Meara, J. G. et al. Global Surgery 2030: evidence and solutions for achieving health, welfare, and economic development. Lancet 386, 569–624 (2015).
Google Scholar
Mao, Y. & Wickström, S. A. Mechanical state transitions in the regulation of tissue form and function. Nat. Rev. Mol. Cell Biol. 25, 654–670 (2024).
Google Scholar
George, W. D. Suturing or stapling in gastrointestinal surgery: a prospective randomized study. Br. J. Surg. 78, 337–341 (1991).
Google Scholar
Chen, Y. et al. Tuning the properties of surgical polymeric materials for improved soft-tissue wound closure and healing. Prog. Mater. Sci. 143, 101249 (2024).
Google Scholar
Taboada, G. M. et al. Overcoming the translational barriers of tissue adhesives. Nat. Rev. Mater. 5, 310–329 (2020).
Google Scholar
Cui, C. & Liu, W. Recent advances in wet adhesives: adhesion mechanism, design principle and applications. Prog. Polym. Sci. 116, 101388 (2021).
Google Scholar
Yuk, H. et al. Rapid and coagulation-independent haemostatic sealing by a paste inspired by barnacle glue. Nat. Biomed. Eng. 5, 1131–1142 (2021).
Google Scholar
Wu, W. et al. Polyurethane-based bioglue for the repair of arterial ruptures. Adv. Funct. Mater. 35, 2417402 (2025).
Google Scholar
Nam, S., Seo, B. R., Najibi, A. J., McNamara, S. L. & Mooney, D. J. Active tissue adhesive activates mechanosensors and prevents muscle atrophy. Nat. Mater. 22, 249–259 (2023).
Google Scholar
Blacklow, S. O. et al. Bioinspired mechanically active adhesive dressings to accelerate wound closure. Sci. Adv. 5, eaaw3963 (2019).
Google Scholar
Liu, Y. et al. Gelation of highly entangled hydrophobic macromolecular fluid for ultrastrong underwater in situ fast tissue adhesion. Sci. Adv. 8, eabm9744 (2022).
Google Scholar
Wang, S. et al. In situ-sprayed bioinspired adhesive conductive hydrogels for cavernous nerve repair. Adv. Mater. 36, 2311264 (2024).
Google Scholar
Yuk, H. et al. Dry double-sided tape for adhesion of wet tissues and devices. Nature 575, 169–174 (2019).
Google Scholar
Li, J. et al. Tough adhesives for diverse wet surfaces. Science 357, 378–381 (2017).
Google Scholar
Yang, J., Bai, R., Chen, B. & Suo, Z. Hydrogel adhesion: a supramolecular synergy of chemistry, topology, and mechanics. Adv. Funct. Mater. 30, 1901693 (2020).
Google Scholar
Liu, J. et al. Fatigue-resistant adhesion of hydrogels. Nat. Commun. 11, 1071 (2020).
Google Scholar
Golman, M. et al. Toughening mechanisms for the attachment of architectured materials: the mechanics of the tendon enthesis. Sci. Adv. 7, eabi5584 (2021).
Google Scholar
McKee, C. T., Last, J. A., Russell, P. & Murphy, C. J. Indentation versus tensile measurements of Young’s modulus for soft biological tissues. Tissue Eng. B Rev. 17, 155–164 (2011).
Google Scholar
Guimarães, C. F., Gasperini, L., Marques, A. P. & Reis, R. L. The stiffness of living tissues and its implications for tissue engineering. Nat. Rev. Mater. 5, 351–370 (2020).
Google Scholar
Park, S. et al. Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity. Nat. Commun. 12, 3435 (2021).
Google Scholar
Sun Han Chang, R. A., Shanley, J. F., Kersh, M. E. & Harley, B. A. C. Tough and tunable scaffold-hydrogel composite biomaterial for soft-to-hard musculoskeletal tissue interfaces. Sci. Adv. 6, eabb6763 (2020).
Google Scholar
Wu, J. et al. Adhesive anti-fibrotic interfaces on diverse organs. Nature 630, 360–367 (2024).
Google Scholar
Assmann, A. et al. A highly adhesive and naturally derived sealant. Biomaterials 140, 115–127 (2017).
Google Scholar
Xie, M. et al. Nano-enabled DNA supramolecular sealant for soft tissue surgical applications. Nano Today 50, 101825 (2023).
Google Scholar
Xiong, X. et al. Polymerizable rotaxane hydrogels for three-dimensional printing fabrication of wearable sensors. Nat. Commun. 14, 1331 (2023).
Google Scholar
Nam, S. & Mooney, D. Polymeric tissue adhesives. Chem. Rev. 121, 11336–11384 (2021).
