Background: Polyhydroxyalkanoate (PHA) are nano-granules naturally produced by bacteria. Two types of proteins, PHA synthase (PhaC) and phasins (PhaPs), are attached to the PHA surface by covalent and hydrophobic interactions. Utilizing these anchored proteins, functionalized PHA nano-granules displaying proteins of interest can be easily prepared by fermentation. Results: In this study, a one-step fabrication method was developed for stable and efficient immobilization of an organophosphorus degrading enzyme on PHA nano-granules. The nano-biocatalysts were produced in recombinant Escherichia coli cells into which the polyhydroxyalkanoate synthesis pathway from Cupriavidus necator had been introduced. Two different strategies, covalent attachment and hydrophobic binding, were investigated by fusing bacterial organophosphorus anhydride hydrolase (OPAA4301) with PhaC and PhaP, respectively. Using both methods, the tetrameric enzyme successfully self-assembled and was displayed on the PHA surface. The display density of the target fused enzyme was enhanced to 6.8% of total protein on decorated PHA by combination of covalent and non-covalent binding modes. Immobilization of the enzyme on PHA granules resulted in higher catalytic efficiency, increased stability and excellent reusability. The k_cat values of the immobilized enzymes increased by threefold compared to that of the free enzyme. The pH stability under acidic conditions was significantly enhanced, and the immobilized enzyme was stable at pH 3.0–11.0. Furthermore, more than 80% of the initial enzyme activity retained after recycling ten times. Conclusions: This study provides a promising approach for cost-efficient in vivo immobilization of a tetrameric organophosphorus degrading enzyme. The immobilization process expands the utility of the enzyme, and may inspire further commercial developments of PHA nano-biocatalysts. As revealed by our results, combination of covalent and non-covalent binding is recommended for display of enzymes on PHA granules.

Effective visual communication is key to improving road safety whenever vulnerable road users (VRUs), e.g. pedestrians and cyclists, interact in daily traffic. The importance of such communication continues to grow as higher levels of automation are achieved and fully automated vehicles (AVs) become increasingly prevalent. This is especially true for AVs above Level 3, which means that the driver is 'not driving' when autonomous driving features are engaged-even if the 'driver's' seat is occupied. Current research shows that external human machine interfaces (eHMIs) may facilitate explicit communication when AVs and VRUs interact. We used a Virtual Reality approach to examine the efficiency of different formats of eHMIs for signaling that an AV was going to give way and stop to let a pedestrian cross a road. Participant's decision times and judgements of the clarity of the signals were measured in studies conducted in the UK and in Germany. Overall, the findings showed that eHMIs were effective in signaling AV intention compared to a no-signal baseline, signal interpretation was more difficult at night than in the day. In addition, the format and type of information displayed influenced the ease of recognition and interpretation of such interfaces with larger light segments aiding visibility and numerical information aiding interpretation. The results are discussed in terms of recommendations for eHMI design and future field testing.

The upcoming proliferation of Automated Vehicles (AVs) above Level 3 fundamentally disrupts established communicative conventions between road users and vehicles, and external Human–Machine Interface (eHMI) emerges as the primary channel for conveying vehicle intent to pedestrians, cyclists, and other drivers. Despite the standardisation of the marker lamp of AVs and the growing research activity since 2016, no internationally harmonized eHMI standard has been established as of early 2026. This Systematic Literature Review (SLR), following the PRISMA 2020 protocol, synthesizes empirical and technical findings from 149 peer-reviewed English journal articles spanning the decade from 2016 to 2026, from Web of Science, Scopus, IEEE Xplore, and Google Scholar. The review covers scenario design, test methodologies, participant demographics, eHMI modalities, and performance evaluation measures by mapping, coding, and presenting in a structured framework the reviewed papers. The key findings are as follows: (1) 13 use cases (50%, out of 26) still need to be further studied; (2) vehicle kinematics remain a primary determinant of crossing decisions, with eHMI signals serving as confirmatory rather than primary cues in many scenarios; and (3) cross-cultural and demographic diversity in empirical studies remains critically insufficient for global regulatory purposes. We synthesize these findings into a structured framework of evidence-based recommendations for international eHMI standardisation organizations and identify critical research gaps requiring resolution before comprehensive standards can be enacted.

Effective visual communication is key to improving road safety whenever vulnerable road users (VRUs), e.g., pedestrians and cyclists, interact in daily traffic. The importance of such communication continues to grow as higher levels of automation are achieved and fully automated vehicles (AVs) become increasingly prevalent. This is especially true for AVs above Level 3, which means that the driver is ‘not driving’ when autonomous driving features are engaged—even if the ‘driver’s’ seat is occupied. Current research shows that external human–machine interfaces (eHMIs) may facilitate explicit communication when AVs and VRUs interact. We used a Virtual Reality approach to examine the efficiency of different formats of eHMIs for signaling that an AV was going to give way and stop to let a pedestrian cross a road. Participants’ decision times and judgements of the clarity of the signals were measured in studies conducted in the UK and in Germany. Overall, the findings showed that eHMIs were effective in signaling AV intention compared to a no-signal baseline; signal interpretation was more difficult at night than in the day. In addition, the format and type of information displayed influenced the ease of recognition and interpretation of such interfaces, with larger light segments aiding visibility and numerical information aiding interpretation. The results are discussed in terms of recommendations for eHMI design and future field testing.