage. We used an atmospheric model at Large Eddy Simulation (LES) scales (~100 m grid spacing) for simulation of flow dynamics over complex, realistic terrain, driven by weather reanalysis and coupled to a fire propagation model. To accurately capture observed fire behavior, particularly across heterogeneous landscapes, we implemented targeted modifications to default fuel characteristics that are often used by fire models. For better representation of the urban environment, we introduced two new fuel types, one representing buildings and the other one suburban landscaping. This modification allows the model to realistically capture when the fire crossed from wildland into urban areas. We also modified fuel characteristics over recent burn scars as these areas act as natural barriers for fire spread. This study demonstrates the feasibility of explicit, high-resolution coupled weather-fire simulations for accurately modeling complex WUI fires. We establish a framework for supporting operational forecasting, mitigation planning, and targeted urban wildfire risk assessment in areas characterized by complex terrain and extreme fire-weather conditions.