Biomimetics

The NerveRepack project is a European initiative that aims to develop biomimetic exoskeletons/exoprostheses for amputated or paralyzed leg patients that will receive and transmit signals to enable movements and sensations for the patient. To implement the project, it is fundamental to develop implantable neuronal electrodes that will allow bidirectional signaling between the sensors placed on the exoskeletons/exoprostheses and the nervous system. In this direction, two electrodes, plug and cuff, have been designed as integral parts of the final implantable device. The electrodes should comply with strict regulations to ensure their safe implantation in patients. The purpose of this study was to support the compliance of the implant platforms of certain key components with the ISO and ASTM standards that would be required for clinical applications. We have used an indirect method to assess the biocompatibility of the developed electrodes against neuronal cells, fibroblasts, and keratinocytes. Also, we assessed hemocompatibility, i.e., the potential of implantable electrodes to induce hemolysis or complement activation. Finally, the mutagenic/genotoxic potential was tested against the internationally recommended CHO cells. Both representative plug and cuff electrode components were found non-cytotoxic, non-mutagenic, and unable to induce hemolysis. Therefore, from the point of early evaluation of in vitro material and process biocompatibility, the selected implant platforms for the electrodes could be implanted in preclinical models to delineate their potential in vivo applications as neuronal interface with the biomimetic exoskeleton/exoprostheses.

Artificial Intelligence (AI) has introduced transformative possibilities in orthodontics by enhancing diagnostic precision, treatment planning, and aesthetic outcomes. In face-driven orthodontics, treatment objectives extend beyond achieving proper occlusion to optimizing facial balance and harmony. With the growing patient demand for aesthetic improvements, AI technologies enable clinicians to integrate facial analysis and dynamic soft-tissue evaluation into personalized treatment approaches. Research in this scoping review analyzed current applications of AI in face-driven orthodontics, focusing on diagnosis, soft-tissue assessment, and individualized treatment planning. A comprehensive search was conducted in PubMed and Scopus for studies published between 2021 and 2025. The review followed the PRISMA-ScR guidelines. Of 54 initially identified studies, 24 met the inclusion criteria after title, abstract, and full-text screening. Extracted data were organized according to the main application areas of AI in face-driven orthodontics. Most studies focused on AI-assisted facial analysis, 3D reconstruction, and treatment simulation. Deep learning models demonstrated high performance in soft-tissue prediction, aesthetic evaluation, and diagnostic accuracy. However, heterogeneity in datasets, a lack of standardized validation protocols, limited external validation across included studies and limited clinical applicability were identified as key limitations. AI-based facial analysis supports a shift toward individualized, aesthetics-oriented orthodontic planning. Although current evidence highlights its potential for improving diagnostic precision and treatment outcomes, further validation through large-scale clinical studies is essential for broader implementation in everyday practice.

Bio-inspired engineering draws on principles refined by natural evolution to tackle persistent challenges in fluid mechanics, structural dynamics, and thermal transport. This article presents a critical, mechanism-driven narrative review that integrates recent advances across three complementary domains that are often treated independently, namely: flow-control strategies such as leading-edge tubercles, alula-like devices, riblets, superhydrophobic skins, and hybrid low-Reynolds-number fliers; fluid-structure interactions inspired by aquatic and aerial organisms that leverage compliant foils, flexible filaments, ciliary arrays, and piezoelectric fluttering plates for propulsion, wake regulation, mixing, and energy harvesting; and phase-change heat-transfer surfaces modeled after stomata, porous biological networks, and textured cuticles that enhance nucleation control, liquid replenishment, and droplet or bubble removal. Rather than providing an exhaustive catalog of biological analogues, this review emphasizes the underlying physical mechanisms that link these domains and enable multifunctional performance. These developments reveal shared physical principles, including multiscale geometry, capillary- and vortex-mediated transport, and compliance-enabled flow tuning, which motivate the integrated treatment of aerodynamic, hydrodynamic, and thermal systems in applications spanning aerospace, energy conversion, and microscale thermal management. The review assesses persistent challenges associated with scaling biological architectures, ensuring long-term durability, and modeling tightly coupled fluid-thermal-structural interactions. By synthesizing insights across flow control, fluid-structure interaction, and phase-change heat transfer, this review provides a unifying conceptual framework that distinguishes it from prior domain-specific reviews. Emerging opportunities in hybrid multi-mechanism designs, data-driven optimization, multiscale modeling, and advanced fabrication are identified as promising pathways to accelerate the translation of biological strategies into robust, multifunctional thermal–fluid systems.