Google Scholar
Theocharidis, G. et al. A strain-programmed patch for the healing of diabetic wounds. Nat. Biomed. Eng. 6, 1118–1133 (2022).
Google Scholar
Ma, Z. et al. Controlled tough bioadhesion mediated by ultrasound. Science 377, 751–755 (2022).
Google Scholar
Ma, Z., Bao, G. & Li, J. Multifaceted design and emerging applications of tissue adhesives. Adv. Mater. 33, 2007663 (2021).
Google Scholar
Yang, Q. et al. Photocurable bioresorbable adhesives as functional interfaces between flexible bioelectronic devices and soft biological tissues. Nat. Mater. 20, 1559–1570 (2021).
Google Scholar
Jia, Y. et al. An endoscopically compatible fast-gelation powder forms Janus-adhesive hydrogel barrier to prevent postoperative adhesions. Proc. Natl Acad. Sci. USA 120, e2219024120 (2023).
Google Scholar
Wu, W. et al. Mechanostructures: rational mechanical design, fabrication, performance evaluation, and industrial application of advanced structures. Prog. Mater. Sci. 131, 101021 (2023).
Google Scholar
Zeni, C. et al. A generative model for inorganic materials design. Nature 639, 624–632 (2025).
Google Scholar
Liao, H. et al. Data-driven de novo design of super-adhesive hydrogels. Nature 644, 89–95 (2025).
Google Scholar
Wang, H. et al. Rational design of mechanical bio-metamaterials for biomedical applications. Prog. Mater. Sci. 156, 101545 (2026).
Google Scholar
Lodeiro, M. J. & Mulligan, D. R. Cure Monitoring Techniques for Polymer Composites, Adhesives and Coatings (The National Physical Laboratory, 2005).
Bo, Y. et al. Sustainably sourced tannic acid enables fast-curing high-strength epoxy adhesives with increased toughness. Ind. Eng. Chem. Res. 63, 11992–12001 (2024).
Google Scholar
Tsapatsaris, L. et al. Structural and dynamical insights into the formation process of a cross-linked polymer network in acrylic adhesives during thermal curing. Macromolecules 58, 8079–8090 (2025).
Google Scholar
Liu, C. et al. Mussel-inspired degradable antibacterial polydopamine/silica nanoparticle for rapid hemostasis. Biomaterials 179, 83–95 (2018).
Google Scholar
Zhao, X., Guo, B., Wu, H., Liang, Y. & Ma, P. X. Injectable antibacterial conductive nanocomposite cryogels with rapid shape recovery for noncompressible hemorrhage and wound healing. Nat. Commun. 9, 2784 (2018).
Google Scholar
Hong, Y. et al. A strongly adhesive hemostatic hydrogel for the repair of arterial and heart bleeds. Nat. Commun. 10, 2060 (2019).
Google Scholar
Cui, C. et al. Water-triggered hyperbranched polymer universal adhesives: from strong underwater adhesion to rapid sealing hemostasis. Adv. Mater. 31, 1905761 (2019).
Google Scholar
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).
Google Scholar
Chen, T. & Guestrin, C. XGBoost: a scalable tree boosting system. In Proc. 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (eds Krishnapuram, B. et al.) 785–794 (ACM, 2016).
Smola, A. J. & Schölkopf, B. A tutorial on support vector regression. Stat. Comput. 14, 199–222 (2004).
Google Scholar
Tibshirani, R. Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. B 58, 267–288 (1996).
Google Scholar
Hoerl, A. E. & Kennard, R. W. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12, 55–67 (1970).
Google Scholar
Geurts, P., Ernst, D. & Wehenkel, L. Extremely randomized trees. Mach. Learn. 63, 3–42 (2006).
Google Scholar
Paszke, A. et al. PyTorch: an imperative style, high-performance deep learning library. Adv. Neural Inf. Process. Syst. 32, 8024–8035 (2019).
Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Lundberg, S. M. & Lee, S.-I. A unified approach to interpreting model predictions. Adv. Neural Inf. Process. Syst. 30, 4768–4777 (2017).
Lundberg, S. M. et al. Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nat. Biomed. Eng. 2, 749–760 (2018).
Google Scholar
Lundberg, S. M. et al. From local explanations to global understanding with explainable AI for trees. Nat. Mach. Intell. 2, 56–67 (2020).
Google Scholar
Xuan, C. Data for ‘Machine learning-guided design of mechanoadaptive bioglues for multi-tissue trauma and first-aid applications’. figshare https://doi.org/10.6084/m9.figshare.31769131 (2026).
Cao, C. TuneGlue. GitHub https://github.com/ChaoyuCao/TuneGlue.git (2024).
